WO2023210209A1 - Resource management device, resource management method, and resource management program - Google Patents

Resource management device, resource management method, and resource management program Download PDF

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Publication number
WO2023210209A1
WO2023210209A1 PCT/JP2023/010861 JP2023010861W WO2023210209A1 WO 2023210209 A1 WO2023210209 A1 WO 2023210209A1 JP 2023010861 W JP2023010861 W JP 2023010861W WO 2023210209 A1 WO2023210209 A1 WO 2023210209A1
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Prior art keywords
resource
virtual
data
capacity
entity
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PCT/JP2023/010861
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French (fr)
Japanese (ja)
Inventor
将人 内海
直 齋藤
ルイス エフライン エドアルド タマヨ
啓生 宮本
敏明 鈴木
良和 石井
民圭 曹
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株式会社日立製作所
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Publication of WO2023210209A1 publication Critical patent/WO2023210209A1/en

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L55/00—Arrangements for supplying energy stored within a vehicle to a power network, i.e. vehicle-to-grid [V2G] arrangements
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply

Definitions

  • the present invention relates to a resource management device, a resource management method, and a resource management program.
  • Patent Document 1 discloses a method of controlling distributed energy devices such as a generator, a power storage device, and a hydrogen storage device based on a predicted energy demand value and a predicted energy supply value. According to Patent Document 1, optimal energy operation is possible in a system using a solar cell as a power source by integrally controlling resources that are a plurality of different types of energy devices.
  • Patent Document 2 describes a first aggregation device that manages the power amount balance based on predictions of power generation and demand, and a second aggregation device that provides electric power sold based on a request from the first aggregation device.
  • a method is disclosed in which the second aggregation device transmits notification information for proceeding with the provision of electric power to a mobile body equipped with a storage battery.
  • Patent Document 2 in order to adjust the supply and demand balance of an electric power system, it is possible to utilize surplus power of a resource that is a plurality of electric vehicles (EVs) equipped with storage batteries.
  • EVs electric vehicles
  • Resources are not always used for one type of purpose; some resources can be used for multiple types of purposes. For example, when transporting storage batteries or hydrogen storage devices as cargo, this transportation resource plays the role of a power distribution resource for energy transportation. For example, when an electric vehicle such as a passenger transport bus is controlled as an energy resource for multiple types of usage purposes, this bus plays both the role of passenger transport and the role of electric power transport.
  • the main objective of the present invention is to improve the utilization rate of resources provided to multiple types of systems.
  • the resource management device of the present invention has the following features.
  • the present invention provides a virtual capability that indicates the ability that the actual resource provides as a virtual resource based on virtualization logic that virtualizes the actual resource from actual resource measurement data that measures the actual resource that is equipment related to energy.
  • a virtual resource capability conversion unit that creates data and constructs a virtual resource that provides the virtual capability data;
  • a capacity allocation unit that causes the resource operation management system to manage the actual resource by allocating the virtual resource constructed by the virtual resource capacity conversion unit to the resource operation management system;
  • the virtualization logic is characterized in that the virtualization logic is individually prepared according to resource request content data indicating the capability of the actual resource requested by the resource operation management system. Other means will be described later.
  • FIG. 1 is a configuration diagram showing a resource operation management system according to the present embodiment.
  • FIG. 1 is a configuration diagram of a resource virtualization system according to the present embodiment.
  • FIG. 3 is a data flow diagram of resource virtualization processing in the resource virtualization system according to the present embodiment. 3 is a flowchart illustrating the processing procedure of resource virtualization processing of the resource virtualization system according to the present embodiment.
  • FIG. 3 is a data flow diagram of a virtual resource capability conversion unit according to the present embodiment. It is a table which shows an example of the resource request content data acquired regarding this embodiment. It is a table showing an example of acquired virtualization definition data regarding this embodiment. It is a table which shows an example of entity resource constraint data regarding this embodiment.
  • FIG. 1 is a configuration diagram showing a resource operation management system according to the present embodiment.
  • FIG. 1 is a configuration diagram of a resource virtualization system according to the present embodiment.
  • FIG. 3 is a data flow diagram of resource virtualization processing in the resource virtualization system according to the
  • FIG. 6 is an explanatory diagram of the processing of the virtualization logic of “P0001” placed in the acquired capability conversion unit according to the present embodiment.
  • FIG. 3 is an explanatory diagram illustrating virtualization logic of "P0001", “P0002”, and “P0003” related to the present embodiment arranged in a capability conversion unit.
  • FIG. 7 is an explanatory diagram of the processing of the virtualization logic of "P0004" placed in the acquired capability conversion unit according to the present embodiment.
  • FIG. 6 is an explanatory diagram of the processing of the virtualization logic of "P0005", "P0002", and “P0006” arranged in the acquired capability conversion unit according to the present embodiment.
  • 9 is a graph showing virtual capability data for specifically explaining "P0001" in FIG. 9 according to the present embodiment.
  • FIG. 3 is a data flow diagram of the ability prediction unit according to the present embodiment.
  • FIG. 3 is a data flow diagram of a capacity allocation unit according to the present embodiment.
  • 3 is a table showing an example of requested resource correspondence data according to the present embodiment.
  • FIG. 2 is an explanatory diagram illustrating an example of a data structure for virtualizing an entity resource according to the present embodiment.
  • FIG. 1 is a hardware configuration diagram of a resource virtualization system according to the present embodiment.
  • 3 is a table showing an example of virtual capability data of each virtual resource according to the present embodiment.
  • FIG. 19 is an explanatory diagram of allocating entity resources to the system.
  • the horizontal axis of this explanatory diagram is the time axis.
  • Schedule 1900 shows how resources are provided in the conventional method.
  • a schedule 1910 shows how resources are provided in this embodiment.
  • the resource request period 1901 from the resource operation control system A and the resource request period 1902 from the resource operation control system B overlap in some time periods. Therefore, the actual resource is exclusively provided to the resource operation control system A, which is the provision target, predetermined in advance, only during the resource provision period 1903. In this way, in the conventional method, the actual resource is provided to an exclusive destination, so the utilization rate of the actual resource is low.
  • specification data indicating the characteristics of the entity resource will be required to match the resource requirements of resource operation control system B. must be changed.
  • the resource request contents of the resource operation control system A and the resource operation control system B are not necessarily of the same type, it is not easy to change the provision destination.
  • one real resource is converted into one or more virtual resources, and each virtual resource is associated with virtual capability data indicating its capability.
  • the following two virtual resources are generated from one real resource.
  • - Virtual resource A is associated with virtual capability data of an actual resource that satisfies the capability requested by resource operation control system A.
  • the resource operation control system A is a system monitoring control system
  • a power supply capacity 1915 and a discharge capacity 1917 are required. Therefore, when the actual resource is an electric vehicle, a virtual resource A is constructed in which the power supply capacity 1915 and discharge capacity 1917 of the battery are described as virtual capacity data.
  • - Virtual resource B is associated with virtual capability data of an actual resource that satisfies the capability requested by resource operation control system B.
  • resource operation control system B is a transportation system
  • transportation capacity 1916 is required. Therefore, when the real resource is an electric vehicle, a virtual resource B is constructed in which the transportation capacity 1916 of the electric vehicle is described as virtual capacity data. In this way, even if the electric vehicle is physically the same, the virtual resources used by the destination system to manage the electric vehicle are defined individually to satisfy the requirements of the destination system. .
  • the difference between the schedule 1900 and the schedule 1910 will be explained from the perspective of managing real resources.
  • the resource request period 1901 and the resource provision period 1903 have a 1:1 correspondence, and one entity resource is exclusively provided to one system. In other words, managing real resources and using real resources have become synonymous.
  • the resource request period 1901 from the resource operation control system A is replaced by the resource management request period 1911.
  • the resource request period 1902 from the resource operation control system B is replaced by the resource management request period 1912.
  • the resource operation control system A can always manage the real resource to be managed via the virtual resource A during the resource management request period 1911.
  • the resource operation control system B can always manage the real resource to be managed via the virtual resource B during the resource management request period 1912.
  • one entity resource can be managed in parallel by two systems.
  • management means notifying each system of the measured value of the real resource related to the virtual capability data that each system requests from the real resource. For example, since the resource operation control system A obtains the power supply capacity 1915 and the discharge capacity 1917 as virtual capacity data, the virtual resource A can constantly notify the resource operation control system A of the current remaining battery level of the electric vehicle. , managed by resource operation control system A. Similarly, since the resource operation control system B obtains the transportation capacity 1916 as virtual capacity data, the virtual resource A can constantly notify the resource operation control system B of the current position and the current number of passengers of the electric vehicle. Managed by operation control system B.
  • an electric vehicle charges its battery from the resource operation control system A at point X using the power supply capacity 1915 in the morning of one day. After charging, the electric vehicle is requested to transport the occupant to point Q from the resource operation control system B at point P at noon, and starts transporting using the transport capacity 1916. After disembarking the passenger at point Q, the electric vehicle is requested by the resource operation control system A at point Y to discharge the battery power using the discharge capacity 1917 at night.
  • the task of supplying power from point X to point Y and the task of transporting personnel from point P to point Q for example, the distance between point When it's close, you can run two tasks in parallel in one day.
  • electric vehicles can improve operating rates by having separate systems manage them in overlapping time periods and using different capacities at different times.
  • operation can be controlled simultaneously in accordance with the content of resource requests from each resource operation control system.
  • FIG. 20 is an explanatory diagram showing an example of a data structure for virtualizing a real resource.
  • Each entity resource is assigned an entity resource ID “AR001 to AR006”.
  • the entity resource ID "AR001" is assigned to the entity resource of a private car.
  • One or more virtual resources are constructed from one real resource.
  • Virtual resource IDs “VR001 to VR006” are assigned to each virtual resource.
  • one virtual resource with virtual resource ID "VR001" is constructed from a real resource with real resource ID "AR001”.
  • Each virtual resource is associated with virtual capability data provided by that virtual resource.
  • Virtual capacity data of a virtual resource is defined according to the requirements of the system in which the virtual resource is provided.
  • the virtual resource ID "VR003" is constructed from two real resource IDs "AR004 and AR005". In this case, by combining the capabilities provided by the two real resources, they can be provided as one virtual resource. Furthermore, two virtual resources with virtual resource IDs "VR002 and VR005" are constructed from the real resource with the real resource ID "AR002". In this case, one physical resource, a truck equipped with a battery, can be defined as a virtual resource ID "VR002" that provides power transport capability, or as a virtual resource ID "VR005" that provides regulated power capability. show.
  • One system issues one or more request IDs "R0001 to R0005".
  • a system called “Monitor A” issues a request ID "R0001” requesting virtual capability data of power supply, and also issues a request ID "R0004" requesting virtual capability data of regulated power supply.
  • Resource allocation means associating one or more virtual resource IDs with one request ID.
  • the arrow of the virtual resource ID "VR001” is connected to the request ID "R0001" requested by the "monitoring A” system.
  • the “monitoring A” system can manage the virtual capability data of power supply provided by the virtual resource ID "VR001".
  • the private car with the real resource ID "AR001” that corresponds to the virtual resource ID "VR001” provides the ability to supply power to the "monitoring A" system.
  • the passenger bus with the physical resource ID "AR003” provides the ability to transport electricity to the "monitoring B” system via the virtual resource ID "VR002" and the “monitoring A” system via the virtual resource ID "VR005". ” provides the capability of regulated power to the system. By virtualizing one real resource into multiple virtual resources in this way, it can be managed by multiple systems simultaneously, as shown in schedule 1910 in FIG. 19.
  • FIG. 1 is a configuration diagram showing a resource operation management system 1.
  • the resource operation management system 1 creates virtual resources from the actual resources 5 in accordance with the operation of each resource operation control system, thereby managing multiple resource operation control systems each having a different operational purpose. enable operation in This enables more efficient operational control of energy-related resources. Therefore, the resource operation management system 1 includes a resource virtualization device 3, a data management device 4, an actual resource 5, a measurement device 6, a monitoring control device 7, an information input/output terminal 8, an information distribution device 9, a resource operation control device 10, a control It is composed of target equipment 12.
  • the communication path 11 is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network), and is a communication path 11 that connects various devices and terminals that constitute the resource operation management system 1 so that they can communicate with each other.
  • LAN Local Area Network
  • WAN Wide Area Network
  • the data management device 4 stores measurement data of the entity resource 5, constraint data such as conditions and constraints related to the operation and control of the entity resource 5, and data on factors that affect the operation of the entity resource 5.
  • the entity resources 5 are, for example, the following devices. - Generators that use fossil fuels - Generators that use renewable energies such as solar, geothermal, wind, and water power - Stationary storage batteries - Mobile vehicles equipped with storage batteries, such as electric cars and electric buses - Substations Substation equipment and power transmission and distribution equipment, such as transformers and phase adjustment equipment - Individual equipment that produces, consumes, or stores energy, or a collection of equipment that consists of a combination of two or more individual equipment.
  • the equipment is, for example, utility equipment on the energy consumption side, such as lighting, air conditioning, and power equipment.
  • the measurement data of the real resource 5 includes at least data recording the operation of the real resource 5 measured over time.
  • the operation of the entity resource 5 includes, for example, the amount of power generation, amount of consumption, amount of stored electricity, amount of power transmission and distribution, movement history, etc. of the entity resource 5.
  • the constraint data of the entity resource 5 includes at least data indicating conditions and constraints related to the operation and control of the entity resource 5.
  • Conditions and constraints related to the operation and control of the entity resource 5 include, for example, the location and possible time of energy production, consumption, and storage, and the amount and time related to the operation of the entity resource 5, such as the upper and lower limits of the amount. This includes data showing the operating range of the location and location, and data showing costs related to operation.
  • the factor data 453A (FIG. 3) acquired from the data management device 4 is, for example, the following data.
  • ⁇ Weather data such as temperature, humidity, solar radiation, wind speed, and atmospheric pressure
  • ⁇ Fuel data such as trading volume and transaction price of crude oil and natural gas
  • Power transmission and distribution line data such as capacity of power transmission and distribution lines
  • Generator operating status data such as schedules - Calendar data such as year, month, day, day of the week, and flag values that indicate the type of arbitrarily set day - Data that indicates whether sudden events such as typhoons or events have occurred
  • Energy consumers Data showing the economic situation, such as numbers, industrial trends, and business conditions.
  • - Data showing the movement status of people and moving objects, such as the occupancy rate of limited express trains, the number of passengers, the number of reserved seats, and road traffic conditions.
  • the data management device 4 stores measurement data and constraint data of the entity resource 5 from a preset past date and time to the latest observation date and time via any one of the measurement device 6, the monitoring control device 7, and the information input/output terminal 8.
  • the data management device 4 also searches for and transmits measurement data and constraint data of the entity resource 5 in response to data acquisition requests from other devices.
  • FIG. 2 is a configuration diagram of the resource virtualization system (resource management device) 2.
  • the resource virtualization system 2 includes a resource virtualization device 3 and a data management device 4.
  • the resource virtualization device 3 uses the data stored in the data management device 4 to convert the data of the real resource 5 into "virtual resource data" indicating a virtual resource. Therefore, the resource virtualization device 3 includes a virtual resource capacity conversion section 351, a capacity prediction section 352, a capacity allocation section 353, and a control planning section 354.
  • the virtual resource capacity conversion unit 351 acquires measurement data and constraint data of the real resource 5 from the data management device 4 .
  • the virtual resource capacity conversion unit 351 converts the measurement data and constraint data of the real resource 5 into "virtual capacity data" indicating the capacity of the virtual resource so as to match the resource request content received from the resource operation control device 10. and configure virtual resources based on virtual capacity data.
  • the virtual resource capacity conversion unit 351 creates virtual capacity data based on the virtualization logic for virtualizing the substance resource 5 from the substance resource measurement data 451A obtained by measuring the substance resource 5, which is energy-related equipment. , construct a virtual resource that provides that virtual capability data.
  • the virtualization logic is individually prepared according to the resource request content data indicating the capability of the actual resource 5 requested by each resource operation management system 1 to which it is allocated.
  • the virtualization logic is a logic that performs a conversion process from real resource measurement data 451A set in advance to virtual capability data in order to construct a virtual resource.
  • an ID starting from P such as P0001, is assigned as an identifier for virtualization logic.
  • the capacity prediction unit 352 identifies a model that predicts the future value of the virtual capacity data based on the past data of the virtual capacity data output by the virtual resource capacity conversion unit 351 and the factor data 453A acquired from the data management device 4. .
  • the ability prediction unit 352 uses the identified model to calculate a predicted value that is the future value of the virtual ability data at a predetermined future date and time.
  • the capacity allocation unit 353 matches the content of the resource request obtained from the resource operation control device 10 with the virtual capacity data calculated by the capacity prediction unit 352, and allocates virtual resources to be provided to the resource operation control device 10. In other words, the capacity allocation unit 353 allows each resource operation management system 1 to manage the actual resource 5 by allocating each virtual resource constructed by the virtual resource capacity conversion unit 351 to the resource operation management system 1 .
  • the capacity allocation unit 353 may allocate each virtual resource constructed by the virtual resource capacity conversion unit 351 to the resource operation management system 1 based on the predicted value calculated by the capacity prediction unit 352.
  • the control planning unit 354 generates a plan for controlling part or all of the real resource 5 incorporated into the virtual resource.
  • the control planning unit 354 generates a control plan for the entity resources 5 constituting the virtual resources allocated by the capacity allocation unit 353, and based on the control plan, the control planning unit 354 sends the entity resources 5 to each resource operation management system 1 to which the capacity allocation unit 353 has allocated. be controlled.
  • the virtual resource capacity conversion unit 351 modifies the virtual capacity data based on the control plan generated by the control planning unit 354.
  • the control planning unit 354 may calculate a temporal change in virtual capacity data related to energy as the real resource 5 operates, and may reflect the temporal change in the virtual capacity data created by the virtual resource capacity conversion unit 351.
  • the resource operation control device 10 is, for example, a device that operates and controls energy generation, consumption, transportation, and transaction.
  • the resource operation control device 10 performs physical equipment operation to achieve a predetermined goal by combining the control target equipment 12 and virtual resources managed by each device based on the virtual capacity data output by the resource virtualization device 3.
  • the physical equipment operation plan is, for example, an operation plan for energy production equipment, distribution equipment, consumption equipment, and storage equipment.
  • the physical equipment operation plan is the following plan.
  • the facility operation plan is not limited to being directly executed by the person using the resource operation control device 10, but may be implemented indirectly.
  • Indirect equipment operation in the electric power sector, is, for example, the operation of physical equipment by another party based on a direct bilateral trading contract or a trading contract via an exchange.
  • the execution plan of the transaction contract corresponds to the equipment operation plan.
  • the information input/output terminal 8 inputs data to the resource virtualization device 3 and data management device 4, and displays data stored or output by these devices.
  • the measurement device 6 periodically measures or collects measurement data regarding the operation of the entity resource 5 at predetermined time intervals, and transmits it to the data management device 4 .
  • the information distribution device 9 transmits measured values and predicted values of factor data 453A that influence the operation of the entity resource 5 to the data management device 4.
  • the monitoring control device 7 monitors and controls the entity resources 5.
  • the data management device 4 includes a CPU 31 (Central Processing Unit) 41 that centrally controls the operation of the data management device 4, an input device 42, an output device 43, a communication device 44, and a storage device 45.
  • the data management device 4 is, for example, an information processing device such as a personal computer, a server computer, or a handheld computer.
  • the input device 42 consists of a keyboard or a mouse, and the output device 43 consists of a display or a printer.
  • the communication device 44 is also configured to include a NIC (Network Interface Card) for connection to a wireless LAN or wired LAN.
  • the storage device 45 is a storage medium such as a RAM (Random Access Memory) or a ROM (Read Only Memory). The output results and intermediate results of each processing unit may be outputted as appropriate via the output device 43.
  • the storage device 45 stores databases such as an actual resource measurement data storage means 451, an actual resource constraint data storage means 452, and a factor data storage means 453.
  • the entity resource measurement data storage means 451 holds entity resource measurement data 451A.
  • the entity resource measurement data 451A is data in which past observed values regarding the operation of the entity resource 5 are stored. Observed values for the operation of entity resources 5 include, for example, the amount of power generated by a generator, the amount of charge and discharge of a storage battery, the amount of charge of an electric vehicle, the amount of remaining charge, the amount of discharge to the power grid, and the latitude and longitude and location of GPS, etc. This includes the movement history of the mobile object indicated by the identifier, the movement history of passenger transportation and cargo transportation, and the history of transportation contents.
  • the entity resource constraint data storage means 452 holds entity resource constraint data 452A (FIG. 8).
  • the entity resource constraint data 452A is data in which conditions and constraints regarding the operation of the entity resource 5 are stored.
  • the conditions and constraints regarding the operation of the entity resource 5 are, for example, the following data. ⁇ Operating time range such as start date and time and end date and time of power generation, charging, storage discharge, movement, etc.
  • ⁇ Operating amount range such as power generation amount, charge amount, storage discharge amount, movement amount, etc. ⁇ Location of power generation, charging, storage discharge, etc.
  • Operating location range such as movement range - Response time, which is the time required to complete the control response when accepting control - Whether or not it is possible to control whether changes in the operation details of the entity resource 5 can be accepted - Whether the above conditions can be changed Whether or not the conditions can be changed, costs related to operation, or costs incurred due to control acceptance and condition changes
  • the factor data storage means 453 holds factor data 453A.
  • the factor data 453A is data in which observed values and predicted values of various factors that influence the operation of the entity resource 5 are stored.
  • the factors are, for example, the following data.
  • ⁇ Weather data such as temperature, humidity, solar radiation, wind speed, and atmospheric pressure
  • ⁇ Energy consumption data such as electricity, gas, and water
  • ⁇ Energy generation data such as solar power generation and wind power generation
  • Power system data such as free capacity, current amount, and voltage for each transmission line, distribution line, or substation
  • ⁇ Market data such as energy transaction volume and transaction price traded on exchanges ⁇ Year, month, day of the week
  • Calendar data such as flag values that indicate the type of day that you have set
  • ⁇ Data that indicates the occurrence of sudden events such as typhoons and events
  • ⁇ Data that indicates economic conditions such as the number of energy consumers, industrial trends, and business conditions
  • the resource virtualization device 3 includes a CPU 31 that centrally controls the operation of the resource virtualization device 3, an input device 32, an output device 33, a communication device 34, and a storage device 35.
  • the resource virtualization device 3 is, for example, an information processing device such as a personal computer, a server computer, or a handheld computer.
  • the storage device 35 stores databases such as a virtualization definition data storage means 357, a virtualization logic pool data storage means 358, and a resource related data storage means 359.
  • the virtualization definition data storage means 357 holds virtualization definition data 357A (FIG. 7).
  • the virtualization definition data 357A is data indicating the correspondence between the content of the resource request received from the resource operation control device 10 and the virtualization logic for constructing a virtual resource that satisfies the request.
  • the virtualized logic pool data storage means 358 holds a virtualized logic pool 358A.
  • the virtualization logic pool 358A stores one or more types of virtualization logic set in advance. The virtualization logic will be illustrated below.
  • the resource-related data storage means 359 holds resource-related data 359A (FIG. 15).
  • the resource relationship data 359A is data indicating the correspondence between a virtual resource and the real resources 5 that constitute the virtual resource.
  • the resource related data 359A is shown, for example, as an arrow from private car "AR001" to virtual resource "VR001" in FIG. 20.
  • the storage device 35 also stores various computer programs such as a virtual resource capacity conversion unit 351, a capacity prediction unit 352, a capacity allocation unit 353, and a control planning unit 354.
  • the virtual resource capacity conversion unit 351 sequentially executes the following processes. - Input the entity resource measurement data 451A and the entity resource constraint data 452A. - Using the virtualization logic in the virtualization logic pool 358A, convert the measurement data of each entity resource 5 included in the entity resource measurement data 451A into virtual capacity data. Information indicating which virtualization logic is used is stored in the virtualization definition data 357A. - Build a resource that satisfies the resource request content received from the resource operation control device 10 as a virtual resource in combination with virtual capability data. ⁇ Output the constructed virtual ability data. - Selection is made based on the correspondence data between the resource request content and the virtualization logic received from the resource operation control device 10.
  • the capacity prediction unit 352 inputs the virtual capacity data outputted by the virtual resource capacity conversion unit 351 and the factor data 453A, identifies a prediction model for calculating a predicted value of the value indicating the capacity at a predetermined future date and time, and performs prediction. It calculates the value and outputs the predicted value to the capacity allocation unit 353.
  • the capacity allocation unit 353 compares the predicted value of the virtual capacity data output by the capacity prediction unit 352 with the content of the resource request obtained from the resource operation control device 10 and determines the virtual resource to be provided to the resource operation control device 10.
  • the control planning unit 354 generates and outputs a control plan for the real resource 5 that constitutes the virtual resource in any of the following cases. - When the capacity allocation unit 353 determines that the predicted value of the virtual capacity data output by the capacity prediction unit 352 does not match the resource request content obtained from the resource operation control device 10 - The resource request content from the resource operation control device 10 In the case where the actual resource 5 that constitutes the virtual resource is changed, the actual resource 5 that constitutes the virtual resource is obtained from the resource relationship data 359A.
  • FIG. 3 is a data flow diagram of resource virtualization processing in the resource virtualization system 2.
  • the data management device 4 receives the entity resource measurement data 451A from the measurement device 6 or the monitoring and control device 7, and stores it in the entity resource measurement data storage means 451.
  • the data management device 4 also receives entity resource constraint data 452A from the information input/output terminal 8, and stores it in the entity resource constraint data storage means 452.
  • the data management device 4 also receives factor data 453A from the information distribution device 9 and stores it in the factor data storage means 453.
  • the virtual resource capacity conversion unit 351 sequentially executes the following processes. - Acquire the measurement data of one or more entity resources 5 recorded in the entity resource measurement data 451A from the entity resource measurement data 451A within a predetermined date and time range. - Obtain data on constraints and conditions regarding the operation of the acquired entity resource 5 from the entity resource constraint data 452A. - Using the resource request content data input from the resource operation control device 10 via the capacity allocation unit 353 as a key, an identifier indicating the virtualization processing logic for converting the measurement data of the real resource 5 into virtual capacity data is virtualized. It is obtained from the definition data 357A.
  • the virtual resource capability conversion unit 351 stores resource relationship data 359A indicating the correspondence between the virtual resource and the entity resources 5 that constitute the virtual resource in the resource relationship data storage unit 359.
  • the ability prediction unit 352 sequentially executes the following processes. - Acquire the virtual resource data output by the virtual resource capacity conversion unit 351 and the factor data 453A from the data management device 4. ⁇ Identify a prediction model for calculating predicted values of virtual ability data. - Calculate the predicted value of the virtual ability data by inputting the factor data 453A of a predetermined future date and time into the identified prediction model. - The predicted value of the data indicating the capacity and the identifier indicating the virtual resource are combined and output as virtual resource capacity prediction result data.
  • the capacity allocation unit 353 sequentially executes the following processes. - Obtain the virtual resource capacity prediction result data obtained from the capacity prediction unit 352 and the resource request content obtained from the resource operation control device 10. - Determine whether the predicted value of the virtual capacity data shown in the virtual resource capacity prediction result data satisfies the resource request content. - If it is determined that the virtual resource is sufficient, the virtual resource is registered as one to be controlled and operated by the resource operation control device 10. - If it is determined that it is not sufficient, outputs control plan generation instruction data to the control planning unit 354 to start a process of generating a control plan that changes the operation of the real resources 5 that constitute the virtual resource.
  • the control planning unit 354 sequentially executes the following processes. -Starts operation upon receiving control plan generation instruction data from the capacity allocation unit 353, - Obtain the resource related data 359A, generate a control plan for one or more real resources 5 that constitute the virtual resource for which the control plan is to be generated, and output it as control plan data. - The output control plan data is input to the capacity prediction unit 352, and the predicted value of the virtual capacity data after the execution of the control plan is calculated again in the capacity prediction unit 352 and output.
  • FIG. 4 is a flowchart showing the procedure of resource virtualization processing in the resource virtualization system 2.
  • This flowchart is a process that starts with one of the following as a trigger, and the resource virtualization device 3 executes the processes from step S401 to step S405.
  • the resource virtualization device 3 has received an input operation from the device user.
  • a resource request has been received from the resource operation control device 10.
  • the preset execution time has arrived.
  • resource virtualization Processing is executed based on various computer programs stored in the CPU 31 and storage device 35 of the device 3 and various computer programs stored in the CPU 41 and storage device 45 of the data management device 4.
  • the processing entities will be described as the resource virtualization device 3 and various computer programs included in the resource virtualization device 3.
  • the virtual resource capability conversion unit 351 acquires the actual resource measurement data 451A and the actual resource constraint data 452A from the data management device 4, and the resource request content data (FIG. 6) from the capacity allocation unit 353. Then, virtualization processing logic is obtained from the virtualization logic pool 358A using the resource request content data and virtualization definition data 357A, and the real resource measurement data 451A is converted into virtual capacity data using the obtained logic. Then, a virtual resource is created by combining the virtual capability data (S401)
  • the capacity prediction unit 352 identifies a prediction model for calculating a predicted value of the virtual capacity data from the virtual resource data output by the virtual resource capacity conversion unit 351 and the factor data 453A acquired from the data management device 4. Then, the ability prediction unit 352 calculates the predicted value of the virtual ability data by inputting the factor data 453A of a predetermined future date and time into the identified prediction model (S402). Note that the capacity prediction unit 352 may modify the predicted value of the virtual capacity data calculated in S402 using the control plan for the real resource 5, which will be described later, in S404.
  • the capacity allocation unit 353 acquires the virtual resource capacity prediction result data from the capacity prediction unit 352, and acquires the resource request content from the resource operation control device 10 (S403). Then, the capacity allocation unit 353 determines whether the predicted value of the virtual capacity data indicated in the virtual resource capacity prediction result data satisfies the resource request content (S403A). If Yes in S403A, the capacity allocation unit 353 registers the virtual resource determined to satisfy the resource request content received from the resource operation control device 10 in the determination in S403 as one to be used for control operation of the resource operation control device 10, The information is transmitted to the resource operation control device 10 (S405).
  • the control planning unit 354 receives a resource configuration change instruction by outputting control plan generation instruction data that starts a control plan generation process that changes the operation of the real resources 5 that constitute the virtual resource. It is determined whether or not to issue (S403B). If Yes in S403B, the process returns to S401 and the resource configuration is changed, thereby changing the calculation result in S402, which is executed again. If No in S403B, the control planning unit 354 acquires the resource relationship data 359A and generates a control plan for one or more real resources 5 that constitute the virtual resource for which the control plan is to be generated (S404). The generated control plan data is input to the capacity prediction unit 352, thereby changing the calculation result of S402, which is executed again. In this way, regardless of whether the branch result of S403B is Yes or No, the calculation result of S402 to be executed again changes, so there is a possibility that the determination result of S403A to be executed again changes to Yes.
  • the capacity allocation unit 353 outputs virtual resource regeneration instruction data for re-executing the virtual resource formation process to the virtual resource capacity conversion unit 351 in any of the following cases. Then, the process is re-executed from S401. - When the number of times control plan generation instruction data is output to the control planning unit 354 exceeds a predetermined number of times. - When no change can be confirmed in the predicted value of the virtual capacity data obtained from the capacity prediction unit 352.
  • FIG. 5 is a data flow diagram of the virtual resource capability conversion unit 351.
  • the virtual resource capacity conversion unit 351 converts the actual resource measurement data 451A into virtual capacity data.
  • a virtual resource is constructed by combining the virtual capability data, and an identifier indicating the constructed virtual resource and data indicating the capability are output as virtual capability data.
  • FIG. 6 is a table showing an example of resource request content data to be acquired.
  • the table in FIG. 6 stores the following data in each column. ⁇ "Request ID" indicating the identifier of the request content in the first column - "Requesting system name” indicating the name of the resource operation control system that is the source of the request in the second column ⁇ "Request resource name” indicating the name of the requested resource in the third column ⁇ "Request period” indicating the resource request period in the fourth column ⁇ "Requested amount” which shows the requested amount of resources in the 5th column ⁇ "Requirement content” indicating the content of requests for resource quality in the 6th column ⁇ "Request location” indicating the content of the request to the resource supply location in the 7th column
  • the request system name is a request presented by "grid monitoring and control system A.”
  • the requested resource is a "power supply resource”.
  • the request period is one year from 2020/01/01 00:00 to 2021/12/31 23:59.
  • the requested amount is "100 MW or more per hour as a supply amount.”
  • the requested location is "supply to point A”.
  • the required quality is "-", indicating that there is no quality requirement.
  • the request system name is a request presented from "grid monitoring and control system B.”
  • the requested resource is "electricity transport resource”.
  • the request period is one day from "2020/01/01 00:00 to 2021/01/01 23:59”.
  • ⁇ The required amount is "10 MW or more per hour as transportation volume.”
  • -Requirements regarding the quality of resources are ⁇ the permissible range for fluctuations in transport volume is within ⁇ 3%, and the permissible range for transport start and end times is within ⁇ 30 minutes.»
  • the requested location is "transportation from point A to point B.”
  • FIG. 22 is a table showing an example of virtual capability data of each virtual resource.
  • the table in FIG. 22 stores at least the following data in each column.
  • the first column stores data indicating the identifier of the virtual resource created by the virtual resource capability conversion unit 351.
  • the second column stores data indicating the date and time.
  • the third column stores data indicating the value of the virtual capacity of the virtual resource shown in the first column at each date and time shown in the second column.
  • the fourth column stores data indicating the unit of the value of the virtual ability shown in the third column.
  • the fifth column stores data indicating the operation details of the virtual resources shown in the first column at the date and time shown in the second column.
  • the sixth column stores data indicating the operating location of the virtual resource shown in the first column at the date and time shown in the second column.
  • all virtual resource identifiers shown in the first column are "VR001".
  • the dates and times shown in the second column are hourly units ranging from 0:00 on January 1, 2021 to 23:00 on December 31, 2021.
  • the virtual resource ID "VR001” is a virtual resource associated with the request ID "R0001", as shown in FIG.
  • the request ID "R0001” is a request received from the "system monitoring and control system A" shown in the first line of the resource request content data in FIG.
  • the request period is “from January 1, 2021 00:00 to December 31, 2021 23:59”, and the request amount is “supply amount is 100MW/ h or more,” and the requested location is “point A.”
  • the virtual resource ID "VR001” always has a power of 100 MW/h or more from "00:00 on January 1, 2021” to "23:00 on December 31, 2021”. This shows that it has the ability to supply power at point A. Therefore, the request satisfaction evaluation unit 353B determines that the virtual resource "VR001" satisfies the request of the request ID "R0001".
  • FIG. 7 is a table showing an example of the acquired virtualization definition data 357A.
  • the capability conversion definition extraction unit 351A acquires virtualization definition data 357A.
  • the table in FIG. 7 stores the following data in each column. - The first column stores the identifier of the resource request content received from the resource operation control device 10 via the capacity allocation unit 353. - The second column stores the identifier of the virtualization logic that has been set and registered to correspond to the resource request content. - The third column stores data indicating the operation details of the entity resource 5 applied to the processing of the virtualization logic.
  • the first line uses the virtualization logic of "P0001" for the resource request content of "R0001", and converts the real resource measurement data 451A of the real resource 5 whose operation content is "discharge or storage/discharge” into virtual capacity data. This shows that the settings are registered to convert to .
  • the second line shows the following. - Multiple virtualization logics "P0001", “P0002”, and “P0003” are used for the resource request content of "R0002". - First, process each of "P0001” and “P0002”, then input each processing result data to "P0003" and process. - Settings and registration are made so that the actual resource measurement data 451A of the actual resource 5 whose operation content is "discharge or storage/discharge, and movement" is converted into virtual capability data.
  • the fourth line shows the following. - For request ID "R0004", three virtualization logics “P0005", “P0002” and “P0006” are used. - The virtualization logic of "P0002” applies the same logic as the virtualization logic used for request ID "R0002".
  • the capacity conversion definition extraction unit 351A uses the identifier of the resource request content acquired from the capacity allocation unit 353 as a key to acquire the identifier of the virtualization logic and the processing order information from the virtualization definition data 357A shown in FIG. 6, and performs capacity conversion. It is output to section 351B.
  • FIG. 8 is a table showing an example of entity resource constraint data 452A.
  • the capability conversion unit 351B first obtains the entity resource measurement data 451A and the entity resource constraint data 452A from the data management device 4.
  • the table in FIG. 8 stores the following data in each column.
  • the first column is the identifier of the entity resource 5.
  • the second column is data indicating the name of the entity resource 5.
  • the third and subsequent columns are data indicating the contents of the constraint conditions for each entity resource 5.
  • the third column is data indicating the operable contents of each entity resource 5.
  • the fourth column is data indicating whether control of each entity resource 5 can be accepted.
  • the fifth column is data indicating the period and time zone during which each entity resource 5 can operate.
  • the sixth column is data indicating the cost incurred when operating as a virtual resource for each of the real resources 5.
  • the seventh column is data indicating whether or not the constraint data of each entity resource 5 can be changed.
  • the entity resource 5 with the entity resource ID "AR001" and the entity resource name "private car” in the first line shows the following. - Capable of "storage/discharge” and “movement” operations. - Acceptance of control is "not possible”. - The operating hours are from 08:00 to 16:00. - There is no cost incurred when operating as a virtual resource. - This is the entity resource 5 that presents the constraint condition that the above-mentioned constraint contents cannot be changed.
  • entity resource 5 is not necessarily limited to a single casing of physical equipment.
  • a collection of physical equipment cases such as the "factory consumer” indicated by the entity resource ID "AR005", or a collection of multiple entities such as the "virtual resource A" indicated by the entity resource ID "AR007”. It may be an aggregate of resources 5.
  • the capability conversion unit 351B acquires the virtualization logic from the virtualization logic pool 358A using the virtualization logic identifiers “P0001 to P0006, etc.” acquired from the capability conversion definition extraction unit 351A.
  • the capability conversion unit 351B processes the virtualization logic according to the processing order acquired from the capability conversion definition extraction unit 351A.
  • FIG. 7 shows the virtualization definition data 357A obtained from the capability conversion definition extraction unit 351A, and shows the ID of the virtualization logic to be applied and the processing order of the virtualization logic for each identifier of the request content data. This is the data. For example, it is shown that the setting is to apply the virtualization logic of "P0001" to the request ID "R0001" shown in the first line of FIG. 7. Therefore, the capability conversion definition extraction unit 351A acquires the virtualization logic of "P0001" from the virtualization logic pool 358A and places it in the capability conversion unit 351B.
  • FIG. 9 is an explanatory diagram of the processing of the virtualization logic of "P0001" placed in the acquired capability conversion unit 351B.
  • the virtualization logic "P0001 (351B1)" placed in the capacity conversion unit 351B acquires the actual resource measurement data 451A from the data management device 4 in the remaining charge estimation unit 351B11, and estimates the time series data of the remaining charge.
  • the acquired entity resource measurement data 451A is indicated as “discharge or storage/discharge” in "operation content” in FIG.
  • the remaining charge amount estimating unit 351B11 calculates whether "AR001,”"AR002,”"AR003,”"AR004,” or "AR005" is indicated as “electricity storage or storage/discharge” in the "operable content" of the entity resource constraint data in FIG. ”, “AR006”, and “AR007”.
  • the remaining charge estimating unit 351B11 performs the remaining charge estimation process by executing the following (estimation method 1) or (estimation method 2) on the acquired entity resource measurement data 451A of each entity resource 5. Execute. (Estimation method 1) If the acquired actual resource measurement data 451A is the time series data of the remaining charge level itself, it is output as is. (Estimation method 2) If the acquired physical resource measurement data 451A is time-series data of the charging history of the charger or time-series data of the charging history of each device such as an electric vehicle connected to the charger, from the start to the end of charging Calculate the amount of charge up to.
  • the value obtained by dividing the calculated amount of charge from the past maximum amount of charge is calculated as the remaining amount of charge at the time of starting charging.
  • the remaining amount of charge during charging is estimated as the remaining amount of charge using the amount of charge. From the end of charging to the end of connection to the charger, the total value of the remaining charge at the time of charging start and the amount of charge charged during charging is estimated as the charge amount.
  • the minimum remaining amount estimating unit 351B12 acquires the time series data of the estimated value of the remaining charging amount from the past to the latest date and time outputted by the remaining charging amount estimating unit 351B11 and the entity resource constraint data 452A, and calculates the charging of the relevant entity resource 5. Estimate the minimum allowable remaining amount. Specifically, the minimum value in the time-series data of estimated values of remaining charge from the past to the latest date and time outputted by the remaining charge estimation unit 351B11 is estimated as the minimum allowable value of the remaining charge of the relevant entity resource 5. . Furthermore, if there is data indicating a constraint on the minimum permissible value of the remaining charge of the resource in the actual resource constraint data 452A, the value of the constraint is estimated as the minimum permissible value of the remaining charge of the resource.
  • the power supply capacity calculation unit 351B13 uses the time series data of estimated values of the remaining charge amount from the past to the latest date and time outputted by the remaining charge estimating unit 351B11, and the minimum allowable remaining charge amount outputted by the minimum remaining amount estimating unit 351B12. The value is acquired, and the power supply capacity of the entity resource 5 is calculated.
  • FIG. 13 is a graph showing virtual ability data for specifically explaining "P0001" in FIG.
  • the white (unpainted) bar graph shown in the left diagram of FIG. 13 represents time-series data of the estimated value of the remaining charge of the entity resource 5 from the past to the latest date and time output by the remaining charge estimating unit 351B11. It shows.
  • a dotted line (1303) in the figure indicates the minimum allowable remaining charge amount estimated and output by the minimum remaining amount estimating unit 351B12.
  • power can be supplied (reverse current).
  • the gray (filled) bar graph shown on the right side of FIG. 13 is a graph showing virtual capacity data of power supply capacity.
  • the power supply capacity calculation unit 351B13 converts into data indicating the power supply capacity shown in 1304 and 1305 in the right diagram during time periods 1301 and 1302 when the battery is connected to the charger after charging is completed. Note that when the power supply capacity calculation unit 351B13 calculates data indicating the power supply capacity, for the entity resource 5 for which there is a constraint related to operation in the acquired entity resource constraint data 452A, the power supply is calculated after satisfying the constraint. Convert to data indicating supply capacity. For example, in the entity resource constraint data 452A shown in FIG.
  • the operating time zone of the entity resource "AR001" is shown as "08:00 to 16:00.” Therefore, in time periods other than this time period, the data indicating the power supply capacity converted from the actual resource measurement data 451A of the relevant actual resource 5 is always converted to zero.
  • the capability conversion definition extraction unit 351A acquires the virtualization logics "P0001,” "P0002,” and "P0003” from the virtualization logic pool 358A, and arranges them in the capability conversion unit 351B according to the set processing order.
  • FIG. 10 is an explanatory diagram in which the virtualization logic of "P0001", “P0002”, and “P0003” is arranged in the capability conversion unit 351B.
  • the virtualization logic “P0001 (351B1)” placed in the capacity conversion unit 351B includes a remaining charge estimation unit 351B11.
  • the remaining charge estimating unit 351B11 performs the actual resource measurement of the actual resource 5 that matches "discharging or storing/discharging and moving" shown in the operation content data shown in the third column of the request ID "R0002" in FIG.
  • Data 451A is acquired from the data management device 4.
  • the remaining charge estimating unit 351B11 estimates time-series data of the power supply capacity of each entity resource 5 using the acquired entity resource measurement data 451A.
  • "P0001 (351B1)" here is the same as "P0001 (351B1)” described above, and data indicating the power supply capacity is calculated by the aforementioned processing procedure.
  • the stop location estimating unit 351B21 of the virtualization logic "P0002 (351B2)" selects "discharge or storage/discharge and movement" as shown in the operation content data shown in the third column of the request ID "R0002" in FIG.
  • the entity resource measurement data 451A of the matching entity resource 5 is acquired from the data management device 4. Then, the stop location estimating unit 351B21 estimates time-series data of the departure location of each entity resource 5 at the time of movement using the acquired entity resource measurement data 451A.
  • the method for estimating time series data is, for example, when the entity of the entity resource measurement data 451A is time series data of latitude and longitude information for each time such as GPS, the time spent at the same latitude and longitude in a predetermined time width. The band and position are extracted and the corresponding position is estimated as the stopping place.
  • the transportation capacity calculation unit 351B22 inputs the time-series data from the past to the present of the stop location of the entity resource 5 calculated by the stop location estimation unit 351B21, and converts it into data indicating the movement capacity of the entity resource 5.
  • the stop location estimating unit 351B21 estimates that the vehicle has the ability to "collect" some kind of cargo at a certain estimated stop location during the time the vehicle is stopped at the stop location.
  • the stop location estimating unit 351B21 estimates that the cargo has the ability to "arrive” at the next stop, and estimates that it has the ability to "transport” the cargo between the two stops. , converted into data indicating the above-mentioned series of transport capacities.
  • the power transport capacity calculation unit 351B31 of "P0003 (351B3)" inputs the data indicating the power supply capacity, the data indicating the movement capacity, and the entity resource constraint data 452A calculated by P0001 and P0002, respectively.
  • the power transport capacity calculation unit 351B31 converts it into data indicating the power transport capacity of the entity resource 5.
  • FIG. 14 is a graph for specifically explaining "P0001", “P0002", and "P0003" in FIG. 10.
  • a graph 1401 shows time-series data of the remaining charge of a certain entity resource 5 estimated by the remaining charge estimation unit 351B11 of P0001.
  • the power supply capacity calculation unit 351B13 inputs the time series data of the estimated remaining charge amount shown in the graph 1401, and calculates the data shown in the graph 1402 as data indicating the power supply capacity of the entity resource 5.
  • the entity resource 5 is being charged with electricity from a charger in a time period 1401A in the graph 1401.
  • the power supply capacity calculation unit 351B13 calculates the negative supply capacity shown in the time period 1402A of the graph 1402, assuming that the entity resource 5 "has a negative supply capacity" in the time period.
  • the power supply capacity calculation unit 351B13 estimates that the entity resource 5 is connected to the charger but is not being charged, and is not charged through the charger during the time period. It is assumed that it has the ability to supply the remaining amount of electricity (reverse flow). As a result, a positive supply capacity is calculated as shown in time zone 1402B of graph 1402.
  • the positive supply capacity is calculated so as to decay over time.
  • the degree of attenuation may be calculated based on the specification information of the amount of power supplied per hour of the relevant entity resource 5, which is obtained in advance. Alternatively, it may be calculated based on the specification information of an entity resource 5 of the same type as the entity resource 5 in question, it may be estimated from data on the past power supply capacity of the entity resource 5 in question, or it may be estimated from data on the past power supply capacity of the entity resource 5 in question, It may also be calculated according to coefficients.
  • a graph 1403 shows time-series data of the stop location and stop time of the entity resource 5 estimated by the stop location estimation unit 351B21 in P0002 (351B2).
  • P0002 estimates data indicating the transportation capacity of the entity resource 5 from the result data of the estimated stop location shown in the graph 1403.
  • the entity resource 5 in question has the ability to "collect cargo” while stationary at point A (time period 1404A).
  • time period 1404B it is estimated that it has the ability to "transport” the collected cargo
  • time period 1404C time period 1404C
  • the power transport capacity calculation unit 351B31 of P0003 calculates the data (graph 1402) indicating the power supply capacity of the entity resource 5 calculated by P0001 and the data (graph 1404) indicating the transportation capacity of the entity resource 5 calculated by P0002. and entity resource constraint data 452A are input and converted into data indicating the power transport capacity shown in graph 1405.
  • 1402A of the graph 1402 is estimated to have a negative supply capacity (charging) at point A, and at the same time, as shown in time period 1404A of the graph 1404, it is assumed that the point A has the ability to collect goods. Estimated.
  • the power transport capacity calculation unit 351B31 estimates that the relevant entity resource 5 has the ability to load the cargo of electricity at point A during the relevant time period, as shown in the time period 1405A of the graph 1405. .
  • the point B has a positive supply capacity (reverse tide)
  • the ability to arrive at the point B is estimated to be positive. It is estimated that the
  • the power transport capacity calculation unit 351B31 estimates that the relevant entity resource 5 has the ability to unload the cargo of electricity at point B during the relevant time period, as shown in the time period 1405B of the graph 1405. . Then, the power transport capacity calculation unit 351B31 calculates that the resource shown in the time period 1404B of the graph 1404 has the ability to transport cargo in the time period when moving from point A to point B. It is assumed that the company has the ability to load the cargo of electricity at A, transport it to point B, and unload it at point B.
  • the request ID "R0003" shown in the third line of FIG. It is defined so that it can be applied to virtual ability data.
  • FIG. 11 is an explanatory diagram of the processing of the virtualization logic of "P0004" placed in the acquired capability conversion unit 351B.
  • the renewable energy supply capacity calculation unit 351B41 located at P0004 (351B4) acquires the entity resource measurement data 451A and the entity resource constraint data 452A from the data management device 4. Then, the renewable energy supply capacity calculation unit 351B41 inputs the acquired entity resource measurement data 451A and entity resource constraint data 452A, and converts them into data indicating the renewable energy supply capacity of each entity resource 5.
  • the value of the amount of electricity derived from renewable energy is determined from the data of the remaining amount of electricity stored or the amount of discharge.
  • the separated value is calculated as data indicating the supply capacity of renewable energy.
  • a known method such as traceability of power generation amount of renewable energy may be applied to the method of separating the value of the amount of power derived from renewable energy.
  • the data stored in the actual resource measurement data 451A is originally actual data on the amount of power generated by renewable energy, the actual data is output as is.
  • the request ID "R0004" shown in the fourth line of FIG. 7 applies the entity resource measurement data 451A of entity resource 5 whose operation content is "freight transportation" to the virtualization logic of "P0005,” “P0002,” and “P0006.” It is defined in such a way that it is converted into virtual ability data.
  • FIG. 12 is an explanatory diagram of the processing of the virtualization logic of "P0005", "P0002", and "P0006” placed in the acquired capability conversion unit 351B.
  • P0005 (351B5) placed in the capability conversion unit 351B acquires the actual resource measurement data 451A from the data management device 4.
  • the entity resource measurement data 451A to be acquired is based on "Freight Transportation” shown in the operation content in the third column of FIG. At least the entity resource measurement data 451A of the entity resource ID "AR003" written as "AR003" is acquired.
  • the free capacity estimating unit 351B51 of P0005 inputs the entity resource measurement data 451A and estimates the free capacity of each entity resource 5 at each time. For example, if the measurement data content of the entity resource measurement data 451A is the number of passengers measured at each time or at each specific point, the number of passengers who can ride the vehicle is calculated by dividing the number of passengers from the maximum number of passengers of the entity resource 5 at each time or at each specific point. It is calculated for each location and output as the estimated free capacity.
  • the capacity cargo conversion unit 351B52 included in P0005 generates a function for calculating the possible loading capacity of cargo from the free capacity of the entity resource 5.
  • the method of generating the function is, for example, if the free capacity is ⁇ 10 people'', the possible cargo loading capacity is ⁇ 5 pieces of 80cm size cargo'', and if there are ⁇ 5 people'', the possible cargo loading capacity is ⁇ 80cm size cargo''.
  • a method of identifying a model that uses a regression model to calculate the possible loading amount of cargo for free space may also be used.
  • the cargo loading capacity calculation unit 351B53 then inputs the data indicating the free capacity calculated by the free capacity estimating unit 351B51 into a function that calculates the possible cargo loading capacity from the free capacity calculated by the capacity cargo conversion unit 351B52. , calculates data indicating the possible cargo loading capacity of the relevant entity resource 5.
  • the possible loading capacity of cargo is calculated as zero during a time period where the constraint conditions of the entity resource 5 shown in the entity resource constraint data 452A cannot be satisfied.
  • P0006 (351B6) placed in the capacity conversion unit 351B contains data indicating the cargo loading capacity calculated by P0005, data indicating the transport capacity calculated by P0002, and entity resource constraint data in the cargo transportation capacity calculation unit 351B61.
  • 452A is input, and data indicating the cargo transportation capacity of each entity resource 5 is calculated.
  • the calculation method is, for example, if the cargo carrying capacity at time T is "5 pieces of 80 cm size cargo", the transport capacity at time T is "collection", and the transport capacity at time T+N is "arrival".
  • the relevant entity resource 5 is calculated as having a cargo transportation capacity to transport "5 pieces of 80 cm cargo" from time T to time T+N.
  • the capacity conversion unit 351B converts the measurement data of each entity resource 5 stored in the entity resource measurement data 451A into virtual capacity data according to the resource request content data acquired from the capacity allocation unit 353. do.
  • the resource forming unit 351C generates one virtual capacity data by summing up the virtual capacity data of each entity resource 5 output by the capacity converting unit 351B at each time, and generates one virtual capacity data, and adds the identifier of the virtual resource and the entity configuring the virtual resource. Data including the identifier of the resource 5 and virtual capability data is output to the capability prediction unit 352 as virtual resource data.
  • the resource forming unit 351C may select all the actual resources 5 output by the capability conversion unit 351B as a method of selecting the actual resources 5 to be added to the virtual resource (corresponding to the virtual resource), or may select some of the actual resources 5 output by the capability converting unit 351B.
  • the entity resource 5 may be selected.
  • the resource forming unit 351C selected "AR001" as the actual resource 5 that corresponds to at least one of the following for the request content of the request R0001 corresponding to the virtual resource VR001. ⁇ Substantive resources that can provide the ability to meet the requested content 5 ⁇ Substantive resources that can provide capabilities within the required period 5 ⁇ Substantive resources 5 that meet the required cost
  • the resource forming unit 351C selects the actual resource 5 to be incorporated into the virtual resource using the predicted value that is the calculation result of the capacity prediction unit 352 instead of the actual measurement value that is the calculation result of the capacity conversion unit 351B.
  • the resource forming unit 351C may calculate the expected value of the predicted value of the virtual capacity data at any future date and time of the virtual resource calculated by the capacity prediction unit 352, the predicted value of the quantile such as the 25% quantile, and the confidence interval.
  • the actual resource 5 may be selected such that the estimated value of the interval, such as the prediction interval or the predicted interval, satisfies a predetermined threshold or a quality condition specified in the resource request content data.
  • the resource forming unit 351C outputs control data that instructs the capacity predicting unit 352 to return prediction result data.
  • the control data is output until the prediction result data of the virtual ability data exceeds a predetermined threshold or until the difference in change between the previous and current values of the prediction result data falls below a predetermined value.
  • the resource forming unit 351C may configure the virtual resource so that the interval estimated value such as the confidence interval or prediction interval of the predicted value of the virtual capacity data at any future date and time of the virtual resource calculated by the capacity prediction unit 352 is minimized. You may select the entity resources 5 to be incorporated into.
  • the resource forming unit 351C outputs control data that instructs the capacity predicting unit 352 to return prediction result data. The control data is output until the prediction result data of the virtual ability data exceeds a predetermined threshold or until the difference in change between the previous and current values of the prediction result data falls below a predetermined value.
  • the resource is formed so that at least one of the expected value, quantile predicted value, and section predicted value of the predicted value of the capacity of the virtual resource at a predetermined date and time calculated by the capacity prediction unit 352 satisfies a predetermined reference value.
  • the unit 351C may select the actual resource 5 to be incorporated into the virtual resource.
  • the virtual resource capability conversion unit 351 constructs a virtual resource by combining a plurality of pre-stored virtualization logics so as to satisfy the capability aspect of the actual resource required by the resource operation management system.
  • the virtual resource capability converter 351 constructs a virtual resource based on the predicted value of the virtual capability data calculated by the capability predictor 352.
  • the virtual resource capability conversion unit 351 ensures that the information indicating the attributes of the virtual resource (controllability and cost) generated based on the information indicating the constraint conditions of each entity resource 5 satisfies predetermined criteria.
  • the combination of real resources 5 that make up the virtual resource may be determined. This makes it possible to form a virtual resource that minimizes uncertainty in the amount and quality of the capacity of the virtual resource.
  • FIG. 15 is a table showing an example of resource related data 359A.
  • the table in FIG. 15 stores the following data in each column.
  • the first column stores identifier data for identifying each virtual resource formed by the resource forming unit 351C.
  • the second column stores data of the identifier of the real resource 5 that constitutes the virtual resource.
  • the third and fourth columns store the start date and time and end date and time at which each real resource 5 is associated as a component of each virtual resource.
  • the table in FIG. 15 stores the following data in each row.
  • the virtual resource ID "VR001” is associated with the entity resource "AR001” as a component, and the period during which the entity resource "AR001” is a component is "2021/01/01 13: 24” to “2021/01/01 14:43”.
  • the virtual resource "VR002" on the second line is associated with the real resource 5 "AR002" as a component.
  • "AR003" is also associated with the virtual resource "VR002" as a component in a different time zone from “AR002".
  • the resource forming unit 351C forms a virtual resource such that a plurality of real resources 5 serve as constituent elements in the same or different time periods for one virtual resource.
  • the actual resource "AR003" that constitutes the virtual resource "VR002” is also shown to be the actual resource 5 that constitutes the virtual resource "VR005" shown in the seventh line. As shown in the periods in the third and fourth columns, it also shows that "AR003" is configured into multiple virtual resources “VR002" and "VR005" at the same time.
  • the virtual resource "VR002” is a virtual resource created for the purpose of providing the requested resource "power transport resource” shown in the second line of the resource request data in FIG. 6, and "VR005" is a virtual resource shown in FIG. 6. This is a virtual resource created for the purpose of providing the "freight transportation resource" shown in the fifth line of the resource request data.
  • the entity resource "AR003” is the entity resource name "customer bus” as shown in the third line of the entity resource constraint data 452A in FIG. 8, and the operation content is "storage/discharge, movement, freight transportation".
  • "AR003" is an actual resource 5 that can simultaneously provide two virtual resources of "ability to transport electricity using rechargeable batteries” and “capacity to transport cargo using passenger space” in the state of movement. be. Therefore, the resource formation unit 351C simultaneously configures the entity resource 5 of "AR003", which has data indicating "power transport capability” and "freight transport capability", into “VR002" and "VR005" at the same time. It shows that there is.
  • the virtual resource capability conversion unit 351 has been explained above.
  • FIG. 16 is a data flow diagram of the ability prediction unit 352.
  • the capacity prediction unit 352 inputs the virtual capacity data output by the virtual resource capacity conversion unit 351 and the factor data 453A, and outputs a predicted value of the virtual capacity data at a predetermined future date and time.
  • the model identification unit 352A inputs the virtual capacity data and factor data 453A output by the virtual resource capacity conversion unit 351, and inputs the values of the virtual capacity data using the values of each factor included in the factor data 453A. Identify the predictive model to output.
  • a known method may be applied to the prediction model identification method. The known method is, for example, any of the following methods.
  • ⁇ Methods that assume linearity such as linear regression models such as multiple regression models and generalized linear models such as logistic regression
  • ⁇ Methods that assume autoregressiveness such as ARX (AutoRegressive with Exogenous) models
  • ARX AutoRegressive with Exogenous
  • Methods that use reduction estimators such as ElasticNet - Methods that use dimension reducers such as partial least squares and principal component regression - Nonlinear models using polynomials, support vector regression, regression trees, Gaussian process regression, and neural networks
  • Regression model methods called non-parametric methods such as ⁇ Not only inductive or interpolation methods such as regression model methods, but also deductive or extrapolation methods such as agent simulation may be used.
  • model identification unit 352A receives input of control plan data for the entity resource 5 created by the control planning unit 354 that has received the activation signal from the capacity allocation unit 353, the model identification unit 352A performs control planning for the entity resource 5 in the prediction model identification process.
  • Planning data is also used. For example, the initial state of operation at time T of the entity resource "AR00X” whose control acceptability is "possible” is “not in operation", and therefore the value of the virtual capacity data is initially zero. think of.
  • the model identification unit 352A generates a virtual After changing the value of the ability data to "a value greater than zero", the predictive model identification process is executed. For example, the following method is used to change the value of the virtual ability data. - A method for changing the virtual ability data to the same value as the value at the closest time to time T. - A method for changing to a predetermined value. - A method for changing the value of the time and factor data 453A to the same value as the value of a similar past date and time, or an average value. How to change
  • the predicted value calculation unit 352B calculates prediction result data of the value of the virtual ability data by inputting the observed value or predicted value of the factor data 453A of the prediction target date and time to the prediction model output by the model identification unit 352A.
  • the format of the predicted result data to be calculated includes an expected value, a predicted value of a quantile such as a 25% point, and an interval estimate such as a confidence interval or a predicted interval.
  • the calculated prediction result data is output to the capacity allocation section 353.
  • control data indicating an instruction to return prediction result data is input from the virtual resource capacity conversion unit 351
  • the prediction result data is output to the virtual resource capacity conversion unit 351 instead of the capacity allocation unit 353.
  • the virtual resource capacity conversion unit 351 that receives the prediction result data re-changes the configuration of the real resource 5 associated with the virtual resource using the prediction result data, as described in the resource formation unit 351C.
  • the prediction result data is output to the capacity allocation unit 353. With this, the operation of the ability prediction unit 352 ends.
  • FIG. 17 is a data flow diagram of the capacity allocation unit 353.
  • the capacity allocation unit 353 inputs data indicating resource request details from the resource operation control device 10 and outputs resource request content data to the virtual resource capacity conversion unit 351 . Thereafter, the capacity allocation unit 353 inputs the prediction result data of the virtual capacity data from the capacity prediction unit 352 and outputs data indicating that the virtual resource is set to be used for operational control of the resource operation control device 10.
  • the resource request data generation unit 353A acquires data indicating the content of the resource request from the resource operation control device 10, and generates resource request content data as shown in FIG.
  • the generated resource request content data is output to the virtual resource capacity conversion unit 351, and thereafter, as explained above, the virtual capacity conversion unit 351 outputs virtual capacity data, and then the capacity prediction unit 352 outputs virtual capacity data. Output the prediction result data.
  • the requirement sufficiency evaluation unit 353B inputs the prediction result data of the virtual capacity data outputted by the capacity prediction unit 352, inputs the resource request content data outputted by the resource request data generation unit 353A, and generates the prediction result data of the virtual capacity data. Determine whether or not the content of the resource request is satisfied.
  • the resource request content of the request ID "R0001" shown in the first line of FIG. 6 has a request period of "2021/01/01 00:00 to 2021/12/31 23:59" and a request amount of " When the supply amount is "100 MW or more per hour” and the requested location is "supply to point A", it is determined whether the prediction result data of the virtual capacity data output by the capacity prediction unit 352 satisfies each request. do.
  • the request sufficiency evaluation unit 353B If it is determined that the request sufficiency evaluation unit 353B is satisfied, the request sufficiency evaluation unit 353B generates request resource correspondence data (FIG. 18) indicating the correspondence between the resource request input from each resource operation control device 10 and the virtual resource.
  • the requested resource correspondence data is, for example, data that associates the virtual resource "VR001" in FIG. 20 with the request ID "R0001".
  • FIG. 18 is a table showing an example of request resource correspondence data.
  • the table in FIG. 18 stores the following data in each column.
  • the first column stores data indicating the identifier of the virtual resource created by the virtual resource capability conversion unit 351.
  • the second and third columns store data indicating the start date and time and end date and time when each virtual resource becomes available.
  • the fourth column stores data indicating whether or not the virtual resource can accept control.
  • the fifth column stores data indicating the identifier of the request from the resource operation control device 10 set by the request sufficiency evaluation unit 353B to provide each virtual resource.
  • the sixth column stores data indicating the characteristics of the virtual resource, and in the example of FIG. 18, the response speed, which is the time from receiving the control signal to reaching the predetermined control amount, is shown. .
  • the first row of the table in FIG. 18 shows that the virtual resource ID "VR001" can be used during the period "2021/01/01 00:00 to 2021/12/31 23:59", and control acceptance is "unavailable”. ” indicates that it is a virtual resource.
  • This virtual resource is determined to satisfy the request with the request ID “R0001” as a result of the determination process by the request satisfaction evaluation unit 353B, and therefore, as shown in the fifth column, it is determined that it is associated with the corresponding request “R0001”. It shows that it is set to .
  • the seventh line of the table in FIG. 18 indicates that the virtual resource ID "VR007" is not associated with any response request, that is, it is an idle virtual resource.
  • the request satisfaction evaluation unit 353B determines whether or not the prediction result data of each virtual capacity data satisfies each resource request content, and if it satisfies each resource request content, is set in association with the ID of each resource request content data.
  • the set request resource correspondence data is sent to the resource operation control device 10, and the resource operation control device 10 determines whether or not to operate the input virtual resource. Sends signal data to execute operation control.
  • the resource virtualization device 3 is a controllable virtual resource and requires control
  • the resource virtualization device 3 transmits a control signal through the control planning unit 354 to the real resource 5 that constitutes the virtual resource.
  • the request satisfaction evaluation unit 353B determines that the prediction result data of the virtual capacity data does not satisfy the resource request content shown in the resource request content data, and the virtual resource in question is a controllable virtual resource. If so, data indicating the content of the sufficiency violation and data indicating an instruction to create a control plan for the virtual resource are output to the control planning unit 354.
  • the control planning unit 354 receives the input data indicating the instruction to create a control plan, and performs control on the controllable entity resources 5 among the entity resources 5 constituting the virtual resource so that the sufficiency violation is resolved. Generate planning data.
  • the created control plan data is input to the capacity prediction section 352 as described above, and the prediction result data of the virtual capacity data is recalculated in the capacity prediction section 352.
  • the request sufficiency evaluation unit 353B performs the determination again. The above operation is repeated until the request satisfaction evaluation unit 353B determines that the resource request content is satisfied or until a predetermined number of times is exceeded.
  • the request satisfaction evaluation unit 353B performs a virtual resource capacity conversion unit.
  • data indicating the content of the sufficiency violation and data indicating an instruction to create a control plan for the virtual resource are output to the control planning unit 354.
  • the virtual resource capability conversion unit 351 which receives the input of the data indicating the instruction to change the configuration of the real resource 5, changes the real resource 5 making up the virtual resource so as to eliminate the request violation.
  • the prediction result data of the virtual capability data is recalculated, and the request satisfaction evaluation section 353B uses the recalculated prediction result data. Make the judgment again. The above operation is repeated until the request satisfaction evaluation unit 353B determines that the resource request content is satisfied or until a predetermined number of times is exceeded. With this, the operation of the capacity allocation section 353 is completed.
  • the control planning unit 354 starts its operation upon input of data indicating support for generation of a control plan from the capacity allocation unit 353.
  • the control planning unit 354 outputs the data indicating the identifier of the virtual resource for which the control plan is to be generated, the data indicating the content of the fulfillment violation of the resource request content, the resource relationship data 359A, and the actual resource constraint data 452A, output by the capacity allocation unit 353.
  • the control plan data of the entity resource 5 is output.
  • the control planning unit 354 inputs the identifier of the virtual resource for which a control plan is to be generated and the resource relationship data 359A from the capacity allocation unit 353. Then, using the identifier of the virtual resource for which the control plan is to be generated as a key, the identifier of the real resource 5 constituting the virtual resource is acquired from the resource relationship data 359A. Next, the control planning unit 354 inputs the entity resource constraint data 452A, and uses the identifier of the entity resource 5 obtained in the above operation as a key to obtain data indicating the constraint conditions of each entity resource 5 from the entity resource constraint data 452A. .
  • control planning unit 354 generates and outputs a control plan for each of the extracted entity resources 5 so that the fulfillment violation of the resource request content output by the capacity allocation unit 353 is resolved.
  • the control planning unit 354 acquires "AR002" and "AR003", which are the identifiers of the real resources 5 that constitute the virtual resource "VR002”, from the resource relationship data 359A shown in FIG. 15.
  • the control planning unit 354 acquires data indicating the contents of the constraint conditions of the entity resources "AR002” and “AR003” from the entity resource constraint data 452A shown in FIG. Extract “AR002” which is entity resource 5.
  • the actual resource "AR002" shown in the second line of the resource related data 359A in FIG. This indicates that it is not operating at the "time 17:00” indicated.
  • the active time period of the entity resource "AR002” shown in the second line of the entity resource constraint data 452A in FIG. The operation at the indicated "time 17:00" satisfies the constraints of the entity resource "AR002".
  • the control planning unit 354 determines that at "time 17:00" indicated in the data indicating the content of the sufficiency violation, "the predicted value of the data indicating the ability is insufficient” indicated in the data indicating the content of the sufficiency violation. Generate control plan data for operating the entity resource "AR002" so as to resolve the issue. The generated control plan data is input to the capacity prediction section 352. Thereafter, the operations described above are performed. In addition, when the resource operation control device 10 inputs data indicating execution of operation control of a virtual resource to the resource virtualization device 3, the control planning unit 354 controls the control device of the real resource 5 based on the control plan data described above. Send control signals.
  • control planning unit 354 is completed, and at the same time, the calculation processing of the resource virtualization system 2 in this embodiment is completed.
  • the virtual resource capability conversion unit 351 in the above embodiment determines the real resources 5 constituting the virtual resource based on the prediction result data of the virtual capability data output by the capability prediction unit 352.
  • the determination is not limited to this explanation, and may be determined according to the state of the virtual ability data from the past to the latest date and time. For example, when the time-series data of the virtual capacity data of each entity resource 5 from the past to the latest date and time are summed up, the time-series data indicating the summed capacity as a virtual resource is configured to have stationarity. Good too. With this configuration, the constancy of the virtual ability data is ensured, and the prediction accuracy of the virtual ability data in the ability prediction unit 352 is improved or stabilized.
  • the determination is not limited to the virtual capacity data alone, but may be determined using data indicating the attributes of the virtual resource as an index.
  • the controllability conditions described in the entity resource constraint data 452A it may be configured with only the entity resources 5 that are controllable or only the entity resources 5 that are not controllable. With this configuration, it becomes possible to manage the virtual resources by separating the reliability and uncertainty of provision of the capacity and quality of the virtual resources.
  • the configuration may be configured such that the total cost of each entity resource 5 constituting the virtual resource is minimized by referring to the "cost" constraint condition of each resource shown in the entity resource constraint data 452A. . With this configuration, it is possible to minimize the cost of moving virtual resources.
  • the capacity allocation unit 353 in the above embodiment has been described on the assumption that the created virtual resource always corresponds to one of the resource request contents.
  • the present invention is not limited to this explanation, and a virtual resource may exist even when there is no corresponding resource request content.
  • a virtual resource that satisfies the currently existing resource request content or the resource request content that existed in the past is created using the virtual resource capacity conversion unit 351, the capacity prediction unit 352, and the control planning unit 354, but the capacity allocation unit 353
  • the resource request to be allocated may be set to "none". As a result, when a similar resource request is newly input from the resource operation control device 10, the virtual resource can be provided immediately, and the control response in the resource operation control device 10 can be improved.
  • the control planning unit 354 in the above embodiment has been described as generating a control plan for an entity resource.
  • the present invention is not limited to this explanation, and a control plan for virtual resources may also be generated.
  • the control planning unit 354 starts its operation upon receiving control plan generation instruction data from the capacity allocation unit 353. From the requested resource correspondence data shown in FIG. 18, the control planning unit 354 identifies virtual resources that have not been allocated to a request and are not scheduled to operate, or virtual resources that have already been allocated and are currently trying to satisfy. Extract virtual resources that can be simultaneously satisfied.
  • the control planning unit 354 incorporates the extracted virtual resource into the virtual resource corresponding to the request that is currently being satisfied. As a result, it is possible to improve the utilization rate of already configured virtual resources, and at the same time, it is possible to increase the possibility of satisfying requests.
  • the capacity prediction unit 352 in the above embodiment has been described as performing prediction processing using the virtual capacity data outputted by the virtual resource capacity conversion unit 351 as is.
  • the capability prediction unit 352 separates the virtual capability data corresponding to controllable real resources from the virtual capability data corresponding to uncontrollable real resources, and Prediction processing may be performed using virtual capability data corresponding to real resources.
  • the predicted data of the virtual capacity data corresponding to the controllable entity resource is calculated as a planned control amount based on the control plan for the entity resource generated by the control planning unit 354, and Final prediction result data is calculated by adding up the prediction result data of the virtual capacity data corresponding to the resource.
  • FIG. 21 is a hardware configuration diagram of the resource virtualization system 2.
  • Each device of the resource virtualization system 2 is configured as a computer 900 having a CPU 901, a RAM 902, a ROM 903, an HDD 904, a communication I/F 905, an input/output I/F 906, and a media I/F 907.
  • Communication I/F 905 is connected to external communication device 915.
  • the input/output I/F 906 is connected to the input/output device 916.
  • the media I/F 907 reads and writes data from the recording medium 917.
  • the CPU 901 controls each processing unit by executing a program (also called an application or an abbreviation thereof) read into the RAM 902 .
  • This program can also be distributed via a communication line or recorded on a recording medium 917 such as a CD-ROM.
  • each of the above-mentioned configurations, functions, processing units, processing means, etc. may be partially or entirely realized in hardware by, for example, designing an integrated circuit.
  • each of the configurations, functions, etc. described above may be realized by software by a processor interpreting and executing programs for realizing the respective functions.
  • Information such as programs, tables, and files that realize each function can be stored in memory, recording devices such as hard disks, SSDs (Solid State Drives), IC (Integrated Circuit) cards, SD cards, DVDs (Digital Versatile Discs), etc. can be stored on any recording medium. It is also possible to utilize the cloud. Further, the control lines and information lines are shown to be necessary for explanation purposes, and not all control lines and information lines are necessarily shown in the product. In reality, almost all configurations may be considered to be interconnected. Furthermore, the communication means for connecting each device is not limited to wireless LAN, but may be changed to wired LAN or other communication means.
  • Resource operation management system 1 Resource operation management system 2 Resource virtualization system (resource management device) 3 Resource virtualization device 4 Data management device 5 Real resource 6 Measurement device 7 Monitoring control device 8 Information input/output terminal 9 Information distribution device 10 Resource operation control device 11 Communication path 12 Control target equipment 31 CPU 32 Input device 33 Output device 34 Communication device 35 Storage device 41 CPU 42 Input device 43 Output device 44 Communication device 45 Storage device 351 Virtual resource capacity conversion section 352 Capacity prediction section 353 Capacity allocation section 354 Control planning section 451A Real resource measurement data

Abstract

A resource virtualization system (2) has: a virtual resource ability conversion unit (351) that, from substantial resource measurement data (451A) obtained by measuring a substantial resource (5) which is a facility related to energy, creates, on the basis of a virtualization logic for virtualizing the substantial resource (5), virtual ability data indicating the ability of the substantial resource (5) to make provision as a virtual resource and constructs a virtual resource for providing the virtual ability data; and an ability assignment unit (353) that, by assigning the virtual resource constructed by the virtual resource ability conversion unit (351) to a resource operation management system (1), causes the resource operation management system (1) to manage the substantial resource (5). The virtualization logic is individually prepared depending on resource request detail data indicating the ability mode of the substantial resource (5) requested by the resource operation management system (1) that is a destination of assignment.

Description

リソース管理装置、リソース管理方法、および、リソース管理プログラムResource management device, resource management method, and resource management program
　本発明は、リソース管理装置、リソース管理方法、および、リソース管理プログラムに関する。 The present invention relates to a resource management device, a resource management method, and a resource management program.
　太陽光発電等の再生可能エネルギーは、天候の状況や時間帯によって出力が変動することが知られている。出力の変動を吸収し、再生可能エネルギーにより発電した電気を最大限有効活用するためには、電力系統に広くかつ大量に分散しているエネルギーに関わる設備を効率的に管理し制御することが重要となる。
　特許文献１には、エネルギーの需要予測値と供給予測値に基づいて、発電機・蓄電器・水素貯蔵器等の分散エネルギー機器を制御する方法が開示されている。特許文献１によれば、種類の異なる複数のエネルギー装置であるリソースを統合的に制御することで、太陽電池を電源とするシステムにおいて最適なエネルギー運用を可能とする。 It is known that the output of renewable energy such as solar power generation fluctuates depending on weather conditions and time of day. In order to absorb fluctuations in output and make the most effective use of electricity generated by renewable energy, it is important to efficiently manage and control energy-related equipment that is widely distributed in large quantities in the power system. becomes.
Patent Document 1 discloses a method of controlling distributed energy devices such as a generator, a power storage device, and a hydrogen storage device based on a predicted energy demand value and a predicted energy supply value. According to Patent Document 1, optimal energy operation is possible in a system using a solar cell as a power source by integrally controlling resources that are a plurality of different types of energy devices.
　特許文献２には、発電と需要の予測から電力量バランスを管理する第１のアグリゲーション装置と、第１のアグリゲーション装置からの要請に基づいて売電を受けた電力を提供する第２のアグリゲーション装置を備え、第２のアグリゲーション装置は、蓄電池搭載の移動体に電力提供を進める通知情報を送信する方法が開示されている。特許文献２によれば、電力システムの需給バランスを調整するために、蓄電池を搭載した複数の電気自動車（ＥＶ：Electric Vehicle）であるリソースの余剰電力を活用可能とする。 Patent Document 2 describes a first aggregation device that manages the power amount balance based on predictions of power generation and demand, and a second aggregation device that provides electric power sold based on a request from the first aggregation device. A method is disclosed in which the second aggregation device transmits notification information for proceeding with the provision of electric power to a mobile body equipped with a storage battery. According to Patent Document 2, in order to adjust the supply and demand balance of an electric power system, it is possible to utilize surplus power of a resource that is a plurality of electric vehicles (EVs) equipped with storage batteries.
特開２００４－３１２７９８号公報Japanese Patent Application Publication No. 2004-312798 特開２０２１－１８６０８号公報JP 2021-18608 Publication
　リソースには、その利用目的が常に１種類とは限らず、複数種類の目的に活用できるものもある。
　１種類の利用目的として、例えば、蓄電池や水素貯蔵装置を貨物として輸送する場合、この輸送リソースはエネルギー輸送による配電リソースの役割を担っている。複数種類の利用目的として、例えば、旅客輸送バスなどの電気自動車をエネルギーリソースとして制御する場合、このバスは旅客輸送の役割と電力輸送の役割との両方を担う。 Resources are not always used for one type of purpose; some resources can be used for multiple types of purposes.
For example, when transporting storage batteries or hydrogen storage devices as cargo, this transportation resource plays the role of a power distribution resource for energy transportation. For example, when an electric vehicle such as a passenger transport bus is controlled as an energy resource for multiple types of usage purposes, this bus plays both the role of passenger transport and the role of electric power transport.
　複数種類の利用目的に役立つリソースを各システムに提供するときには、提供先のシステムごとに使いやすいように事前にリソースの特性を個別に定義することが求められる。しかし、同じリソースを目的の異なる複数のシステムで管理制御する手段は、いずれの文献にも開示されていない。
　また、同じリソースを同時期に複数のシステムが管理制御することで、同じリソースを複数のシステムで使用できるようになり、リソースの稼働率を向上することが期待される。しかし、従来の技術では、同じ時間帯では同じリソースを１つのシステムに占有させるように管理制御されることを前提としていた。 When providing resources that are useful for multiple types of usage purposes to each system, it is necessary to individually define the characteristics of the resources in advance for each system to which the resources are provided so that they are easy to use. However, none of the documents discloses a means for managing and controlling the same resource using multiple systems with different purposes.
Furthermore, by having multiple systems manage and control the same resource at the same time, the same resource can be used by multiple systems, which is expected to improve resource utilization. However, the conventional technology assumes that management control is performed so that one system occupies the same resources during the same time period.
　そこで、本発明は、複数種類のシステムに対して提供するリソースの稼働率を向上させることを、主な課題とする。 Therefore, the main objective of the present invention is to improve the utilization rate of resources provided to multiple types of systems.
　前記課題を解決するために、本発明のリソース管理装置は、以下の特徴を有する。
　本発明は、エネルギーに関わる設備である実体リソースを計測した実体リソース計測データから、前記実体リソースを仮想化する仮想化ロジックをもとに、前記実体リソースが仮想リソースとして提供する能力を示す仮想能力データを作成し、その仮想能力データを提供する仮想リソースを構築する仮想リソース能力変換部と、
　前記仮想リソース能力変換部が構築した前記仮想リソースをリソース運用管理システムに割り当てることで、前記実体リソースを前記リソース運用管理システムに管理させる能力割当部とを有しており、
　前記仮想化ロジックが、前記リソース運用管理システムが要求する前記実体リソースの能力様態を示すリソース要求内容データに応じて個別に用意されることを特徴とする。
　その他の手段は、後記する。 In order to solve the above problems, the resource management device of the present invention has the following features.
The present invention provides a virtual capability that indicates the ability that the actual resource provides as a virtual resource based on virtualization logic that virtualizes the actual resource from actual resource measurement data that measures the actual resource that is equipment related to energy. a virtual resource capability conversion unit that creates data and constructs a virtual resource that provides the virtual capability data;
a capacity allocation unit that causes the resource operation management system to manage the actual resource by allocating the virtual resource constructed by the virtual resource capacity conversion unit to the resource operation management system;
The virtualization logic is characterized in that the virtualization logic is individually prepared according to resource request content data indicating the capability of the actual resource requested by the resource operation management system.
Other means will be described later.
　本発明によれば、複数種類のシステムに対して提供するリソースの稼働率を向上させることができる。 According to the present invention, it is possible to improve the utilization rate of resources provided to multiple types of systems.
本実施形態に関するリソース運用管理システムを示す構成図である。FIG. 1 is a configuration diagram showing a resource operation management system according to the present embodiment. 本実施形態に関するリソース仮想化システムの構成図である。FIG. 1 is a configuration diagram of a resource virtualization system according to the present embodiment. 本実施形態に関するリソース仮想化システムのリソース仮想化処理のデータフロー図である。FIG. 3 is a data flow diagram of resource virtualization processing in the resource virtualization system according to the present embodiment. 本実施形態に関するリソース仮想化システムのリソース仮想化処理の処理手順を示すフローチャートである。3 is a flowchart illustrating the processing procedure of resource virtualization processing of the resource virtualization system according to the present embodiment. 本実施形態に関する仮想リソース能力変換部のデータフロー図である。FIG. 3 is a data flow diagram of a virtual resource capability conversion unit according to the present embodiment. 本実施形態に関する取得するリソース要求内容データの一例を示すテーブルである。It is a table which shows an example of the resource request content data acquired regarding this embodiment. 本実施形態に関する取得した仮想化定義データの一例を示すテーブルである。It is a table showing an example of acquired virtualization definition data regarding this embodiment. 本実施形態に関する実体リソース制約データ一例を示すテーブルである。It is a table which shows an example of entity resource constraint data regarding this embodiment. 本実施形態に関する取得した能力変換部に配置した「P0001」の仮想化ロジックの処理の説明図である。FIG. 6 is an explanatory diagram of the processing of the virtualization logic of “P0001” placed in the acquired capability conversion unit according to the present embodiment. 本実施形態に関する「P0001」「P0002」「P0003」の仮想化ロジックを能力変換部内に配置した説明図である。FIG. 3 is an explanatory diagram illustrating virtualization logic of "P0001", "P0002", and "P0003" related to the present embodiment arranged in a capability conversion unit. 本実施形態に関する取得した能力変換部内に配置した「P0004」の仮想化ロジックの処理の説明図である。FIG. 7 is an explanatory diagram of the processing of the virtualization logic of "P0004" placed in the acquired capability conversion unit according to the present embodiment. 本実施形態に関する取得した能力変換部内に配置した「P0005」「P0002」「P0006」の仮想化ロジックの処理の説明図である。FIG. 6 is an explanatory diagram of the processing of the virtualization logic of "P0005", "P0002", and "P0006" arranged in the acquired capability conversion unit according to the present embodiment. 本実施形態に関する図９の「P0001」を具体的に説明するための仮想能力データを示すグラフである。9 is a graph showing virtual capability data for specifically explaining "P0001" in FIG. 9 according to the present embodiment. 本実施形態に関する図１０の「P0001」「P0002」「P0003」を具体的に説明するためのグラフである。It is a graph for specifically explaining "P0001", "P0002", and "P0003" in FIG. 10 regarding this embodiment. 本実施形態に関するリソース関係データの例を示すテーブルである。It is a table showing an example of resource related data related to this embodiment. 本実施形態に関する能力予測部のデータフロー図である。FIG. 3 is a data flow diagram of the ability prediction unit according to the present embodiment. 本実施形態に関する能力割当部のデータフロー図である。FIG. 3 is a data flow diagram of a capacity allocation unit according to the present embodiment. 本実施形態に関する要求リソース対応データの一例を示すテーブルである。3 is a table showing an example of requested resource correspondence data according to the present embodiment. 本実施形態に関する実体リソースをシステムに割り当てる旨の説明図である。It is an explanatory diagram to the effect that entity resources concerning this embodiment are allocated to a system. 本実施形態に関する実体リソースを仮想化するデータ構造の一例を示す説明図である。FIG. 2 is an explanatory diagram illustrating an example of a data structure for virtualizing an entity resource according to the present embodiment. 本実施形態に関するリソース仮想化システムのハードウェア構成図である。FIG. 1 is a hardware configuration diagram of a resource virtualization system according to the present embodiment. 本実施形態に関する各仮想リソースの仮想能力データの一例を示すテーブルである。3 is a table showing an example of virtual capability data of each virtual resource according to the present embodiment.
　本発明を実施するための形態を、図面を参照しながら詳細に説明する。 Embodiments for carrying out the present invention will be described in detail with reference to the drawings.
　まず、図１９および図２０を参照して、本実施形態の概要を説明する。
　図１９は、実体リソースをシステムに割り当てる旨の説明図である。この説明図の横軸は時間軸である。
　スケジュール１９００は、従来の方法におけるリソースの提供様態を示す。
　スケジュール１９１０は、本実施形態におけるリソースの提供様態を示す。 First, an overview of this embodiment will be explained with reference to FIGS. 19 and 20.
FIG. 19 is an explanatory diagram of allocating entity resources to the system. The horizontal axis of this explanatory diagram is the time axis.
Schedule 1900 shows how resources are provided in the conventional method.
A schedule 1910 shows how resources are provided in this embodiment.
　スケジュール１９００では、リソース運用制御システムＡからのリソース要求期間１９０１と、リソース運用制御システムＢからのリソース要求期間１９０２とが一部の時間帯で重複する。
　そこで、実体リソースは、予め定めている提供対象のリソース運用制御システムＡに対して、リソース提供期間１９０３の時間帯だけ占有的に提供される。このように、従来の手法では実体リソースの提供先は排他的であるため、実体リソースの稼働率は低い。
　また、仮に実体リソースの提供先をリソース運用制御システムＡからリソース運用制御システムＢに変更しようとした場合、リソース運用制御システムＢのリソースの要求内容に一致させるように実体リソースの特性を示す仕様データを変更しなければならない。しかし、リソース運用制御システムＡとリソース運用制御システムＢのリソースの要求内容が必ずしも同種では無いため、提供先の変更も容易ではなかった。 In the schedule 1900, the resource request period 1901 from the resource operation control system A and the resource request period 1902 from the resource operation control system B overlap in some time periods.
Therefore, the actual resource is exclusively provided to the resource operation control system A, which is the provision target, predetermined in advance, only during the resource provision period 1903. In this way, in the conventional method, the actual resource is provided to an exclusive destination, so the utilization rate of the actual resource is low.
In addition, if an attempt is made to change the provision destination of an entity resource from resource operation control system A to resource operation control system B, specification data indicating the characteristics of the entity resource will be required to match the resource requirements of resource operation control system B. must be changed. However, since the resource request contents of the resource operation control system A and the resource operation control system B are not necessarily of the same type, it is not easy to change the provision destination.
　一方、スケジュール１９１０では、１つの実体リソースを１つ以上の仮想リソースに変換し、各仮想リソースには、その能力を示す仮想能力データが対応付けられる。例えば、１つの実体リソースからは、以下の２つの仮想リソースが生成される。
　・仮想リソースＡは、リソース運用制御システムＡが要求する能力を満たす実体リソースの仮想能力データが対応付けられる。具体的には、リソース運用制御システムＡは系統監視制御システムであるので、給電能力１９１５と放電能力１９１７とが求められる。よって、実体リソースが電気自動車である場合、そのバッテリの給電能力１９１５と放電能力１９１７とが仮想能力データとして記述された仮想リソースＡが構築される。
　・仮想リソースＢは、リソース運用制御システムＢが要求する能力を満たす実体リソースの仮想能力データが対応付けられる。具体的には、リソース運用制御システムＢは輸送システムであるので、輸送能力１９１６が求められる。よって、実体リソースが電気自動車である場合、その輸送能力１９１６が仮想能力データとして記述された仮想リソースＢが構築される。
　このように、物理的には同じ電気自動車であっても、提供先のシステムの要求を充足するように、その提供先のシステムが電気自動車を管理するときの仮想リソースは、個別に定義される。 On the other hand, in the schedule 1910, one real resource is converted into one or more virtual resources, and each virtual resource is associated with virtual capability data indicating its capability. For example, the following two virtual resources are generated from one real resource.
- Virtual resource A is associated with virtual capability data of an actual resource that satisfies the capability requested by resource operation control system A. Specifically, since the resource operation control system A is a system monitoring control system, a power supply capacity 1915 and a discharge capacity 1917 are required. Therefore, when the actual resource is an electric vehicle, a virtual resource A is constructed in which the power supply capacity 1915 and discharge capacity 1917 of the battery are described as virtual capacity data.
- Virtual resource B is associated with virtual capability data of an actual resource that satisfies the capability requested by resource operation control system B. Specifically, since resource operation control system B is a transportation system, transportation capacity 1916 is required. Therefore, when the real resource is an electric vehicle, a virtual resource B is constructed in which the transportation capacity 1916 of the electric vehicle is described as virtual capacity data.
In this way, even if the electric vehicle is physically the same, the virtual resources used by the destination system to manage the electric vehicle are defined individually to satisfy the requirements of the destination system. .
　さらに、スケジュール１９００とスケジュール１９１０との違いを、実体リソースの管理面から説明する。
　スケジュール１９００では、リソース要求期間１９０１とリソース提供期間１９０３とが１：１対応し、１つの実体リソースが１つのシステムに占有的に提供されていた。つまり、実体リソースを管理することと、実体リソースを使用することとが同義になっていた。
　スケジュール１９１０では、リソース運用制御システムＡからのリソース要求期間１９０１がリソース管理要求期間１９１１に置き換わる。同様に、リソース運用制御システムＢからのリソース要求期間１９０２がリソース管理要求期間１９１２に置き換わる。これにより、リソース運用制御システムＡは、リソース管理要求期間１９１１の間は、仮想リソースＡを介して管理対象の実体リソースを常時管理できる。一方、リソース運用制御システムＢは、リソース管理要求期間１９１２の間は、仮想リソースＢを介して管理対象の実体リソースを常時管理できる。つまり、１つの実体リソースが２つのシステムによって並列的に管理可能となる。 Furthermore, the difference between the schedule 1900 and the schedule 1910 will be explained from the perspective of managing real resources.
In the schedule 1900, the resource request period 1901 and the resource provision period 1903 have a 1:1 correspondence, and one entity resource is exclusively provided to one system. In other words, managing real resources and using real resources have become synonymous.
In the schedule 1910, the resource request period 1901 from the resource operation control system A is replaced by the resource management request period 1911. Similarly, the resource request period 1902 from the resource operation control system B is replaced by the resource management request period 1912. Thereby, the resource operation control system A can always manage the real resource to be managed via the virtual resource A during the resource management request period 1911. On the other hand, the resource operation control system B can always manage the real resource to be managed via the virtual resource B during the resource management request period 1912. In other words, one entity resource can be managed in parallel by two systems.
　なお、管理とは、各システムが実体リソースに要求する仮想能力データに関連する実体リソースの計測値を、各システムに通知することなどである。例えば、リソース運用制御システムＡは給電能力１９１５と放電能力１９１７とを仮想能力データとして求めるので、仮想リソースＡは、電気自動車の現在のバッテリ残量を、常時リソース運用制御システムＡに通知することで、リソース運用制御システムＡに管理される。
　同様に、リソース運用制御システムＢは輸送能力１９１６を仮想能力データとして求めるので、仮想リソースＡは、電気自動車の現在位置および現在の乗員数を、常時リソース運用制御システムＢに通知することで、リソース運用制御システムＢに管理される。 Note that management means notifying each system of the measured value of the real resource related to the virtual capability data that each system requests from the real resource. For example, since the resource operation control system A obtains the power supply capacity 1915 and the discharge capacity 1917 as virtual capacity data, the virtual resource A can constantly notify the resource operation control system A of the current remaining battery level of the electric vehicle. , managed by resource operation control system A.
Similarly, since the resource operation control system B obtains the transportation capacity 1916 as virtual capacity data, the virtual resource A can constantly notify the resource operation control system B of the current position and the current number of passengers of the electric vehicle. Managed by operation control system B.
　一方、実体リソースを使用することについては、リソース運用制御システムＡでの使用場所と、リソース運用制御システムＢでの使用場所が一致しない限りは、同じ１つの実体リソースは、各システムに排他的に使用される。
　例えば、電気自動車は、ある日の朝に地点Ｘのリソース運用制御システムＡから給電能力１９１５によりバッテリに充電する。
　充電後の電気自動車は、昼に地点Ｐのリソース運用制御システムＢから乗員を地点Ｑに輸送するように依頼され、輸送能力１９１６により輸送を開始する。地点Ｑで乗員を降ろした後の電気自動車は、夜に地点Ｙのリソース運用制御システムＡからバッテリの電力を放電能力１９１７により放電するように依頼される。 On the other hand, regarding the use of entity resources, unless the location of use in resource operation control system A and the location of use in resource operation control system B do not match, the same entity resource will be used exclusively in each system. used.
For example, an electric vehicle charges its battery from the resource operation control system A at point X using the power supply capacity 1915 in the morning of one day.
After charging, the electric vehicle is requested to transport the occupant to point Q from the resource operation control system B at point P at noon, and starts transporting using the transport capacity 1916. After disembarking the passenger at point Q, the electric vehicle is requested by the resource operation control system A at point Y to discharge the battery power using the discharge capacity 1917 at night.
　ここで、地点Ｘ→地点Ｙの電力供給のタスクと、地点Ｐ→地点Ｑの人員輸送のタスクとで、例えば、地点Ｘと地点Ｐとの距離が近く、地点Ｙと地点Ｑとの距離が近いときには、１日で２つのタスクを並列に実行できる。このように、電気自動車は、別々のシステムに対して、重複する時間帯で管理させつつ、別々の能力を時間差で使用させることで、稼働率を向上できる。つまり、実体リソースを１つ以上の仮想能力データに変換することで、各リソース運用制御システムからのリソースの要求内容に合わせて、同時に運用制御できる。 Here, the task of supplying power from point X to point Y and the task of transporting personnel from point P to point Q, for example, the distance between point When it's close, you can run two tasks in parallel in one day. In this way, electric vehicles can improve operating rates by having separate systems manage them in overlapping time periods and using different capacities at different times. In other words, by converting a real resource into one or more pieces of virtual capability data, operation can be controlled simultaneously in accordance with the content of resource requests from each resource operation control system.
　図２０は、実体リソースを仮想化するデータ構造の一例を示す説明図である。
　各実体リソースには、実体リソースＩＤ「AR001～AR006」が割り当てられる。例えば、自家用車の実体リソースには、実体リソースＩＤ「AR001」が割り当てられる。
　１つの実体リソースからは、１つ以上の仮想リソースが構築される。各仮想リソースには、仮想リソースＩＤ「VR001～VR006」が割り当てられる。例えば、実体リソースＩＤ「AR001」の実体リソースからは、仮想リソースＩＤ「VR001」となる１つの仮想リソースが構築される。各仮想リソースには、その仮想リソースが提供する仮想能力データが対応付けられる。仮想リソースの仮想能力データは、仮想リソースが提供されるシステムの要求に応じて定義される。 FIG. 20 is an explanatory diagram showing an example of a data structure for virtualizing a real resource.
Each entity resource is assigned an entity resource ID “AR001 to AR006”. For example, the entity resource ID "AR001" is assigned to the entity resource of a private car.
One or more virtual resources are constructed from one real resource. Virtual resource IDs “VR001 to VR006” are assigned to each virtual resource. For example, one virtual resource with virtual resource ID "VR001" is constructed from a real resource with real resource ID "AR001". Each virtual resource is associated with virtual capability data provided by that virtual resource. Virtual capacity data of a virtual resource is defined according to the requirements of the system in which the virtual resource is provided.
　なお、仮想リソースＩＤ「VR003」は、２つの実体リソースＩＤ「AR004、AR005」から構築される。この場合、２つの実体リソースが提供する能力を合わせることで、１つの仮想リソースとして提供可能となる。
　また、実体リソースＩＤ「AR002」の実体リソースからは、仮想リソースＩＤ「VR002、VR005」という２つの仮想リソースが構築される。この場合、バッテリを搭載したトラックという１つの実体リソースが、電力輸送能力を提供する仮想リソースＩＤ「VR002」としても定義できるし、調整電源能力を提供する仮想リソースＩＤ「VR005」としても定義できることを示す。 Note that the virtual resource ID "VR003" is constructed from two real resource IDs "AR004 and AR005". In this case, by combining the capabilities provided by the two real resources, they can be provided as one virtual resource.
Furthermore, two virtual resources with virtual resource IDs "VR002 and VR005" are constructed from the real resource with the real resource ID "AR002". In this case, one physical resource, a truck equipped with a battery, can be defined as a virtual resource ID "VR002" that provides power transport capability, or as a virtual resource ID "VR005" that provides regulated power capability. show.
　１つのシステムは、１つ以上の要求ＩＤ「R0001～R0005」を発行する。例えば、「監視Ａ」というシステムは、電力供給という仮想能力データを求める旨の要求ＩＤ「R0001」を発行するとともに、調整電源という仮想能力データを求める旨の要求ＩＤ「R0004」を発行する。
　リソースの割り当てとは、１つ以上の仮想リソースＩＤを、１つの要求ＩＤに対応付けることである。例えば、「監視Ａ」のシステムが要求する要求ＩＤ「R0001」に対して、図２０では、仮想リソースＩＤ「VR001」の矢印が接続される。これにより、仮想リソースＩＤ「VR001」が提供する電力供給という仮想能力データを、「監視Ａ」のシステムが管理可能となる。実際には、仮想リソースＩＤ「VR001」に対応する実体リソースＩＤ「AR001」の自家用車が、「監視Ａ」のシステムに対して電力供給という能力を提供する。 One system issues one or more request IDs "R0001 to R0005". For example, a system called "Monitor A" issues a request ID "R0001" requesting virtual capability data of power supply, and also issues a request ID "R0004" requesting virtual capability data of regulated power supply.
Resource allocation means associating one or more virtual resource IDs with one request ID. For example, in FIG. 20, the arrow of the virtual resource ID "VR001" is connected to the request ID "R0001" requested by the "monitoring A" system. As a result, the "monitoring A" system can manage the virtual capability data of power supply provided by the virtual resource ID "VR001". In reality, the private car with the real resource ID "AR001" that corresponds to the virtual resource ID "VR001" provides the ability to supply power to the "monitoring A" system.
　また、実体リソースＩＤ「AR003」の旅客バスは、仮想リソースＩＤ「VR002」を介して「監視Ｂ」のシステムに電力輸送という能力を提供しつつ、仮想リソースＩＤ「VR005」を介して「監視Ａ」のシステムに調整電源という能力を提供する。
　このように、１つの実体リソースを複数の仮想リソースに仮想化することで、図１９のスケジュール１９１０に示したように、同時に複数のシステムから管理可能となる。 In addition, the passenger bus with the physical resource ID "AR003" provides the ability to transport electricity to the "monitoring B" system via the virtual resource ID "VR002" and the "monitoring A" system via the virtual resource ID "VR005". ” provides the capability of regulated power to the system.
By virtualizing one real resource into multiple virtual resources in this way, it can be managed by multiple systems simultaneously, as shown in schedule 1910 in FIG. 19.
　図１は、リソース運用管理システム１を示す構成図である。リソース運用管理システム１は、図１９で説明したように、実体リソース５から、各リソース運用制御システムの運用に沿った仮想リソースを作成することで、それぞれで動作目的が異なる複数のリソース運用制御システムでの運用を可能にする。これにより、エネルギーに関わるリソースのより効率的な運用制御を行う。
　そのため、リソース運用管理システム１はリソース仮想化装置３、データ管理装置４、実体リソース５、計測装置６、監視制御装置７、情報入出力端末８、情報配信装置９、リソース運用制御装置１０、制御対象設備１２から構成される。また通信経路１１は、例えばＬＡＮ（Local Area Network）やＷＡＮ（Wide Area Network）であり、リソース運用管理システム１を構成する各種装置および端末を互いに通信可能に接続する通信経路１１である。 FIG. 1 is a configuration diagram showing a resource operation management system 1. As shown in FIG. As explained in FIG. 19, the resource operation management system 1 creates virtual resources from the actual resources 5 in accordance with the operation of each resource operation control system, thereby managing multiple resource operation control systems each having a different operational purpose. enable operation in This enables more efficient operational control of energy-related resources.
Therefore, the resource operation management system 1 includes a resource virtualization device 3, a data management device 4, an actual resource 5, a measurement device 6, a monitoring control device 7, an information input/output terminal 8, an information distribution device 9, a resource operation control device 10, a control It is composed of target equipment 12. Further, the communication path 11 is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network), and is a communication path 11 that connects various devices and terminals that constitute the resource operation management system 1 so that they can communicate with each other.
　データ管理装置４は、実体リソース５の計測データや、実体リソース５の運用や制御に関わる条件や制約等の制約データと、実体リソース５の稼働に影響を及ぼす因子のデータを記憶する。実体リソース５とは、例えば以下の機器である。
　・化石燃料を利用した発電機
　・太陽光や地熱や風力や水力などの再生可能エネルギーを利用した発電機
　・定置型の蓄電池
　・電気自動車や電気バスなどの蓄電池を搭載した移動体
　・変電所の変圧器や調相設備などの変電設備や送配電設備
　・エネルギーを生産または消費または貯蔵する個々の設備または個々の設備を二つ以上組み合わせで構成する設備の集合体。設備とは、例えば、照明や空調や動力設備などのエネルギー消費側の用益設備である。 The data management device 4 stores measurement data of the entity resource 5, constraint data such as conditions and constraints related to the operation and control of the entity resource 5, and data on factors that affect the operation of the entity resource 5. The entity resources 5 are, for example, the following devices.
- Generators that use fossil fuels - Generators that use renewable energies such as solar, geothermal, wind, and water power - Stationary storage batteries - Mobile vehicles equipped with storage batteries, such as electric cars and electric buses - Substations Substation equipment and power transmission and distribution equipment, such as transformers and phase adjustment equipment - Individual equipment that produces, consumes, or stores energy, or a collection of equipment that consists of a combination of two or more individual equipment. The equipment is, for example, utility equipment on the energy consumption side, such as lighting, air conditioning, and power equipment.
　実体リソース５の計測データには、時間推移に伴い計測された実体リソース５の動作を記録したデータを少なくとも含む。実体リソース５の動作とは例えば、実体リソース５の発電量、消費量、蓄電量、送配電量、移動履歴などである。
　実体リソース５の制約データには、実体リソース５の運用や制御に関わる条件や制約を示すデータを少なくとも含む。実体リソース５の運用や制御に関わる条件や制約とは、例えば、エネルギーの生産、消費、蓄積の場所や、可能な時間や、量の上下限などの、実体リソース５の稼働に関わる量と時間と場所の稼働範囲を示すデータ、稼働に関わるコストなどを示すデータなどである。 The measurement data of the real resource 5 includes at least data recording the operation of the real resource 5 measured over time. The operation of the entity resource 5 includes, for example, the amount of power generation, amount of consumption, amount of stored electricity, amount of power transmission and distribution, movement history, etc. of the entity resource 5.
The constraint data of the entity resource 5 includes at least data indicating conditions and constraints related to the operation and control of the entity resource 5. Conditions and constraints related to the operation and control of the entity resource 5 include, for example, the location and possible time of energy production, consumption, and storage, and the amount and time related to the operation of the entity resource 5, such as the upper and lower limits of the amount. This includes data showing the operating range of the location and location, and data showing costs related to operation.
　データ管理装置４から取得される因子データ４５３Ａ（図３）とは、例えば以下のデータである。
　・気温、湿度、日射量、風速、気圧などの気象データ
　・原油や天然ガスなどの取引量や取引価格などの燃料データ
　・送配電線の容量などの送配電線データ
　・発電機の運転または保守スケジュールなどの発電機稼働状況データ
　・年月日、曜日、任意に設定した日の種別を示すフラグ値などの暦日データ
　・台風やイベントなどの突発事象の発生有無を示すデータ
　・エネルギーの消費者数、産業動向や景況指数などの経済状況を示すデータ
　・特急列車の乗車率、乗車客数、予約席数、あるいは道路交通状況などの人や移動体の移動状況を示すデータ The factor data 453A (FIG. 3) acquired from the data management device 4 is, for example, the following data.
・Weather data such as temperature, humidity, solar radiation, wind speed, and atmospheric pressure ・Fuel data such as trading volume and transaction price of crude oil and natural gas ・Power transmission and distribution line data such as capacity of power transmission and distribution lines ・Operation or maintenance of generators Generator operating status data such as schedules - Calendar data such as year, month, day, day of the week, and flag values that indicate the type of arbitrarily set day - Data that indicates whether sudden events such as typhoons or events have occurred - Energy consumers Data showing the economic situation, such as numbers, industrial trends, and business conditions. - Data showing the movement status of people and moving objects, such as the occupancy rate of limited express trains, the number of passengers, the number of reserved seats, and road traffic conditions.
　データ管理装置４は、計測装置６、監視制御装置７、情報入出力端末８のいずれか介して予め設定した過去日時から最新の観測日時までの実体リソース５の計測データと制約データを記憶する。またデータ管理装置４は、他装置からのデータ取得要求に応じて、実体リソース５の計測データと制約データの検索および送信を行う。 The data management device 4 stores measurement data and constraint data of the entity resource 5 from a preset past date and time to the latest observation date and time via any one of the measurement device 6, the monitoring control device 7, and the information input/output terminal 8. The data management device 4 also searches for and transmits measurement data and constraint data of the entity resource 5 in response to data acquisition requests from other devices.
　図２は、リソース仮想化システム（リソース管理装置）２の構成図である。リソース仮想化システム２はリソース仮想化装置３とデータ管理装置４とから構成される。
　リソース仮想化装置３は、データ管理装置４に記憶されたデータを用いて、実体リソース５のデータを、仮想リソースを示す「仮想リソースデータ」に変換する。そのため、リソース仮想化装置３は、仮想リソース能力変換部３５１と、能力予測部３５２と、能力割当部３５３と、制御計画部３５４とを有する。 FIG. 2 is a configuration diagram of the resource virtualization system (resource management device) 2. As shown in FIG. The resource virtualization system 2 includes a resource virtualization device 3 and a data management device 4.
The resource virtualization device 3 uses the data stored in the data management device 4 to convert the data of the real resource 5 into "virtual resource data" indicating a virtual resource. Therefore, the resource virtualization device 3 includes a virtual resource capacity conversion section 351, a capacity prediction section 352, a capacity allocation section 353, and a control planning section 354.
　仮想リソース能力変換部３５１は、データ管理装置４から実体リソース５の計測データと制約データとを取得する。仮想リソース能力変換部３５１は、リソース運用制御装置１０から受信したリソースの要求内容に適合する様に実体リソース５の計測データと制約データとを、仮想リソースの能力を示す「仮想能力データ」に変換し、仮想能力データに基づいて仮想リソースを構成する。
　つまり、仮想リソース能力変換部３５１は、エネルギーに関わる設備である実体リソース５を計測した実体リソース計測データ４５１Ａから、実体リソース５を仮想化する仮想化ロジックをもとに、仮想能力データを作成し、その仮想能力データを提供する仮想リソースを構築する。
　仮想化ロジックは、割当先の各リソース運用管理システム１が要求する実体リソース５の能力様態を示すリソース要求内容データに応じて個別に用意される。仮想化ロジックとは、仮想リソースを構築するために、事前に設定した実体リソース計測データ４５１Ａから仮想能力データへの変換処理を行うロジックである。本明細書では、仮想化ロジックの識別子として、P0001などのPから始まるIDが割り当てられる。 The virtual resource capacity conversion unit 351 acquires measurement data and constraint data of the real resource 5 from the data management device 4 . The virtual resource capacity conversion unit 351 converts the measurement data and constraint data of the real resource 5 into "virtual capacity data" indicating the capacity of the virtual resource so as to match the resource request content received from the resource operation control device 10. and configure virtual resources based on virtual capacity data.
In other words, the virtual resource capacity conversion unit 351 creates virtual capacity data based on the virtualization logic for virtualizing the substance resource 5 from the substance resource measurement data 451A obtained by measuring the substance resource 5, which is energy-related equipment. , construct a virtual resource that provides that virtual capability data.
The virtualization logic is individually prepared according to the resource request content data indicating the capability of the actual resource 5 requested by each resource operation management system 1 to which it is allocated. The virtualization logic is a logic that performs a conversion process from real resource measurement data 451A set in advance to virtual capability data in order to construct a virtual resource. In this specification, an ID starting from P, such as P0001, is assigned as an identifier for virtualization logic.
　能力予測部３５２は、仮想リソース能力変換部３５１が出力した仮想能力データの過去データとデータ管理装置４から取得した因子データ４５３Ａとに基づいて仮想能力データの将来の値を予測するモデルを同定する。能力予測部３５２は、同定したモデルを用いて所定の将来の日時における仮想能力データの将来の値である予測値を算出する。 The capacity prediction unit 352 identifies a model that predicts the future value of the virtual capacity data based on the past data of the virtual capacity data output by the virtual resource capacity conversion unit 351 and the factor data 453A acquired from the data management device 4. . The ability prediction unit 352 uses the identified model to calculate a predicted value that is the future value of the virtual ability data at a predetermined future date and time.
　能力割当部３５３は、リソース運用制御装置１０から取得したリソースの要求内容と、能力予測部３５２が算出した仮想能力データとを突き合わせて、リソース運用制御装置１０に供する仮想リソースを割り当てる。つまり、能力割当部３５３は、仮想リソース能力変換部３５１が構築した仮想リソースごとにリソース運用管理システム１に割り当てることで、実体リソース５を各リソース運用管理システム１に管理させる。能力割当部３５３は、能力予測部３５２が算出した予測値をもとに、仮想リソース能力変換部３５１が構築した仮想リソースごとにリソース運用管理システム１に割り当ててもよい。 The capacity allocation unit 353 matches the content of the resource request obtained from the resource operation control device 10 with the virtual capacity data calculated by the capacity prediction unit 352, and allocates virtual resources to be provided to the resource operation control device 10. In other words, the capacity allocation unit 353 allows each resource operation management system 1 to manage the actual resource 5 by allocating each virtual resource constructed by the virtual resource capacity conversion unit 351 to the resource operation management system 1 . The capacity allocation unit 353 may allocate each virtual resource constructed by the virtual resource capacity conversion unit 351 to the resource operation management system 1 based on the predicted value calculated by the capacity prediction unit 352.
　制御計画部３５４は、仮想リソースに組み込まれた実体リソース５の一部または全部の制御を行う計画を生成する。つまり、制御計画部３５４は、能力割当部３５３が割り当てた仮想リソースを構成する実体リソース５に対する制御計画を生成し、その制御計画をもとに割当先の各リソース運用管理システム１に実体リソース５を制御させる。仮想リソース能力変換部３５１は、制御計画部３５４が生成した制御計画に基づいて仮想能力データを修正する。
　制御計画部３５４は、実体リソース５の稼働に伴いエネルギーに関わる仮想能力データの時間変化を算出し、その時間変化を仮想リソース能力変換部３５１が作成する仮想能力データに反映させてもよい。 The control planning unit 354 generates a plan for controlling part or all of the real resource 5 incorporated into the virtual resource. In other words, the control planning unit 354 generates a control plan for the entity resources 5 constituting the virtual resources allocated by the capacity allocation unit 353, and based on the control plan, the control planning unit 354 sends the entity resources 5 to each resource operation management system 1 to which the capacity allocation unit 353 has allocated. be controlled. The virtual resource capacity conversion unit 351 modifies the virtual capacity data based on the control plan generated by the control planning unit 354.
The control planning unit 354 may calculate a temporal change in virtual capacity data related to energy as the real resource 5 operates, and may reflect the temporal change in the virtual capacity data created by the virtual resource capacity conversion unit 351.
　リソース運用制御装置１０は、例えば、エネルギーの生成、消費、輸送、取引の運用や制御を行う装置である。リソース運用制御装置１０は、リソース仮想化装置３が出力した仮想能力データを基に、各々が管理する制御対象設備１２と仮想リソースとを組み合わせて所定の目標を達成するための物理的な設備運用計画を作成し実行する。ここで物理的な設備運用計画とは、エネルギー分野においては、例えば、エネルギーの生産設備、流通設備、消費装置、蓄積装置の運転計画である。物理的な設備運用計画とは、具体的には、以下の計画である。
　・発電機や蓄電池の起動台数およびそれら発電機や蓄電池の出力配分の計画
　・電気自動車の充電器や充電ステーションの充電または放電制御の計画
　・ガス導管や水道管に流すガスや水の流量や圧力の配分計画
　・再生可能エネルギーに由来する電力の要求を優先的に行うための蓄電池の充放電制御計画
　・デマンドレスポンスと呼ばれる電力需要の調整制御においては、デマンドレスポンスに参加している電力消費者または電力消費者の需要設備の需要調整量配分の計画や調整制御の実行
　・運送分野においては、例えば、旅客輸送や貨物輸送のためのバスやトラック等の輸送車の配車計画 The resource operation control device 10 is, for example, a device that operates and controls energy generation, consumption, transportation, and transaction. The resource operation control device 10 performs physical equipment operation to achieve a predetermined goal by combining the control target equipment 12 and virtual resources managed by each device based on the virtual capacity data output by the resource virtualization device 3. Create and execute a plan. In the energy field, the physical equipment operation plan is, for example, an operation plan for energy production equipment, distribution equipment, consumption equipment, and storage equipment. Specifically, the physical equipment operation plan is the following plan.
・Planning the number of generators and storage batteries to start and the output distribution of those generators and storage batteries ・Planning the charging or discharging control of electric vehicle chargers and charging stations ・Flow rate and pressure of gas and water flowing into gas pipes and water pipes・Charge/discharge control plan for storage batteries to prioritize requests for electricity derived from renewable energy ・In adjustment control of electricity demand called demand response, electricity consumers participating in demand response or Planning and adjustment control of demand adjustment amount allocation for electricity consumers' demand facilities. - In the transportation field, for example, planning the allocation of transportation vehicles such as buses and trucks for passenger transportation and cargo transportation.
　なお設備の運転計画は、リソース運用制御装置１０を利用する主体者による直接的な実行に限定されるものではなく、間接的に実現される形態でもよい。間接的な設備の運転とは、電力分野においては、例えば、直接的な相対取引契約や取引所を介した取引契約に基づいた他者による物理的な設備の運転である。この場合、取引契約の実行計画が設備の運転計画に相当する。 Note that the facility operation plan is not limited to being directly executed by the person using the resource operation control device 10, but may be implemented indirectly. Indirect equipment operation, in the electric power sector, is, for example, the operation of physical equipment by another party based on a direct bilateral trading contract or a trading contract via an exchange. In this case, the execution plan of the transaction contract corresponds to the equipment operation plan.
　情報入出力端末８は、リソース仮想化装置３、データ管理装置４へのデータ入力や、これら装置が記憶するデータまたは出力するデータの表示を行う。計測装置６は、実体リソース５の稼働に関する計測データを所定の時間間隔で定期的に計測または収集し、データ管理装置４に送信する。情報配信装置９は、実体リソース５の稼働に影響を及ぼす因子データ４５３Ａの計測値や予測値をデータ管理装置４に送信する。監視制御装置７は、実体リソース５の監視や制御を行う。 The information input/output terminal 8 inputs data to the resource virtualization device 3 and data management device 4, and displays data stored or output by these devices. The measurement device 6 periodically measures or collects measurement data regarding the operation of the entity resource 5 at predetermined time intervals, and transmits it to the data management device 4 . The information distribution device 9 transmits measured values and predicted values of factor data 453A that influence the operation of the entity resource 5 to the data management device 4. The monitoring control device 7 monitors and controls the entity resources 5.
　データ管理装置４は、データ管理装置４の動作を統括的に制御するＣＰＵ３１（Central Processing Unit）４１、入力装置４２、出力装置４３、通信装置４４および記憶装置４５から構成される。データ管理装置４は、例えばパーソナルコンピュータ、サーバコンピュータまたはハンドヘルドコンピュータなどの情報処理装置である。
　入力装置４２は、キーボードまたはマウスから構成され、出力装置４３は、ディスプレイまたはプリンタから構成される。また通信装置４４は、無線ＬＡＮまたは有線ＬＡＮに接続するためのＮＩＣ（Network Interface Card）を備えて構成される。また記憶装置４５は、ＲＡＭ（Random Access Memory）やＲＯＭ（Read Only Memory）などの記憶媒体である。出力装置４３を介して各処理部の出力結果や、中間結果を適宜出力してもよい。 The data management device 4 includes a CPU 31 (Central Processing Unit) 41 that centrally controls the operation of the data management device 4, an input device 42, an output device 43, a communication device 44, and a storage device 45. The data management device 4 is, for example, an information processing device such as a personal computer, a server computer, or a handheld computer.
The input device 42 consists of a keyboard or a mouse, and the output device 43 consists of a display or a printer. The communication device 44 is also configured to include a NIC (Network Interface Card) for connection to a wireless LAN or wired LAN. The storage device 45 is a storage medium such as a RAM (Random Access Memory) or a ROM (Read Only Memory). The output results and intermediate results of each processing unit may be outputted as appropriate via the output device 43.
　記憶装置４５には、実体リソース計測データ記憶手段４５１、実体リソース制約データ記憶手段４５２、因子データ記憶手段４５３などのデータベースが格納されている。
　実体リソース計測データ記憶手段４５１には実体リソース計測データ４５１Ａが保持されている。
　実体リソース計測データ４５１Ａは、実体リソース５の稼働に関する過去の観測値が記憶されたデータである。実体リソース５の稼働の観測値とは、例えば発電機の発電量、蓄電池の充電量や放電量、電気自動車の充電量、充電残量、電力系統への放電量、ＧＰＳ等の緯度経度や場所の識別子で示される移動体の移動履歴、旅客輸送や貨物輸送の移動履歴や輸送内容履歴などである。 The storage device 45 stores databases such as an actual resource measurement data storage means 451, an actual resource constraint data storage means 452, and a factor data storage means 453.
The entity resource measurement data storage means 451 holds entity resource measurement data 451A.
The entity resource measurement data 451A is data in which past observed values regarding the operation of the entity resource 5 are stored. Observed values for the operation of entity resources 5 include, for example, the amount of power generated by a generator, the amount of charge and discharge of a storage battery, the amount of charge of an electric vehicle, the amount of remaining charge, the amount of discharge to the power grid, and the latitude and longitude and location of GPS, etc. This includes the movement history of the mobile object indicated by the identifier, the movement history of passenger transportation and cargo transportation, and the history of transportation contents.
　実体リソース制約データ記憶手段４５２には、実体リソース制約データ４５２Ａ（図８）が保持されている。実体リソース制約データ４５２Ａは、実体リソース５の稼働に関する条件や制約が記憶されたデータである。実体リソース５の稼働に関する条件や制約とは、例えば以下のデータである。
　・発電、充電、蓄電放電、移動等の開始日時や終了日時などの稼働時間範囲
　・発電量、充電量、蓄電放電量、移動量等などの稼働量範囲
　・発電、充電、蓄電放電の場所や移動範囲等の稼働場所範囲
　・制御を受け入れる場合の制御応答完了までの所要時間である応動時間
　・実体リソース５の稼働内容の変更を受け入れ可能か否かの制御可否
　・上記の条件の変更可能か否かの条件変更可否、稼働に関わるコストあるいは制御受け入れや条件変更に伴い生じるコスト The entity resource constraint data storage means 452 holds entity resource constraint data 452A (FIG. 8). The entity resource constraint data 452A is data in which conditions and constraints regarding the operation of the entity resource 5 are stored. The conditions and constraints regarding the operation of the entity resource 5 are, for example, the following data.
・Operating time range such as start date and time and end date and time of power generation, charging, storage discharge, movement, etc. ・Operating amount range such as power generation amount, charge amount, storage discharge amount, movement amount, etc. ・Location of power generation, charging, storage discharge, etc. Operating location range such as movement range - Response time, which is the time required to complete the control response when accepting control - Whether or not it is possible to control whether changes in the operation details of the entity resource 5 can be accepted - Whether the above conditions can be changed Whether or not the conditions can be changed, costs related to operation, or costs incurred due to control acceptance and condition changes
　因子データ記憶手段４５３には、因子データ４５３Ａが保持されている。因子データ４５３Ａは、実体リソース５の稼働に影響を与える各種因子の観測値や予測値が記憶されたデータである。因子とは、例えば以下のデータである。
　・気温、湿度、日射量、風速、気圧などの気象データ
　・電力、ガス、水道などのエネルギーの消費データ
　・太陽光発電や風力発電などのエネルギーの発電データ
　・発電機の稼働休止の状況や予定データ
　・送電線や配電線、あるいは変電所毎の空き容量、電流量、電圧などの電力系統データ
　・取引所で取引されるエネルギーの取引量や取引価格などの市場データ
　・年月日、曜日、任意に設定した日の種別を示すフラグ値などの暦日データ
　・台風やイベントなどの突発事象の発生有無を示すデータ
　・エネルギーの消費者数、産業動向や景況指数などの経済状況を示すデータ
　・特急列車の乗車率、乗車客数、予約席数、あるいは道路交通状況などの人や移動体の移動状況を示すデータ
　また上記の予測対象の過去の観測データ、あるいは予測結果データそのものなども含む。 The factor data storage means 453 holds factor data 453A. The factor data 453A is data in which observed values and predicted values of various factors that influence the operation of the entity resource 5 are stored. The factors are, for example, the following data.
・Weather data such as temperature, humidity, solar radiation, wind speed, and atmospheric pressure ・Energy consumption data such as electricity, gas, and water ・Energy generation data such as solar power generation and wind power generation ・Status and schedule for generator outage Data ・Power system data such as free capacity, current amount, and voltage for each transmission line, distribution line, or substation ・Market data such as energy transaction volume and transaction price traded on exchanges ・Year, month, day of the week, Calendar data such as flag values that indicate the type of day that you have set ・Data that indicates the occurrence of sudden events such as typhoons and events ・Data that indicates economic conditions such as the number of energy consumers, industrial trends, and business conditions ・Data that shows the movement status of people and moving objects, such as the occupancy rate of limited express trains, the number of passengers, the number of reserved seats, and road traffic conditions.It also includes past observation data of the above prediction target, or the prediction result data itself.
　リソース仮想化装置３は、リソース仮想化装置３の動作を統括的に制御するＣＰＵ３１、入力装置３２、出力装置３３、通信装置３４および記憶装置３５から構成される。リソース仮想化装置３は、例えばパーソナルコンピュータ、サーバコンピュータまたはハンドヘルドコンピュータなどの情報処理装置である。
　記憶装置３５には、仮想化定義データ記憶手段３５７、仮想化ロジックプールデータ記憶手段３５８、リソース関係データ記憶手段３５９などのデータベースが格納されている。 The resource virtualization device 3 includes a CPU 31 that centrally controls the operation of the resource virtualization device 3, an input device 32, an output device 33, a communication device 34, and a storage device 35. The resource virtualization device 3 is, for example, an information processing device such as a personal computer, a server computer, or a handheld computer.
The storage device 35 stores databases such as a virtualization definition data storage means 357, a virtualization logic pool data storage means 358, and a resource related data storage means 359.
　仮想化定義データ記憶手段３５７には仮想化定義データ３５７Ａ（図７）が保持されている。仮想化定義データ３５７Ａは、リソース運用制御装置１０から受信するリソースの要求内容と、要求を充足させる仮想リソースを構築するための仮想化ロジックとの対応関係を示すデータである。
　仮想化ロジックプールデータ記憶手段３５８には、仮想化ロジックプール３５８Ａが保持されている。仮想化ロジックプール３５８Ａは、事前に設定した仮想化ロジックを１種類以上格納している。以下、仮想化ロジックを例示する。
　・実体リソース計測データ４５１Ａの物理量とは異なる種類の物理量を示す仮想能力データに変換する仮想化ロジック
　・２種類以上の既存の仮想能力データの組み合わせから、新たな仮想能力データを生成する仮想化ロジック
　・実体リソース５の稼働に伴うエネルギーの残量を示す実体リソース計測データ４５１Ａから、実体リソース５のエネルギーの正または負の供給能力を示す仮想能力データに変換する仮想化ロジック
　・実体リソース５の稼働に伴う移動履歴を示す実体リソース計測データ４５１Ａから、実体リソース５の貨物の輸送能力を示す仮想能力データに変換する仮想化ロジック
　・実体リソース５のエネルギーの正または負の供給能力を示す実体リソース計測データ４５１Ａと、実体リソース５の貨物の輸送能力を示す実体リソース計測データ４５１Ａとを用いて、実体リソース５のエネルギーの輸送能力を示す仮想能力データに変換する仮想化ロジック The virtualization definition data storage means 357 holds virtualization definition data 357A (FIG. 7). The virtualization definition data 357A is data indicating the correspondence between the content of the resource request received from the resource operation control device 10 and the virtualization logic for constructing a virtual resource that satisfies the request.
The virtualized logic pool data storage means 358 holds a virtualized logic pool 358A. The virtualization logic pool 358A stores one or more types of virtualization logic set in advance. The virtualization logic will be illustrated below.
・Virtualization logic that converts the actual resource measurement data 451A into virtual capacity data that indicates a different type of physical quantity from the physical quantity ・Virtualization logic that generates new virtual capacity data from a combination of two or more types of existing virtual capacity data・Virtualization logic that converts the actual resource measurement data 451A indicating the remaining amount of energy accompanying the operation of the actual resource 5 into virtual capacity data indicating the positive or negative energy supply capacity of the actual resource 5 ・Operation of the actual resource 5 Virtualization logic that converts the physical resource measurement data 451A that indicates the movement history associated with the physical resource 5 into virtual capacity data that indicates the cargo transportation capacity of the physical resource 5 - The physical resource measurement that indicates the positive or negative energy supply capacity of the physical resource 5 Virtualization logic that converts the data 451A and the physical resource measurement data 451A indicating the cargo transportation capacity of the physical resource 5 into virtual capacity data indicating the energy transportation capacity of the physical resource 5
　リソース関係データ記憶手段３５９には、リソース関係データ３５９Ａ（図１５）が保持されている。リソース関係データ３５９Ａは、仮想リソースと仮想リソースを構成する実体リソース５との対応関係を示すデータである。リソース関係データ３５９Ａは、例えば、図２０の自家用車「AR001」→仮想リソース「VR001」の矢印として示される。 The resource-related data storage means 359 holds resource-related data 359A (FIG. 15). The resource relationship data 359A is data indicating the correspondence between a virtual resource and the real resources 5 that constitute the virtual resource. The resource related data 359A is shown, for example, as an arrow from private car "AR001" to virtual resource "VR001" in FIG. 20.
　また記憶装置３５には、仮想リソース能力変換部３５１、能力予測部３５２、能力割当部３５３、制御計画部３５４などの各種コンピュータプログラムが格納されている。
　仮想リソース能力変換部３５１は、以下の処理を順に実行する。
　・実体リソース計測データ４５１Ａと実体リソース制約データ４５２Ａを入力する。
　・仮想化ロジックプール３５８Ａ内の仮想化ロジックを用いて、実体リソース計測データ４５１Ａに含まれる個々の実体リソース５の計測データをそれぞれ仮想能力データに変換する。どの仮想化ロジックを用いるかを示す情報は、仮想化定義データ３５７Ａに格納されている。
　・リソース運用制御装置１０から受信したリソースの要求内容を充足するリソースを、仮想能力データと組み合わせた仮想リソースとして構築する。
　・構築した仮想能力データを出力する。
　・リソース運用制御装置１０から受信するリソース要求内容と仮想化ロジックとの対応関係データに基づいて選定する。 The storage device 35 also stores various computer programs such as a virtual resource capacity conversion unit 351, a capacity prediction unit 352, a capacity allocation unit 353, and a control planning unit 354.
The virtual resource capacity conversion unit 351 sequentially executes the following processes.
- Input the entity resource measurement data 451A and the entity resource constraint data 452A.
- Using the virtualization logic in the virtualization logic pool 358A, convert the measurement data of each entity resource 5 included in the entity resource measurement data 451A into virtual capacity data. Information indicating which virtualization logic is used is stored in the virtualization definition data 357A.
- Build a resource that satisfies the resource request content received from the resource operation control device 10 as a virtual resource in combination with virtual capability data.
・Output the constructed virtual ability data.
- Selection is made based on the correspondence data between the resource request content and the virtualization logic received from the resource operation control device 10.
　能力予測部３５２は、仮想リソース能力変換部３５１が出力した仮想能力データと、因子データ４５３Ａとを入力し、所定の将来日時における能力を示す値の予測値を算出する予測モデルを同定し、予測値を算出し、予測値を能力割当部３５３に出力する。
　能力割当部３５３は、能力予測部３５２が出力した仮想能力データの予測値と、リソース運用制御装置１０から取得したリソース要求内容とを照らし合わせ、リソース運用制御装置１０に供する仮想リソースを決定する。 The capacity prediction unit 352 inputs the virtual capacity data outputted by the virtual resource capacity conversion unit 351 and the factor data 453A, identifies a prediction model for calculating a predicted value of the value indicating the capacity at a predetermined future date and time, and performs prediction. It calculates the value and outputs the predicted value to the capacity allocation unit 353.
The capacity allocation unit 353 compares the predicted value of the virtual capacity data output by the capacity prediction unit 352 with the content of the resource request obtained from the resource operation control device 10 and determines the virtual resource to be provided to the resource operation control device 10.
　制御計画部３５４は、以下のいずれかの場合に、仮想リソースを構成する実体リソース５の制御計画を生成し出力する。
　・能力割当部３５３において、能力予測部３５２が出力した仮想能力データの予測値がリソース運用制御装置１０から取得したリソース要求内容に適合しないと判定した場合
　・リソース運用制御装置１０からのリソース要求内容が変更された場合
　仮想リソースを構成する実体リソース５は、リソース関係データ３５９Ａから取得する。 The control planning unit 354 generates and outputs a control plan for the real resource 5 that constitutes the virtual resource in any of the following cases.
- When the capacity allocation unit 353 determines that the predicted value of the virtual capacity data output by the capacity prediction unit 352 does not match the resource request content obtained from the resource operation control device 10 - The resource request content from the resource operation control device 10 In the case where the actual resource 5 that constitutes the virtual resource is changed, the actual resource 5 that constitutes the virtual resource is obtained from the resource relationship data 359A.
　以下、図３および図４を参照して、リソース仮想化システム２の処理およびデータフローについて説明する。
　図３は、リソース仮想化システム２のリソース仮想化処理のデータフロー図である。
　データ管理装置４は、計測装置６または監視制御装置７から実体リソース計測データ４５１Ａを受信し、実体リソース計測データ記憶手段４５１に格納する。またデータ管理装置４は、情報入出力端末８から実体リソース制約データ４５２Ａを受信し、実体リソース制約データ記憶手段４５２に格納する。またデータ管理装置４は、情報配信装置９から因子データ４５３Ａを受信し、因子データ記憶手段４５３に格納する。 The processing and data flow of the resource virtualization system 2 will be described below with reference to FIGS. 3 and 4.
FIG. 3 is a data flow diagram of resource virtualization processing in the resource virtualization system 2.
The data management device 4 receives the entity resource measurement data 451A from the measurement device 6 or the monitoring and control device 7, and stores it in the entity resource measurement data storage means 451. The data management device 4 also receives entity resource constraint data 452A from the information input/output terminal 8, and stores it in the entity resource constraint data storage means 452. The data management device 4 also receives factor data 453A from the information distribution device 9 and stores it in the factor data storage means 453.
　仮想リソース能力変換部３５１は、以下の処理を順に実行する。
　・実体リソース計測データ４５１Ａに記録されている１つ以上の実体リソース５の計測データを、予め定めた日時の範囲で実体リソース計測データ４５１Ａから取得する。
　・取得した実体リソース５の稼働に関する制約や条件のデータを、実体リソース制約データ４５２Ａから取得する。
　・能力割当部３５３を介してリソース運用制御装置１０から入力されたリソース要求内容のデータをキーとして、実体リソース５の計測データを仮想能力データに変換するための仮想化処理ロジックを示す識別子を仮想化定義データ３５７Ａから取得する。
　・取得した仮想化処理ロジックを示す識別子をキーとして、仮想化処理ロジックを仮想化ロジックプール３５８Ａから取得する。
　・取得した仮想化処理ロジックに、取得した各実体リソース５の実体リソース計測データ４５１Ａと実体リソース制約データ４５２Ａを入力し、仮想能力データに変換する。
　・仮想能力データを組み合わせることで仮想リソースを構築する。
　・構築した仮想リソースを示す識別子と能力を示すデータとを仮想能力データとして出力する。
　・仮想リソース能力変換部３５１は、当該仮想リソースと仮想リソースを構成する実体リソース５との対応関係を示すリソース関係データ３５９Ａを、リソース関係データ記憶手段３５９に格納する。 The virtual resource capacity conversion unit 351 sequentially executes the following processes.
- Acquire the measurement data of one or more entity resources 5 recorded in the entity resource measurement data 451A from the entity resource measurement data 451A within a predetermined date and time range.
- Obtain data on constraints and conditions regarding the operation of the acquired entity resource 5 from the entity resource constraint data 452A.
- Using the resource request content data input from the resource operation control device 10 via the capacity allocation unit 353 as a key, an identifier indicating the virtualization processing logic for converting the measurement data of the real resource 5 into virtual capacity data is virtualized. It is obtained from the definition data 357A.
- Acquire the virtualization processing logic from the virtualization logic pool 358A using the obtained identifier indicating the virtualization processing logic as a key.
- Input the acquired entity resource measurement data 451A and entity resource constraint data 452A of each entity resource 5 into the acquired virtualization processing logic and convert them into virtual capability data.
- Build virtual resources by combining virtual capacity data.
- Output an identifier indicating the constructed virtual resource and data indicating the capability as virtual capability data.
- The virtual resource capability conversion unit 351 stores resource relationship data 359A indicating the correspondence between the virtual resource and the entity resources 5 that constitute the virtual resource in the resource relationship data storage unit 359.
　能力予測部３５２は、以下の処理を順に実行する。
　・仮想リソース能力変換部３５１が出力した仮想リソースデータと、データ管理装置４から因子データ４５３Ａを取得する。
　・仮想能力データの予測値を算出するための予測モデルを同定する。
　・同定した予測モデルにあらかじめ定めた将来日時の因子データ４５３Ａを入力することで仮想能力データの予測値を算出する。
　・能力を示すデータの予測値と、仮想リソースを示す識別子とを合わせて仮想リソース能力予測結果データとして出力する。 The ability prediction unit 352 sequentially executes the following processes.
- Acquire the virtual resource data output by the virtual resource capacity conversion unit 351 and the factor data 453A from the data management device 4.
・Identify a prediction model for calculating predicted values of virtual ability data.
- Calculate the predicted value of the virtual ability data by inputting the factor data 453A of a predetermined future date and time into the identified prediction model.
- The predicted value of the data indicating the capacity and the identifier indicating the virtual resource are combined and output as virtual resource capacity prediction result data.
　能力割当部３５３は、以下の処理を順に実行する。
　・能力予測部３５２から取得した仮想リソース能力予測結果データと、リソース運用制御装置１０から取得したリソース要求内容とを取得する。
　・仮想リソース能力予測結果データに示される仮想能力データの予測値がリソース要求内容を充足するか否かを判定する。
　・充足すると判定した場合は、当該仮想リソースをリソース運用制御装置１０の制御運用に供するものとして登録する。
　・充足しないと判定した場合は、制御計画部３５４に対して当該仮想リソースを構成する実体リソース５の稼働を変更する制御計画の生成処理を起動する制御計画生成指示データを出力する。 The capacity allocation unit 353 sequentially executes the following processes.
- Obtain the virtual resource capacity prediction result data obtained from the capacity prediction unit 352 and the resource request content obtained from the resource operation control device 10.
- Determine whether the predicted value of the virtual capacity data shown in the virtual resource capacity prediction result data satisfies the resource request content.
- If it is determined that the virtual resource is sufficient, the virtual resource is registered as one to be controlled and operated by the resource operation control device 10.
- If it is determined that it is not sufficient, outputs control plan generation instruction data to the control planning unit 354 to start a process of generating a control plan that changes the operation of the real resources 5 that constitute the virtual resource.
　制御計画部３５４は、以下の処理を順に実行する。
　・能力割当部３５３からの制御計画生成指示データの受信を以て動作を開始し、
　・リソース関係データ３５９Ａを取得し、制御計画生成対象の仮想リソースを構成する１つ以上の実体リソース５の制御計画を生成し、制御計画データとして出力する。
　・出力した制御計画データは能力予測部３５２に入力し、制御計画実行後における当該仮想能力データの予測値を能力予測部３５２において再度算出し出力する。 The control planning unit 354 sequentially executes the following processes.
-Starts operation upon receiving control plan generation instruction data from the capacity allocation unit 353,
- Obtain the resource related data 359A, generate a control plan for one or more real resources 5 that constitute the virtual resource for which the control plan is to be generated, and output it as control plan data.
- The output control plan data is input to the capacity prediction unit 352, and the predicted value of the virtual capacity data after the execution of the control plan is calculated again in the capacity prediction unit 352 and output.
　図４は、リソース仮想化システム２のリソース仮想化処理の処理手順を示すフローチャートである。このフローチャートは、以下のいずれかを契機として始まる処理であり、リソース仮想化装置３によりステップＳ４０１からステップＳ４０５の処理が実行される。
　・リソース仮想化装置３が装置利用者からの入力操作を受け付けたこと
　・リソース運用制御装置１０からリソースの要求を受け付けたこと
　・予め設定した実行時刻になったこと
　なお実際には、リソース仮想化装置３のＣＰＵ３１および記憶装置３５に格納されている各種コンピュータプログラムならびにデータ管理装置４のＣＰＵ４１および記憶装置４５に格納されている各種コンピュータプログラムに基づいて処理が実行される。説明の便宜上、処理主体をリソース仮想化装置３およびリソース仮想化装置３が有する各種コンピュータプログラムとして説明する。 FIG. 4 is a flowchart showing the procedure of resource virtualization processing in the resource virtualization system 2. This flowchart is a process that starts with one of the following as a trigger, and the resource virtualization device 3 executes the processes from step S401 to step S405.
- The resource virtualization device 3 has received an input operation from the device user. - A resource request has been received from the resource operation control device 10. - The preset execution time has arrived. In reality, resource virtualization Processing is executed based on various computer programs stored in the CPU 31 and storage device 35 of the device 3 and various computer programs stored in the CPU 41 and storage device 45 of the data management device 4. For convenience of explanation, the processing entities will be described as the resource virtualization device 3 and various computer programs included in the resource virtualization device 3.
　仮想リソース能力変換部３５１は、データ管理装置４から実体リソース計測データ４５１Ａと実体リソース制約データ４５２Ａを、能力割当部３５３からリソース要求内容データ（図６）をそれぞれ取得する。そしてリソース要求内容データと仮想化定義データ３５７Ａを用いて仮想化ロジックプール３５８Ａから仮想化処理ロジックを取得し、取得したロジックを用いて実体リソース計測データ４５１Ａを仮想能力データに変換する。そして仮想能力データを組み合わせて仮想リソースを作成する（Ｓ４０１） The virtual resource capability conversion unit 351 acquires the actual resource measurement data 451A and the actual resource constraint data 452A from the data management device 4, and the resource request content data (FIG. 6) from the capacity allocation unit 353. Then, virtualization processing logic is obtained from the virtualization logic pool 358A using the resource request content data and virtualization definition data 357A, and the real resource measurement data 451A is converted into virtual capacity data using the obtained logic. Then, a virtual resource is created by combining the virtual capability data (S401)
　能力予測部３５２は、仮想リソース能力変換部３５１が出力した仮想リソースデータと、データ管理装置４から取得した因子データ４５３Ａとから、仮想能力データの予測値を算出するための予測モデルを同定する。そして、能力予測部３５２は、同定した予測モデルにあらかじめ定めた将来日時の因子データ４５３Ａを入力することで仮想能力データの予測値を算出する（Ｓ４０２）。
　なお、能力予測部３５２は、Ｓ４０４で後記する実体リソース５の制御計画を用いて、Ｓ４０２で算出した仮想能力データの予測値を修正してもよい。 The capacity prediction unit 352 identifies a prediction model for calculating a predicted value of the virtual capacity data from the virtual resource data output by the virtual resource capacity conversion unit 351 and the factor data 453A acquired from the data management device 4. Then, the ability prediction unit 352 calculates the predicted value of the virtual ability data by inputting the factor data 453A of a predetermined future date and time into the identified prediction model (S402).
Note that the capacity prediction unit 352 may modify the predicted value of the virtual capacity data calculated in S402 using the control plan for the real resource 5, which will be described later, in S404.
　能力割当部３５３は、能力予測部３５２から仮想リソース能力予測結果データを取得し、リソース運用制御装置１０からリソース要求内容を取得する（Ｓ４０３）。そして、能力割当部３５３は、仮想リソース能力予測結果データに示される仮想能力データの予測値がリソース要求内容を充足するか否かを判定する（Ｓ４０３Ａ）。
　Ｓ４０３ＡでYesなら、能力割当部３５３は、Ｓ４０３の判定にてリソース運用制御装置１０から受信したリソース要求内容を充足すると判定した仮想リソースをリソース運用制御装置１０の制御運用に供するものとして登録し、リソース運用制御装置１０に送信する（Ｓ４０５）。 The capacity allocation unit 353 acquires the virtual resource capacity prediction result data from the capacity prediction unit 352, and acquires the resource request content from the resource operation control device 10 (S403). Then, the capacity allocation unit 353 determines whether the predicted value of the virtual capacity data indicated in the virtual resource capacity prediction result data satisfies the resource request content (S403A).
If Yes in S403A, the capacity allocation unit 353 registers the virtual resource determined to satisfy the resource request content received from the resource operation control device 10 in the determination in S403 as one to be used for control operation of the resource operation control device 10, The information is transmitted to the resource operation control device 10 (S405).
　Ｓ４０３ＡでNoなら、制御計画部３５４に対して当該仮想リソースを構成する実体リソース５の稼働を変更する制御計画の生成処理を起動する制御計画生成指示データを出力することで、リソース構成の変更指示を出すか否かを判定する（Ｓ４０３Ｂ）。
　Ｓ４０３ＢでYesなら、Ｓ４０１に戻り、リソース構成の変更を実行することで、再度実行するＳ４０２の算出結果が変化する。
　Ｓ４０３ＢでNoなら、制御計画部３５４は、リソース関係データ３５９Ａを取得し、制御計画生成対象の仮想リソースを構成する１つ以上の実体リソース５の制御計画を生成する（Ｓ４０４）。生成した制御計画データは能力予測部３５２に入力されることで、再度実行するＳ４０２の算出結果が変化する。
　このように、Ｓ４０３Ｂの分岐結果がYesでもNoでも、再度実行するＳ４０２の算出結果が変化するので、再度実行するＳ４０３Ａの判定結果がYesに変化する可能性がある。 If No in S403A, the control planning unit 354 receives a resource configuration change instruction by outputting control plan generation instruction data that starts a control plan generation process that changes the operation of the real resources 5 that constitute the virtual resource. It is determined whether or not to issue (S403B).
If Yes in S403B, the process returns to S401 and the resource configuration is changed, thereby changing the calculation result in S402, which is executed again.
If No in S403B, the control planning unit 354 acquires the resource relationship data 359A and generates a control plan for one or more real resources 5 that constitute the virtual resource for which the control plan is to be generated (S404). The generated control plan data is input to the capacity prediction unit 352, thereby changing the calculation result of S402, which is executed again.
In this way, regardless of whether the branch result of S403B is Yes or No, the calculation result of S402 to be executed again changes, so there is a possibility that the determination result of S403A to be executed again changes to Yes.
　なお、能力割当部３５３は、以下のいずれかの場合に、仮想リソース能力変換部３５１に対して仮想リソースの形成処理を再実行する仮想リソース再生成指示データを出力する。そして、Ｓ４０１の処理から再実行される。
　・制御計画部３５４への制御計画生成指示データの出力回数が予め定めた回数を超過した場合
　・能力予測部３５２から取得する仮想能力データの予測値に変更が確認できない場合 Note that the capacity allocation unit 353 outputs virtual resource regeneration instruction data for re-executing the virtual resource formation process to the virtual resource capacity conversion unit 351 in any of the following cases. Then, the process is re-executed from S401.
- When the number of times control plan generation instruction data is output to the control planning unit 354 exceeds a predetermined number of times. - When no change can be confirmed in the predicted value of the virtual capacity data obtained from the capacity prediction unit 352.
　以下、図５から図７を用いて、各構成要素の詳細な実施形態を説明する。
　図５は、仮想リソース能力変換部３５１のデータフロー図である。
　仮想リソース能力変換部３５１は、実体リソース計測データ４５１Ａを仮想能力データに変換する。そして仮想能力データを組み合わせることで仮想リソースを構築し、構築した仮想リソースを示す識別子と能力を示すデータとを仮想能力データとして出力する。 Hereinafter, detailed embodiments of each component will be described using FIGS. 5 to 7.
FIG. 5 is a data flow diagram of the virtual resource capability conversion unit 351.
The virtual resource capacity conversion unit 351 converts the actual resource measurement data 451A into virtual capacity data. A virtual resource is constructed by combining the virtual capability data, and an identifier indicating the constructed virtual resource and data indicating the capability are output as virtual capability data.
　能力変換定義抽出部３５１Ａは、能力割当部３５３からリソース要求内容データを取得する。
　図６は、取得するリソース要求内容データの一例を示すテーブルである。図６のテーブルは、各列に以下のデータを格納している。
　・１列目に要求内容の識別子を示す「要求ＩＤ」
　・２列目に要求の提示元のリソース運用制御システムの名称を示す「要求システム名」
　・３列目に要求リソースの名称を示す「要求リソース名」
　・４列目にリソースの要求期間を示す「要求期間」
　・５列目にリソースの要求量を示す「要求量」
　・６列目にリソース品質への要求内容を示す「要求内容」
　・７列目にリソース供出場所への要求内容を示す「要求場所」 The capability conversion definition extraction unit 351A acquires resource request content data from the capability allocation unit 353.
FIG. 6 is a table showing an example of resource request content data to be acquired. The table in FIG. 6 stores the following data in each column.
・"Request ID" indicating the identifier of the request content in the first column
- "Requesting system name" indicating the name of the resource operation control system that is the source of the request in the second column
・"Request resource name" indicating the name of the requested resource in the third column
・"Request period" indicating the resource request period in the fourth column
・"Requested amount" which shows the requested amount of resources in the 5th column
・"Requirement content" indicating the content of requests for resource quality in the 6th column
・"Request location" indicating the content of the request to the resource supply location in the 7th column
　図６のテーブルの１行目の要求ＩＤが「R0001」の要求内容として、以下のデータを格納している。
　・要求システム名が「系統監視制御システムＡ」から提示された要求である。
　・要求しているリソースは「電力供給リソース」である。
　・要求期間は「２０２０／０１／０１　００：００から２０２１／１２／３１　２３：５９」の一年間である。
　・要求する量は「供給量として毎時１００ＭＷ以上」である。
　・要求場所は「地点Ａに供給すること」である。
　・要求品質は「－」であり、品質に対する要求は無いことを示している。 The following data is stored as the request contents of the request ID "R0001" in the first line of the table in FIG.
- The request system name is a request presented by "grid monitoring and control system A."
- The requested resource is a "power supply resource".
・The request period is one year from 2020/01/01 00:00 to 2021/12/31 23:59.
・The requested amount is "100 MW or more per hour as a supply amount."
- The requested location is "supply to point A".
- The required quality is "-", indicating that there is no quality requirement.
　図６のテーブルの２行目の要求ＩＤが「R0002」の要求内容として、以下のデータを格納している。
　・要求システム名が「系統監視制御システムＢ」から提示された要求である。
　・要求しているリソースは「電力輸送リソース」である。
　・要求期間は「２０２０／０１／０１　００：００から２０２１／０１／０１　２３：５９」の一日間である。
　・要求する量は「輸送量として毎時１０ＭＷ以上」である。
　・リソースの品質に対する要求は「輸送量の変動の許容範囲が、輸送量は±３％以内であること、さらに輸送開始と終了時刻の許容範囲が±３０分以内であること」である。
　・要求場所は「地点Ａから地点Ｂに輸送すること」である。 The following data is stored as the request contents of the request ID "R0002" in the second line of the table in FIG.
- The request system name is a request presented from "grid monitoring and control system B."
- The requested resource is "electricity transport resource".
- The request period is one day from "2020/01/01 00:00 to 2021/01/01 23:59".
・The required amount is "10 MW or more per hour as transportation volume."
-Requirements regarding the quality of resources are ``the permissible range for fluctuations in transport volume is within ±3%, and the permissible range for transport start and end times is within ±30 minutes.»
- The requested location is "transportation from point A to point B."
　図２２は、各仮想リソースの仮想能力データの一例を示すテーブルである。図２２のテーブルは、少なくとも各列に以下のデータを格納している。
　・１列目は、仮想リソース能力変換部３５１において形成した仮想リソースの識別子を示すデータが格納されている。
　・２列目は、日時を示すデータが格納されている。
　・３列目は、２列目に示す各日時における、１列目に示す仮想リソースの仮想能力の値を示すデータが格納されている。
　・４列目は、３列目に示す仮想能力の値の単位を示すデータが格納されている。
　・５列目は、２列目に示す日時における、１列目に示す仮想リソースの稼働内容を示すデータが格納されている。
　・６列目は、２列目に示す日時における、１列目に示す仮想リソースの稼働場所を示すデータが格納されている。 FIG. 22 is a table showing an example of virtual capability data of each virtual resource. The table in FIG. 22 stores at least the following data in each column.
- The first column stores data indicating the identifier of the virtual resource created by the virtual resource capability conversion unit 351.
- The second column stores data indicating the date and time.
- The third column stores data indicating the value of the virtual capacity of the virtual resource shown in the first column at each date and time shown in the second column.
- The fourth column stores data indicating the unit of the value of the virtual ability shown in the third column.
- The fifth column stores data indicating the operation details of the virtual resources shown in the first column at the date and time shown in the second column.
- The sixth column stores data indicating the operating location of the virtual resource shown in the first column at the date and time shown in the second column.
　この図２２では、説明の簡単のために、１列目に示す仮想リソースの識別子はすべて「VR001」としている。また同様に説明の簡単のため、２列目に示す日時は２０２１年１月１日の０時台から２０２１年１２月３１日の２３時台までを範囲とした１時間単位としている。
　ここで仮想リソースＩＤ「VR001」は、図２０に示すように、要求ＩＤ「R0001」に対応づけられた仮想リソースである。そして要求ＩＤ「R0001」は図６のリソース要求内容データの１行目に示す「系統監視制御システムＡ」から受信した要求である。 In FIG. 22, for ease of explanation, all virtual resource identifiers shown in the first column are "VR001". Similarly, for ease of explanation, the dates and times shown in the second column are hourly units ranging from 0:00 on January 1, 2021 to 23:00 on December 31, 2021.
Here, the virtual resource ID "VR001" is a virtual resource associated with the request ID "R0001", as shown in FIG. The request ID "R0001" is a request received from the "system monitoring and control system A" shown in the first line of the resource request content data in FIG.
　図６の１行目の要求内容によれば、要求期間が「２０２１年１月１日　００：００から２０２１年１２月３１日　２３：５９まで」であり、要求量は「供給量が１００ＭＷ／ｈ以上」であり、要求場所が「地点Ａ」である。
　図２２に示す仮想能力データでは、仮想リソースＩＤ「VR001」は、「２０２１年１月１日の０時台」から「２０２１年１２月３１日の２３時台」までにおいて常に１００ＭＷ／ｈ以上の地点Ａにおける電力供給能力を持つことを示している。従って要求充足評価部３５３Ｂは、仮想リソース「VR001」は要求ＩＤ「R0001」の要求を充足していると判定する。 According to the request content in the first line of Figure 6, the request period is “from January 1, 2021 00:00 to December 31, 2021 23:59”, and the request amount is “supply amount is 100MW/ h or more,” and the requested location is “point A.”
In the virtual capacity data shown in Figure 22, the virtual resource ID "VR001" always has a power of 100 MW/h or more from "00:00 on January 1, 2021" to "23:00 on December 31, 2021". This shows that it has the ability to supply power at point A. Therefore, the request satisfaction evaluation unit 353B determines that the virtual resource "VR001" satisfies the request of the request ID "R0001".
　図７は、取得した仮想化定義データ３５７Ａの一例を示すテーブルである。能力変換定義抽出部３５１Ａは仮想化定義データ３５７Ａを取得する。図７のテーブルは、各列に以下のデータを格納している。
　・１列目には、能力割当部３５３を経由してリソース運用制御装置１０から受信したリソース要求内容の識別子が格納されている。
　・２列目には、リソース要求内容に対応する様に設定登録している仮想化ロジックの識別子を格納している。
　・３列目には、仮想化ロジックの処理に適用する実体リソース５の稼働内容を示すデータが格納されている。 FIG. 7 is a table showing an example of the acquired virtualization definition data 357A. The capability conversion definition extraction unit 351A acquires virtualization definition data 357A. The table in FIG. 7 stores the following data in each column.
- The first column stores the identifier of the resource request content received from the resource operation control device 10 via the capacity allocation unit 353.
- The second column stores the identifier of the virtualization logic that has been set and registered to correspond to the resource request content.
- The third column stores data indicating the operation details of the entity resource 5 applied to the processing of the virtualization logic.
　例えば１行目は、「R0001」のリソース要求内容に対しは「P0001」の仮想化ロジックを用いて、稼働内容が「放電または蓄放電」の実体リソース５の実体リソース計測データ４５１Ａを仮想能力データに変換する様に設定登録していることを示している。 For example, the first line uses the virtualization logic of "P0001" for the resource request content of "R0001", and converts the real resource measurement data 451A of the real resource 5 whose operation content is "discharge or storage/discharge" into virtual capacity data. This shows that the settings are registered to convert to .
　また２行目は、以下を示している。
　・「R0002」のリソース要求内容に対しは「P0001」「P0002」「P0003」の複数の仮想化ロジックを用いている。
　・まず「P0001」「P0002」のそれぞれで処理をしたのち、各処理結果データを「P0003」に入力し処理する。
　・稼働内容が「放電または蓄放電であって、かつ移動」の実体リソース５の実体リソース計測データ４５１Ａを仮想能力データに変換する様に設定登録している。 The second line shows the following.
- Multiple virtualization logics "P0001", "P0002", and "P0003" are used for the resource request content of "R0002".
- First, process each of "P0001" and "P0002", then input each processing result data to "P0003" and process.
- Settings and registration are made so that the actual resource measurement data 451A of the actual resource 5 whose operation content is "discharge or storage/discharge, and movement" is converted into virtual capability data.
　また４行目は、以下を示している。
　・要求ＩＤが「R0004」に対しては、「P0005」「P0002」「P0006」の３つの仮想化ロジックを用いている。
　・「P0002」の仮想化ロジックは要求ＩＤ「R0002」でも用いている仮想化ロジックと同様のロジックを適用している。
　能力変換定義抽出部３５１Ａは、能力割当部３５３から取得したリソース要求内容の識別子をキーとして、図６に示す仮想化定義データ３５７Ａから仮想化ロジックの識別子および処理順序の情報を取得し、能力変換部３５１Ｂに出力する。 Furthermore, the fourth line shows the following.
- For request ID "R0004", three virtualization logics "P0005", "P0002" and "P0006" are used.
- The virtualization logic of "P0002" applies the same logic as the virtualization logic used for request ID "R0002".
The capacity conversion definition extraction unit 351A uses the identifier of the resource request content acquired from the capacity allocation unit 353 as a key to acquire the identifier of the virtualization logic and the processing order information from the virtualization definition data 357A shown in FIG. 6, and performs capacity conversion. It is output to section 351B.
　図８は、実体リソース制約データ４５２Ａの一例を示すテーブルである。能力変換部３５１Ｂは、まずデータ管理装置４から実体リソース計測データ４５１Ａと実体リソース制約データ４５２Ａを取得する。図８のテーブルは、各列に以下のデータを格納している。
　・１列目は実体リソース５の識別子である。
　・２列目は実体リソース５の名称を示すデータである。
　３列目以降は各実体リソース５の制約条件の内容を示すデータである。
　・３列目は各実体リソース５の稼働可能な内容を示すデータである。
　・４列目は各実体リソース５の制御の受け入れ可否を示すデータである。
　・５列目は各実体リソース５の稼働可能な日時の期間や時間帯を示すデータである。
　・６列目は実体リソース５それぞれについて、仮想リソースとして稼働した時に生じるコストを示すデータである。
　・７列目は、各実体リソース５の制約条件データを変更可能か否かを示すデータである。 FIG. 8 is a table showing an example of entity resource constraint data 452A. The capability conversion unit 351B first obtains the entity resource measurement data 451A and the entity resource constraint data 452A from the data management device 4. The table in FIG. 8 stores the following data in each column.
- The first column is the identifier of the entity resource 5.
- The second column is data indicating the name of the entity resource 5.
The third and subsequent columns are data indicating the contents of the constraint conditions for each entity resource 5.
- The third column is data indicating the operable contents of each entity resource 5.
- The fourth column is data indicating whether control of each entity resource 5 can be accepted.
- The fifth column is data indicating the period and time zone during which each entity resource 5 can operate.
- The sixth column is data indicating the cost incurred when operating as a virtual resource for each of the real resources 5.
- The seventh column is data indicating whether or not the constraint data of each entity resource 5 can be changed.
　例えば１行目の実体リソースＩＤ「AR001」である実体リソース名「自家用車」の実体リソース５は、以下を示している。
　・「蓄放電」と「移動」の稼働が可能である。
　・制御の受け入れは「不可」である。
　・稼働時間帯は「０８：００から１６：００」の時間帯である。
　・仮想リソースとして稼働した場合に生じるコストは「なし」である。
　・前述までの制約条件内容の変更は「不可」という制約条件を提示している実体リソース５である。 For example, the entity resource 5 with the entity resource ID "AR001" and the entity resource name "private car" in the first line shows the following.
- Capable of "storage/discharge" and "movement" operations.
- Acceptance of control is "not possible".
- The operating hours are from 08:00 to 16:00.
- There is no cost incurred when operating as a virtual resource.
- This is the entity resource 5 that presents the constraint condition that the above-mentioned constraint contents cannot be changed.
　なお実体リソース５は必ずしも一筐体の物理的な設備に限らない。例えば実体リソースＩＤ「AR005」に示す「工場の需要家」の様に物理的な設備筐体の集合体や、あるいは実体リソースＩＤ「AR007」に示す「仮想リソースＡ」の様に、複数の実体リソース５の集合体であってもよい。 Note that the entity resource 5 is not necessarily limited to a single casing of physical equipment. For example, a collection of physical equipment cases such as the "factory consumer" indicated by the entity resource ID "AR005", or a collection of multiple entities such as the "virtual resource A" indicated by the entity resource ID "AR007". It may be an aggregate of resources 5.
　そして能力変換部３５１Ｂは、能力変換定義抽出部３５１Ａから取得した仮想化ロジックの識別子「P0001～P0006など」を用いて仮想化ロジックプール３５８Ａから仮想化ロジックを取得する。能力変換部３５１Ｂは、能力変換定義抽出部３５１Ａから取得した処理順序に従って仮想化ロジックの処理を行う。 Then, the capability conversion unit 351B acquires the virtualization logic from the virtualization logic pool 358A using the virtualization logic identifiers “P0001 to P0006, etc.” acquired from the capability conversion definition extraction unit 351A. The capability conversion unit 351B processes the virtualization logic according to the processing order acquired from the capability conversion definition extraction unit 351A.
　以下、図７から図１５を用いて、能力変換部３５１Ｂの具体的な処理の流れを説明する。能力変換部３５１Ｂ内の仮想化ロジックが複雑になるのは、実体リソース５に要求される能力が要求元のシステムに応じて多種多様であるためである。
　前述の通り図７は、能力変換定義抽出部３５１Ａから取得した仮想化定義データ３５７Ａであり、要求内容データの識別子のそれぞれに対し、適用する仮想化ロジックのＩＤと仮想化ロジックの処理順序を示したデータである。
　例えば図７の１行目に示されている要求ＩＤ「R0001」に対しては、「P0001」の仮想化ロジックを適用する設定であることが示されている。従って能力変換定義抽出部３５１Ａは、仮想化ロジックプール３５８Ａから「P0001」の仮想化ロジックを取得し能力変換部３５１Ｂ内に配置する。 The specific processing flow of the ability converter 351B will be described below with reference to FIGS. 7 to 15. The reason why the virtualization logic in the capability conversion unit 351B is complicated is that the capabilities required of the actual resource 5 vary depending on the requesting system.
As mentioned above, FIG. 7 shows the virtualization definition data 357A obtained from the capability conversion definition extraction unit 351A, and shows the ID of the virtualization logic to be applied and the processing order of the virtualization logic for each identifier of the request content data. This is the data.
For example, it is shown that the setting is to apply the virtualization logic of "P0001" to the request ID "R0001" shown in the first line of FIG. 7. Therefore, the capability conversion definition extraction unit 351A acquires the virtualization logic of "P0001" from the virtualization logic pool 358A and places it in the capability conversion unit 351B.
　図９は、取得した能力変換部３５１Ｂ内に配置した「P0001」の仮想化ロジックの処理の説明図である。
　まず能力変換部３５１Ｂに配置した仮想化ロジック「P0001（３５１Ｂ１）」は、充電残量推定部３５１Ｂ１１においてデータ管理装置４から実体リソース計測データ４５１Ａを取得し、充電残量の時系列データを推定する。取得する実体リソース計測データ４５１Ａは、図７の「稼働内容」に「放電または蓄放電」と示されている。
　そのため、充電残量推定部３５１Ｂ１１は、図８の実体リソース制約条件データの「稼働可能内容」に「蓄電または蓄放電」と示されている「AR001」「AR002」「AR003」「AR004」「AR005」「AR006」「AR007」を少なくとも取得する。 FIG. 9 is an explanatory diagram of the processing of the virtualization logic of "P0001" placed in the acquired capability conversion unit 351B.
First, the virtualization logic "P0001 (351B1)" placed in the capacity conversion unit 351B acquires the actual resource measurement data 451A from the data management device 4 in the remaining charge estimation unit 351B11, and estimates the time series data of the remaining charge. . The acquired entity resource measurement data 451A is indicated as "discharge or storage/discharge" in "operation content" in FIG.
Therefore, the remaining charge amount estimating unit 351B11 calculates whether "AR001,""AR002,""AR003,""AR004," or "AR005" is indicated as "electricity storage or storage/discharge" in the "operable content" of the entity resource constraint data in FIG. ”, “AR006”, and “AR007”.
　そして、充電残量推定部３５１Ｂ１１は、取得した各実体リソース５の実体リソース計測データ４５１Ａに対して、以下の（推定手法１）または（推定方法２）を実行することにより、充電残量推定処理を実行する。
　（推定手法１）取得した実体リソース計測データ４５１Ａが充電残量の時系列データそのものである場合、そのまま出力する。
　（推定手法２）取得した実体リソース計測データ４５１Ａがある充電器に充電履歴の時系列データまたは充電器に接続した電気自動車等の各デバイスの充電履歴の時系列データである場合、充電開始から終了までの充電量を計算する。そして、過去の最大充電量から計算した充電量を除算した値を充電開始時点の充電残量として算出する。そして充電中の充電残量は充電量を以て充電残量として推定する。そして充電終了後から充電器接続終了後までは、充電開始時点の充電残量と充電中に充電した充電量の合計値の値を充電量として推定する。 Then, the remaining charge estimating unit 351B11 performs the remaining charge estimation process by executing the following (estimation method 1) or (estimation method 2) on the acquired entity resource measurement data 451A of each entity resource 5. Execute.
(Estimation method 1) If the acquired actual resource measurement data 451A is the time series data of the remaining charge level itself, it is output as is.
(Estimation method 2) If the acquired physical resource measurement data 451A is time-series data of the charging history of the charger or time-series data of the charging history of each device such as an electric vehicle connected to the charger, from the start to the end of charging Calculate the amount of charge up to. Then, the value obtained by dividing the calculated amount of charge from the past maximum amount of charge is calculated as the remaining amount of charge at the time of starting charging. The remaining amount of charge during charging is estimated as the remaining amount of charge using the amount of charge. From the end of charging to the end of connection to the charger, the total value of the remaining charge at the time of charging start and the amount of charge charged during charging is estimated as the charge amount.
　最小残量推定部３５１Ｂ１２は、充電残量推定部３５１Ｂ１１が出力した過去から最新日時までの充電残量の推定値の時系列データと実体リソース制約データ４５２Ａを取得し、当該の実体リソース５の充電残量の許容最小値を推定する。具体的には充電残量推定部３５１Ｂ１１が出力した過去から最新日時までの充電残量の推定値の時系列データにおける最小値を、当該の実体リソース５の充電残量の許容最低値として推定する。
　また実体リソース制約データ４５２Ａにおいて当該リソースの充電残量の許容最低値の制約条件を示すデータが存在している場合は、その制約条件の値を充電残量の許容最低値として推定する。 The minimum remaining amount estimating unit 351B12 acquires the time series data of the estimated value of the remaining charging amount from the past to the latest date and time outputted by the remaining charging amount estimating unit 351B11 and the entity resource constraint data 452A, and calculates the charging of the relevant entity resource 5. Estimate the minimum allowable remaining amount. Specifically, the minimum value in the time-series data of estimated values of remaining charge from the past to the latest date and time outputted by the remaining charge estimation unit 351B11 is estimated as the minimum allowable value of the remaining charge of the relevant entity resource 5. .
Furthermore, if there is data indicating a constraint on the minimum permissible value of the remaining charge of the resource in the actual resource constraint data 452A, the value of the constraint is estimated as the minimum permissible value of the remaining charge of the resource.
　電力供給能力算出部３５１Ｂ１３は、充電残量推定部３５１Ｂ１１が出力した過去から最新日時までの充電残量の推定値の時系列データと、最小残量推定部３５１Ｂ１２が出力した充電残量の許容最低値を取得し、当該実体リソース５の電力供給能力を算出する。 The power supply capacity calculation unit 351B13 uses the time series data of estimated values of the remaining charge amount from the past to the latest date and time outputted by the remaining charge estimating unit 351B11, and the minimum allowable remaining charge amount outputted by the minimum remaining amount estimating unit 351B12. The value is acquired, and the power supply capacity of the entity resource 5 is calculated.
　図１３は、図９の「P0001」を具体的に説明するための仮想能力データを示すグラフである。
　図１３の左側の図に示す白色の（塗られていない）棒グラフは、充電残量推定部３５１Ｂ１１が出力した過去から最新日時までの当該実体リソース５の充電残量の推定値の時系列データを示している。そして図中の点線（１３０３）は最小残量推定部３５１Ｂ１２が推定し出力した充電残量の許容最低値を示している。ここで充電完了後で充電器に接続した状態にある１３０１と１３０２の時間帯においては、電力を供給（逆潮）することが可能な時間帯である。 FIG. 13 is a graph showing virtual ability data for specifically explaining "P0001" in FIG.
The white (unpainted) bar graph shown in the left diagram of FIG. 13 represents time-series data of the estimated value of the remaining charge of the entity resource 5 from the past to the latest date and time output by the remaining charge estimating unit 351B11. It shows. A dotted line (1303) in the figure indicates the minimum allowable remaining charge amount estimated and output by the minimum remaining amount estimating unit 351B12. Here, during the time periods 1301 and 1302 in which the battery is connected to the charger after charging is completed, power can be supplied (reverse current).
　図１３の右側の図に示す灰色の（塗られている）棒グラフは、電力供給能力の仮想能力データを示すグラフである。
　電力供給能力算出部３５１Ｂ１３は、充電完了後で充電器に接続した状態にある１３０１と１３０２の時間帯において、右図における１３０４と１３０５に示す電力供給能力を示すデータに変換する。なお電力供給能力算出部３５１Ｂ１３において電力供給能力を示すデータの算出を行う際、取得した実体リソース制約データ４５２Ａに稼働に関わる制約が存在する実体リソース５に対しては、制約を充足した上で電力供給能力を示すデータに変換する。例えば図８に示す実体リソース制約データ４５２Ａの中で、実体リソース「AR001」の稼働時間帯は「０８：００から１６：００」と示されている。従ってこの時間帯以外の時間帯においては、当該の実体リソース５の実体リソース計測データ４５１Ａから変換する電力供給能力を示すデータは常にゼロと変換する。 The gray (filled) bar graph shown on the right side of FIG. 13 is a graph showing virtual capacity data of power supply capacity.
The power supply capacity calculation unit 351B13 converts into data indicating the power supply capacity shown in 1304 and 1305 in the right diagram during time periods 1301 and 1302 when the battery is connected to the charger after charging is completed. Note that when the power supply capacity calculation unit 351B13 calculates data indicating the power supply capacity, for the entity resource 5 for which there is a constraint related to operation in the acquired entity resource constraint data 452A, the power supply is calculated after satisfying the constraint. Convert to data indicating supply capacity. For example, in the entity resource constraint data 452A shown in FIG. 8, the operating time zone of the entity resource "AR001" is shown as "08:00 to 16:00." Therefore, in time periods other than this time period, the data indicating the power supply capacity converted from the actual resource measurement data 451A of the relevant actual resource 5 is always converted to zero.
　さらに、能力変換部３５１Ｂにおける仮想化ロジックの他の配置例を説明する。他に図７の２行目に示されている要求ＩＤ「R0002」に対しては、「P0001」「P0002」「P0003」の３つの仮想化ロジックを適用する設定であることが示されている。さらに、まず「P0001」「P0002」をそれぞれ動作させたのち、各結果データを入力とした「P0003」を動作させることで仮想能力データに変換する処理手順として設定されている。従って能力変換定義抽出部３５１Ａは、仮想化ロジックプール３５８Ａから「P0001」「P0002」「P0003」の仮想化ロジックを取得し、設定された処理順序に従って能力変換部３５１Ｂ内に配置する。 Furthermore, another example of arrangement of the virtualization logic in the capability conversion unit 351B will be explained. Additionally, for the request ID "R0002" shown in the second line of Figure 7, it is shown that three virtualization logics "P0001", "P0002", and "P0003" are applied. . Furthermore, the processing procedure is set to first operate "P0001" and "P0002" and then operate "P0003" with each result data as input to convert it into virtual ability data. Therefore, the capability conversion definition extraction unit 351A acquires the virtualization logics "P0001," "P0002," and "P0003" from the virtualization logic pool 358A, and arranges them in the capability conversion unit 351B according to the set processing order.
　図１０は、「P0001」「P0002」「P0003」の仮想化ロジックを能力変換部３５１Ｂ内に配置した説明図である。
　能力変換部３５１Ｂに配置した仮想化ロジック「P0001（３５１Ｂ１）」は、充電残量推定部３５１Ｂ１１を有する。
　充電残量推定部３５１Ｂ１１は、図７の要求ＩＤ「R0002」の３列目に示す稼働内容のデータに示す「放電または蓄放電であって、かつ移動」に合致する実体リソース５の実体リソース計測データ４５１Ａをデータ管理装置４から取得する。そして、充電残量推定部３５１Ｂ１１は、取得した実体リソース計測データ４５１Ａを用いて各実体リソース５の電力供給能力の時系列データを推定する。ここでの「P0001（３５１Ｂ１）」は前述した「P0001（３５１Ｂ１）」と同一であり、前述の処理手順によって電力供給能力を示すデータを算出する。 FIG. 10 is an explanatory diagram in which the virtualization logic of "P0001", "P0002", and "P0003" is arranged in the capability conversion unit 351B.
The virtualization logic “P0001 (351B1)” placed in the capacity conversion unit 351B includes a remaining charge estimation unit 351B11.
The remaining charge estimating unit 351B11 performs the actual resource measurement of the actual resource 5 that matches "discharging or storing/discharging and moving" shown in the operation content data shown in the third column of the request ID "R0002" in FIG. Data 451A is acquired from the data management device 4. Then, the remaining charge estimating unit 351B11 estimates time-series data of the power supply capacity of each entity resource 5 using the acquired entity resource measurement data 451A. "P0001 (351B1)" here is the same as "P0001 (351B1)" described above, and data indicating the power supply capacity is calculated by the aforementioned processing procedure.
　仮想化ロジック「P0002（３５１Ｂ２）」の停留場所推定部３５１Ｂ２１は、図７の要求ＩＤ「R0002」の３列目に示す稼働内容のデータに示す「放電または蓄放電であって、かつ移動」に合致する実体リソース５の実体リソース計測データ４５１Ａをデータ管理装置４から取得する。そして、停留場所推定部３５１Ｂ２１は、取得した実体リソース計測データ４５１Ａを用いて各実体リソース５の移動時における出発場所の時系列データを推定する。 The stop location estimating unit 351B21 of the virtualization logic "P0002 (351B2)" selects "discharge or storage/discharge and movement" as shown in the operation content data shown in the third column of the request ID "R0002" in FIG. The entity resource measurement data 451A of the matching entity resource 5 is acquired from the data management device 4. Then, the stop location estimating unit 351B21 estimates time-series data of the departure location of each entity resource 5 at the time of movement using the acquired entity resource measurement data 451A.
　時系列データの推定方法は、例えば、実体リソース計測データ４５１Ａの実体がＧＰＳなどの時刻毎の緯度経度情報の時系列データとした場合、所定の時間幅で同一の緯度経度に停留している時間帯と位置を抽出し、当該の位置を停留場所として推定する。次いで輸送能力算出部３５１Ｂ２２は、停留場所推定部３５１Ｂ２１が算出した当該実体リソース５の停留場所の過去から現在に至る時系列データを入力し、当該実体リソース５の移動能力を示すデータに変換する。
　停留場所推定部３５１Ｂ２１は、例えば、推定したある停留場所において当該の停留場所に停留している時間の中で何かしらの貨物を「集荷」する能力を有すると推定する。また停留場所推定部３５１Ｂ２１は、次の停留所においてその貨物を「着荷」する能力を有するものとして推定し、二か所の停留場所の間を当該貨物を「輸送」する能力を有するものとして推定し、前述の一連の輸送能力を示すデータに変換する。 The method for estimating time series data is, for example, when the entity of the entity resource measurement data 451A is time series data of latitude and longitude information for each time such as GPS, the time spent at the same latitude and longitude in a predetermined time width. The band and position are extracted and the corresponding position is estimated as the stopping place. Next, the transportation capacity calculation unit 351B22 inputs the time-series data from the past to the present of the stop location of the entity resource 5 calculated by the stop location estimation unit 351B21, and converts it into data indicating the movement capacity of the entity resource 5.
For example, the stop location estimating unit 351B21 estimates that the vehicle has the ability to "collect" some kind of cargo at a certain estimated stop location during the time the vehicle is stopped at the stop location. In addition, the stop location estimating unit 351B21 estimates that the cargo has the ability to "arrive" at the next stop, and estimates that it has the ability to "transport" the cargo between the two stops. , converted into data indicating the above-mentioned series of transport capacities.
　最後に「P0003（３５１Ｂ３）」が有する電力輸送能力算出部３５１Ｂ３１は、P0001およびP0002がそれぞれ算出した電力供給能力を示すデータと移動能力を示すデータおよび実体リソース制約データ４５２Ａを入力する。電力輸送能力算出部３５１Ｂ３１は、当該実体リソース５の電力輸送能力を示すデータに変換する。 Finally, the power transport capacity calculation unit 351B31 of "P0003 (351B3)" inputs the data indicating the power supply capacity, the data indicating the movement capacity, and the entity resource constraint data 452A calculated by P0001 and P0002, respectively. The power transport capacity calculation unit 351B31 converts it into data indicating the power transport capacity of the entity resource 5.
　図１４は、図１０の「P0001」「P0002」「P0003」を具体的に説明するためのグラフである。
　グラフ１４０１は、P0001の充電残量推定部３５１Ｂ１１が推定したある実体リソース５の充電残量の時系列データを示している。そして電力供給能力算出部３５１Ｂ１３は、グラフ１４０１に示す推定した充電残量の時系列データを入力し、当該実体リソース５の電力供給能力を示すデータとしてグラフ１４０２に示すデータを算出する。
　例えば当該実体リソース５は、グラフ１４０１における時間帯１４０１Ａにおいて充電器から電気を充電している。従って電力供給能力算出部３５１Ｂ１３は、当該実体リソース５は当該時間帯に「負の供給能力を有する」ものとして、グラフ１４０２の時間帯１４０２Ａに示す負の供給能力を算出する。
　そしてグラフ１４０１の時間帯１４０１Ｂにおいては、電力供給能力算出部３５１Ｂ１３は当該実体リソース５は充電器に接続しているものの充電はしていない時間帯と推定し、当該時間帯においては充電器を通じて充電残量の電気を供給（逆潮）する能力を有するものと推定する。結果、グラフ１４０２の時間帯１４０２Ｂに示すように正の供給能力を算出する。 FIG. 14 is a graph for specifically explaining "P0001", "P0002", and "P0003" in FIG. 10.
A graph 1401 shows time-series data of the remaining charge of a certain entity resource 5 estimated by the remaining charge estimation unit 351B11 of P0001. Then, the power supply capacity calculation unit 351B13 inputs the time series data of the estimated remaining charge amount shown in the graph 1401, and calculates the data shown in the graph 1402 as data indicating the power supply capacity of the entity resource 5.
For example, the entity resource 5 is being charged with electricity from a charger in a time period 1401A in the graph 1401. Therefore, the power supply capacity calculation unit 351B13 calculates the negative supply capacity shown in the time period 1402A of the graph 1402, assuming that the entity resource 5 "has a negative supply capacity" in the time period.
In the time period 1401B of the graph 1401, the power supply capacity calculation unit 351B13 estimates that the entity resource 5 is connected to the charger but is not being charged, and is not charged through the charger during the time period. It is assumed that it has the ability to supply the remaining amount of electricity (reverse flow). As a result, a positive supply capacity is calculated as shown in time zone 1402B of graph 1402.
　なお電力供給能力は電力の供給開始後に時間と共に低下する。従って時間帯１４０２Ｂに示すように、正の供給能力は時間減衰する様に算出する。減衰の程度の算出方法は、当該の予め取得した当該の実体リソース５の時間当たりの電力供給量の仕様情報に基づいて算出してもよい。または、当該の実体リソース５と同種の実体リソース５の仕様情報に基づいて算出してもよいし、当該の実体リソース５の過去の電力供給能力のデータから推定してもよいし、予め定めた係数に従って算出してもよい。 Note that the power supply capacity decreases over time after the start of power supply. Therefore, as shown in time period 1402B, the positive supply capacity is calculated so as to decay over time. The degree of attenuation may be calculated based on the specification information of the amount of power supplied per hour of the relevant entity resource 5, which is obtained in advance. Alternatively, it may be calculated based on the specification information of an entity resource 5 of the same type as the entity resource 5 in question, it may be estimated from data on the past power supply capacity of the entity resource 5 in question, or it may be estimated from data on the past power supply capacity of the entity resource 5 in question, It may also be calculated according to coefficients.
　次にグラフ１４０３は、P0002（３５１Ｂ２）における停留場所推定部３５１Ｂ２１が推定した当該実体リソース５の停留場所と停留時刻の時系列データを示している。当該の実体リソース５は、時間帯１４０３Ａに「地点Ａ」に停留し、その後時間をおいて移動したのち、時間帯１４０３Ｂに「地点Ｂ」に停留したものとして推定していることを意味している。そしてP0002（３５１Ｂ２）は、グラフ１４０３に示す推定した停留場所の結果データから、当該実体リソース５の輸送能力を示すデータを推定する。具体的にグラフ１４０４に示す様に、当該の実体リソース５は、地点Ａに停留している状態において「集荷」の能力を有していると推定する（時間帯１４０４Ａ）。その次に集荷した貨物を「輸送」する能力を有しているものと推定し（時間帯１４０４Ｂ）、そして地点Ｂにおいて貨物を「着荷」する能力を有するものとして推定している（時間帯１４０４Ｃ）ことを意味している。 Next, a graph 1403 shows time-series data of the stop location and stop time of the entity resource 5 estimated by the stop location estimation unit 351B21 in P0002 (351B2). This means that the relevant entity resource 5 is estimated to have stopped at "point A" in time zone 1403A, moved after some time, and then stopped at "point B" in time zone 1403B. There is. Then, P0002 (351B2) estimates data indicating the transportation capacity of the entity resource 5 from the result data of the estimated stop location shown in the graph 1403. Specifically, as shown in the graph 1404, it is estimated that the entity resource 5 in question has the ability to "collect cargo" while stationary at point A (time period 1404A). Next, it is estimated that it has the ability to "transport" the collected cargo (time period 1404B), and it is estimated that it has the ability to "arrive" the cargo at point B (time period 1404C). ) means that
　そして最後にP0003の電力輸送能力算出部３５１Ｂ３１は、P0001が算出した実体リソース５の電力供給能力を示すデータ（グラフ１４０２）と、P0002が算出した実体リソース５の輸送能力を示すデータ（グラフ１４０４）と、実体リソース制約データ４５２Ａとを入力し、グラフ１４０５に示す電力輸送能力を示すデータに変換する。具体的にまずグラフ１４０２の１４０２Ａには地点Ａにおいて負の供給能力（充電）を有するものとして推定されており、同時にグラフ１４０４の時間帯１４０４Ａに示すように地点Ａにおいて集荷の能力を有するものとして推定されている。 Finally, the power transport capacity calculation unit 351B31 of P0003 calculates the data (graph 1402) indicating the power supply capacity of the entity resource 5 calculated by P0001 and the data (graph 1404) indicating the transportation capacity of the entity resource 5 calculated by P0002. and entity resource constraint data 452A are input and converted into data indicating the power transport capacity shown in graph 1405. Specifically, first, 1402A of the graph 1402 is estimated to have a negative supply capacity (charging) at point A, and at the same time, as shown in time period 1404A of the graph 1404, it is assumed that the point A has the ability to collect goods. Estimated.
　従って電力輸送能力算出部３５１Ｂ３１は、グラフ１４０５の時間帯１４０５Ａに示すように、当該の実体リソース５は、当該の時間帯において、地点Ａにおいて電気という貨物を荷入れする能力を有するものとして推定する。そして同様に、グラフ１４０２の時間帯１４０２Ｂには地点Ｂにおいて正の供給能力（逆潮）を有するものとして推定されており、同時にグラフ１４０４の時間帯１４０４Ｃに示すように地点Ｂにおいて着荷する能力を有するものとして推定されている。 Therefore, the power transport capacity calculation unit 351B31 estimates that the relevant entity resource 5 has the ability to load the cargo of electricity at point A during the relevant time period, as shown in the time period 1405A of the graph 1405. . Similarly, in the time period 1402B of the graph 1402, it is estimated that the point B has a positive supply capacity (reverse tide), and at the same time, as shown in the time period 1404C of the graph 1404, the ability to arrive at the point B is estimated to be positive. It is estimated that the
　従って電力輸送能力算出部３５１Ｂ３１は、グラフ１４０５の時間帯１４０５Ｂに示すように、当該の実体リソース５は、当該の時間帯において、地点Ｂにおいて電気という貨物を荷下ろしする能力を有するものとして推定する。そして電力輸送能力算出部３５１Ｂ３１は、グラフ１４０４の時間帯１４０４Ｂに示す当該リソースが地点Ａから地点Ｂに移動する時間帯で貨物を輸送する能力を有するとの推定結果を基に、当該リソースは地点Ａで電気という貨物を荷入れし、地点Ｂに輸送し、地点Ｂで荷下ろしする能力を有するとして推定する。 Therefore, the power transport capacity calculation unit 351B31 estimates that the relevant entity resource 5 has the ability to unload the cargo of electricity at point B during the relevant time period, as shown in the time period 1405B of the graph 1405. . Then, the power transport capacity calculation unit 351B31 calculates that the resource shown in the time period 1404B of the graph 1404 has the ability to transport cargo in the time period when moving from point A to point B. It is assumed that the company has the ability to load the cargo of electricity at A, transport it to point B, and unload it at point B.
　さらに、能力変換部３５１Ｂにおける仮想化ロジックの他の配置例を説明する。図７の３行目に示している要求ＩＤ「R0003」は、稼働内容が「放電または蓄放電であって、再エネ」の実体リソース５の実体リソース計測データ４５１Ａを「P0004」の仮想化ロジックに適用して、仮想能力データに変換する様に定義されている。 Furthermore, another example of arrangement of the virtualization logic in the capability conversion unit 351B will be explained. The request ID "R0003" shown in the third line of FIG. It is defined so that it can be applied to virtual ability data.
　図１１は、取得した能力変換部３５１Ｂ内に配置した「P0004」の仮想化ロジックの処理の説明図である。
　P0004（３５１Ｂ４）に配置された再エネ供給能力算出部３５１Ｂ４１は、データ管理装置４から実体リソース計測データ４５１Ａと実体リソース制約データ４５２Ａを取得する。そして再エネ供給能力算出部３５１Ｂ４１は、取得した実体リソース計測データ４５１Ａと実体リソース制約データ４５２Ａを入力して、各実体リソース５の再生可能エネルギーの供給能力を示すデータに変換する。
　例えば、実体リソース計測データ４５１Ａに格納されているデータが、蓄電池としての実体リソース５の蓄電残量や放電量である場合、蓄電残量や放電量のデータから再生可能エネルギー由来の電力量の値を分離し、分離した値を再生可能エネルギーの供給能力を示すデータとして算出する。なお再生可能エネルギー由来の電力量の値を分離する手法は、再生可能エネルギーの発電量のトレーサビリティなどの公知の手法を適用してよい。なお実体リソース計測データ４５１Ａに格納されているデータが、元々再生可能エネルギーの発電量の実績データである場合は、その実績データをそのまま出力する。 FIG. 11 is an explanatory diagram of the processing of the virtualization logic of "P0004" placed in the acquired capability conversion unit 351B.
The renewable energy supply capacity calculation unit 351B41 located at P0004 (351B4) acquires the entity resource measurement data 451A and the entity resource constraint data 452A from the data management device 4. Then, the renewable energy supply capacity calculation unit 351B41 inputs the acquired entity resource measurement data 451A and entity resource constraint data 452A, and converts them into data indicating the renewable energy supply capacity of each entity resource 5.
For example, if the data stored in the entity resource measurement data 451A is the remaining amount of electricity stored or the amount of discharge of the entity resource 5 as a storage battery, the value of the amount of electricity derived from renewable energy is determined from the data of the remaining amount of electricity stored or the amount of discharge. The separated value is calculated as data indicating the supply capacity of renewable energy. Note that a known method such as traceability of power generation amount of renewable energy may be applied to the method of separating the value of the amount of power derived from renewable energy. Note that if the data stored in the actual resource measurement data 451A is originally actual data on the amount of power generated by renewable energy, the actual data is output as is.
　さらに、能力変換部３５１Ｂにおける仮想化ロジックの他の配置例を説明する。図７の４行目に示している要求ＩＤ「R0004」は、稼働内容が「貨物輸送」の実体リソース５の実体リソース計測データ４５１Ａを「P0005」「P0002」「P0006」の仮想化ロジックに適用して、仮想能力データに変換する様に定義されている。 Furthermore, another example of arrangement of the virtualization logic in the capability conversion unit 351B will be explained. The request ID "R0004" shown in the fourth line of FIG. 7 applies the entity resource measurement data 451A of entity resource 5 whose operation content is "freight transportation" to the virtualization logic of "P0005," "P0002," and "P0006." It is defined in such a way that it is converted into virtual ability data.
　図１２は、取得した能力変換部３５１Ｂ内に配置した「P0005」「P0002」「P0006」の仮想化ロジックの処理の説明図である。
　まず能力変換部３５１Ｂに配置されたP0005（３５１Ｂ５）は、データ管理装置４から実体リソース計測データ４５１Ａを取得する。取得する実体リソース計測データ４５１Ａは、図７の３列目の稼働内容に示す「貨物輸送」に基づいて、図８に示す実体リソース制約データ４５２Ａの参列名の「稼働可能内容」に「貨物輸送」と記されている実体リソースＩＤ「AR003」の実体リソース計測データ４５１Ａを少なくとも取得する。 FIG. 12 is an explanatory diagram of the processing of the virtualization logic of "P0005", "P0002", and "P0006" placed in the acquired capability conversion unit 351B.
First, P0005 (351B5) placed in the capability conversion unit 351B acquires the actual resource measurement data 451A from the data management device 4. The entity resource measurement data 451A to be acquired is based on "Freight Transportation" shown in the operation content in the third column of FIG. At least the entity resource measurement data 451A of the entity resource ID "AR003" written as "AR003" is acquired.
　そしてP0005が有する空き容量推定部３５１Ｂ５１は、実体リソース計測データ４５１Ａを入力して、各実体リソース５の時刻毎の空き容量を推定する。例えば実体リソース計測データ４５１Ａの計測データ内容が時刻毎または特定の地点ごとに計測された乗車人数である場合、当該実体リソース５の最大乗車人数から乗車人数を除算した乗車可能人数を、時刻毎または地点ごとに算出し、空き容量の推定結果として出力する。 Then, the free capacity estimating unit 351B51 of P0005 inputs the entity resource measurement data 451A and estimates the free capacity of each entity resource 5 at each time. For example, if the measurement data content of the entity resource measurement data 451A is the number of passengers measured at each time or at each specific point, the number of passengers who can ride the vehicle is calculated by dividing the number of passengers from the maximum number of passengers of the entity resource 5 at each time or at each specific point. It is calculated for each location and output as the estimated free capacity.
　そしてP0005が有する容量貨物変換部３５１Ｂ５２は、実体リソース５の空き容量から貨物の可能積載量を算出するための関数を生成する。関数の生成方法は、例えば、空き容量が「１０人」であれば貨物の可能積載量は「８０センチサイズの貨物５個」、「５人」であれば貨物の可能積載量は「８０センチサイズの貨物２個」などの様に、空き容量から貨物の可能積載量との対応関係の設定データを予め設定する方法、過去の貨物積載履歴とその時の空き容量のデータから重回帰モデル等の回帰モデルを用いて空き容量に対する貨物の可能積載量を算出するモデルを同定する方法などでも良い。 Then, the capacity cargo conversion unit 351B52 included in P0005 generates a function for calculating the possible loading capacity of cargo from the free capacity of the entity resource 5. The method of generating the function is, for example, if the free capacity is ``10 people'', the possible cargo loading capacity is ``5 pieces of 80cm size cargo'', and if there are ``5 people'', the possible cargo loading capacity is ``80cm size cargo''. A method of presetting setting data of the correspondence relationship between available capacity and possible loading capacity of cargo, such as "2 pieces of cargo of the same size", and a method of creating a multiple regression model etc. from past cargo loading history and data of free capacity at that time. A method of identifying a model that uses a regression model to calculate the possible loading amount of cargo for free space may also be used.
　そして貨物可載能力算出部３５１Ｂ５３は、空き容量推定部３５１Ｂ５１が算出した空き容量を示すデータを、容量貨物変換部３５１Ｂ５２が算出した空き容量から貨物の可能積載量を算出する関数に入力することで、当該の実体リソース５の貨物の可能積載能力を示すデータを算出する。なお算出においては、実体リソース制約データ４５２Ａに示されている当該実体リソース５の制約条件を充足できない時間帯等においては、貨物の可能積載量をゼロとして算出する。 The cargo loading capacity calculation unit 351B53 then inputs the data indicating the free capacity calculated by the free capacity estimating unit 351B51 into a function that calculates the possible cargo loading capacity from the free capacity calculated by the capacity cargo conversion unit 351B52. , calculates data indicating the possible cargo loading capacity of the relevant entity resource 5. In addition, in the calculation, the possible loading capacity of cargo is calculated as zero during a time period where the constraint conditions of the entity resource 5 shown in the entity resource constraint data 452A cannot be satisfied.
　また能力変換部３５１Ｂに配置したP0002（３５１Ｂ２）において、図１０で説明した方法で、当該実体リソース５の輸送能力を示すデータを算出する。 Furthermore, in P0002 (351B2) arranged in the capacity conversion unit 351B, data indicating the transport capacity of the relevant entity resource 5 is calculated using the method explained in FIG.
　そして能力変換部３５１Ｂに配置したP0006（３５１Ｂ６）は、貨物輸送能力算出部３５１Ｂ６１において、P0005が算出した貨物可載能力を示すデータと、P0002が算出した輸送能力を示すデータ、および実体リソース制約データ４５２Ａを入力し、各実体リソース５の貨物輸送能力を示すデータを算出する。算出の方法は、例えば時刻Ｔおける貨物可載能力が「８０センチサイズの貨物５個」であり、さらに時刻Ｔにおける輸送能力が「集荷」であり、また時刻Ｔ＋Ｎにおける輸送能力が「着荷」である場合、当該の実体リソース５は、時刻Ｔから時刻Ｔ＋Ｎにかけて「８０センチサイズの貨物５個」の貨物を輸送する貨物輸送能力を有するものとして算出する。 P0006 (351B6) placed in the capacity conversion unit 351B contains data indicating the cargo loading capacity calculated by P0005, data indicating the transport capacity calculated by P0002, and entity resource constraint data in the cargo transportation capacity calculation unit 351B61. 452A is input, and data indicating the cargo transportation capacity of each entity resource 5 is calculated. The calculation method is, for example, if the cargo carrying capacity at time T is "5 pieces of 80 cm size cargo", the transport capacity at time T is "collection", and the transport capacity at time T+N is "arrival". In one case, the relevant entity resource 5 is calculated as having a cargo transportation capacity to transport "5 pieces of 80 cm cargo" from time T to time T+N.
　以上説明した処理動作によって、能力変換部３５１Ｂは、実体リソース計測データ４５１Ａに格納されている各実体リソース５の計測データを、能力割当部３５３から取得したリソース要求内容データに従い、仮想能力データに変換する。
　リソース形成部３５１Ｃは、能力変換部３５１Ｂが出力した各実体リソース５の仮想能力データを時刻毎に合算することで、１つの仮想能力データを生成し、仮想リソースの識別子、仮想リソースを構成する実体リソース５の識別子、および仮想能力データを含むデータを、仮想リソースデータとして能力予測部３５２に対して出力する。なお、リソース形成部３５１Ｃは、仮想リソースに合算する（仮想リソースに対応付ける）実体リソース５を選択する方法として、能力変換部３５１Ｂが出力したすべての実体リソース５を選択してもよいし、一部の実体リソース５を選択してもよい。 Through the processing operations described above, the capacity conversion unit 351B converts the measurement data of each entity resource 5 stored in the entity resource measurement data 451A into virtual capacity data according to the resource request content data acquired from the capacity allocation unit 353. do.
The resource forming unit 351C generates one virtual capacity data by summing up the virtual capacity data of each entity resource 5 output by the capacity converting unit 351B at each time, and generates one virtual capacity data, and adds the identifier of the virtual resource and the entity configuring the virtual resource. Data including the identifier of the resource 5 and virtual capability data is output to the capability prediction unit 352 as virtual resource data. Note that the resource forming unit 351C may select all the actual resources 5 output by the capability conversion unit 351B as a method of selecting the actual resources 5 to be added to the virtual resource (corresponding to the virtual resource), or may select some of the actual resources 5 output by the capability converting unit 351B. The entity resource 5 may be selected.
　例えば、図２０の仮想リソースVR001は、実体リソース５「AR001～AR006」のうちの「AR001」だけが選択されて構成要素となっている。リソース形成部３５１Ｃは、仮想リソースVR001に対応する要求R0001の要求内容に対して、以下に列挙した少なくとも１つに該当する実体リソース５として「AR001」を選択した。
　・要求する内容を満たす能力を提供できる実体リソース５
　・要求する期間で能力を提供できる実体リソース５
　・要求するコストを満たす実体リソース５ For example, in the virtual resource VR001 in FIG. 20, only "AR001" among the real resources 5 "AR001 to AR006" is selected and becomes a component. The resource forming unit 351C selected "AR001" as the actual resource 5 that corresponds to at least one of the following for the request content of the request R0001 corresponding to the virtual resource VR001.
・Substantive resources that can provide the ability to meet the requested content 5
・Substantive resources that can provide capabilities within the required period 5
・Substantive resources 5 that meet the required cost
　ここで、リソース形成部３５１Ｃは、能力変換部３５１Ｂの算出結果である実測値の代わりに、能力予測部３５２の算出結果である予測値を用いて、仮想リソースに組み込む実体リソース５を選択してもよい。例えば、リソース形成部３５１Ｃは、能力予測部３５２が算出した当該仮想リソースの任意の将来日時における仮想能力データの予測値の期待値、２５％分位点などの分位点の予測値、信頼区間や予測区間などの区間推定値が、あらかじめ定めた閾値やリソース要求内容データに指定されている品質の条件を満たすように、実体リソース５を選択してもよい。
　この場合リソース形成部３５１Ｃは、能力予測部３５２に対して、予測結果データを戻す指示を行う制御データを出力する。制御データの出力は、仮想能力データの予測結果データが予め定めた閾値を超えるまでまたは予測結果データの値の前回と今回の変化差分が予め定めた値を下回るまで行う。
　これにより、仮想リソースの能力の量や品質の確実性を担保した仮想リソースの形成が可能となる。 Here, the resource forming unit 351C selects the actual resource 5 to be incorporated into the virtual resource using the predicted value that is the calculation result of the capacity prediction unit 352 instead of the actual measurement value that is the calculation result of the capacity conversion unit 351B. Good too. For example, the resource forming unit 351C may calculate the expected value of the predicted value of the virtual capacity data at any future date and time of the virtual resource calculated by the capacity prediction unit 352, the predicted value of the quantile such as the 25% quantile, and the confidence interval. The actual resource 5 may be selected such that the estimated value of the interval, such as the prediction interval or the predicted interval, satisfies a predetermined threshold or a quality condition specified in the resource request content data.
In this case, the resource forming unit 351C outputs control data that instructs the capacity predicting unit 352 to return prediction result data. The control data is output until the prediction result data of the virtual ability data exceeds a predetermined threshold or until the difference in change between the previous and current values of the prediction result data falls below a predetermined value.
This makes it possible to form a virtual resource that guarantees the quantity and quality of the virtual resource's capacity.
　あるいは、能力予測部３５２において算出した当該仮想リソースの任意の将来日時における仮想能力データの予測値の信頼区間や予測区間などの区間推定値が最小となるように、リソース形成部３５１Ｃは、仮想リソースに組み込む実体リソース５を選択してもよい。この場合リソース形成部３５１Ｃは、能力予測部３５２に対して、予測結果データを戻す指示を行う制御データを出力する。制御データの出力は、仮想能力データの予測結果データが予め定めた閾値を超えるまでまたは予測結果データの値の前回と今回の変化差分が予め定めた値を下回るまで行う。
　または、能力予測部３５２が算出する所定日時における仮想リソースの能力の予測値の期待値、分位点予測値、区間予測値の少なくともいずれか１つが予め定めた基準値を満たすように、リソース形成部３５１Ｃは、仮想リソースに組み込む実体リソース５を選択してもよい。 Alternatively, the resource forming unit 351C may configure the virtual resource so that the interval estimated value such as the confidence interval or prediction interval of the predicted value of the virtual capacity data at any future date and time of the virtual resource calculated by the capacity prediction unit 352 is minimized. You may select the entity resources 5 to be incorporated into. In this case, the resource forming unit 351C outputs control data that instructs the capacity predicting unit 352 to return prediction result data. The control data is output until the prediction result data of the virtual ability data exceeds a predetermined threshold or until the difference in change between the previous and current values of the prediction result data falls below a predetermined value.
Alternatively, the resource is formed so that at least one of the expected value, quantile predicted value, and section predicted value of the predicted value of the capacity of the virtual resource at a predetermined date and time calculated by the capacity prediction unit 352 satisfies a predetermined reference value. The unit 351C may select the actual resource 5 to be incorporated into the virtual resource.
　このように、仮想リソース能力変換部３５１は、事前に記憶された複数の仮想化ロジックを、リソース運用管理システムが要求する実体リソースの能力様態を充足するように組み合わせることで仮想リソースを構築する。
　または、仮想リソース能力変換部３５１は、能力予測部３５２が計算した仮想能力データの予測値に基づいて仮想リソースを構築する。
　ここで、仮想リソース能力変換部３５１は、各実体リソース５の制約条件を示す情報に基づいて生成される仮想リソースの属性を示す情報（制御可否やコスト）が、予め定めた基準を充足するように仮想リソースを構成する実体リソース５の組み合わせを決定してもよい。
　これにより、仮想リソースの能力の量や品質の不確実性を最小化した仮想リソースの形成が可能となる。 In this way, the virtual resource capability conversion unit 351 constructs a virtual resource by combining a plurality of pre-stored virtualization logics so as to satisfy the capability aspect of the actual resource required by the resource operation management system.
Alternatively, the virtual resource capability converter 351 constructs a virtual resource based on the predicted value of the virtual capability data calculated by the capability predictor 352.
Here, the virtual resource capability conversion unit 351 ensures that the information indicating the attributes of the virtual resource (controllability and cost) generated based on the information indicating the constraint conditions of each entity resource 5 satisfies predetermined criteria. The combination of real resources 5 that make up the virtual resource may be determined.
This makes it possible to form a virtual resource that minimizes uncertainty in the amount and quality of the capacity of the virtual resource.
　なおリソース形成部３５１Ｃは、形成した仮想リソースと仮想リソースを構成する実体リソース５との対応関係を示すデータをリソース関係データ３５９Ａとして出力し、リソース関係データ記憶手段３５９に格納する。
　図１５は、リソース関係データ３５９Ａの例を示すテーブルである。図１５のテーブルは、各列に以下のデータを格納している。
　・１列目はリソース形成部３５１Ｃが形成した仮想リソースそれぞれを識別する識別子のデータが格納されている。
　・２列目は、仮想リソースを構成する実体リソース５の識別子のデータが格納されている。
　・３列目および４列目は、各実体リソース５が各仮想リソースの構成要素として対応づけられる開始日時と終了日時が格納されている。 Note that the resource forming unit 351C outputs data indicating the correspondence between the formed virtual resources and the real resources 5 constituting the virtual resources as resource relationship data 359A, and stores the data in the resource relationship data storage unit 359.
FIG. 15 is a table showing an example of resource related data 359A. The table in FIG. 15 stores the following data in each column.
- The first column stores identifier data for identifying each virtual resource formed by the resource forming unit 351C.
- The second column stores data of the identifier of the real resource 5 that constitutes the virtual resource.
- The third and fourth columns store the start date and time and end date and time at which each real resource 5 is associated as a component of each virtual resource.
　図１５のテーブルは、各行に以下のデータを格納している。
　・１行目には、仮想リソースＩＤ「VR001」には実体リソース「AR001」が構成要素として対応づけられており、実体リソース「AR001」が構成要素となる期間は「２０２１／０１／０１　１３：２４」から「２０２１／０１／０１　１４：４３」であることが示されている。
　・２行目の「VR002」の仮想リソースには「AR002」の実体リソース５が構成要素として対応づけられている。
　・３行目に示すように「VR002」の仮想リソースには、「AR002」とは異なる時間帯において「AR003」も構成要素として対応づけられていることが示されている。
　この様にリソース形成部３５１Ｃは、１つの仮想リソースに対して、同一あるいは異なる時間帯において複数の実体リソース５が構成要素となる様に仮想リソースを形成する。 The table in FIG. 15 stores the following data in each row.
- In the first line, the virtual resource ID "VR001" is associated with the entity resource "AR001" as a component, and the period during which the entity resource "AR001" is a component is "2021/01/01 13: 24” to “2021/01/01 14:43”.
- The virtual resource "VR002" on the second line is associated with the real resource 5 "AR002" as a component.
- As shown in the third line, it is shown that "AR003" is also associated with the virtual resource "VR002" as a component in a different time zone from "AR002".
In this manner, the resource forming unit 351C forms a virtual resource such that a plurality of real resources 5 serve as constituent elements in the same or different time periods for one virtual resource.
　また「VR002」の仮想リソースを構成する実体リソース「AR003」は、７行目に示す仮想リソース「VR005」を構成する実体リソース５でもあることを示している。そして３列目と４列目の期間に示すように、「AR003」は「VR002」と「VR005」の複数の仮想リソースに同時に構成されていることも示している。
　ここで「VR002」の仮想リソースは図６のリソース要求データの２行目に示す要求リソース「電力輸送リソース」に供することを目的に形成された仮想リソースであり、「VR005」は図６に示すリソース要求データの５行目に示す「貨物輸送リソース」に供する目的で形成した仮想リソースである。 Further, the actual resource "AR003" that constitutes the virtual resource "VR002" is also shown to be the actual resource 5 that constitutes the virtual resource "VR005" shown in the seventh line. As shown in the periods in the third and fourth columns, it also shows that "AR003" is configured into multiple virtual resources "VR002" and "VR005" at the same time.
Here, the virtual resource "VR002" is a virtual resource created for the purpose of providing the requested resource "power transport resource" shown in the second line of the resource request data in FIG. 6, and "VR005" is a virtual resource shown in FIG. 6. This is a virtual resource created for the purpose of providing the "freight transportation resource" shown in the fifth line of the resource request data.
　ここで実体リソース「AR003」は図８の実体リソース制約データ４５２Ａの３行目に示すように実体リソース名「顧客バス」であり、稼働内容は「蓄放電、移動、貨物輸送」である。すなわち「AR003」は、移動の状態において「充電池を用いた電力の輸送能力」と「旅客スペースを用いた貨物輸送能力」の二つの仮想リソースとして能力を同時に供することが可能な実体リソース５である。
　従ってリソース形成部３５１Ｃは、同一時刻に「電力輸送の能力」と「貨物輸送の能力」を示すデータが存在する「AR003」の実体リソース５を、「VR002」と「VR005」に同時に構成していることを示している。
　以上をもって仮想リソース能力変換部３５１を説明した。 Here, the entity resource "AR003" is the entity resource name "customer bus" as shown in the third line of the entity resource constraint data 452A in FIG. 8, and the operation content is "storage/discharge, movement, freight transportation". In other words, "AR003" is an actual resource 5 that can simultaneously provide two virtual resources of "ability to transport electricity using rechargeable batteries" and "capacity to transport cargo using passenger space" in the state of movement. be.
Therefore, the resource formation unit 351C simultaneously configures the entity resource 5 of "AR003", which has data indicating "power transport capability" and "freight transport capability", into "VR002" and "VR005" at the same time. It shows that there is.
The virtual resource capability conversion unit 351 has been explained above.
　図１６は、能力予測部３５２のデータフロー図である。能力予測部３５２は、仮想リソース能力変換部３５１が出力した仮想能力データと、因子データ４５３Ａとを入力し、所定の将来の日時における仮想能力データの予測値を出力する。 FIG. 16 is a data flow diagram of the ability prediction unit 352. The capacity prediction unit 352 inputs the virtual capacity data output by the virtual resource capacity conversion unit 351 and the factor data 453A, and outputs a predicted value of the virtual capacity data at a predetermined future date and time.
　具体的にまずモデル同定部３５２Ａは、仮想リソース能力変換部３５１が出力した仮想能力データと因子データ４５３Ａとを入力し、因子データ４５３Ａに含まれる各因子の値を入力に仮想能力データの値を出力する予測モデルを同定する。予測モデルの同定手法は公知の手法を適用してよい。公知の手法とは例えば、以下のいずれかの手法である。
　・重回帰モデルなどの線形回帰モデルやロジスティック回帰などの一般化線形モデルなどの線形性を仮定する手法
　・ＡＲＸ（AutoRegressive with Exogenous）モデルなどの自己回帰性を仮定する手法
　・Ｒｉｄｇｅ回帰、Ｌａｓｓｏ回帰、ＥｌａｓｔｉｃＮｅｔなどの縮小推定器を利用する手法
　・部分最小二乗法や主成分回帰などの次元縮退器を利用する手法
　・多項式を用いた非線形モデル、あるいはサポートベクトル回帰、回帰木、ガウス過程回帰、ニューラルネットなどのノンパラメトリックと呼ばれる回帰モデル手法
　・また回帰モデル手法などの帰納的あるいは内挿的な手法のみならず、エージェントシミュレーションなどの演繹的あるいは外挿的な手法でもよい。 Specifically, first, the model identification unit 352A inputs the virtual capacity data and factor data 453A output by the virtual resource capacity conversion unit 351, and inputs the values of the virtual capacity data using the values of each factor included in the factor data 453A. Identify the predictive model to output. A known method may be applied to the prediction model identification method. The known method is, for example, any of the following methods.
・Methods that assume linearity such as linear regression models such as multiple regression models and generalized linear models such as logistic regression ・Methods that assume autoregressiveness such as ARX (AutoRegressive with Exogenous) models ・Ridge regression, Lasso regression, Methods that use reduction estimators such as ElasticNet - Methods that use dimension reducers such as partial least squares and principal component regression - Nonlinear models using polynomials, support vector regression, regression trees, Gaussian process regression, and neural networks Regression model methods called non-parametric methods such as ・Not only inductive or interpolation methods such as regression model methods, but also deductive or extrapolation methods such as agent simulation may be used.
　なおモデル同定部３５２Ａは、能力割当部３５３からの起動信号を受け取った制御計画部３５４が作成した実体リソース５の制御計画データの入力を受けた場合、予測モデルの同定処理に実体リソース５の制御計画データも用いる。例えば、制御受け入れ可否が「可」である実体リソース「AR00X」の時刻Ｔにおける初期状態の稼働が「稼働しない」という状態の例であって、従って仮想能力データの値が当初はゼロである場面を考える。
　この場面で、制御計画部３５４において「AR00X」の時刻Ｔにおける稼働を「稼働する」と変更する制御計画データを生成したとした場合、モデル同定部３５２Ａは実体リソース「AR00X」の時刻Ｔにおける仮想能力データの値を「ゼロより大きい値」に変更した上で、予測モデル同定処理を実行する。仮想能力データの値の変更方法は、例えば、以下の方法を用いる。
　・時刻Ｔの至近の時刻における仮想能力データの値と同値に変更する方法
　・予め定めた値に変更する方法
　・時刻や因子データ４５３Ａの値が類似する過去の日時の値と同値または平均値に変更する方法 Note that when the model identification unit 352A receives input of control plan data for the entity resource 5 created by the control planning unit 354 that has received the activation signal from the capacity allocation unit 353, the model identification unit 352A performs control planning for the entity resource 5 in the prediction model identification process. Planning data is also used. For example, the initial state of operation at time T of the entity resource "AR00X" whose control acceptability is "possible" is "not in operation", and therefore the value of the virtual capacity data is initially zero. think of.
In this situation, if the control planning unit 354 generates control plan data that changes the operation of “AR00X” at time T to “operating”, the model identification unit 352A generates a virtual After changing the value of the ability data to "a value greater than zero", the predictive model identification process is executed. For example, the following method is used to change the value of the virtual ability data.
- A method for changing the virtual ability data to the same value as the value at the closest time to time T. - A method for changing to a predetermined value. - A method for changing the value of the time and factor data 453A to the same value as the value of a similar past date and time, or an average value. How to change
　予測値算出部３５２Ｂは、モデル同定部３５２Ａが出力した予測モデルに対し、予測対象日時の因子データ４５３Ａの観測値または予測値を入力することで、仮想能力データの値の予測結果データを算出する。算出する予測結果データの形態は、期待値、２５％文位点などの分位点の予測値、信頼区間や予測区間などの区間推定値などである。算出した予測結果データは、能力割当部３５３に対して出力する。 The predicted value calculation unit 352B calculates prediction result data of the value of the virtual ability data by inputting the observed value or predicted value of the factor data 453A of the prediction target date and time to the prediction model output by the model identification unit 352A. . The format of the predicted result data to be calculated includes an expected value, a predicted value of a quantile such as a 25% point, and an interval estimate such as a confidence interval or a predicted interval. The calculated prediction result data is output to the capacity allocation section 353.
　なお仮想リソース能力変換部３５１から予測結果データを戻す指示を示す制御データを入力されている場合は、予測結果データは能力割当部３５３ではなく、仮想リソース能力変換部３５１に対して出力する。予測結果データの入力を受けた仮想リソース能力変換部３５１は、リソース形成部３５１Ｃで説明したように、予測結果データを用いて仮想リソースに対応付ける実体リソース５の構成を再変更する。仮想リソース能力変換部３５１から予測結果データを戻す指示を示す制御データの入力がなくなった場合、予測結果データは能力割当部３５３に出力する。
　以上をもって能力予測部３５２の動作を終了する。 Note that if control data indicating an instruction to return prediction result data is input from the virtual resource capacity conversion unit 351, the prediction result data is output to the virtual resource capacity conversion unit 351 instead of the capacity allocation unit 353. The virtual resource capacity conversion unit 351 that receives the prediction result data re-changes the configuration of the real resource 5 associated with the virtual resource using the prediction result data, as described in the resource formation unit 351C. When there is no longer input of control data indicating an instruction to return prediction result data from the virtual resource capacity conversion unit 351, the prediction result data is output to the capacity allocation unit 353.
With this, the operation of the ability prediction unit 352 ends.
　図１７は、能力割当部３５３のデータフロー図である。能力割当部３５３は、リソース運用制御装置１０からリソースの要求内容を示すデータを入力して、仮想リソース能力変換部３５１に対してリソース要求内容データを出力する。その後、能力割当部３５３は、能力予測部３５２から仮想能力データの予測結果データを入力し、リソース運用制御装置１０の運用制御に供する様に仮想リソースを設定したことを示すデータを出力する。 FIG. 17 is a data flow diagram of the capacity allocation unit 353. The capacity allocation unit 353 inputs data indicating resource request details from the resource operation control device 10 and outputs resource request content data to the virtual resource capacity conversion unit 351 . Thereafter, the capacity allocation unit 353 inputs the prediction result data of the virtual capacity data from the capacity prediction unit 352 and outputs data indicating that the virtual resource is set to be used for operational control of the resource operation control device 10.
　具体的にまずリソース要求データ生成部３５３Ａは、リソース運用制御装置１０からリソースの要求内容を示すデータを取得し、図６のようなリソース要求内容データを生成する。生成したリソース要求内容データは仮想リソース能力変換部３５１に対して出力し、以降は前述で説明した通り、仮想リソース能力変換部３５１において仮想能力データを出力し、次いで能力予測部３５２で仮想能力データの予測結果データを出力する。 Specifically, first, the resource request data generation unit 353A acquires data indicating the content of the resource request from the resource operation control device 10, and generates resource request content data as shown in FIG. The generated resource request content data is output to the virtual resource capacity conversion unit 351, and thereafter, as explained above, the virtual capacity conversion unit 351 outputs virtual capacity data, and then the capacity prediction unit 352 outputs virtual capacity data. Output the prediction result data.
　次いで要求充足評価部３５３Ｂは、能力予測部３５２が出力した仮想能力データの予測結果データを入力と、リソース要求データ生成部３５３Ａが出力したリソース要求内容データを入力し、仮想能力データの予測結果データがリソース要求内容を充足しているか否かを判定する。例えば、図６の１行目に示す要求ＩＤ「R0001」のリソース要求内容は、要求期間が「２０２１／０１／０１　００：００から２０２１／１２／３１　２３：５９」であり、要求量が「供給量が毎時１００ＭＷ以上」であり、要求場所が「地点Ａに供給」であるのに対し、能力予測部３５２が出力した仮想能力データの予測結果データが各要求を充足するか否かを判定する。充足すると判定した場合、要求充足評価部３５３Ｂは、各リソース運用制御装置１０から入力を受けたリソースの要求と仮想リソースとの対応付けを示す要求リソース対応データ（図１８）を生成する。要求リソース対応データは、例えば、図２０の仮想リソース「VR001」と、要求ＩＤ「R0001」とを対応付けるデータである。 Next, the requirement sufficiency evaluation unit 353B inputs the prediction result data of the virtual capacity data outputted by the capacity prediction unit 352, inputs the resource request content data outputted by the resource request data generation unit 353A, and generates the prediction result data of the virtual capacity data. Determine whether or not the content of the resource request is satisfied. For example, the resource request content of the request ID "R0001" shown in the first line of FIG. 6 has a request period of "2021/01/01 00:00 to 2021/12/31 23:59" and a request amount of " When the supply amount is "100 MW or more per hour" and the requested location is "supply to point A", it is determined whether the prediction result data of the virtual capacity data output by the capacity prediction unit 352 satisfies each request. do. If it is determined that the request sufficiency evaluation unit 353B is satisfied, the request sufficiency evaluation unit 353B generates request resource correspondence data (FIG. 18) indicating the correspondence between the resource request input from each resource operation control device 10 and the virtual resource. The requested resource correspondence data is, for example, data that associates the virtual resource "VR001" in FIG. 20 with the request ID "R0001".
　図１８は、要求リソース対応データの一例を示すテーブルである。図１８のテーブルは、各列に以下のデータを格納している。
　・１列目は仮想リソース能力変換部３５１において形成した仮想リソースの識別子を示すデータが格納されている。
　・２列目と３列目は、各仮想リソースが利用可能となる開始日時と終了日時を示すデータが格納されている。
　・４列目は制御受け入れが可能な仮想リソースか否かを示すデータが格納されている。
　・５列目は、各仮想リソースを供する様に要求充足評価部３５３Ｂが設定したリソース運用制御装置１０からの要求の識別子を示すデータが格納されている。
　・６列目には、仮想リソースの特性を示すデータが格納されており、図１８の例では、制御信号の受信から所定の制御量に到達するまでの時間である応答速度が示されている。 FIG. 18 is a table showing an example of request resource correspondence data. The table in FIG. 18 stores the following data in each column.
- The first column stores data indicating the identifier of the virtual resource created by the virtual resource capability conversion unit 351.
- The second and third columns store data indicating the start date and time and end date and time when each virtual resource becomes available.
- The fourth column stores data indicating whether or not the virtual resource can accept control.
- The fifth column stores data indicating the identifier of the request from the resource operation control device 10 set by the request sufficiency evaluation unit 353B to provide each virtual resource.
- The sixth column stores data indicating the characteristics of the virtual resource, and in the example of FIG. 18, the response speed, which is the time from receiving the control signal to reaching the predetermined control amount, is shown. .
　図１８のテーブルの１行目は、仮想リソースＩＤ「VR001」が「２０２１／０１／０１　００：００から２０２１／１２／３１　２３：５９」の期間で利用可能であり、また制御受け入れは「不可」である仮想リソースであることを示している。この仮想リソースは要求充足評価部３５３Ｂの判定処理の結果として要求ＩＤ「R0001」の要求を充足していると判定されており、従って５列目に示す通り、対応要求「R0001」に対応づけるように設定されていることを示している。
　図１８のテーブルの７行目は、仮想リソースＩＤ「VR007」がどの対応要求にも対応づけられていないこと、つまり、遊休状態の仮想リソースであることを示している。 The first row of the table in FIG. 18 shows that the virtual resource ID "VR001" can be used during the period "2021/01/01 00:00 to 2021/12/31 23:59", and control acceptance is "unavailable". ” indicates that it is a virtual resource. This virtual resource is determined to satisfy the request with the request ID “R0001” as a result of the determination process by the request satisfaction evaluation unit 353B, and therefore, as shown in the fifth column, it is determined that it is associated with the corresponding request “R0001”. It shows that it is set to .
The seventh line of the table in FIG. 18 indicates that the virtual resource ID "VR007" is not associated with any response request, that is, it is an idle virtual resource.
　図１８の他の行に例示している様に、要求充足評価部３５３Ｂは、各仮想能力データの予測結果データが各リソース要求内容を充足しているか否かを判定し、充足している場合は各リソース要求内容データのＩＤを対応付けて設定する。設定した要求リソース対応データは、リソース運用制御装置１０に送信し、リソース運用制御装置１０は入力を受けた仮想リソースを稼働させるか否かの判定を行い、稼働させる場合はリソース仮想化装置３に対して稼働制御を実行するための信号データを送信する。そしてリソース仮想化装置３は、制御可能な仮想リソースであって、かつ制御が必要な場合は、当該仮想リソースを構成する実体リソース５に対して、制御計画部３５４を通じて制御信号を送信する。 As illustrated in the other rows of FIG. 18, the request satisfaction evaluation unit 353B determines whether or not the prediction result data of each virtual capacity data satisfies each resource request content, and if it satisfies each resource request content, is set in association with the ID of each resource request content data. The set request resource correspondence data is sent to the resource operation control device 10, and the resource operation control device 10 determines whether or not to operate the input virtual resource. Sends signal data to execute operation control. When the resource virtualization device 3 is a controllable virtual resource and requires control, the resource virtualization device 3 transmits a control signal through the control planning unit 354 to the real resource 5 that constitutes the virtual resource.
　なお、要求充足評価部３５３Ｂは、仮想能力データの予測結果データがリソース要求内容データに示すリソースの要求内容を充足しないと判定した場合であって、当該の仮想リソースが制御可能な仮想リソースである場合は、充足違反の内容を示すデータと、当該の仮想リソースの制御計画の作成の指示を示すデータとを制御計画部３５４に出力する。制御計画の作成の指示を示すデータの入力を受けた制御計画部３５４は、充足違反が解消する様に、当該の仮想リソースを構成する実体リソース５の中の制御可能な実体リソース５についての制御計画データを生成する。作成した制御計画データは、前述の説明の通り能力予測部３５２に入力され、能力予測部３５２において仮想能力データの予測結果データが再算出される。そして再算出された予測結果データを用いて、要求充足評価部３５３Ｂは再度判定を行う。以上の動作は、要求充足評価部３５３Ｂがリソース要求内容を充足すると判定するまでまたは予め定めた回数を超えるまで繰り返す。 Note that the request satisfaction evaluation unit 353B determines that the prediction result data of the virtual capacity data does not satisfy the resource request content shown in the resource request content data, and the virtual resource in question is a controllable virtual resource. If so, data indicating the content of the sufficiency violation and data indicating an instruction to create a control plan for the virtual resource are output to the control planning unit 354. The control planning unit 354 receives the input data indicating the instruction to create a control plan, and performs control on the controllable entity resources 5 among the entity resources 5 constituting the virtual resource so that the sufficiency violation is resolved. Generate planning data. The created control plan data is input to the capacity prediction section 352 as described above, and the prediction result data of the virtual capacity data is recalculated in the capacity prediction section 352. Then, using the recalculated prediction result data, the request sufficiency evaluation unit 353B performs the determination again. The above operation is repeated until the request satisfaction evaluation unit 353B determines that the resource request content is satisfied or until a predetermined number of times is exceeded.
　さらに、要求充足評価部３５３Ｂは、前述の動作が予め定めた回数を超えた場合またはリソースの要求内容を充足しないと判定した仮想リソースが制御不可能な仮想リソースである場合、仮想リソース能力変換部３５１に対して、充足違反の内容を示すデータと、当該の仮想リソースの制御計画の作成の指示を示すデータとを制御計画部３５４に出力する。実体リソース５の構成を変更する指示を示すデータの入力を受けた仮想リソース能力変換部３５１は、要求違反を解消する様に、仮想リソースを構成する実体リソース５を変更する。そして実体リソース５の構成を変更した仮想能力データを能力予測部３５２に入力することで仮想能力データの予測結果データを再算出し、要求充足評価部３５３Ｂは再算出された予測結果データを用いて再度判定を行う。以上の動作は、要求充足評価部３５３Ｂがリソース要求内容を充足すると判定するまでまたは予め定めた回数を超えるまで繰り返す。
　以上をもって能力割当部３５３の動作を終了する。 Furthermore, if the above-mentioned operation exceeds a predetermined number of times or if the virtual resource determined not to satisfy the request content of the resource is an uncontrollable virtual resource, the request satisfaction evaluation unit 353B performs a virtual resource capacity conversion unit. 351, data indicating the content of the sufficiency violation and data indicating an instruction to create a control plan for the virtual resource are output to the control planning unit 354. The virtual resource capability conversion unit 351, which receives the input of the data indicating the instruction to change the configuration of the real resource 5, changes the real resource 5 making up the virtual resource so as to eliminate the request violation. Then, by inputting the virtual capability data in which the configuration of the real resource 5 has been changed into the capability prediction section 352, the prediction result data of the virtual capability data is recalculated, and the request satisfaction evaluation section 353B uses the recalculated prediction result data. Make the judgment again. The above operation is repeated until the request satisfaction evaluation unit 353B determines that the resource request content is satisfied or until a predetermined number of times is exceeded.
With this, the operation of the capacity allocation section 353 is completed.
　制御計画部３５４のデータフローおよび処理動作を説明する。
　制御計画部３５４は、能力割当部３５３からの制御計画の生成を支持を示すデータの入力を以て動作を開始する。制御計画部３５４は、能力割当部３５３が出力した制御計画生成対象の仮想リソースの識別子を示すデータとリソース要求内容の充足違反の内容を示すデータ、リソース関係データ３５９Ａ、および実体リソース制約データ４５２Ａを入力し、実体リソース５の制御計画データを出力する。 The data flow and processing operation of the control planning unit 354 will be explained.
The control planning unit 354 starts its operation upon input of data indicating support for generation of a control plan from the capacity allocation unit 353. The control planning unit 354 outputs the data indicating the identifier of the virtual resource for which the control plan is to be generated, the data indicating the content of the fulfillment violation of the resource request content, the resource relationship data 359A, and the actual resource constraint data 452A, output by the capacity allocation unit 353. The control plan data of the entity resource 5 is output.
　具体的にまず制御計画部３５４は、能力割当部３５３から制御計画生成対象の仮想リソースの識別子と、リソース関係データ３５９Ａを入力する。そして制御計画生成対象の仮想リソースの識別子をキーとして、リソース関係データ３５９Ａから当該の仮想リソースを構成する実体リソース５の識別子を取得する。次に制御計画部３５４は、実体リソース制約データ４５２Ａを入力し、前述の動作で取得した実体リソース５の識別子をキーとして各実体リソース５の制約条件を示すデータを実体リソース制約データ４５２Ａから取得する。
　そして実体リソース５の制約条件の中から、制御可否が「可」の実体リソース５を抽出する。そして制御計画部３５４は、能力割当部３５３が出力したリソース要求内容の充足違反が解消する様に、抽出した実体リソース５のそれぞれについて制御計画を生成し出力する。 Specifically, first, the control planning unit 354 inputs the identifier of the virtual resource for which a control plan is to be generated and the resource relationship data 359A from the capacity allocation unit 353. Then, using the identifier of the virtual resource for which the control plan is to be generated as a key, the identifier of the real resource 5 constituting the virtual resource is acquired from the resource relationship data 359A. Next, the control planning unit 354 inputs the entity resource constraint data 452A, and uses the identifier of the entity resource 5 obtained in the above operation as a key to obtain data indicating the constraint conditions of each entity resource 5 from the entity resource constraint data 452A. .
Then, from among the constraint conditions of the entity resources 5, entity resources 5 whose controllability is "possible" are extracted. Then, the control planning unit 354 generates and outputs a control plan for each of the extracted entity resources 5 so that the fulfillment violation of the resource request content output by the capacity allocation unit 353 is resolved.
　具体的な例で説明する。能力割当部３５３から入力された制御計画生成対象の仮想リソースが「VR002」であり、充足違反の内容を示すデータが「時刻１７：００における能力を示すデータの予測値が不足」である場合の例で説明する。
　まず制御計画部３５４は、図１５に示すリソース関係データ３５９Ａから、仮想リソース「VR002」を構成する実体リソース５の識別子である「AR002」と「AR003」を取得する。次に制御計画部３５４は、図８に示す実体リソース制約データ４５２Ａから、実体リソース「AR002」と「AR003」の制約条件内容を示すデータを取得し、制約条件の制御可否が「可」である実体リソース５である「AR002」を抽出する。 This will be explained using a specific example. When the virtual resource for which control plan generation is input from the capacity allocation unit 353 is "VR002" and the data indicating the content of the sufficiency violation is "the predicted value of the data indicating the capacity at time 17:00 is insufficient"Let's explain with an example.
First, the control planning unit 354 acquires "AR002" and "AR003", which are the identifiers of the real resources 5 that constitute the virtual resource "VR002", from the resource relationship data 359A shown in FIG. 15. Next, the control planning unit 354 acquires data indicating the contents of the constraint conditions of the entity resources "AR002" and "AR003" from the entity resource constraint data 452A shown in FIG. Extract “AR002” which is entity resource 5.
　ここで図１５のリソース関係データ３５９Ａの２行目に示している実体リソース「AR002」は、稼働終了日時が「２０２１／０１／０１　１６：２１」であり、充足違反の内容を示すデータに示されている「時刻１７：００」時点では稼働していないことを示している。
　一方で図８の実体リソース制約データ４５２Ａの２行目に示されている実体リソース「AR002」の可動時間帯は「０９：００から２３：００」であって、充足違反の内容を示すデータに示されている「時刻１７：００」での稼働は実体リソース「AR002」の制約を充足する。 Here, the actual resource "AR002" shown in the second line of the resource related data 359A in FIG. This indicates that it is not operating at the "time 17:00" indicated.
On the other hand, the active time period of the entity resource "AR002" shown in the second line of the entity resource constraint data 452A in FIG. The operation at the indicated "time 17:00" satisfies the constraints of the entity resource "AR002".
　従って制御計画部３５４は、充足違反の内容を示すデータに示されている「時刻１７：００」において、充足違反の内容を示すデータに示されている「能力を示すデータの予測値が不足」を解消する様に、実体リソース「AR002」を稼働する内容の制御計画データを生成する。
　生成した制御計画データは能力予測部３５２に入力する。以降は前述までに説明した動作を行う。また制御計画部３５４は、リソース運用制御装置１０が仮想リソースの運用制御の実行を示すデータをリソース仮想化装置３に入力してきた場合、前述の制御計画データに基づいて実体リソース５の制御装置に制御信号を送信する。 Therefore, the control planning unit 354 determines that at "time 17:00" indicated in the data indicating the content of the sufficiency violation, "the predicted value of the data indicating the ability is insufficient" indicated in the data indicating the content of the sufficiency violation. Generate control plan data for operating the entity resource "AR002" so as to resolve the issue.
The generated control plan data is input to the capacity prediction section 352. Thereafter, the operations described above are performed. In addition, when the resource operation control device 10 inputs data indicating execution of operation control of a virtual resource to the resource virtualization device 3, the control planning unit 354 controls the control device of the real resource 5 based on the control plan data described above. Send control signals.
　以上をもって制御計画部３５４の動作を終了し、同時に、本実施形態におけるリソース仮想化システム２の演算処理が完結する。 With this, the operation of the control planning unit 354 is completed, and at the same time, the calculation processing of the resource virtualization system 2 in this embodiment is completed.
　上記の実施形態における仮想リソース能力変換部３５１では、能力予測部３５２が出力した仮想能力データの予測結果データに基づいて仮想リソースを構成する実体リソース５を決定する様に説明した。この説明に限らず、仮想能力データの過去から最新日時までに至るデータの様態に従って決定してもよい。
　例えば、各実体リソース５の仮想能力データの過去から最新日時までの時系列データを合算した時、合算した仮想リソースとしての能力を示す時系列データが定常性を有するデータとなる様に構成してもよい。この様に構成することで、仮想能力データの定常性が担保され、能力予測部３５２における仮想能力データの予測精度が向上または安定する。 It has been described that the virtual resource capability conversion unit 351 in the above embodiment determines the real resources 5 constituting the virtual resource based on the prediction result data of the virtual capability data output by the capability prediction unit 352. The determination is not limited to this explanation, and may be determined according to the state of the virtual ability data from the past to the latest date and time.
For example, when the time-series data of the virtual capacity data of each entity resource 5 from the past to the latest date and time are summed up, the time-series data indicating the summed capacity as a virtual resource is configured to have stationarity. Good too. With this configuration, the constancy of the virtual ability data is ensured, and the prediction accuracy of the virtual ability data in the ability prediction unit 352 is improved or stabilized.
　また仮想能力データのみに限らず、仮想リソースの属性を示すデータを指標として決定してもよい。例えば、実体リソース制約データ４５２Ａに記載されている制御可否の条件を参照し、制御「可」の実体リソース５のみまたは制御「不可」の実体リソース５のみでそれぞれ構成してもよい。
　この様に構成することで、仮想リソースの仮想リソースの能力の量や品質の供出確実性と不確実性を切り分けた仮想リソースの管理が可能となる。あるいは、実体リソース制約データ４５２Aに示されている各リソースの「コスト」の制約条件を参照し、仮想リソースを構成する各実体リソース５のコストの合計値が最小となる様に構成してもよい。この様に構成することで、仮想リソースの可動によるコストを最小化することが可能となる。 Further, the determination is not limited to the virtual capacity data alone, but may be determined using data indicating the attributes of the virtual resource as an index. For example, referring to the controllability conditions described in the entity resource constraint data 452A, it may be configured with only the entity resources 5 that are controllable or only the entity resources 5 that are not controllable.
With this configuration, it becomes possible to manage the virtual resources by separating the reliability and uncertainty of provision of the capacity and quality of the virtual resources. Alternatively, the configuration may be configured such that the total cost of each entity resource 5 constituting the virtual resource is minimized by referring to the "cost" constraint condition of each resource shown in the entity resource constraint data 452A. . With this configuration, it is possible to minimize the cost of moving virtual resources.
　上記の実施形態における能力割当部３５３では、形成した仮想リソースは必ずいずれかのリソース要求内容に対応させるものとして説明した。この説明に限らず、対応するリソース要求内容が無い場合であっても仮想リソースを存在させてもよい。
　例えば、現在存在するリソース要求内容、あるいは過去に存在したリソース要求内容を充足させる仮想リソースを仮想リソース能力変換部３５１、能力予測部３５２、制御計画部３５４を用いて形成し、ただし能力割当部３５３において割り当てるリソース要求が「無し」として設定してもよい。これにより、同様のリソース要求を新たにリソース運用制御装置１０から入力されたとき、直ちに仮想リソースの提供が可能であり、リソース運用制御装置１０における制御応答を向上させることができる。 The capacity allocation unit 353 in the above embodiment has been described on the assumption that the created virtual resource always corresponds to one of the resource request contents. The present invention is not limited to this explanation, and a virtual resource may exist even when there is no corresponding resource request content.
For example, a virtual resource that satisfies the currently existing resource request content or the resource request content that existed in the past is created using the virtual resource capacity conversion unit 351, the capacity prediction unit 352, and the control planning unit 354, but the capacity allocation unit 353 The resource request to be allocated may be set to "none". As a result, when a similar resource request is newly input from the resource operation control device 10, the virtual resource can be provided immediately, and the control response in the resource operation control device 10 can be improved.
　上記の実施形態における制御計画部３５４では、実体リソースの制御計画を生成するものとして説明した。この説明に限らず、仮想リソースの制御計画も生成してもよい。
　例えば、制御計画部３５４は、能力割当部３５３からの制御計画生成指示データの受信を以て動作を開始する。
　制御計画部３５４は、図１８に示す要求リソース対応データから、要求に対する割り当ての無く稼働予定のない仮想リソース、あるいは既に割当が決定している仮想リソースであって、かつ現在充足しようとしている要求も同時に充足可能な仮想リソースを抽出する。制御計画部３５４は、抽出した仮想リソースを現在充足しようとしている要求に対応する仮想リソースに組み入れる。
　これにより、既に構成済みの仮想リソースの稼働率を向上させることが出来ると同時に、要求の充足可能性も高めることが出来る。 The control planning unit 354 in the above embodiment has been described as generating a control plan for an entity resource. The present invention is not limited to this explanation, and a control plan for virtual resources may also be generated.
For example, the control planning unit 354 starts its operation upon receiving control plan generation instruction data from the capacity allocation unit 353.
From the requested resource correspondence data shown in FIG. 18, the control planning unit 354 identifies virtual resources that have not been allocated to a request and are not scheduled to operate, or virtual resources that have already been allocated and are currently trying to satisfy. Extract virtual resources that can be simultaneously satisfied. The control planning unit 354 incorporates the extracted virtual resource into the virtual resource corresponding to the request that is currently being satisfied.
As a result, it is possible to improve the utilization rate of already configured virtual resources, and at the same time, it is possible to increase the possibility of satisfying requests.
　上記の実施形態における能力予測部３５２は、仮想リソース能力変換部３５１が出力した仮想能力データをそのまま用いて予測処理を行うものとして説明した。これに限らず、能力予測部３５２は、仮想能力データの内、制御可能な実体リソースに対応する仮想能力データと制御不可能な実体リソースに対応する仮想能力データとを分離し、制御不可能な実体リソースに対応する仮想能力データを用いて予測処理を行ってもよい。
　なおこの場合、制御可能な実体リソースに対応する仮想能力データの予測データは、制御計画部３５４において生成された実体リソースの制御計画に基づいた予定制御量として算出され、上記の制御不可能な実体リソースに対応する仮想能力データの予測結果データに合算することで、最終的な予測結果データが算出される。
　これにより、制御可能な実体リソースに対応する仮想能力データを予め分離しておくことで、仮想能力データの予測モデルのモデル化精度の低下を防ぐことが出来る。 The capacity prediction unit 352 in the above embodiment has been described as performing prediction processing using the virtual capacity data outputted by the virtual resource capacity conversion unit 351 as is. However, the capability prediction unit 352 separates the virtual capability data corresponding to controllable real resources from the virtual capability data corresponding to uncontrollable real resources, and Prediction processing may be performed using virtual capability data corresponding to real resources.
In this case, the predicted data of the virtual capacity data corresponding to the controllable entity resource is calculated as a planned control amount based on the control plan for the entity resource generated by the control planning unit 354, and Final prediction result data is calculated by adding up the prediction result data of the virtual capacity data corresponding to the resource.
Thereby, by separating the virtual capability data corresponding to the controllable real resources in advance, it is possible to prevent the modeling accuracy of the predictive model of the virtual capability data from decreasing.
　図２１は、リソース仮想化システム２のハードウェア構成図である。
　リソース仮想化システム２の各装置は、ＣＰＵ９０１と、ＲＡＭ９０２と、ＲＯＭ９０３と、ＨＤＤ９０４と、通信Ｉ／Ｆ９０５と、入出力Ｉ／Ｆ９０６と、メディアＩ／Ｆ９０７とを有するコンピュータ９００として構成される。
　通信Ｉ／Ｆ９０５は、外部の通信装置９１５と接続される。入出力Ｉ／Ｆ９０６は、入出力装置９１６と接続される。メディアＩ／Ｆ９０７は、記録媒体９１７からデータを読み書きする。さらに、ＣＰＵ９０１は、ＲＡＭ９０２に読み込んだプログラム（アプリケーションや、その略のアプリとも呼ばれる）を実行することにより、各処理部を制御する。そして、このプログラムは、通信回線を介して配布したり、ＣＤ－ＲＯＭ等の記録媒体９１７に記録して配布したりすることも可能である。 FIG. 21 is a hardware configuration diagram of the resource virtualization system 2.
Each device of the resource virtualization system 2 is configured as a computer 900 having a CPU 901, a RAM 902, a ROM 903, an HDD 904, a communication I/F 905, an input/output I/F 906, and a media I/F 907.
Communication I/F 905 is connected to external communication device 915. The input/output I/F 906 is connected to the input/output device 916. The media I/F 907 reads and writes data from the recording medium 917. Further, the CPU 901 controls each processing unit by executing a program (also called an application or an abbreviation thereof) read into the RAM 902 . This program can also be distributed via a communication line or recorded on a recording medium 917 such as a CD-ROM.
　以上、本発明の実施形態について述べたが、本発明は前述の実施形態に限定されるものでなく、特許請求の範囲に記載された範囲を逸脱しない範囲で種々の変更を行うことができる。例えば、前述した実施の形態は本発明を詳細に説明したものであり、必ずしも説明した全ての構成を備える必要はない。また、構成に他の実施形態の構成を加えることも可能ある。加えて、構成の一部について、追加、削除、置き換えが可能である。 Although the embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments, and various changes can be made without departing from the scope of the claims. For example, the embodiments described above describe the present invention in detail, and it is not necessary to necessarily include all the configurations described. It is also possible to add configurations of other embodiments to the configuration. In addition, it is possible to add, delete, or replace a part of the configuration.
　また、各実施例の構成の一部について、他の構成の追加・削除・置換をすることが可能である。また、上記の各構成、機能、処理部、処理手段などは、それらの一部または全部を、例えば集積回路で設計するなどによりハードウェアで実現してもよい。
　また、前記の各構成、機能などは、プロセッサがそれぞれの機能を実現するプログラムを解釈し、実行することによりソフトウェアで実現してもよい。 Further, it is possible to add, delete, or replace a part of the configuration of each embodiment with other configurations. Further, each of the above-mentioned configurations, functions, processing units, processing means, etc. may be partially or entirely realized in hardware by, for example, designing an integrated circuit.
Further, each of the configurations, functions, etc. described above may be realized by software by a processor interpreting and executing programs for realizing the respective functions.
　各機能を実現するプログラム、テーブル、ファイルなどの情報は、メモリや、ハードディスク、ＳＳＤ（Solid State Drive）などの記録装置、または、ＩＣ（Integrated Circuit）カード、ＳＤカード、ＤＶＤ（Digital Versatile Disc）などの記録媒体におくことができる。また、クラウドを活用することもできる。
　また、制御線や情報線は説明上必要と考えられるものを示しており、製品上必ずしも全ての制御線や情報線を示しているとは限らない。実際にはほとんど全ての構成が相互に接続されていると考えてもよい。さらに、各装置を繋ぐ通信手段は、無線ＬＡＮに限定せず、有線ＬＡＮやその他の通信手段に変更してもよい。 Information such as programs, tables, and files that realize each function can be stored in memory, recording devices such as hard disks, SSDs (Solid State Drives), IC (Integrated Circuit) cards, SD cards, DVDs (Digital Versatile Discs), etc. can be stored on any recording medium. It is also possible to utilize the cloud.
Further, the control lines and information lines are shown to be necessary for explanation purposes, and not all control lines and information lines are necessarily shown in the product. In reality, almost all configurations may be considered to be interconnected. Furthermore, the communication means for connecting each device is not limited to wireless LAN, but may be changed to wired LAN or other communication means.
　１　　　リソース運用管理システム
　２　　　リソース仮想化システム（リソース管理装置）
　３　　　リソース仮想化装置
　４　　　データ管理装置
　５　　　実体リソース
　６　　　計測装置
　７　　　監視制御装置
　８　　　情報入出力端末
　９　　　情報配信装置
　１０　　リソース運用制御装置
　１１　　通信経路
　１２　　制御対象設備
　３１　　ＣＰＵ
　３２　　入力装置
　３３　　出力装置
　３４　　通信装置
　３５　　記憶装置
　４１　　ＣＰＵ
　４２　　入力装置
　４３　　出力装置
　４４　　通信装置
　４５　　記憶装置
　３５１　仮想リソース能力変換部
　３５２　能力予測部
　３５３　能力割当部
　３５４　制御計画部
　４５１Ａ　実体リソース計測データ 1 Resource operation management system 2 Resource virtualization system (resource management device)
3 Resource virtualization device 4 Data management device 5 Real resource 6 Measurement device 7 Monitoring control device 8 Information input/output terminal 9 Information distribution device 10 Resource operation control device 11 Communication path 12 Control target equipment 31 CPU
32 Input device 33 Output device 34 Communication device 35 Storage device 41 CPU
42 Input device 43 Output device 44 Communication device 45 Storage device 351 Virtual resource capacity conversion section 352 Capacity prediction section 353 Capacity allocation section 354 Control planning section 451A Real resource measurement data

Claims (14)

  1. 　エネルギーに関わる設備である実体リソースを計測した実体リソース計測データから、前記実体リソースを仮想化する仮想化ロジックをもとに、前記実体リソースが仮想リソースとして提供する能力を示す仮想能力データを作成し、その仮想能力データを提供する仮想リソースを構築する仮想リソース能力変換部と、
    　前記仮想リソース能力変換部が構築した前記仮想リソースをリソース運用管理システムに割り当てることで、前記実体リソースを前記リソース運用管理システムに管理させる能力割当部とを有しており、
    　前記仮想化ロジックは、前記リソース運用管理システムが要求する前記実体リソースの能力様態を示すリソース要求内容データに応じて個別に用意されることを特徴とする
    　リソース管理装置。     Based on the physical resource measurement data obtained by measuring the physical resource, which is energy-related equipment, virtual capability data indicating the ability of the physical resource to be provided as a virtual resource is created based on virtualization logic that virtualizes the physical resource. , a virtual resource capability conversion unit that constructs a virtual resource that provides the virtual capability data;
    a capacity allocation unit that causes the resource operation management system to manage the actual resource by allocating the virtual resource constructed by the virtual resource capacity conversion unit to the resource operation management system;
    A resource management device, wherein the virtualization logic is individually prepared according to resource request content data indicating a capability of the actual resource requested by the resource operation management system.
  2. 　前記リソース管理装置は、さらに、前記仮想能力データの将来の値である予測値を算出する能力予測部を有しており、
    　前記能力割当部は、前記能力予測部が算出した予測値をもとに、前記仮想リソース能力変換部が構築した前記仮想リソースを前記リソース運用管理システムに割り当てることを特徴とする
    　請求項１に記載のリソース管理装置。     The resource management device further includes a capability prediction unit that calculates a predicted value that is a future value of the virtual capability data,
    2. The capacity allocation unit allocates the virtual resource constructed by the virtual resource capacity conversion unit to the resource operation management system based on the predicted value calculated by the capacity prediction unit. resource management device.
  3. 　前記リソース管理装置は、さらに、制御計画部を有しており、
    　前記制御計画部は、前記能力割当部が割り当てた前記仮想リソースを構成する前記実体リソースに対する制御計画を生成し、その制御計画をもとに割当先の前記各リソース運用管理システムに前記実体リソースを制御させ、
    　前記仮想リソース能力変換部は、前記制御計画部が生成した前記制御計画に基づいて前記仮想能力データを修正することを特徴とする
    　請求項１に記載のリソース管理装置。     The resource management device further includes a control planning section,
    The control planning unit generates a control plan for the real resources constituting the virtual resources allocated by the capacity allocation unit, and based on the control plan, sends the real resources to each of the resource operation management systems to which they are allocated. control,
    The resource management device according to claim 1, wherein the virtual resource capacity conversion unit modifies the virtual capacity data based on the control plan generated by the control planning unit.
  4. 　前記仮想リソース能力変換部は、事前に記憶された複数の前記仮想化ロジックを、前記リソース運用管理システムが要求する前記実体リソースの能力様態を充足するように組み合わせることで前記仮想リソースを構築することを特徴とする
    　請求項１に記載のリソース管理装置。     The virtual resource capability conversion unit constructs the virtual resource by combining the plurality of virtualization logics stored in advance so as to satisfy a capability aspect of the real resource required by the resource operation management system. The resource management device according to claim 1, characterized by:
  5. 　前記仮想リソース能力変換部は、前記能力予測部が計算した前記仮想能力データの予測値に基づいて前記仮想リソースを構築することを特徴とする
    　請求項２に記載のリソース管理装置。     The resource management device according to claim 2, wherein the virtual resource capacity conversion unit constructs the virtual resource based on a predicted value of the virtual capacity data calculated by the capacity prediction unit.
  6. 　前記仮想リソース能力変換部は、事前に記憶された複数の前記仮想化ロジックを組み合わせる処理について、前記各実体リソースの制約条件を示す情報に基づいて生成される前記仮想リソースの属性を示す情報が、予め定めた基準を充足するように前記仮想リソースを構成する前記実体リソースの組み合わせを決定することを特徴とする
    　請求項４または請求項５に記載のリソース管理装置。     The virtual resource capability conversion unit is configured to generate information indicating an attribute of the virtual resource generated based on information indicating a constraint condition of each of the entity resources in a process of combining a plurality of virtualization logics stored in advance. The resource management device according to claim 4 or 5, wherein the combination of the real resources constituting the virtual resource is determined so as to satisfy a predetermined criterion.
  7. 　前記制御計画部は、前記実体リソースの稼働に伴いエネルギーに関わる前記仮想能力データの時間変化を算出し、その時間変化を前記仮想リソース能力変換部が作成する前記仮想能力データに反映させることを特徴とする
    　請求項３に記載のリソース管理装置。     The control planning unit calculates a temporal change in the virtual capacity data related to energy as the physical resource operates, and reflects the temporal change in the virtual capacity data created by the virtual resource capacity conversion unit. The resource management device according to claim 3.
  8. 　前記仮想化ロジックは、前記実体リソース計測データの物理量とは異なる種類の物理量を示す前記仮想能力データに変換することを特徴とする
    　請求項１に記載のリソース管理装置。     The resource management device according to claim 1, wherein the virtualization logic converts the virtual capacity data to the virtual capacity data indicating a different type of physical quantity from the physical quantity of the actual resource measurement data.
  9. 　前記仮想化ロジックは、２種類以上の前記仮想能力データの組み合わせから、新たな前記仮想能力データを生成することを特徴とする
    　請求項１に記載のリソース管理装置。     The resource management device according to claim 1, wherein the virtualization logic generates new virtual capability data from a combination of two or more types of virtual capability data.
  10. 　前記仮想化ロジックは、前記実体リソースの稼働に伴うエネルギーの残量を示す前記実体リソース計測データから、前記実体リソースのエネルギーの正または負の供給能力を示す前記仮想能力データに変換することを特徴とする
    　請求項１に記載のリソース管理装置。     The virtualization logic converts the physical resource measurement data indicating the remaining amount of energy accompanying the operation of the physical resource into the virtual capacity data indicating a positive or negative energy supply capacity of the physical resource. The resource management device according to claim 1.
  11. 　前記仮想化ロジックは、前記実体リソースの稼働に伴う移動履歴を示す前記実体リソース計測データから、前記実体リソースの貨物の輸送能力を示す前記仮想能力データに変換することを特徴とする
    　請求項１に記載のリソース管理装置。     According to claim 1, the virtualization logic converts the physical resource measurement data indicating the movement history associated with the operation of the physical resource to the virtual capacity data indicating the cargo transportation capacity of the physical resource. The resource management device described.
  12. 　前記仮想化ロジックは、前記実体リソースのエネルギーの正または負の供給能力を示す前記実体リソース計測データと、前記実体リソースの貨物の輸送能力を示す前記実体リソース計測データとを用いて、前記実体リソースのエネルギーの輸送能力を示す前記仮想能力データに変換することを特徴とする
    　請求項１に記載のリソース管理装置。     The virtualization logic uses the entity resource measurement data indicating the positive or negative energy supply capacity of the entity resource and the entity resource measurement data indicating the cargo transportation capacity of the entity resource to generate the entity resource. The resource management device according to claim 1, wherein the resource management device converts the virtual capacity data into the virtual capacity data indicating the energy transport capacity of the virtual capacity data.
  13. 　リソース管理装置は、仮想リソース能力変換部と、能力割当部とを有しており、
    　前記仮想リソース能力変換部は、エネルギーに関わる設備である実体リソースを計測した実体リソース計測データから、前記実体リソースを仮想化する仮想化ロジックをもとに、前記実体リソースが仮想リソースとして提供する能力を示す仮想能力データを作成し、その仮想能力データを提供する仮想リソースを構築し、
    　前記能力割当部は、前記仮想リソース能力変換部が構築した前記仮想リソースをリソース運用管理システムに割り当てることで、前記実体リソースを前記リソース運用管理システムに管理させ、
    　前記仮想化ロジックは、前記リソース運用管理システムが要求する前記実体リソースの能力様態を示すリソース要求内容データに応じて個別に用意されることを特徴とする
    　リソース管理方法。     The resource management device includes a virtual resource capacity conversion unit and a capacity allocation unit,
    The virtual resource capacity conversion unit converts the ability of the real resource to be provided as a virtual resource based on virtualization logic for virtualizing the real resource from real resource measurement data obtained by measuring the real resource, which is equipment related to energy. Create virtual capability data indicating the virtual capability data, construct a virtual resource that provides that virtual capability data,
    The capacity allocation unit allocates the virtual resource constructed by the virtual resource capacity conversion unit to a resource operation management system, thereby causing the resource operation management system to manage the actual resource,
    The resource management method is characterized in that the virtualization logic is individually prepared according to resource request content data indicating a capability of the actual resource requested by the resource operation management system.
  14. 　コンピュータを、請求項１に記載のリソース管理装置として機能させるためのリソース管理プログラム。 A resource management program for causing a computer to function as the resource management device according to claim 1.
PCT/JP2023/010861 2022-04-26 2023-03-20 Resource management device, resource management method, and resource management program WO2023210209A1 (en)

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JP2012048620A (en) * 2010-08-30 2012-03-08 Central Res Inst Of Electric Power Ind Shared data generation method, generation device and generation program
JP2018508174A (en) * 2015-02-11 2018-03-22 アルカテル−ルーセント Method and system for providing energy services
JP2020137395A (en) * 2019-02-26 2020-08-31 株式会社日立製作所 Energy management method and energy management device

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012048620A (en) * 2010-08-30 2012-03-08 Central Res Inst Of Electric Power Ind Shared data generation method, generation device and generation program
JP2018508174A (en) * 2015-02-11 2018-03-22 アルカテル−ルーセント Method and system for providing energy services
JP2020137395A (en) * 2019-02-26 2020-08-31 株式会社日立製作所 Energy management method and energy management device

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