CN115187144B - Virtual power plant power flow method, device, equipment, medium and program product - Google Patents
Virtual power plant power flow method, device, equipment, medium and program product Download PDFInfo
- Publication number
- CN115187144B CN115187144B CN202211098601.1A CN202211098601A CN115187144B CN 115187144 B CN115187144 B CN 115187144B CN 202211098601 A CN202211098601 A CN 202211098601A CN 115187144 B CN115187144 B CN 115187144B
- Authority
- CN
- China
- Prior art keywords
- information
- target
- load
- algorithm
- day
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 75
- 230000004044 response Effects 0.000 claims abstract description 37
- 238000012545 processing Methods 0.000 claims abstract description 21
- 238000012790 confirmation Methods 0.000 claims description 28
- 238000012546 transfer Methods 0.000 claims description 27
- 238000010248 power generation Methods 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 13
- 238000003860 storage Methods 0.000 claims description 12
- 238000012163 sequencing technique Methods 0.000 claims description 6
- 238000001514 detection method Methods 0.000 claims description 2
- 230000006870 function Effects 0.000 description 26
- 238000000354 decomposition reaction Methods 0.000 description 19
- 230000001186 cumulative effect Effects 0.000 description 17
- 238000004378 air conditioning Methods 0.000 description 14
- 238000004146 energy storage Methods 0.000 description 14
- 230000005611 electricity Effects 0.000 description 11
- 238000010586 diagram Methods 0.000 description 9
- 238000004891 communication Methods 0.000 description 6
- 239000013643 reference control Substances 0.000 description 5
- 239000003795 chemical substances by application Substances 0.000 description 4
- 230000000694 effects Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 4
- 238000005457 optimization Methods 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 3
- 238000013439 planning Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000003213 activating effect Effects 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000006735 deficit Effects 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000007667 floating Methods 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 238000012913 prioritisation Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
Images
Classifications
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- 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—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Power Engineering (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- Development Economics (AREA)
- Physics & Mathematics (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Educational Administration (AREA)
- Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
Embodiments of the present disclosure disclose virtual power plant power flow methods, apparatus, devices, media, and program products. One embodiment of the method comprises: generating an energy equipment information table; in response to the received energy equipment selection information, instantiation processing is carried out on the energy equipment selection information to obtain a target energy equipment instance information set; determining the device type identifier corresponding to each target energy device instance information as a target device type identifier to obtain a target device type identifier group; determining initial prompt information matched with each target equipment type identifier in a preset initial prompt information set as user prompt information to obtain a user prompt information group; generating first algorithm interface information; generating next day load curve information; generating second algorithm interface information; generating power flow declaration strategy information; generating third algorithm interface information; and generating a target clearing curve information set. The method and the device can improve the accuracy of virtual power plant power flow.
Description
Technical Field
Embodiments of the present disclosure relate to the field of computer technologies, and in particular, to a virtual power plant power flow method, apparatus, device, medium, and program product.
Background
A virtual power plant power transfer method is a technology for a virtual power plant to participate in power transfer. At present, when virtual power plant power circulation, the mode that usually adopts is: the virtual power plant directly adopts a background preset algorithm to generate data required by power flow declaration and carry out load decomposition to obtain a clearing curve corresponding to each energy device so that the virtual power plant can control each energy device to carry out load clearing according to the corresponding clearing curve. Thus, the virtual power plant completes the power flow.
However, the inventor finds that when the virtual power plant power flow is completed in the above manner, the following technical problems often exist:
firstly, in order to adapt to a constantly changing power flow mode of a virtual power plant, a background preset algorithm needs to be continuously optimized and adjusted, however, the background cannot be edited at the front end, so that the background preset algorithm is inconvenient to be optimized and adjusted, and the power flow accuracy of the virtual power plant is low;
secondly, due to the fact that virtual power plant power transfer modes are not uniform from place to place, background preset algorithms cannot be applicable to various virtual power plant power transfer modes, and a uniform custom algorithm interface is lacked, so that the universality of the virtual power plant power transfer method is low;
thirdly, when load decomposition is carried out, the difference of load adjusting capacities of different types of energy equipment is often easily ignored, and the influence of the new energy power generation power and the load prediction precision on the load decomposition is ignored, so that the accuracy of tracking a load clearing curve is low, and the power flow accuracy of a virtual power plant is low.
The above information disclosed in this background section is only for enhancement of understanding of the background of the inventive concept and, therefore, it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art in this country.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some embodiments of the present disclosure propose virtual plant power flow methods, apparatus, devices, media and program products to address one or more of the technical problems noted in the background section above.
In a first aspect, some embodiments of the present disclosure provide a virtual power plant power flow method, the method including: generating an energy equipment information table for selecting information of each energy equipment based on declaration confirmation information in response to receiving declaration confirmation information for declaring information to be confirmed of power circulation; in response to receiving energy equipment selection information aiming at each piece of energy equipment information in the energy equipment information table, instantiation processing is carried out on the energy equipment selection information to obtain a target energy equipment instance information set; determining a device type identifier corresponding to each piece of target energy device instance information in the target energy device instance information set as a target device type identifier to obtain a target device type identifier group; determining initial prompt information which is matched with each target equipment type identifier in the target equipment type identifier group in a preset initial prompt information set as user prompt information to obtain a user prompt information group; generating first algorithm interface information based on the target energy equipment instance information set and the user prompt information set; generating next-day load curve information based on the first algorithm interface information; generating second algorithm interface information based on the target energy equipment instance information set and the user prompt information set; generating power flow declaration strategy information based on the next day load curve information and the second algorithm interface information; generating third algorithm interface information based on the target energy equipment instance information set and the user prompt information set in response to receiving the next-day birth-clearing curve information; and generating a target clearing curve information set for the virtual power plant to execute power transfer based on the next-day clearing curve information and the third algorithm interface information.
In a second aspect, some embodiments of the present disclosure provide a virtual power plant power flow device, the device comprising: a first generation unit configured to generate an energy device information table for selecting each energy device information based on declaration confirmation information in response to reception of declaration confirmation information for declaring information to be confirmed for power flow; the instantiation processing unit is configured to respond to the received energy equipment selection information aiming at each energy equipment information in the energy equipment information table, perform instantiation processing on the energy equipment selection information and obtain a target energy equipment instance information set; a first determining unit, configured to determine, as a target device type identifier, a device type identifier corresponding to each piece of target energy device instance information in the target energy device instance information set, so as to obtain a target device type identifier group; the second determination unit is configured to determine initial prompt information which is matched with each target equipment type identifier in the target equipment type identifier group in a preset initial prompt information set as user prompt information to obtain a user prompt information group; a second generating unit configured to generate first algorithm interface information based on the target energy device instance information set and the user prompt information set; a third generating unit configured to generate next-day load curve information based on the first algorithm interface information; a fourth generating unit configured to generate second algorithm interface information based on the target energy device instance information set and the user prompt information set; a fifth generating unit configured to generate power flow declaration policy information based on the next-day load curve information and the second algorithm interface information; a sixth generating unit configured to generate third algorithm interface information based on the target energy device instance information set and the user prompt information set in response to receiving the next-day birth-to-death curve information; and a seventh generating unit configured to generate a target clearance curve information set for the virtual power plant to execute power transfer based on the next-day clearance curve information and the third algorithm interface information.
In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors, cause the one or more processors to implement the method described in any of the implementations of the first aspect.
In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium on which a computer program is stored, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect.
In a fifth aspect, some embodiments of the present disclosure provide a computer program product comprising a computer program that, when executed by a processor, implements the method described in any of the implementations of the first aspect above.
The above embodiments of the present disclosure have the following advantages: through the virtual power plant power flow method of some embodiments of the present disclosure, the accuracy of virtual power plant power flow can be improved. Specifically, the reason for the low accuracy of power flow in the virtual power plant is that: in order to adapt to the changing power transfer mode of the virtual power plant, the background preset algorithm needs to be continuously optimized and adjusted, however, the background cannot be edited at the front end, so that the background preset algorithm is inconvenient to be optimized and adjusted, and the power transfer accuracy of the virtual power plant is low. Based on this, the virtual power plant power flow method of some embodiments of the present disclosure first generates an energy device information table for selecting each energy device information based on the declaration confirmation information in response to receiving declaration confirmation information for reporting to-be-confirmed information of power flow. Therefore, the virtual power plant power flow declaration work can be started, and the class instance corresponding to each energy device can be conveniently generated subsequently by selecting each energy device participating in the declaration work. Secondly, in response to receiving energy device selection information aiming at each piece of energy device information in the energy device information table, instantiation processing is carried out on the energy device selection information, and a target energy device instance information set is obtained. Therefore, target energy equipment instance information corresponding to each energy equipment can be obtained, and algorithm interface information corresponding to the target energy equipment instance information set can be conveniently generated subsequently, and each subsequent algorithm can call the corresponding class instance. Therefore, the optimization and adjustment of the background preset algorithm can be facilitated. And determining the device type identifier corresponding to each piece of target energy device instance information in the target energy device instance information set as a target device type identifier to obtain a target device type identifier group. And determining the initial prompt information matched with each target equipment type identifier in the target equipment type identifier group in a preset initial prompt information set as the user prompt information to obtain a user prompt information group. Therefore, the equipment type of each energy equipment selected by the target user and the user prompt information corresponding to each equipment type can be obtained, and the subsequent target user can conveniently and correctly input information according to the prompt content. And then, generating first algorithm interface information based on the target energy equipment instance information set and the user prompt information set. And generating the next day load curve information based on the first algorithm interface information. Therefore, first algorithm interface information corresponding to the load generation algorithm can be obtained, and information input by a target user can be received through the first algorithm interface corresponding to the first algorithm interface information to optimize and adjust the load generation algorithm preset in the background, so that more accurate next-day load curve information can be obtained, and further, the next-day load curve information can be conveniently referred to later to generate better power flow declaration strategy information. And then, generating second algorithm interface information based on the target energy equipment instance information set and the user prompt information set. And generating power flow declaration strategy information based on the next day load curve information and the second algorithm interface information. Therefore, second algorithm interface information corresponding to the price curve generation algorithm can be obtained, and information input by a target user can be received through the second algorithm interface corresponding to the second algorithm interface information to optimize and adjust the price curve generation algorithm preset in the background, so that more accurate electricity price curve information can be obtained, and further more excellent power flow declaration strategy information is generated for declaration. And finally, responding to the received next-day birth-clearing curve information, and generating third algorithm interface information based on the target energy equipment instance information set and the user prompt information set. And generating a target clearing curve information set for power circulation of the virtual power plant based on the next-day clearing curve information and the third algorithm interface information. Therefore, third algorithm interface information corresponding to the load decomposition algorithm can be obtained, and through the third algorithm interface corresponding to the third algorithm interface information, information input by a target user can be received to optimize and adjust the load decomposition algorithm preset in the background, so that more accurate target clearing curve information corresponding to each energy device can be obtained, each energy device can be controlled by the virtual power plant to carry out load clearing according to the corresponding target clearing curve information, and power circulation is completed. Therefore, the virtual power plant power flow method of the embodiment of the disclosure can achieve optimization and adjustment of each background preset algorithm at the front end, so as to obtain more accurate next-day load curve information for reference, generate more excellent power flow reporting strategy information for reporting, and generate more accurate target clearing curve information set for the virtual power plant to control each energy device to execute power flow tasks strictly according to the corresponding target clearing curve information. Therefore, the accuracy of virtual power plant power flow can be improved.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and elements are not necessarily drawn to scale.
FIG. 1 is a flow diagram of some embodiments of a virtual plant power flow method according to the present disclosure;
FIG. 2 is a schematic block diagram of some embodiments of a virtual plant power flow device according to the present disclosure;
FIG. 3 is a schematic block diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. It should be understood that the drawings and the embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a" or "an" in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will appreciate that references to "one or more" are intended to be exemplary and not limiting unless the context clearly indicates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
FIG. 1 illustrates a flow 100 of some embodiments of a virtual plant power flow method according to the present disclosure. The virtual power plant power transfer method comprises the following steps:
In some embodiments, an executing agent (e.g., a computing device) of the virtual power plant power flow method may generate an energy device information table for selecting respective energy device information based on the declared confirmation information in response to receiving declared confirmation information for power flow declared to-be-confirmed information. The information to be confirmed in the power flow declaration may be information indicating whether to perform a power flow declaration operation. The above-mentioned power flow may be power participating in the flow. The target user may be a person responsible for the power flow declaration operation. The declaration confirmation information may be information for confirming that the power circulation declaration operation is performed. The energy device information in the energy device information table can be used for representing the energy devices participating in the power flow declaration. The energy equipment information table may be generated for selecting the respective energy equipment information based on the declaration confirmation information by:
firstly, initial equipment information meeting preset state conditions is selected from a preset initial equipment information table to serve as energy equipment information, and an energy equipment information table is obtained to enable a target user to select the energy equipment information. The initial device information in the preset initial device information table may be used to characterize the energy device. The initial device information in the preset initial device information table may include a device status. The device status may indicate whether the energy device is operating properly. The preset state condition may be that the device state representation included in the initial device information table corresponds to normal operation of the energy device.
As an example, the energy device may include, but is not limited to, at least one of: photovoltaic power generation energy equipment, wind power generation energy equipment, electric vehicle charging pile equipment and the like. The equipment state can be equipment normal, equipment failure or equipment maintenance.
Optionally, before generating an energy device information table for selecting information of each energy device based on the declaration confirmation information in response to receiving declaration confirmation information for the to-be-confirmed information of power flow declaration, the execution main body may generate the to-be-confirmed information of power flow declaration for confirmation of the target user in response to receiving the power flow information of day ahead. The day-ahead power circulation information may be information of the next-day power supply and demand transmitted by the power circulation center. The power flow center may be an organization that governs the power flow process. The next day power supply and demand may be the next day power supply and demand in the area of the power distribution center. The day-ahead power flow information may include, but is not limited to, at least one of: the date of issuance, the date of the quasi-declaration, the time-sharing rules, the power demand and the power supply. The text transmission date may be a date when the previous power flow information is transmitted. For example, the quasi-declaration date may be the next day of the posting day. The time division rule may be a rule that divides a time of 1 day by a preset interval duration. The preset interval duration may be a duration consumed from one time to another. For example, the preset interval time may be 15 minutes. The time sharing rule and the quasi-declaration date can be determined as power flow declaration information to be confirmed for confirmation of a target user.
In some embodiments, the execution subject may perform instantiation processing on the energy device selection information in response to receiving the energy device selection information for each energy device information in the energy device information table in various ways, so as to obtain a target energy device instance information set. The energy device selection information may be information of each energy device selected by the target user. The target energy device instance information in the target energy device instance information set may be used to characterize a class instance corresponding to the energy device. The class instance may be obtained by instantiating a class of energy devices. The above-mentioned energy device class may be a class predefined by an object-oriented method. The target energy device instance information in the target energy device instance information set may include a device name, a device code identifier, and a device type identifier. The device code identification may be a unique identification for the energy device. The device type identifier may uniquely identify the energy device type. The above-mentioned energy device type may be a type of energy device.
As an example, the energy device type may be, but is not limited to, one of the following: the type of the photovoltaic power generation equipment, the type of the energy storage equipment, the type of a building air conditioner and the type of the electric automobile charging pile equipment.
In some optional implementations of some embodiments, the energy device selection information may include a target energy device information set, and each target energy device information in the target energy device information set may include a device code identifier and a device type identifier. The execution main body can perform instantiation processing on the energy device selection information to obtain a target energy device instance information set. The following steps may be performed for each target energy device information in the target energy device information set:
the method comprises the steps of firstly, generating energy equipment instance information based on equipment code identification and equipment type identification included in the target energy equipment information. The energy device instance information may be used to characterize a class instance corresponding to the energy device selected by the target user. The energy device instance information may be generated based on the device code identifier and the device type identifier included in the target energy device information by:
the first substep is to determine the energy device class corresponding to the device type identifier included in the target energy device information.
And a second substep, using the device code identifier included in the target energy device information as a construction function of the energy device class corresponding to the input parameter input, instantiating the energy device class, and obtaining energy device instance information. Wherein the input parameters may be used for characterizing properties of the energy device.
And secondly, generating a next-day generated power time sequence and a next-day load time sequence based on the energy equipment instance information. The time series of the generated power of the next day may be an ordered set of the predicted values of the generated power of each time segment of the next day. The time period may be a time interval divided according to the time sharing rule. The generated power predicted value may be a predicted value of the generated power of the power generation energy device. The power generation energy device may be an energy device for generating electricity. The next day load time series may be an ordered set of predicted load values for each time period of the next day. The load prediction value may be a prediction value of the power consumption of the electric energy device. The electricity energy device may be an energy device that consumes electric energy. The next-day generated power time series and the next-day load time series can be generated based on the energy device instance information by the following steps:
in the first sub-step, a next-day generated power time sequence can be generated based on the energy equipment instance information through a preset new energy generated power prediction method.
As an example, the preset new energy power generation prediction method may include, but is not limited to, at least one of the following: a similar day clustering selection algorithm, a time series method and a Kalman filtering method.
And a second sub-step, generating a next-day load time sequence based on the energy equipment instance information through a preset load prediction method.
As an example, the preset load prediction method may include, but is not limited to, at least one of the following: regression model prediction, load density, and elastic coefficient.
And thirdly, determining the energy equipment instance information, the next-day generated power time series and the next-day load time series as target energy equipment instance information.
In some embodiments, the executing entity may determine, as the target device type identifier, a device type identifier corresponding to each piece of target energy device instance information in the target energy device instance information set, to obtain the target device type identifier group. The target device type identifier in the target device type identifier group may uniquely identify the device type of the energy device. Specifically, the following steps can be performed:
the method comprises the steps of firstly, determining a device type identifier corresponding to each piece of target energy device instance information in the target energy device instance information set as an initial device type identifier, and obtaining an initial device type identifier group. The initial device type identifier in the initial device type identifier group may uniquely identify the device type of the energy device.
And secondly, deleting the repeated initial equipment type identifiers in the initial equipment type identifier group to obtain the deleted initial equipment type identifier group.
And thirdly, determining the initial equipment type identifier in the deleted initial equipment type identifier group as a target equipment type identifier to obtain a target equipment type identifier group.
And 104, determining the initial prompt information matched with each target equipment type identifier in the target equipment type identifier group in a preset initial prompt information set as the user prompt information to obtain a user prompt information group.
In some embodiments, the execution subject may determine, as the user prompt information, initial prompt information in a preset initial prompt information set that matches each target device type identifier in the target device type identifier group, to obtain a user prompt information group. The initial prompt information in the preset initial prompt information set may be information of input parameters or output parameters related to a preset algorithm. The user prompt may be an initial prompt related to the energy device type of the energy device selected by the target user. The user prompt information may include first entering description information, second entering description information, third entering description information, first leaving description information, second leaving description information, and third leaving description information. The first reference information may be information for explaining an input parameter related to a preset load generation algorithm. The second reference information may be information for explaining an input parameter related to a preset price curve generating algorithm. The third reference information may be information for interpreting an input parameter related to a preset load split algorithm. The first reference information may be information for explaining an output parameter related to a preset load generation algorithm. The second reference information may be information for interpreting an output parameter related to a preset price curve generation algorithm. The third reference information may be information for interpreting an output parameter related to a preset load split algorithm.
As an example, the preset algorithm may include, but is not limited to, at least one of: a preset load generation algorithm, a preset price curve generation algorithm and a preset load decomposition algorithm. The preset load generation algorithm may include, but is not limited to, at least one of the following: a floating load baseline method, a rated power method and a power curve self-defining method. The preset valence curve generation algorithm may include, but is not limited to, at least one of the following: an average curve algorithm in the whole day and a curve algorithm in the peak period. The preset load split algorithm may include, but is not limited to, at least one of the following: dynamic graded compensation method.
And 105, generating first algorithm interface information based on the target energy equipment instance information set and the user prompt information set.
In some embodiments, the executing agent may generate the first algorithm interface information based on the target energy device instance information set and the user prompt information set. The first algorithm interface information can be used for representing an interface for receiving information input by a target user to generate a next day load curve. First algorithm interface information may be generated based on the target energy device instance information set and the user prompt information set by:
the method comprises the steps of firstly, generating first label switching control information corresponding to each preset first algorithm information in a preset first algorithm information set, and obtaining a first label switching control information set. Each first algorithm information in the preset first algorithm information set may be used to represent a preset load generation algorithm. Each of the preset first algorithm information sets may include a first algorithm identification. The first algorithm identification may be an identification of a corresponding load generation algorithm. For example, the first algorithm identifier may be a name or an ID (identification number) code of the corresponding load generation algorithm. The first label switching control information in the first label switching control information group may include a first control identifier and a first algorithm identifier. The first control identifier may be an identifier of a first label switching control. The first control identifier may correspond to the first label switching control one to one. For example, the first control identification may be a name or ID code corresponding to the first label switching control. The first label switching control may be a control having a function of switching an interface or a panel. The following steps may be performed for each first algorithm information in a preset first algorithm information set:
a first substep of determining a first label switching control. A control with a function of switching an interface or a panel can be selected from a preset control library to serve as a first label switching control.
As an example, the preset control library may be, but is not limited to, one of the following: WPF (Windows Presentation Foundation, windows-based user interface framework) controls library.
And a second substep of determining a first control identifier corresponding to the first label switching control and a first algorithm identifier included in the first algorithm information as first label switching control information.
And secondly, determining each first entry description information in the user prompt information group as first target entry description information. The first target entry instruction information may be information for explaining an input parameter related to the preset load generation algorithm.
And thirdly, determining each piece of first reference information in the user prompt information group as first target reference information. The first target specification reference information may be information for specifying an output parameter related to the preset load generation algorithm.
And fourthly, for each piece of first label switching control information in the first label switching control information group, determining the first label switching control information, the first target entry introduction control information, the preset entry control information and the first algorithm information corresponding to the first label switching control information as first preset algorithm interface information to obtain a first preset algorithm interface information group. The first preset algorithm interface information in the first preset algorithm interface information group may be used to represent an interface or a panel corresponding to the preset load generation algorithm. The preset input control information may be information of a textbox input control for receiving input parameters. The above-described textbox input control may be a control for receiving input text.
And fifthly, determining preset first custom algorithm label switching control information, the first target entry reference information, the first target exit reference information, the preset entry reference control information, the preset exit reference input control information, the preset code input control information and a preset custom algorithm identifier as first custom algorithm interface information. The preset first custom algorithm tag switching control information may be information of a control having a function of switching a custom algorithm interface or a panel. The preset parameter input control information may be information of a textbox input control for receiving the output parameter. The preset code input control information may be information of a text box input control that receives a code of a custom algorithm. The custom algorithm may be an algorithm different from the preset algorithm input by the target user. The preset custom algorithm identifier may be an identifier of a custom algorithm. The preset custom algorithm identifier may be a name or an ID code corresponding to the custom algorithm. The first custom algorithm interface information may be used to characterize an interface corresponding to a custom load generation algorithm.
And sixthly, determining the first preset algorithm interface information group, the first self-defined algorithm interface information, the first preset algorithm operation control information and preset result display control information as first algorithm interface information. The first preset algorithm running control information may be information of a control executing a load generation algorithm. The preset result display control information may be information of a control for displaying a result output by the algorithm.
And 106, generating load curve information of the next day based on the first algorithm interface information.
In some embodiments, the execution subject may generate the next-day load curve information based on the first algorithm interface information in various ways. The next-day load curve information can be prediction information of the next-day upper and lower load limits of the virtual power plant. The next-day upper and lower load limits may include a next-day upper load limit value sequence and a next-day lower load limit value sequence. The next-day upper limit value in the next-day upper limit value sequence can be a predicted value of the load upper limit of the virtual power plant in the corresponding time period. The load upper limit may be a critical value that the electric load can reach upward. The next-day load lower limit value in the next-day load lower limit value sequence can be a predicted value of the load lower limit of the virtual power plant in the corresponding time period. The lower load limit may be a critical value that can be reached by the electric load downward.
In some optional implementations of some embodiments, the first algorithm interface information may include a first preset algorithm interface information set, first custom algorithm interface information, and first preset algorithm execution control information. The executing body may generate the next-day load curve information based on the first algorithm interface information by:
the method comprises the steps of responding to the detected selection operation of each first label switching control, and displaying first preset algorithm interface information or first user-defined algorithm interface information corresponding to the selected first label switching control so as to receive target user input. The corresponding first label switching control can be activated through the selection operation, and first preset algorithm interface information or first self-defined algorithm interface information corresponding to the selected first label switching control is displayed.
By way of example, the selection operation described above may include, but is not limited to, at least one of: click operation, hover operation, drag operation, and the like.
And secondly, responding to the click operation detected aiming at the first preset algorithm operation control, and acquiring first target algorithm input information. The first target algorithm input information may be input information related to the load generation algorithm on an interface corresponding to the first label switching control selected by the target user. The first target algorithm input information can be obtained by obtaining information of the load generation algorithm corresponding to the selected first label switching control and information input by a user.
And thirdly, determining the first target algorithm input information, the algorithm information corresponding to the first label switching control and the target energy equipment instance information set as load generation algorithm information. The load generation algorithm information may be information of the selected load generation algorithm and information input by the target user.
And fourthly, generating a target load curve information set based on the load generation algorithm information. The target load curve information in the target load curve information set may be prediction information of the power load of the energy device. The target load curve information set may be generated by a load generation algorithm corresponding to the load generation algorithm information.
And fifthly, generating load curve information of the next day based on the target load curve information set. The next-day load curve information may be generated based on the above-described target load curve information set in various ways.
In some optional implementations of some embodiments, each of the target load curve information sets includes a target load upper limit value time series and a target load lower limit value time series. The time series of the upper limit values of the target loads may be an ordered set of the upper limit values of the target loads in each time period of the next day. The target load upper limit value may be a predicted value of an electric power load upper limit value. The time series of the lower limit values of the target load may be an ordered set of the lower limit values of the target load for each time period of the next day. The target load lower limit value may be a predicted value of a power load lower limit value. The execution body may generate the next-day load curve information based on the target load curve information set by:
the first step, for each time-sharing identification in the preset time-sharing identification sequence, executing the following steps:
a first substep of determining, as the next-day upper limit load value, the sum of the upper limit load values corresponding to the time-sharing identifier in the time series of upper limit target load values included in each set of target load curve information. The time-sharing identifier in the preset time-sharing identifier sequence can uniquely identify the time slot. First, for each piece of target load curve information in the set of target load curve information, a target load upper limit value corresponding to the time-sharing flag is selected from a time series of target load upper limit values included in the target load curve information, and a set of target load upper limit values is obtained. The target load upper limit value group may be a set of target load upper limit values of the respective energy devices corresponding to the same time zone. Next, the sum of the respective target load upper limit values in the target load upper limit value group is determined as the next day load upper limit value.
And a second substep of determining the sum of the lower limit values of the respective target loads corresponding to the time-sharing identifier in the time series of the lower limit values of the target loads included in the pieces of target load curve information in the set of target load curve information as the lower limit value of the next-day load. First, for each piece of target load curve information in the set of target load curve information, a target load lower limit value corresponding to the time-sharing flag is selected from a time series of target load lower limit values included in the target load curve information, and a set of target load lower limit values is obtained. The target load lower limit value group may be a set of target load lower limit values of the respective energy devices corresponding to the same time zone. Next, the sum of the respective target load lower limit values in the target load lower limit value group is determined as the next-day load lower limit value.
And secondly, sequencing the determined upper limit values of the loads of the next day to obtain a time sequence of the upper limit values of the loads of the next day. The determined load upper limit values of the next day can be sorted according to the time sequence of the time period corresponding to the load upper limit value of each next day, so as to obtain the time sequence of the load upper limit values of the next day.
And thirdly, sequencing the determined lower limit values of the loads of the next day to obtain a time sequence of the lower limit values of the loads of the next day. The determined next-day load lower limit values can be sorted according to the time sequence of the time period corresponding to each next-day load lower limit value, so as to obtain the time sequence of the next-day load lower limit values.
And fourthly, determining the time sequence of the upper limit value of the next-day load and the time sequence of the lower limit value of the next-day load as the next-day load curve information.
And 107, generating second algorithm interface information based on the target energy equipment instance information set and the user prompt information set.
In some embodiments, the executing agent may generate second algorithm interface information based on the target energy device instance information set and the user prompt information set. The second algorithm interface information may be used to characterize an interface that receives information input by a target user to generate electricity price curve information. Second algorithm interface information may be generated based on the target energy device instance information set and the user prompt information set by:
the method comprises the steps of firstly, generating second label switching control information corresponding to preset second algorithm information for each second algorithm information in a second algorithm information set to obtain a second label switching control information set. Each second algorithm information in the preset second algorithm information set may be used to represent a preset price curve generation algorithm. Each of the preset second algorithm information sets may include a second algorithm identifier. The second algorithm identifier may be an identifier corresponding to the price curve generation algorithm. For example, the second algorithm identification may be a name or ID code corresponding to the valence curve generation algorithm. The second label switching control information in the second label switching control information group may include a second control identifier and a second algorithm identifier. The second control identifier may be an identifier of a second label switching control. The second control identifier may correspond to the second label switching control one to one. For example, the second control identification may be a name or ID code corresponding to the second label switching control. The second label switching control may be a control having a function of switching an interface or a panel. The following steps may be performed for each second algorithm information in a preset second algorithm information set:
a first sub-step of determining a second label switching control. And selecting a control with interface or panel switching function from the preset control library as a second label switching control.
And a second substep, determining a second control identifier corresponding to the second label switching control and a second algorithm identifier included in the second algorithm information as second label switching control information.
And secondly, determining each second entering-reference information in the user prompt information group as second target entering-reference information. The second target entry information may be information for explaining an input parameter related to the preset cost curve generation algorithm.
And thirdly, determining each second reference information in the user prompt information group as second target reference information. The second target specification information may be information for explaining an output parameter related to the preset cost curve generation algorithm.
And fourthly, for each piece of second label switching control information in the second label switching control information group, determining second algorithm information corresponding to the second label switching control information, the second target entry introduction information, the preset entry control information and the second label switching control information as second preset algorithm interface information to obtain a second preset algorithm interface information group. The second preset algorithm interface information in the second preset algorithm interface information group may be used to represent an interface or a panel corresponding to the preset price curve generation algorithm.
And fifthly, determining preset second custom algorithm label switching control information, the second target entry reference information, the second target exit reference information, the preset entry reference control information, the preset exit reference control information, the preset code entry control information and a preset custom algorithm identifier as second custom algorithm interface information. The preset second custom algorithm label switching control information may be information of a control having a function of switching a custom algorithm interface or a panel. The second custom algorithm interface information may be used to characterize an interface corresponding to a custom price curve generation algorithm.
And sixthly, determining the second preset algorithm interface information group, the second self-defined algorithm interface information, the second preset algorithm operation control information and the preset result display control information as second algorithm interface information. The second preset algorithm running control information may be information of a control executing the price curve generation algorithm.
And 108, generating power flow declaration strategy information based on the next day load curve information and the second algorithm interface information.
In some embodiments, the execution subject may generate the power flow declaration policy information based on the next-day load curve information and the second algorithm interface information in various ways. The power flow declaration strategy information can be information of the next day load upper and lower limits of the virtual power plant, declared electric quantity and corresponding price.
In some optional implementation manners of some embodiments, the second algorithm interface information may include a second preset algorithm interface information set, second customized algorithm interface information, and second preset algorithm execution control information. The execution body may generate power flow declaration policy information based on the next-day load curve information and the second algorithm interface information by:
and in a first step, responding to the detected selection operation aiming at each second label switching control, displaying second preset algorithm interface information or second self-defined algorithm interface information corresponding to the selected second label switching control so as to receive the input of a target user. And activating the corresponding second label switching control through the selection operation, and displaying second preset algorithm interface information or second self-defined algorithm interface information corresponding to the selected second label switching control.
And secondly, responding to the click operation detected aiming at the second preset algorithm operation control, and acquiring second target algorithm input information. The second target algorithm input information may be input information related to a price curve generation algorithm. The information of the price curve generation algorithm corresponding to the selected second label switching control and the information input by the user can be obtained, so that the input information of the second target algorithm can be obtained.
And thirdly, determining the second target algorithm input information, the algorithm information corresponding to the second label switching control and the target energy equipment instance information set as price curve generation algorithm information. The price curve generation algorithm information may be information input by a price curve generation algorithm and a target user.
And fourthly, generating algorithm information based on the price curve to generate electric quantity price curve information. The electric quantity price curve information can be used for representing the relation between the electric quantity and the price. The electricity price curve information may be generated by a price curve generation algorithm corresponding to the price curve generation algorithm information.
And fifthly, sending the electric quantity price curve information to a preset price electric quantity declaration interface for receiving price electric quantity declaration information. The preset price electric quantity declaration interface can be an interface used for filling electric power circulation declaration information. The price electric quantity declaration information may be information of electric quantity and corresponding price. The electricity quantity price curve information can be sent to a price electricity quantity declaration interface so that a target user can fill in price electricity quantity declaration information on the price electricity quantity declaration interface after referring to the electricity quantity price curve information.
And sixthly, in response to the received price electric quantity declaration information, determining the next-day load curve information and the price electric quantity declaration information as power circulation declaration strategy information.
And step 109, generating third algorithm interface information based on the target energy equipment instance information set and the user prompt information set in response to the received next-day birth-clearing curve information.
In some embodiments, the executing agent may generate third algorithm interface information based on the target energy device instance information set and the user prompt information set in response to receiving the next-day birth-to-death curve information. The next-day coming-and-going curve information can be information of power circulation of the virtual power plant the next day. The third algorithm interface information may be used to characterize an interface that receives information input by a target user to generate the next-day-to-date-birth-curve information. Third algorithm interface information may be generated based on the set of target energy device instance information and the set of user prompt information by:
the method comprises the steps of firstly, generating third label switching control information corresponding to third algorithm information for each third algorithm information in a preset third algorithm information set, and obtaining a third label switching control information set. Each of the third algorithm information in the preset third algorithm information set may be used to characterize a preset load splitting algorithm. Each of the third algorithm information in the preset third algorithm information set may include a third algorithm flag. The third algorithm identification may be an identification of a corresponding load split algorithm. For example, the third algorithm identification may be a name or an ID code corresponding to the load split algorithm. The third label switching control information in the third label switching control information group may include a third control identifier and a third algorithm identifier. The third control identifier may be an identifier of a third label switching control. The third control identifier may correspond to the third label switching control one to one. For example, the third control identifier may be a name or an ID code corresponding to the third label switching control. The third label switching control may be a control having a function of switching an interface or a panel. For each third algorithm information in a preset third algorithm information set, the following steps may be performed:
a first substep of determining a third label switching control. The control with the function of switching the interface or the panel can be selected from the preset control library.
And a second substep of determining a third control identifier corresponding to the third label switching control and a third algorithm identifier included in the third algorithm information as third label switching control information.
And secondly, determining each third entering-reference information in the user prompt information group as third target entering-reference information. The third target entry information may be information for interpreting an input parameter related to the preset load split algorithm.
And thirdly, determining each third reference information in the user prompt information group as second target reference information. The third target specification information may be information for specifying an output parameter related to the preset load split algorithm.
And fourthly, for each piece of third label switching control information in the third label switching control information group, determining third algorithm information corresponding to the third label switching control information, the third target entry introduction description information, the preset entry control information and the third label switching control information as third preset algorithm interface information to obtain a third preset algorithm interface information group. The third preset algorithm interface information in the third preset algorithm interface information group may be used to represent an interface or a panel corresponding to the preset load splitting algorithm.
And fifthly, determining preset third custom algorithm label switching control information, the third target entry reference description information, the third target exit reference description information, the preset entry reference control information, the preset exit reference control information, the preset code entry control information and a preset custom algorithm identifier as third custom algorithm interface information. The preset third custom algorithm tag switching control information may be information of a control having a function of switching a custom algorithm interface or a panel. The third custom algorithm interface information may be used to characterize an interface corresponding to the custom load splitting algorithm.
And sixthly, determining the third preset algorithm interface information group, the third self-defined algorithm interface information, the third preset algorithm operation control information and the preset result display control information as third algorithm interface information. The third preset algorithm running control information may be information of a control executing a load decomposition algorithm.
The steps and related contents of the generation and use of the interface information of each custom algorithm are used as an invention point of the embodiment of the disclosure, and the technical problem that the background technology is mentioned in the second paragraph, "the background preset algorithm cannot be applied to various virtual power plant power flow modes due to the fact that the virtual power plant power flow modes are not uniform everywhere, and the universality of the virtual power plant power flow method is low due to the lack of uniform custom algorithm interfaces". The problem that the universality of the power transfer method of the virtual power plant is low is often as follows: due to the fact that the virtual power plant power transfer modes are not uniform from place to place, background preset algorithms cannot be applied to various virtual power plant power transfer modes, and a uniform custom algorithm interface is lacked, the virtual power plant power transfer method is low in universality. If the problems are solved, the effect of improving the universality of the power transfer method of the virtual power plant can be achieved. In order to achieve the effect, the method comprises the steps of firstly providing description information of input parameters and output parameters in a user-defined algorithm interface so that a target user can refer to the description information, inputting user-defined algorithm information matched with a virtual power plant power circulation mode in the user-defined algorithm interface, then receiving and operating the input user-defined algorithm information, and finally obtaining an algorithm result meeting the requirements of the target user. Therefore, the universality of the virtual power plant power transfer method can be improved.
And step 110, generating a target clearing curve information set for the virtual power plant to execute power circulation based on the next-day clearing curve information and the third algorithm interface information.
In some embodiments, the execution subject may generate a target birth curve information set for the virtual power plant to execute power transfer based on the next-day birth curve information and the third algorithm interface information in various ways. The target clearing curve information in the target clearing curve information set may be the next day clearing curve information of the corresponding energy device.
In some optional implementation manners of some embodiments, the third algorithm interface information may include a third preset algorithm interface information set, third custom algorithm interface information, and third preset algorithm execution control information. The execution main body can generate a target clearance curve information set for the virtual power plant to execute power circulation based on the next-day clearance curve information and the third algorithm interface information through the following steps:
and step one, generating an energy equipment priority information sequence based on a preset equipment type priority information sequence and the target energy equipment instance information set. The device type priority information in the preset device type priority information sequence may be information of a device type and a corresponding priority. The priority can be used for representing the load regulation capacity of the energy equipment. The energy device priority information in the energy device priority information sequence may be information of the energy device and a priority corresponding to the energy device. The energy device priority information sequence can be obtained by sequencing the target energy device instance information in the target energy device instance information set according to the priority sequence of each device type in the preset device type priority information sequence and the device type of the energy device corresponding to each target energy device instance information in the target energy device instance information set through a preset sequencing algorithm.
As an example, the preset sorting algorithm may be, but is not limited to, one of the following: bubble ordering, quicksort, and insert ordering.
And secondly, in response to the detection of the selection operation for each third label switching control in the third label switching control group, displaying third preset algorithm interface information or third self-defined algorithm interface information corresponding to the third label switching control to receive the input of a target user. And activating the corresponding third label switching control through the selection operation, and displaying third preset algorithm interface information or third self-defined algorithm interface information corresponding to the selected third label switching control so as to receive the input of the target user.
And thirdly, responding to the click operation detected aiming at the third preset algorithm operation control, and acquiring third target algorithm input information. The third target algorithm input information may be input information related to a load split algorithm. The third target algorithm input information can be obtained by obtaining the information of the load decomposition algorithm corresponding to the selected third label switching control and the information input by the user.
And fourthly, determining the third target algorithm input information, the algorithm information corresponding to the third label switching control and the target energy equipment instance information set as load decomposition algorithm information. The load resolution algorithm information may be information of a load resolution algorithm and a code input by a target user.
And fifthly, generating a target output curve information set for the virtual power plant to execute power circulation based on the output curve information of the next day, the target load curve information sequence and the load decomposition algorithm information. And generating a target output curve information set for the virtual power plant to execute power flow based on the next-day output curve information, the target load curve information sequence and the load decomposition algorithm information through a load decomposition algorithm corresponding to the load decomposition algorithm information.
Optionally, the dynamic hierarchical compensation method may be performed by:
the method comprises the steps of firstly, obtaining a next-day clear power time sequence and a next-day predicted power time sequence set. The power time series of the next day of the production may be an ordered set of powers of each time period of the production day of the virtual power plant. The next-day predicted power time series in the next-day predicted power time series set may be an ordered set of predicted powers of the corresponding energy devices in each time period of the day of birth and death. The predicted power may be a power predicted to be discharged by the corresponding energy device during a time period on the current date of the birth. The next-day-coming power-time series and the next-day predicted power-time series set may be read from a preset database storing power flow data.
And secondly, determining the sum of each next-day output power in the next-day output power time sequence and each next-day output power before the corresponding time period as an accumulated output power to obtain an accumulated output power time sequence. The cumulative output power in the cumulative output power time series may be the total power output from the 1 st time period to the corresponding time period on the output day.
And thirdly, generating an accumulated predicted power time sequence set based on the predicted power time sequence set of the next day. The cumulative predicted power time series in the cumulative predicted power time series set may be an ordered set of the cumulative predicted power of the corresponding energy device in each time period on the day of the morning and evening. The accumulated predicted power may be a total power predicted to be discharged by the corresponding energy device from the 1 st time period to the corresponding time period on the day of the birth and death. For each next-day predicted power time series in the next-day predicted power time series set, the sum of each next-day predicted power in the next-day predicted power time series and each next-day predicted power before the corresponding time period may be determined as the accumulated predicted power, so as to obtain the accumulated predicted power time series corresponding to the next-day predicted power time series.
And fourthly, generating an accumulated difference power time series based on the accumulated clear power time series and the accumulated predicted power time series set. The accumulated difference power in the accumulated difference power time series may be the accumulated predicted power left by the virtual power plant after removing each accumulated predicted power corresponding to the first preset energy device set from the accumulated difference power from the 1 st time period to the corresponding time period on the day of the birth and death. The first preset energy device in the first preset energy device set may be an energy device set by the target user according to the power flow demand. For example, the above power flow demand may be a demand for promoting new energy generation or a demand for ensuring factory production power. For example, the first preset energy device in the first preset energy device set may be, but is not limited to, one of the following: photovoltaic power generation equipment, factory electrical equipment and wind power generation equipment. The following steps may be specifically performed:
the first substep, select the accumulated prediction power time series which satisfies the preset equipment condition from the above-mentioned accumulated prediction power time series set. The preset device condition may be that the energy device corresponding to the accumulated predicted power time series in the accumulated predicted power time series set is a first preset energy device in the first preset energy device set.
And a second substep of generating a time series of base load values based on the predetermined time-sharing identification series and the selected respective cumulative predicted power time series. The base load value in the base load value time sequence may be the predicted power of the virtual power plant which needs to be released from the 1 st time period to the corresponding time period on the day of release and clearance. For each time-sharing identifier in the preset time-sharing identifier sequence, the sum of the accumulated predicted powers corresponding to the time-sharing identifier included in each selected accumulated predicted power time sequence may be determined as the base load value.
And a third substep of determining a difference between each cumulative emerging power in the cumulative emerging power time series and the base load value corresponding to the same time period in the base load value time series as a cumulative difference power to obtain a cumulative difference power time series.
And sixthly, generating equipment clearing curve information corresponding to each energy equipment based on a preset constraint condition group, a preset objective function, the accumulated difference power time series and the accumulated predicted power time series set. The preset constraint condition set may be a set of conditions for constraining each energy device. For example, the preset constraint condition group may include a constraint condition corresponding to the energy storage device, a constraint condition corresponding to the electric vehicle charging pile device, and a constraint condition corresponding to the building air conditioning device. The building air conditioning equipment can be air conditioning equipment in a building. The preset objective function may be used to characterize the relationship between the cumulative planned power for each energy device and the corresponding cumulative predicted power and the cumulative difference power of the virtual power plant. The accumulated planned power may be the accumulated planned power corresponding to the energy device being cleared the power of clearing is planned from the 1 st time period to the corresponding time period on the same day. The preset objective function may be constrained by the following preset set of constraint conditions:
wherein,
representing the power rating of the energy storage device.
Representing the planned power of the energy storage device. The planned power may be power planned to be cleared in any one of the time periods corresponding to the accumulated planned power. The planned power is in a power range obtained by multiplying the rated power of the energy storage equipment by a preset charging and discharging coefficient. The preset charge and discharge coefficients may include a charge coefficient and a discharge coefficient. The charge factor was 0.6. The discharge coefficient was-0.6.
Representing the capacity of the energy storage device at any one time period. The ratio of the capacity of the energy storage device to the rated capacity of the corresponding energy storage device is between 0.4 and 0.8.
Is the number of time periods.
Is shown as
The capacity of the time period energy storage device.
Denotes the first
Capacity of the time period energy storage device.
Is shown as
The projected power of the energy storage device.
Representing the rated capacity of the energy storage device.
Indicating the above-mentioned preset interval duration.
And representing the planned power of the electric automobile charging pile equipment.
And the rated power of the electric automobile charging pile equipment is shown.
Representing the planned power of the building air conditioning equipment.
Indicating the rated power of the building air conditioning equipment.
The target clearing curve information corresponding to each energy device may be generated by the following formula:
wherein,
represents the minimum target value of the preset target function.
Represents the sum of the squares of the cumulative projected power error values for each time period of the virtual plant. Wherein, the aboveThe cumulative planned power error value is a difference of the cumulative difference power and a sum of the cumulative planned powers corresponding to the respective energy devices.
And the sum of squares of error values between the total accumulated planned power and the total accumulated predicted power of the electric vehicle charging pile equipment groups corresponding to the time periods is represented. The total accumulated planned power of the electric vehicle charging pile equipment group is the sum of the accumulated planned powers corresponding to the electric vehicle charging pile equipment. The total accumulated predicted power of the electric vehicle charging pile equipment group is the sum of the accumulated predicted power corresponding to each electric vehicle charging pile equipment.
And a sum of squares of error values between the total accumulated planned power and the total accumulated predicted power of the building air conditioning equipment groups corresponding to the respective time periods is represented. The total accumulated planned power of the building air conditioning equipment group is the sum of the accumulated planned power corresponding to each building air conditioning equipment. The total accumulated predicted power of the building air-conditioning equipment group is the sum of the accumulated predicted power corresponding to each building air-conditioning equipment.
The serial number corresponding to the last time period of the current day is cleared.
Representing virtual power plant correspondences from time period 1 to time period
Accumulated power of the deficit over the time period.
Indicating the corresponding time periods from 1 st to the first
The sum of the accumulated planned power for the time period.
Showing that the electric automobile fills corresponding from the 1 st time slot to the 1 st time slot of electric pile equipment
The sum of the accumulated planned power for the time period.
Indicating the time period from 1 st to the first st corresponding to each building air conditioner
The sum of the accumulated planned power for the time period.
And the serial number is the corresponding serial number of the energy storage equipment.
Is the number of energy storage devices.
Denotes the first
Corresponding from 1 st time period to the first time period
Cumulative projected power for the time period.
The serial numbers correspond to the electric automobile charging pile equipment.
The number of the electric automobile charging pile equipment is shown.
Is shown as
The electric automobile fills corresponding from 1 st time quantum to the 1 st time quantum of electric pile equipment
Cumulative projected power for the time period.
Is the serial number corresponding to the building air conditioning equipment.
Is the number of the building air-conditioning equipment.
Denotes the first
From the 1 st time period to the 1 st time period corresponding to each building air conditioning equipment
Cumulative projected power for the time period.
Is shown as
The electric automobile fills corresponding from 1 st time quantum to the 1 st time quantum of electric pile equipment
Accumulated predicted power for the time period.
Denotes the first
From the 1 st time period to the 1 st time period corresponding to each building air conditioning equipment
The accumulated predicted power for the time period.
In practice, the execution main body may input the preset objective function by using the next-day clear power time series and the next-day predicted power time series set as input parameters, to obtain a minimum objective function, and solve the minimum objective function by using a preset planning method, to obtain target clear curve information corresponding to each energy device.
As an example, the preset planning method may be, but is not limited to, one of the following: linear programming, genetic algorithms, particle swarm algorithms, and the like.
The steps and related contents of the energy equipment priority information sequence generation and dynamic grading compensation method serve as an invention point of the embodiment of the disclosure, and the technical problems mentioned in the background art are solved, namely, the difference of load adjustment capacities of different types of energy equipment is often ignored easily during load decomposition, and the influence of the generation power of new energy and the load prediction precision on the load decomposition is ignored, so that the accuracy of tracking a load clearing curve is low, and therefore, the power flow accuracy of a virtual power plant is low. The problem that the accuracy of power flow of the virtual power plant is low is often as follows: when load decomposition is carried out, the difference of load adjusting capacities of different types of energy equipment is often easily ignored, and the influence of new energy power generation power and load prediction precision on load decomposition is ignored, so that the accuracy of tracking a load clearing curve is low, and the power flow accuracy of a virtual power plant is low. If the problem is solved, the effect of improving the accuracy of the power flow of the virtual power plant can be achieved. To achieve this effect, the present disclosure may divide energy devices with different load adjustment capabilities into different priorities by a prioritization method, so as to give full play to the new energy power generation capability when the load is decomposed, and to tend to distribute the power load task to the energy devices with stronger load adjustment capabilities. Secondly, in the dynamic grading compensation method, a compensation relation between the planned power and the predicted power of each energy device and the differential power of the virtual power plant is established, a minimum value objective function is set, and target load curve information of each energy device is obtained through solving through a preset planning algorithm, so that a load clearing curve can be tracked accurately. Therefore, the accuracy of power transfer of the virtual power plant can be improved. Further, the deviation assessment is reduced.
Optionally, each piece of target clearance curve information in the set of target clearance curve information may include a time-sharing clearance load value time series. The time-sharing output load value time series may be an ordered set of output load values of the corresponding energy device in each time period. The output load value may be a power generation power value or a power consumption power value. The executing main body may further execute the following steps for each time-sharing identifier in a preset time-sharing identifier time sequence:
and step one, in response to the fact that the current time is matched with the time-sharing identification, selecting a time-sharing output load value matched with the time-sharing identification from each time-sharing output load value time sequence corresponding to the target output load curve information set as a target output load value, and obtaining a target output load value set. The matching with the time-sharing identifier may be that a time period corresponding to the current time is the same as a time period corresponding to the time-sharing identifier. The time-sharing load shedding value matched with the time-sharing identifier may be that a time period corresponding to the time-sharing load shedding value in the time series of the time-sharing load shedding value is the same as a time period corresponding to the time-sharing identifier. The target output load clear value set may be a set of time-sharing output load clear values corresponding to the current time of each energy device.
And secondly, sending the target output clear load value to corresponding energy equipment for the virtual power plant to execute power transfer for each target output clear load value in the target output clear load value set. The virtual power plant can control each energy device to generate power or use power to transfer power according to the corresponding target output clear load value.
Optionally, the executing body may further execute the following steps:
and acquiring an actual clear load value time sequence of the energy equipment corresponding to each target clear curve information in the target clear curve information set, acquiring an actual clear load value time sequence set, and storing the actual clear load value time sequence set. The time series of the actual load shedding values in the time series set of the actual load shedding values may be an ordered set of actual powers of the corresponding energy devices in each time period. The actual power may be generated power or used power actually generated. The energy devices corresponding to each target clearing curve information in the target clearing curve information set can be connected to obtain corresponding actual clearing load value time series, obtain an actual clearing load value time series set, and store the actual clearing load value time series set in the database.
Optionally, the executing body may further execute the following steps:
and generating single-day power flow information for display based on the preset database and the historical flow query request information in response to receiving the historical flow query request information. The historical power flow query request information may be request information for querying historical power flow details. The above-described historical power flow details may be power flow information for a past single day.
By way of example, the historical power flow details described above may include, but are not limited to, at least one of: next day load curve information, power circulation declaration strategy information and clearing curve information. The above-mentioned single-day power circulation information may be power circulation information of one day.
The above embodiments of the present disclosure have the following advantages: through the virtual power plant power flow method of some embodiments of the disclosure, the accuracy of virtual power plant power flow can be improved. Specifically, the reason for the low accuracy of power flow in the virtual power plant is that: in order to adapt to the changing virtual power plant power transfer mode, the background preset algorithm needs to be continuously optimized and adjusted, however, the background cannot be edited at the front end, so that the background preset algorithm is inconvenient to optimize and adjust, and the virtual power plant power transfer accuracy is low. Based on this, the virtual power plant power flow method according to some embodiments of the present disclosure first generates an energy device information table for selecting each energy device information based on the declaration confirmation information in response to receiving declaration confirmation information for power flow declaration to-be-confirmed information. Therefore, the virtual power plant power flow declaration work can be started, and the class instance corresponding to each energy device can be conveniently generated subsequently by selecting each energy device participating in the declaration work. Secondly, in response to receiving energy device selection information aiming at each piece of energy device information in the energy device information table, instantiation processing is carried out on the energy device selection information, and a target energy device instance information set is obtained. Therefore, target energy equipment instance information corresponding to each energy equipment can be obtained, and algorithm interface information corresponding to the target energy equipment instance information set can be conveniently generated subsequently, and each subsequent algorithm can call the corresponding class instance. Therefore, the optimization and adjustment of the background preset algorithm can be facilitated. And thirdly, determining the device type identifier corresponding to each piece of target energy device instance information in the target energy device instance information set as a target device type identifier to obtain a target device type identifier group. And determining the initial prompt information matched with each target equipment type identifier in the target equipment type identifier group in a preset initial prompt information set as the user prompt information to obtain a user prompt information group. Therefore, the equipment type of each energy equipment selected by the target user and the user prompt information corresponding to each equipment type can be obtained, and the subsequent target user can conveniently and correctly input information according to the prompt content. And then, generating first algorithm interface information based on the target energy equipment instance information set and the user prompt information set. And generating load curve information of the next day based on the first algorithm interface information. Therefore, first algorithm interface information corresponding to the load generation algorithm can be obtained, and information input by a target user can be received through the first algorithm interface corresponding to the first algorithm interface information to optimize and adjust the load generation algorithm preset in the background, so that more accurate next-day load curve information can be obtained, and further, the next-day load curve information can be conveniently referred to later to generate better power flow declaration strategy information. And then, generating second algorithm interface information based on the target energy equipment instance information set and the user prompt information set. And generating power flow declaration strategy information based on the next day load curve information and the second algorithm interface information. Therefore, second algorithm interface information corresponding to the price curve generation algorithm can be obtained, and information input by a target user can be received through the second algorithm interface corresponding to the second algorithm interface information to optimize and adjust the price curve generation algorithm preset in the background, so that more accurate electricity price curve information can be obtained, and further more excellent power flow declaration strategy information is generated for declaration. And finally, responding to the received information of the next-day birth-clearing curve, and generating third algorithm interface information based on the target energy equipment instance information set and the user prompt information set. And generating a target clearing curve information set for power circulation of the virtual power plant based on the next-day clearing curve information and the third algorithm interface information. Therefore, third algorithm interface information corresponding to the load decomposition algorithm can be obtained, and through the third algorithm interface corresponding to the third algorithm interface information, information input by a target user can be received to optimize and adjust the load decomposition algorithm preset in the background, so that more accurate target clearing curve information corresponding to each energy device can be obtained, each energy device can be controlled by the virtual power plant to carry out load clearing according to the corresponding target clearing curve information, and power circulation is completed. Therefore, the virtual power plant power flow method of the embodiment of the disclosure can realize optimization and adjustment of each background preset algorithm at the front end, so that more accurate next-day load curve information can be obtained conveniently for reference, more excellent power flow declaration strategy information can be generated for declaration, and more accurate target clearing curve information sets can be generated for the virtual power plant to control each energy device to execute power flow tasks strictly according to the corresponding target clearing curve information. Therefore, the accuracy of virtual power plant power flow can be improved.
With further reference to fig. 2, as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a virtual power plant power flow device, which correspond to those shown in fig. 1, and which may be specifically applied in various electronic devices.
As shown in FIG. 2, the virtual plant power flow device 200 of some embodiments includes: a first generation unit 201, an instantiation processing unit 202, a first determination unit 203, a second determination unit 204, a second generation unit 205, a third generation unit 206, a fourth generation unit 207, a fifth generation unit 208, a sixth generation unit 209, and a seventh generation unit 210. Wherein the first generating unit 201 is configured to generate an energy device information table for selecting each energy device information based on declaration confirmation information in response to receiving declaration confirmation information for declaring to-be-confirmed information of power flow; an instantiation processing unit 202, configured to, in response to receiving energy device selection information for each energy device information in the energy device information table, perform instantiation processing on the energy device selection information to obtain a target energy device instance information set; a first determining unit 203, configured to determine a device type identifier corresponding to each piece of target energy device instance information in the target energy device instance information set as a target device type identifier, to obtain a target device type identifier group; a second determining unit 204, configured to determine, as user prompt information, initial prompt information in a preset initial prompt information set that matches each target device type identifier in the target device type identifier group, so as to obtain a user prompt information group; a second generating unit 205 configured to generate first algorithm interface information based on the target energy device instance information set and the user prompt information set; a third generating unit 206 configured to generate next-day load curve information based on the first algorithm interface information; a fourth generating unit 207 configured to generate second algorithm interface information based on the target energy device instance information set and the user prompt information set; a fifth generating unit 208 configured to generate power flow declaration policy information based on the next-day load curve information and the second algorithm interface information; a sixth generating unit 209 configured to generate third algorithm interface information based on the target energy device instance information set and the user prompt information set in response to receiving the next-day birth-and-death curve information; a seventh generating unit 210 configured to generate a target clearance curve information set for the virtual power plant to perform power transfer based on the next-day clearance curve information and the third algorithm interface information.
It will be understood that the units described in the apparatus 200 correspond to the various steps in the method described with reference to fig. 1. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 200 and the units included therein, and are not described herein again.
With further reference to fig. 3, a schematic structural diagram of an electronic device 300 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 3, electronic device 300 may include a processing device (e.g., central processing unit, graphics processor, etc.) 301 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage device 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data necessary for the operation of the electronic apparatus 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
Generally, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, or the like; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage devices 308 including, for example, magnetic tape, hard disk, etc.; and a communication device 309. The communication means 309 may allow the electronic device 300 to communicate wirelessly or by wire with other devices to exchange data. While fig. 3 illustrates an electronic device 300 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may be alternatively implemented or provided. Each block shown in fig. 3 may represent one device or may represent multiple devices, as desired.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. The computer program, when executed by the processing apparatus 301, performs the above-described functions defined in the methods of some embodiments of the present disclosure.
It should be noted that the computer readable medium described above in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the apparatus described above; or may be separate and not incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: generating an energy equipment information table for selecting information of each energy equipment based on received declaration confirmation information aiming at power flow declaration to-be-confirmed information in response to receiving declaration confirmation information; in response to receiving energy equipment selection information aiming at each piece of energy equipment information in the energy equipment information table, instantiation processing is carried out on the energy equipment selection information to obtain a target energy equipment instance information set; determining a device type identifier corresponding to each piece of target energy device instance information in the target energy device instance information set as a target device type identifier to obtain a target device type identifier group; determining initial prompt information which is matched with each target equipment type identifier in the target equipment type identifier group in a preset initial prompt information set as user prompt information to obtain a user prompt information group; generating first algorithm interface information based on the target energy equipment instance information set and the user prompt information set; generating next-day load curve information based on the first algorithm interface information; generating second algorithm interface information based on the target energy equipment instance information set and the user prompt information set; generating power flow declaration strategy information based on the next day load curve information and the second algorithm interface information; generating third algorithm interface information based on the target energy equipment instance information set and the user prompt information set in response to receiving the next-day birth-to-death curve information; and generating a target clearing curve information set for the virtual power plant to execute power transfer based on the next-day clearing curve information and the third algorithm interface information.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes a first generation unit, an instantiation processing unit, a first determination unit, a second generation unit, a third generation unit, a fourth generation unit, a fifth generation unit, a sixth generation unit, and a seventh generation unit. Here, the names of the units do not constitute a limitation to the units themselves in some cases, and for example, the first generation unit may also be described as "a unit that generates an energy device information table for selecting each energy device information based on the above-described declaration confirmation information in response to reception of declaration confirmation information for declaring information to be confirmed for a power flow".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems on a chip (SOCs), complex Programmable Logic Devices (CPLDs), and the like.
Some embodiments of the present disclosure also provide a computer program product comprising a computer program that when executed by a processor implements any of the virtual plant power flow methods described above.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (9)
1. A virtual plant power flow method, comprising:
in response to receiving declaration confirmation information for power flow declaration to-be-confirmed information, generating an energy equipment information table for selecting information of each energy equipment based on the declaration confirmation information;
in response to receiving energy equipment selection information aiming at each piece of energy equipment information in the energy equipment information table, instantiation processing is carried out on the energy equipment selection information to obtain a target energy equipment instance information set;
determining a device type identifier corresponding to each piece of target energy device instance information in the target energy device instance information set as a target device type identifier to obtain a target device type identifier group;
determining initial prompt information which is matched with each target equipment type identifier in the target equipment type identifier group in a preset initial prompt information set as user prompt information to obtain a user prompt information group;
generating first algorithm interface information based on the target energy equipment instance information set and the user prompt information set;
generating next-day load curve information based on the first algorithm interface information;
generating second algorithm interface information based on the target energy equipment instance information set and the user prompt information set;
generating power flow declaration strategy information based on the next day load curve information and the second algorithm interface information;
generating third algorithm interface information based on the target energy equipment instance information set and the user prompt information set in response to receiving the next-day birth-clearing curve information;
generating a target clearing curve information set for the virtual power plant to execute power transfer based on the next-day clearing curve information and the third algorithm interface information;
the energy device selection information comprises a target energy device information set, and each piece of target energy device information in the target energy device information set comprises a device code identifier and a device type identifier; and
the instantiating the energy equipment selection information to obtain a target energy equipment instance information set comprises:
for each target energy device information in the set of target energy device information, performing the following steps:
generating energy equipment instance information based on the equipment code identification and the equipment type identification included in the target energy equipment information;
generating a next-day generating power time series and a next-day load time series based on the energy equipment instance information;
and determining the energy equipment instance information, the next-day power generation time series and the next-day load time series as target energy equipment instance information.
2. The method of claim 1, wherein the first algorithmic interface information comprises a first set of pre-set algorithmic interface information, first custom algorithmic interface information, and first pre-set algorithmic run control information; and
the generating of the next-day load curve information based on the first algorithm interface information comprises:
in response to the detection of the selection operation aiming at each first label switching control, displaying first preset algorithm interface information or first user-defined algorithm interface information corresponding to the selected first label switching control so as to receive the input of a target user;
responding to the click operation detected aiming at the first preset algorithm operation control, and acquiring first target algorithm input information;
determining the first target algorithm input information, the algorithm information corresponding to the first label switching control and the target energy equipment instance information set as load generation algorithm information;
generating a target load curve information set based on the load generation algorithm information;
and generating the next day load curve information based on the target load curve information set.
3. The method of claim 2, wherein each target load curve information in the set of target load curve information comprises a target load upper bound value time series and a target load lower bound value time series; and
generating next-day load curve information based on the target load curve information set, including:
for each time-sharing identification in the preset time-sharing identification sequence, executing the following steps:
determining the sum of the upper limit values of the target loads corresponding to the time-sharing identification in the time sequence of the upper limit values of the target loads included in the information of the target load curves in the information set of the target load curves as the upper limit value of the next day;
determining the sum of the lower limit values of the target loads corresponding to the time-sharing identification in the time sequence of the lower limit values of the target loads included in the information of the target load curves in the information set of the target load curves as the lower limit value of the next day;
sequencing the determined load upper limit values of the next day to obtain a time sequence of the load upper limit values of the next day;
sequencing the determined lower limit values of the loads of the next day to obtain a time sequence of the lower limit values of the loads of the next day;
and determining the time sequence of the next-day upper limit value of the load and the time sequence of the next-day lower limit value of the load as the next-day load curve information.
4. The method according to one of claims 1 to 3, wherein each target birth curve information of the set of target birth curve information comprises a time-shared birth load value time series; and
the method further comprises the following steps:
for each time-sharing identification in the preset time-sharing identification time sequence, executing the following steps:
in response to the fact that the current time is matched with the time-sharing identification, selecting a time-sharing load-shedding value matched with the time-sharing identification from each time-sharing load-shedding value time sequence corresponding to the target load-shedding curve information set as a target load-shedding value to obtain a target load-shedding value set;
and for each target output clear load value in the target output clear load value set, sending the target output clear load value to corresponding energy equipment so as to enable the virtual power plant to execute power circulation.
5. The method of claim 4, wherein the method further comprises:
and acquiring an actual clear load value time sequence of the energy equipment corresponding to each target clear curve information in the target clear curve information set to obtain an actual clear load value time sequence set, and storing the actual clear load value time sequence set.
6. The method of claim 5, wherein the method further comprises:
in response to receiving the historical circulation query request information, generating single-day power circulation information for display based on a preset database and the historical circulation query request information.
7. A virtual plant power flow device, comprising:
a first generation unit configured to generate an energy device information table for selecting each energy device information based on declaration confirmation information in response to reception of declaration confirmation information that declares information to be confirmed for a power flow;
the instantiation processing unit is configured to respond to the received energy equipment selection information aiming at each energy equipment information in the energy equipment information table, and conduct instantiation processing on the energy equipment selection information to obtain a target energy equipment instance information set;
a first determining unit, configured to determine, as a target device type identifier, a device type identifier corresponding to each piece of target energy device instance information in the target energy device instance information set, to obtain a target device type identifier group;
the second determination unit is configured to determine initial prompt information which is matched with each target equipment type identifier in the target equipment type identifier group in a preset initial prompt information set as user prompt information to obtain a user prompt information group;
a second generating unit configured to generate first algorithm interface information based on the target energy device instance information set and the user prompt information set;
a third generating unit configured to generate next-day load curve information based on the first algorithm interface information;
a fourth generating unit configured to generate second algorithm interface information based on the target energy device instance information set and the user prompt information set;
a fifth generating unit configured to generate power flow declaration policy information based on the next-day load curve information and the second algorithm interface information;
a sixth generating unit configured to generate third algorithm interface information based on the target energy device instance information set and the user prompt information set in response to receiving the next-day birth-to-death curve information;
a seventh generating unit configured to generate a target clearing curve information set for the virtual power plant to perform power transfer based on the next-day clearing curve information and the third algorithm interface information;
the energy device selection information comprises a target energy device information set, and each piece of target energy device information in the target energy device information set comprises a device code identifier and a device type identifier; and
the instantiating the energy device selection information to obtain a target energy device instance information set includes:
for each target energy device information in the set of target energy device information, performing the following steps:
generating energy equipment instance information based on the equipment code identification and the equipment type identification included in the target energy equipment information;
generating a next-day power generation power time sequence and a next-day load time sequence based on the energy equipment instance information;
and determining the energy equipment instance information, the next-day power generation time series and the next-day load time series as target energy equipment instance information.
8. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-6.
9. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211098601.1A CN115187144B (en) | 2022-09-09 | 2022-09-09 | Virtual power plant power flow method, device, equipment, medium and program product |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211098601.1A CN115187144B (en) | 2022-09-09 | 2022-09-09 | Virtual power plant power flow method, device, equipment, medium and program product |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115187144A CN115187144A (en) | 2022-10-14 |
| CN115187144B true CN115187144B (en) | 2022-12-09 |
Family
ID=83524108
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211098601.1A Active CN115187144B (en) | 2022-09-09 | 2022-09-09 | Virtual power plant power flow method, device, equipment, medium and program product |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115187144B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116702523B (en) * | 2023-08-08 | 2023-10-27 | 北京中电普华信息技术有限公司 | Simulation method for power resource regulation, electronic equipment and computer medium |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5255462B2 (en) * | 2009-01-13 | 2013-08-07 | 株式会社日立製作所 | Power supply and demand operation management server and power supply and demand operation management system |
| CN114583708A (en) * | 2022-03-18 | 2022-06-03 | 南方电网科学研究院有限责任公司 | Virtual power plant day-ahead accurate peak clipping method, system, equipment and storage medium |
-
2022
- 2022-09-09 CN CN202211098601.1A patent/CN115187144B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN115187144A (en) | 2022-10-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP2020501491A (en) | System and method for dynamic energy storage system control | |
| CN105868949A (en) | Logistics distribution scheduling method and apparatus | |
| CN110333945A (en) | A kind of dynamic load balancing method, system and terminal | |
| CN112070301B (en) | User electricity consumption adjustment method, system and equipment | |
| CN109345166B (en) | Method and apparatus for generating information | |
| CN115187144B (en) | Virtual power plant power flow method, device, equipment, medium and program product | |
| CN115081958B (en) | User power adjustment method and device, electronic equipment and computer readable medium | |
| Onumanyi et al. | Transactive energy: State-of-the-art in control strategies, architectures, and simulators | |
| CN113034090A (en) | Transportation equipment scheduling method and device, electronic equipment and computer readable medium | |
| Jin et al. | Optimal priority rule-enhanced deep reinforcement learning for charging scheduling in an electric vehicle battery swapping station | |
| CN118052424B (en) | Material distribution method and device, electronic equipment and storage medium | |
| CN111105050B (en) | Fan maintenance plan generation method, device, equipment and storage medium | |
| CN115511631A (en) | Carbon transaction method and device, electronic equipment and storage medium | |
| Chiu et al. | Multiobjective demand response for internet data centers | |
| CN117063132A (en) | Optimized controller for distributed energy resources | |
| Burmeister et al. | A memetic NSGA-II for the multi-objective flexible job shop scheduling problem with real-time energy tariffs | |
| CN112801374B (en) | Model training method, power load prediction method, device and equipment | |
| WO2024105199A1 (en) | System and method to control electric vehicle fleet charging or microgrid operation considering a heuristic approach to extend battery life | |
| CN108846561A (en) | Demand response integrator resource allocation strategy based on statistical simulation hybrid particle swarm | |
| CN115222338A (en) | Material purchasing system, purchasing list generation method and component | |
| CN114971736A (en) | Power metering material demand prediction method and device, electronic equipment and storage medium | |
| KR102197767B1 (en) | Integration of renewable energy and electric vehicle charging in smart cities | |
| Aragón et al. | Optimization Framework for short-term control of Energy Storage Systems | |
| JPWO2014033893A1 (en) | Power accommodation group creation method and power accommodation group creation device | |
| CN111985967A (en) | Article information generation method and device, electronic equipment and computer readable medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |