JP2017220068A - Energy management device, energy management method and energy management program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an energy management device capable of reducing energy cost even when a plurality of annual restrictions are satisfied, an energy management method and an energy management program.SOLUTION: The energy management device has a long-term prediction part, a long-term planning part, a short-term prediction part and a short-term planning part. The long-term prediction part predicts an energy demand amount which is a burden for a predetermined long term. The long-term planning part determines an operation plan of an energy supply apparatus for the long term within a range which satisfies a plurality of restrictions on the basis of the prediction result of the energy demand amount for the long term. The short-term prediction part predicts an energy demand amount which is a burden for a short term included in the long term. The short-term planning part determines an operation plan of the energy supply amount for the short term within a range which satisfies the plurality of restrictions on the basis of the operation plan of the energy supply apparatus for the long term and the prediction result of the energy demand amount for the short term.SELECTED DRAWING: Figure 1

Description

  Embodiments described herein relate generally to an energy management apparatus, an energy management method, and an energy management program.

  In recent years, there has been an increasing interest in the Business Continuity Plan (BCP) in the event of an earthquake disaster. In addition, as a measure against global warming, it is required to reduce carbon dioxide (CO2) emissions.

  Under these circumstances, efforts toward smart communities are becoming more active. In a smart community, an energy management system (EMS: Energy Management System) manages energy such as electric power using information communication technology (ICT).

  FEMS (Factory Energy Management System) manages energy in a factory. BEMS (Building Energy Management System) manages energy in a building. The HEMS (Home Energy Management System) manages energy in a house. An EMS (hereinafter referred to as “regional EMS”) for a business such as a specific electric power company or a specific supply business manages energy in a specific region. When the energy supply and demand in the region is tight, the regional EMS encourages consumers to reduce the amount of energy demand by using a demand response (DR).

  Consumers may be subject to annual energy production constraints such as Zero Energy Building (ZEB), Positive Energy Building (PEB), Zero Energy House (ZEH). In addition, there are cases where annual gas demand restriction is imposed on the consumer in exchange for a reduction in the gas unit price. However, when the energy management apparatus satisfies a plurality of annual constraints such as an annual energy production constraint and an annual gas demand constraint, the energy cost may not be reduced.

Japanese Patent Laying-Open No. 2015-77014 Japanese Patent Laying-Open No. 2015-135571

  The problem to be solved by the present invention is to provide an energy management device, an energy management method, and an energy management program capable of reducing energy costs even when a plurality of annual constraints are satisfied.

  The energy management apparatus according to the embodiment includes a long-term prediction unit, a long-term plan unit, a short-term forecast unit, and a short-term plan unit. The long-term prediction unit predicts an energy demand amount of a load to which energy is supplied from the energy supply device for a predetermined long period. The long-term planning unit determines an operation plan for the long-term energy supply device within a range satisfying a plurality of constraints based on the prediction result of the energy demand amount for the long-term. The short-term prediction unit predicts the load energy demand for a short period included in a long period. The short-term planning unit determines an operation plan for the energy supply device in a short period within a range that satisfies a plurality of constraints based on the operation plan for the energy supply device for a long period and the prediction result of the energy demand in the short period.

The figure which shows the example of a structure of the energy management system in 1st Embodiment. The figure which shows the example of a structure of the energy management apparatus in 1st Embodiment. The figure which shows the example of a structure with an external energy source, an energy supply plant, and a customer group in 1st Embodiment. The flowchart which shows the example of operation | movement of the energy management apparatus in 1st Embodiment. The figure which shows the example of a structure of the annual driving | operation plan part in 1st Embodiment. The flowchart which shows the example of operation | movement of the annual driving | operation plan part in 1st Embodiment. The figure which shows the update of an annual constraint coefficient in 1st Embodiment for every energy classification. The figure which shows the update of an annual constraint coefficient in 1st Embodiment. The figure which shows the example of a display of an annual driving | operation plan in 1st Embodiment. The figure which shows the example of a structure of the daily operation plan part in 1st Embodiment. The flowchart which shows the example of operation | movement of the daily operation plan part in 1st Embodiment. The figure which shows the example of a display of a daily operation plan in 1st Embodiment. The figure which shows the example of a structure of the energy management system in 2nd Embodiment. The figure which shows the example of a structure of the energy management apparatus in 2nd Embodiment. The figure which shows the example of a structure of the performance evaluation part in 2nd Embodiment. The flowchart which shows the example of operation | movement of the annual driving | operation plan part in 2nd Embodiment. The figure which shows the example of a structure of DR calculating part in 2nd Embodiment. The flowchart which shows the example of operation | movement of the daily operation plan part in 2nd Embodiment. The figure which shows the example of a structure of the energy management system in 3rd Embodiment. The figure which shows the example of a structure of the energy management apparatus in 3rd Embodiment. The figure which shows the example of a display of energy distribution in 3rd Embodiment.

  Hereinafter, an energy management device, an energy management method, and an energy management program according to embodiments will be described with reference to the drawings.

(First embodiment)
FIG. 1 is a diagram illustrating an example of the configuration of the energy management system 1a. The energy management system 1a is a system for managing energy in a consumer group. The energy management system 1 a includes an energy management device 2, an external energy source 3, an energy supply plant 4, and a customer group 5. The internal network 100 is a communication line. The internal network 100 is, for example, an optical fiber or a coaxial cable.

  The energy management device 2 is an information processing device such as a server device. The energy management device 2 is a device for managing the energy of the energy supply device of the energy supply plant 4 so as to match the load of the consumer group 5. The operator of the energy management device 2 is, for example, a building manager, a factory operator, a general householder, a local energy company, a manager, or an operation management consignor.

  The energy management device 2 communicates with the energy supply plant 4 via the internal network 100. The energy management device 2 supplies energy to the customer group 5 via the energy supply plant 4 by controlling the operation of the energy supply plant 4 via the internal network 100. The energy management device 2 may communicate with the customer group 5 via the internal network 100.

  The energy management device 2 may be separate from the energy supply plant 4 or may be integrated with the energy supply plant 4 as an information processing device in a local monitoring room such as a local BEMS or a factory monitoring room. The energy management device 2 may remotely control the energy supply plant 4 by cloud computing technology. For example, the energy management apparatus 2 may execute processing related to district heating and cooling (DHC). For example, the energy management apparatus 2 may be a cloud type BEMS.

  The external energy source 3 is a facility for supplying energy. The external energy source 3 is operated by an external operator different from the operator of the energy management device 2. The external energy source 3 supplies energy to the energy supply plant 4. The energy is, for example, power such as grid power, external power supply power, and market power. The grid power is, for example, power supplied from an electric power company, a power plant, a new power company, market power, an external power supplier, and the like. The energy may be, for example, a fuel such as gas, hydrogen, kerosene, coal, oil and firewood. The gas is supplied from, for example, a gas company.

  The energy supply plant 4 is a facility for supplying energy such as electric power, cold heat, heat, and steam to the consumer group 5 according to the energy supplied from the external energy source 3. Based on the control by the energy management device 2, the energy supply plant 4 supplies energy such as electric power, cold energy, heat, and steam generated using the energy supplied from the external energy source 3 to the consumer group 5. .

  The customer group 5 is a customer 500 in a specific area. The customer group 5 may be a plurality of customers 500 in a specific area. The consumer 500 is a building (building), a factory facility, a building, a house, a hospital facility, a commercial facility, or the like. The customer 500 includes a load. The loads are, for example, an electric load, a cold load, a thermal load, and a steam load. The load of the consumer 500 consumes the energy supplied from the energy supply plant 4.

  The load of the consumer group 5 may consume energy supplied from the energy supply device of the consumer group 5. The energy demand of the consumer group 5 decreases as energy is supplied from the energy supply device of the consumer group 5 to the load of the consumer group 5. That is, the amount of energy that the external energy source 3 supplies to the energy supply plant 4 decreases as energy is supplied from the energy supply device of the consumer group 5 to the load of the consumer group 5.

  In the following, regarding the amount of energy (energy supply amount) that the external energy source 3 supplies to the energy supply plant 4, annual restrictions are imposed on the consumer group 5. The annual constraints are, for example, annual energy production constraints (constraints on the annual primary energy balance) such as ZEB, PEB, and ZEH. The annual restriction may be, for example, an annual gas demand restriction based on a large-scale supply contract between a gas company and a consumer. The annual constraint may be, for example, an annual transaction volume contract with an external power supplier. The annual constraint may be, for example, a constraint related to the operation of the energy supply device.

  FIG. 2 is a diagram illustrating an example of the configuration of the energy management device 2. The energy management device 2 includes a process data acquisition unit 21, a process data storage unit 22, a setting data acquisition unit 23, an acquisition control unit 24, a setting data storage unit 25, a calculation processing unit 26, and a calculation result storage unit. 27.

  Some or all of the process data acquisition unit 21, the process data storage unit 22, the setting data acquisition unit 23, the acquisition control unit 24, and the arithmetic processing unit 26 are stored by a processor such as a CPU (Central Processing Unit), for example. This is a software function unit that functions by executing a program stored in the unit.

  Some or all of the process data acquisition unit 21, the process data storage unit 22, the setting data acquisition unit 23, the acquisition control unit 24, and the arithmetic processing unit 26 are LSI (Large Scale Integration) or ASIC (Application Specific Integrated Circuit). It may be a hardware function unit such as.

  The setting data storage unit 25 and the calculation result storage unit 27 include, for example, a nonvolatile storage medium (non-temporary recording medium) such as a ROM (Read Only Memory), a flash memory, and an HDD (Hard Disk Drive). The setting data storage unit 25 and the calculation result storage unit 27 may include a volatile storage medium such as a RAM or a register, for example.

  The communication unit 20 communicates with the energy supply plant 4 via the internal network 100. For example, the communication unit 20 acquires the process data 220 from the measurement device of the energy supply plant 4 via the internal network 100. The process data 220 is data representing, for example, the remaining energy (measured remaining data), the operation state, the failure state, the remaining fuel amount, and the plant configuration of the energy supply device of the energy supply plant 4. The process data 220 may be data representing an operation record of the energy supply plant 4, for example. The process data 220 may be, for example, data representing the remaining energy amount, operation state, failure state, remaining fuel amount, and plant configuration of the energy supply equipment owned by the customer group 5. The process data 220 may be data representing a record of the energy load of the customer group 5, for example. The communication unit 20 transmits the process data 220 acquired via the internal network 100 to the process data acquisition unit 21.

  The process data acquisition unit 21 acquires process data 220 related to the energy supply plant 4 from the communication unit 20. The process data acquisition unit 21 may acquire process data from the energy supply plant 4 without using the communication unit 20. The process data acquisition unit 21 stores the acquired process data 220 in the process data storage unit 22 in association with the time. The unit of time is 1 hour, for example. The process data storage unit 22 stores the process data 220 in association with the date and time.

  The setting data acquisition unit 23 (data acquisition unit) is an operation unit such as a keyboard, a touch panel, and a mouse. The setting data acquisition unit 23 acquires setting data of the energy supply device of the energy supply plant 4 in response to an operation on the setting data acquisition unit 23. The energy supply device of the energy supply plant 4 is, for example, a storage battery, a cold / hot tank, or a hot / heat tank. The setting data of the energy supply equipment of the energy supply plant 4 is, for example, plant model data 251 and model parameter data 252.

  The plant model data 251 is setting data indicating an aspect of the energy supply plant 4. For example, the plant model data 251 may be data representing the type of energy supply equipment of the energy supply plant 4. For example, the plant model data 251 may be data representing a connection mode of energy supply equipment of the energy supply plant 4. The connection mode is, for example, an energy flow mode or a communication flow mode.

  The model parameter data 252 is setting data indicating details of the energy supply equipment of the energy supply plant 4. For example, the model parameter data 252 may be data representing the maximum output and the minimum output of energy supplied by the energy supply device. For example, the model parameter data 252 may be data representing energy conversion efficiency. The energy conversion efficiency is expressed based on the amount of energy generated by the energy supply device with respect to the amount of energy consumed by the energy supply device of the energy supply plant 4.

  For example, the model parameter data 252 may be data representing an energy unit price. The energy unit price is, for example, a unit price of energy consumed when the energy supply device of the energy supply plant 4 generates energy. The model parameter data 252 may be associated with the date and time. The energy consumed when the energy supply device produces energy is supplied from the external energy source 3. The energy consumed when the energy supply device produces energy is, for example, energy such as electric power, gas, kerosene, coal, oil, natural gas, and soot.

  The model parameter data 252 may be data representing the amount of energy generated according to the weather conditions for a photovoltaic power generation facility (PV: Photo Voltaics) whose energy generation efficiency changes according to the weather conditions. The model parameter data 252 may be data representing the amount of energy that can be stored by the energy supply equipment of the energy supply plant 4.

  The setting data acquisition unit 23 may include a communication interface. The setting data acquisition unit 23 may acquire setting data of the energy supply device of the energy supply plant 4 from the external storage device via the communication interface.

  The acquisition control unit 24 stores the setting data acquired by the setting data acquisition unit 23 in the setting data storage unit 25. The acquisition control unit 24 stores the evaluation period data 250 in the setting data storage unit 25. The evaluation period data 250 is data representing a period (hereinafter referred to as “evaluation period”) for which the arithmetic processing unit 26 creates an operation plan. Evaluation period data 250 further includes data representing the setting contents of annual constraints in the evaluation period. The setting data storage unit 25 stores evaluation period data 250, plant model data 251, and model parameter data 252.

  The arithmetic processing unit 26 acquires the process data 220 from the process data storage unit 22. The arithmetic processing unit 26 acquires evaluation period data 250, plant model data 251, and model parameter data 252 from the setting data storage unit 25. The arithmetic processing unit 26 creates annual constraint coefficient data 270 related to the energy supply plant 4 based on the process data 220, the evaluation period data 250, the plant model data 251, and the model parameter data 252.

  The arithmetic processing unit 26 creates annual demand forecast data 271 in the customer group 5 based on the process data 220, the evaluation period data 250, the plant model data 251, and the model parameter data 252. The annual demand prediction data 271 is data representing a prediction result of annual energy demand (energy consumption) in the customer group 5. The annual demand forecast data 271 is expressed in units of one hour, for example. The arithmetic processing unit 26 creates daily demand forecast data 273 related to the energy supply plant 4 based on the process data 220, the evaluation period data 250, the plant model data 251, and the model parameter data 252.

  The arithmetic processing unit 26 stores the annual constraint coefficient data 270, the annual demand forecast data 271, the annual operation plan data 272, the daily demand forecast data 273, and the daily operation plan data 274 in the calculation result storage unit 27. .

  The arithmetic processing unit 26 includes an annual constraint priority calculation unit 260, an annual demand prediction unit 261, an annual operation planning unit 262, a daily demand prediction unit 263, and a daily operation planning unit 264.

  The annual constraint priority calculation unit 260 (priority determination unit) acquires the evaluation period data 250 from the setting data storage unit 25. The annual constraint priority calculation unit 260 extracts data representing the setting contents of the annual constraint from the evaluation period data 250. The annual constraint priority calculation unit 260 determines the priority of the annual constraint according to a predetermined standard based on the setting content of the annual constraint and the setting content of the objective function. When there are a plurality of annual constraints, the annual constraint priority calculation unit 260 determines a priority for each of the annual constraints.

  The annual constraint priority calculation unit 260 transmits the annual constraint priority to the annual operation planning unit 262. The annual constraint priority calculation unit 260 includes the annual constraint priority in the annual constraint coefficient data 270 and stores it in the calculation result storage unit 27.

  The annual constraint priority calculation unit 260 calculates the priority of the annual constraint for reducing the annual energy cost based on the setting content of the annual constraint and the setting content of the objective function. The priority is expressed by a number representing the priority order. The priority may be expressed by a value representing weighting. The annual constraint priority calculation unit 260 may calculate the priority of the annual constraint for reducing the CO2 emission based on the setting content of the annual constraint and the setting content of the objective function.

  Annual constraints may vary in the ease of achieving the target energy cost. The annual constraint priority calculation unit 260 may give a greater weight to an annual constraint that is difficult to achieve. That is, the annual constraint priority calculation unit 260 may give a larger coefficient corresponding to a larger weight as the annual constraint is difficult to achieve. The annual constraint becomes easier to achieve as the weighting increases. The energy cost increases as the annual constraint weight increases.

  The annual demand prediction unit 261 (long-term prediction unit) acquires the process data 220 from the process data storage unit 22. The annual demand prediction unit 261 predicts the annual energy demand in the customer group 5 based on the process data 220. The annual demand prediction unit 261 transmits the prediction result of the annual energy demand in the customer group 5 to the annual operation planning unit 262. The annual demand prediction unit 261 stores the prediction result of the annual energy demand in the customer group 5 in the calculation result storage unit 27 as the annual demand prediction data 271 in association with the date and time.

  The annual operation planning unit 262 (long-term planning unit) acquires evaluation period data 250, plant model data 251, and model parameter data 252 from the setting data storage unit 25. The annual operation planning unit 262 acquires the annual constraint coefficient data 270 and the annual demand forecast data 271 from the calculation result storage unit 27.

  The annual operation planning unit 262 creates an annual operation plan for the energy supply plant 4 based on the evaluation period data 250, the plant model data 251, the model parameter data 252, the annual constraint coefficient data 270, and the annual demand prediction data 271. For example, the annual operation plan unit 262 creates an annual operation plan for the energy supply plant 4 by minimizing the energy cost within a range that satisfies a plurality of constraints such as an annual fuel constraint and an operation constraint for the energy supply plant 4. For example, the energy cost of power is an amount based on the result of multiplying the power demand by the power unit price. For example, the energy cost of gas is an amount based on the result of multiplying the gas demand by the gas unit price. The annual operation planning unit 262 minimizes the energy cost based on a mathematical programming method or a heuristic method.

  Based on the annual operation plan of the energy supply plant 4, the annual operation plan unit 262 determines a coefficient relating to constraints such as annual energy demand and operation (hereinafter referred to as “annual constraint coefficient”). The annual operation plan unit 262 creates an annual operation plan by determining an annual constraint coefficient. As the annual constraint factor increases, more energy is used. For example, as the annual constraint factor of gas increases, more gas is used.

  The annual operation planning unit 262 includes the annual constraint coefficient in the annual constraint coefficient data 270 and causes the calculation result storage unit 27 to store it. Therefore, the annual constraint coefficient data 270 includes the priority of the annual constraint created by the annual constraint priority calculation unit 260 and the annual constraint coefficient created by the annual operation planning unit 262.

  The annual operation plan unit 262 stores data representing the annual operation plan of the energy supply plant 4 in the calculation result storage unit 27 as the annual operation plan data 272. That is, the annual operation plan data 272 is data representing an annual operation plan of the energy supply equipment of the energy supply plant 4. The annual operation plan data 272 indicates, for example, an annual operation plan for the energy supply equipment of the energy supply plant 4 in units of one hour. The energy supply device is a device that supplies energy to a load. The energy supply device is, for example, a storage battery, a water-cooled chiller, an absorption refrigerator (ABR), a co-generation system (CGS).

  The daily demand prediction unit 263 (short-term prediction unit) acquires the process data 220 from the process data storage unit 22. The daily demand prediction unit 263 predicts the daily energy demand in the customer group 5 based on the process data 220. The daily demand prediction unit 263 transmits the prediction result of the daily energy demand in the customer group 5 to the daily operation planning unit 264.

  The daily demand prediction unit 263 stores the prediction result of the daily energy demand in the customer group 5 in the calculation result storage unit 27 as the daily demand prediction data 273 in association with the date and time. That is, the daily demand forecast data 273 is data representing the forecast result of the daily energy demand in the consumer group 5. The daily demand forecast data 273 is expressed in units of one hour, for example.

  The daily operation planning unit 264 (short-term planning unit) acquires evaluation period data 250, plant model data 251, and model parameter data 252 from the setting data storage unit 25. The daily operation planning unit 264 acquires the annual constraint coefficient data 270 and the daily demand prediction data 273 from the calculation result storage unit 27.

  The daily operation plan unit 264 creates a daily operation plan for the energy supply plant 4 based on the evaluation period data 250, the plant model data 251, the model parameter data 252, the annual constraint coefficient data 270, and the daily demand prediction data 273. For example, the daily operation plan unit 264 creates a daily operation plan for the energy supply plant 4 by minimizing the energy cost within a range that satisfies a plurality of constraints such as annual fuel constraints and operation constraints of the energy supply plant 4. The daily operation planning unit 264 minimizes the energy cost based on a mathematical programming method or a heuristic method.

  The daily operation planning unit 264 determines an operation plan for the energy supply device in a short period within a range that satisfies a plurality of predetermined constraints for a long period of time. The daily operation planning unit 264 determines an operation plan for the energy supply device in a short period included in the evaluation period.

  The daily operation plan unit 264 stores the daily operation plan of the energy supply plant 4 in the calculation result storage unit 27 as the daily operation plan data 274. That is, the daily operation plan data 274 is data representing a daily operation plan of the energy supply equipment of the energy supply plant 4. The daily operation plan data 274 is expressed in units of one hour, for example.

  The calculation result storage unit 27 stores annual constraint coefficient data 270, annual demand prediction data 271, annual operation plan data 272, daily demand prediction data 273, and daily operation plan data 274.

  FIG. 3 is a diagram illustrating an example of the configuration of the external energy source 3, the energy supply plant 4, and the customer group 5. In FIG. 3, the external energy source 3 includes an electric power company 30, a new electric power company (PPS: Power Producer and Supplier) 31, an electric power market 32, a gas company 33, and a fuel company 34.

  The device of the electric power company 30 supplies system power to the energy supply plant 4. The apparatus of the new electric power company 31 supplies power from the external power source to the energy supply plant 4. Devices such as the power market 32 supply power to the energy supply plant 4. The apparatus of the gas company 33 supplies gas to the energy supply plant 4. The gas is supplied to the gas tank of the energy supply plant 4 by, for example, a gas pipeline or a tank truck, and the device of the fuel company 34 supplies the fuel to the energy supply plant 4.

  The energy supply plant 4 includes a power receiving facility 400, a PV 401 (solar power generation facility), a storage battery 402, a water-cooled chiller 403, an air-cooled HP chiller 404 (Heat-Pomp, a heat pump), a heat recovery HP chiller 405, and a CGS 406. And a boiler 407, an ABR 408, a cooling / heating tank 409, and a heating / heating tank 410 are provided as energy supply devices.

  The power receiving facility 400 acquires system power from the device of the power company 30. The power receiving facility 400 converts the system power voltage into a voltage suitable for the energy supply plant 4. The power receiving facility 400 acquires the power of the external power source from the device of the new power company 31. The power receiving facility 400 converts the power voltage of the external power source into a voltage suitable for the energy supply plant 4. The power receiving facility 400 acquires power from devices in the power market 32. The power receiving facility 400 converts the acquired power voltage into a voltage suitable for the energy supply plant 4. The power receiving facility 400 supplies power to the storage battery 402, the water-cooled chiller 403, the air-cooled HP chiller 404, the heat recovery HP chiller 405, and the customer 500.

  PV 401 is a power generation facility. PV401 is provided with a solar panel. Solar panels convert sunlight into electrical energy. The amount of power generated by the PV 401 changes according to weather conditions such as the weather. The PV 401 supplies power to the storage battery 402 and the customer 500.

  The storage battery 402 is a secondary battery. The storage battery 402 is charged or discharged. The storage battery 402 supplies power to the consumer 500. The water-cooled chiller 403 generates cold water by changing the phase of the refrigerant using water as a heat source. The water-cooled chiller 403 supplies cold water to the cold heat tank 409 and the customer 500.

  The air-cooled HP chiller 404 generates cold water or hot water by changing the phase of the refrigerant using air as a heat source. The air-cooled HP chiller 404 supplies cold water or hot water (cold heat) to the cold heat tank 409 and the customer 500. The heat recovery HP chiller 405 generates cold water or hot water by changing the phase of the refrigerant using water or air as a heat source. The heat recovery HP chiller 405 supplies cold water or hot water (cold heat) to the cold heat tank 409 and the customer 500.

  The CGS 406 includes an internal combustion engine or an external combustion engine. The CGS 406 generates power with an internal combustion engine or an external combustion engine. The CGS 406 supplies exhaust heat as hot heat to the ABR 408, the hot water tank 410, and the customer 500. The boiler 407 supplies heat or steam to the ABR 408, the heat tank 410, and the customer 500 using gas as an energy source.

  The ABR 408 generates water vapor absorption and a steam regeneration process by a heat source between the refrigerant condenser and the evaporator. The ABR 408 may use gas as an energy source or biomass fuel as an energy source. The ABR 408 supplies cold water to the cold heat tank 409 and the customer 500.

  The cold heat tank 409 is, for example, a water heat storage tank, an ice heat storage tank, or a latent heat storage tank. The cold heat tank 409 stores heat using the stored heat medium. The hot water tank 410 is, for example, a water heat storage tank. The hot water tank 410 stores heat using the stored heat medium.

  The consumer 500 of the consumer group 5 includes an electric power load 501, a cold load 502, a thermal load 503, and a steam load 504. The power load 501 acquires power from the energy supply device of the energy supply plant 4. The cold load 502 acquires cold from the energy supply device of the energy supply plant 4 using water as a medium. The heat load 503 acquires heat from the energy supply device of the energy supply plant 4 using water as a medium. The steam load 504 acquires steam from the energy supply equipment of the energy supply plant 4.

  FIG. 4 is a flowchart showing an example of the operation of the energy management device 2. The energy management device 2 may periodically perform the operation shown in FIG. For example, the energy management apparatus 2 may execute the operations from step S104 to step S107 shown in FIG. 4 every month. For example, the energy management apparatus 2 may execute the operations from step S106 to step S107 shown in FIG. 4 every day.

  The arithmetic processing unit 26 of the energy management device 2 acquires process data from the process data storage unit 22. The arithmetic processing unit 26 of the energy management device 2 acquires the evaluation period data 250, the plant model data 251 and the model parameter data 252 from the setting data storage unit 25 (step S101).

  The annual demand prediction unit 261 predicts the annual energy demand in the customer group 5. For example, the annual demand prediction unit 261 predicts the annual energy demand in the customer group 5 on the assumption that the average value of the monthly energy demand in the past year lasts for one year.

  For example, the annual demand forecasting unit 261 calculates the actual value or the average value of the energy demand for the most recent N days (N is an integer of 1 or more) by the moving average method, the weighted moving average method, the exponential smoothing method, or the like. The annual energy demand in the consumer group 5 may be predicted by calculating every hour. For example, the annual demand prediction unit 261 may predict the annual energy demand in the customer group 5 based on the daily demand prediction data 273 calculated in Step S106 (Step S102).

  The annual operation planning unit 262 creates an annual operation plan for the energy supply plant 4 based on the evaluation period data 250, the plant model data 251, the model parameter data 252, the annual constraint coefficient data 270, and the annual demand prediction data 271 ( Step S103).

  The annual demand prediction unit 261 creates updated annual demand prediction data 271 by updating the prediction result of the annual energy demand in the customer group 5 every month. For example, the annual demand forecasting unit 261 may create the updated annual demand forecast data 271 using the same method as in Step S102 (Step S104).

  The annual operation plan unit 262 updates the annual operation plan of the energy supply plant 4 based on the updated annual demand prediction data 271. For example, the annual operation plan unit 262 may update the annual operation plan of the energy supply plant 4 using the same method as in step S103 (step S105).

  The daily demand prediction unit 263 creates the daily demand prediction data 273 by predicting the daily energy demand in the customer group 5 every day based on the process data 220. For example, the daily demand prediction unit 263 may create the daily demand prediction data 273 using the same method as in step S102. For example, the daily demand prediction unit 263 may extract data of energy demand on a day similar to the evaluation target date from the history data of energy demand on the customer 500. The daily demand prediction unit 263 may create the daily demand prediction data 273 by applying pattern matching to the history data of the energy demand on the extracted day for each hour (step S106).

  The daily operation plan unit 264 creates a daily operation plan for the energy supply plant 4 based on the annual constraint coefficient data 270 and the daily demand forecast data 273 (step S107).

Next, creation of an annual operation plan for minimizing energy costs will be described.
The energy load in the consumer 500 of the consumer group 5 is an electric power load, a cold load, a thermal load, and a steam load. Hereinafter, the subscript representing the power load is e. A subscript representing the cooling load is C. The suffix indicating the thermal load is H. The subscript representing the steam load is S.

  The energy supplied by the external energy source 3 is system power, power from an external power source, gas, and fuel such as kerosene. Hereinafter, the superscript indicating the system power is G. The subscript indicating the system power is e. The superscript indicating the power of the external power supply is out. The subscript representing gas is g. The subscript representing the fuel is o.

Hereinafter, the objective function of the operation plan is a function aiming at minimizing the energy cost. The objective function of the operation plan may be a function aimed at minimizing CO2 emission. An upper limit and a lower limit are set in the annual procurement amount restriction of the electric power of the external power source which is one of the annual restrictions. An upper limit and a lower limit are set in the annual supply amount restriction of gas, which is one of the annual restrictions. Time ^{t d} represents the time t in the day d. The time t ^d and date d and time t, all of which are discrete values. Time t ^d may be a continuous value. If the time t ^d is a continuous value, sigma in equation (sum) may be read as ∫ (integration). The configuration of the external energy source may be different from the configuration shown in FIG. The number of annual constraints may be arbitrary.

  The annual operation planning unit 262 calculates an expression (1) representing an objective function for minimizing the energy cost in step S103 shown in FIG. Expression (1) is an annual integrated value. The annual operation plan unit 262 creates an annual operation plan based on the formula (1).

  Here, the equations (2) to (16) hold. Expression (2) is an annual integrated value, and is a conditional expression that represents the annual external power demand restriction. Expression (3) is an annual integrated value, and is a conditional expression representing the annual gas demand constraint. Expression (4) is a conditional expression representing the power supply / demand balance. Expression (5) is a conditional expression that represents the cold supply and demand balance. Expression (6) is a conditional expression that represents a supply and demand balance of heat. Expression (7) is a conditional expression representing the supply and demand balance of steam. Expression (8) is a conditional expression representing the remaining amount of energy in a device that accumulates energy (hereinafter referred to as “energy storage device”). The energy storage device is, for example, the storage battery 402, the cold / heat tank 409, and the warm / heat tank 410. Expression (9) is a conditional expression representing the gas demand. Expression (10) is a conditional expression representing the fuel demand. Expression (11) is a conditional expression that represents the electric heat output of the CGS 406. Expression (12) is a conditional expression representing the cold output of the ABR 408. Expression (13) is a conditional expression representing the heat source output of the power supply device. Expression (14) is a conditional expression representing the heat output of the boiler 407. Expression (15) is a conditional expression representing a capacity constraint in the energy storage device. Expression (16) is a conditional expression representing a constraint determined by the upper limit output and the lower limit output of each energy supply device. Expressions (4) to (16) represent constraint conditions at each time.

  The description of each symbol in the formulas (1) to (16) is as follows.

Next, relaxation of a plurality of constraints such as annual constraints in the annual operation plan will be described.
When the concept of Lagrangian relaxation is applied to formulas (2) and (3), formulas (17) to (19) are obtained based on formulas (1) to (16). Equation (17) represents an objective function for minimizing the annual energy cost when the constraints are relaxed.

  Here, in the equations (4) to (16), the equations (18) and (19) are established. Expression (18) is a conditional expression representing an annual external power supply restriction coefficient. The annual external power supply restriction coefficient is a restriction coefficient related to the power of the external power supply during the year. Expression (19) is a conditional expression representing an annual constraint coefficient of gas.

Here, γ ₁ represents an annual constraint coefficient related to the power of the external power supply. γ ₂ represents the annual constraint coefficient for gas. The annual constraint coefficient γ is in an arbitrary range as shown in Equation (18) when the annual constraint is determined by the upper limit value and the lower limit value. When the annual constraint is determined by the lower limit value, the annual constraint coefficient γ is (γ ≧ 0) as shown in Expression (19). The annual constraint coefficient γ is (γ ≦ 0) when the annual constraint is determined by the upper limit value.

Hereinafter, the result of subtracting the coefficient from the energy unit price is referred to as “virtual energy unit price”. Hereinafter, the result of subtracting the annual constraint coefficient γ ₁ from the energy unit price P _e ^out (t ^d ) of the power of the external power source is referred to as “virtual energy unit price of the power of the external power source”. The virtual energy unit price (= energy unit price P _e ^out (t ^d ) −γ ₁ ) of the power of the external power source decreases as the annual constraint coefficient γ ₁ related to the power of the external power source increases. As a result, the amount of power demand from the external power source increases as the annual constraint coefficient γ ₁ related to the power from the external power source increases.

Hereinafter, the result of subtracting the annual constraint coefficient γ ₂ from the gas energy unit price P _g (t ^d ) is referred to as “virtual energy unit price of gas”. The virtual energy unit price of gas (= gas energy unit price P _g (t ^d ) −γ ₂ ) decreases as the annual constraint coefficient γ ₂ related to gas increases. Thereby, the demand amount of gas increases, so that the annual constraint coefficient (gamma) ₂ regarding gas becomes large.

  Equation (17) differs from equation (1) in that it includes the virtual energy unit price of the external power supply instead of the energy unit price of the external power supply. Equation (17) differs from equation (1) in that it includes the virtual energy unit price of gas instead of the energy unit cost of gas.

  The constraint condition of Expression (17) is only the constraint condition based on the unit price of virtual energy at each time because Expressions (2) and (3) representing the annual constraint are excluded from the constraint condition of Expression (17). . As a result, the daily operation plan unit 264 can create a daily operation plan that satisfies the annual constraints.

Next, relaxation of a plurality of constraints in the daily operation plan will be described.
Equation (20) represents an objective function for minimizing the daily energy cost when the constraints are relaxed.

  Here, the equations (4) to (16), (18), and (19) hold. The annual constraint may not be a constraint condition determined based on gas or fuel. For example, the annual constraint may be a composite annual constraint. The combined annual constraint is, for example, an annual constraint (annual energy production constraint) in ZEB.

  FIG. 5 is a diagram illustrating an example of the configuration of the annual operation planning unit 262. The annual operation plan unit 262 includes an annual constraint coefficient initialization unit 2620, a convergence determination unit 2621, and an annual constraint coefficient update unit 2622. The annual constraint coefficient initialization unit 2620 initializes the annual constraint coefficient.

  The daily operation planning unit 264 acquires the initialized annual constraint coefficient from the annual constraint coefficient initialization unit 2620. The daily operation planning unit 264 acquires the updated annual constraint coefficient from the annual constraint coefficient update unit 2622. The daily operation planning unit 264 creates a daily operation plan of the energy supply plant 4 based on the searched annual constraint coefficient by searching for an annual constraint coefficient that minimizes the energy cost. The daily operation plan unit 264 creates a daily operation plan for the energy supply plant 4 for one year based on the converged annual constraint coefficient.

  The convergence determination unit 2621 determines whether or not the annual constraint coefficient has converged in the process of searching for the annual constraint coefficient. When the annual constraint coefficient converges, the convergence determination unit 2621 transmits the converged annual constraint coefficient to the annual constraint priority calculation unit 260.

  The annual constraint priority calculation unit 260 calculates the priority of the annual constraint based on the setting content of the annual constraint and the setting content of the objective function. The annual constraint priority calculation unit 260 transmits the priority of the annual constraint to the annual constraint coefficient update unit 2622.

  The annual constraint coefficient update unit 2622 updates the annual constraint coefficient. The annual constraint coefficient update unit 2622 transmits the annual constraint coefficient data 270 including the updated annual constraint coefficient to the daily operation planning unit 264.

FIG. 6 is a flowchart illustrating an example of the operation (step S103) of the annual operation planning unit 262. When the annual operation plan unit 262 creates an annual operation plan (step S103), the annual constraint coefficient initialization unit 2620 of the annual operation plan unit 262 initializes the annual constraint coefficient data 270. For example, the annual constraint coefficient initialization unit 2620 initializes the annual constraint coefficient data 270 with the annual constraint coefficient γ _i ⁰ included in the model parameter data 252 (step S201).

  When the annual constraint coefficient data 270 is not updated, the daily operation plan unit 264 sets the daily operation plan of the energy supply plant 4 for one year based on the initialized annual constraint coefficient data 270 and the annual demand forecast data 271. Create about. When the annual constraint coefficient data 270 is updated, the daily operation plan unit 264 sets the daily operation plan of the energy supply plant 4 for one year based on the updated annual constraint coefficient data 270 and the annual demand prediction data 271. Create (step S107).

  The convergence determination unit 2621 determines whether or not the annual constraint coefficient has converged. For example, the convergence determination unit 2621 satisfies the formula (21) representing the absolute error and the formulas (2) and (3) representing the annual constraint based on the setting contents of the annual constraint included in the evaluation period data 250. It is determined whether or not.

Here, γ _i ^k represents the update value of the k-th annual constraint coefficient related to the annual constraint i. ε _i is a positive constant value related to the annual constraint coefficient of the annual constraint i (step S202).

When the annual constraint coefficient has not converged (step S202: NO), the annual constraint priority calculation unit 260 calculates the priority of the annual constraint based on the setting content of the annual constraint and the setting content of the objective function. For example, the annual constraint priority calculation unit 260 sets the priority of the annual constraint to a value equal to the weighting value w _i determined in advance for the annual constraint i. For example, the annual constraint priority calculation unit 260 may calculate Expression (22) and Expression (23) based on the margin (upper limit and lower limit) of the annual constraint. Expression (22) represents the priority (weighted value) of the annual constraint i regarding the power of the external power supply. Formula (23) represents the priority (weighting value) of the annual constraint i regarding gas. E _g in equation (23) is the lower limit of the constraint value. Therefore, Formula (23) represents the difference between the lower limit of the constraint value and the gas demand (step S203).

  The annual constraint coefficient update unit 2622 updates the annual constraint coefficient based on the priority of the annual constraint. For example, the annual constraint coefficient update unit 2622 updates the annual constraint coefficient by executing a bisection method or a gradient method for each variable of the energy cost.

  FIG. 7 is a diagram illustrating the update of the annual constraint coefficient for each energy type. The horizontal axis indicates the energy type. The vertical axis represents energy demand. The annual constraint coefficient update unit 2622 may preferentially update the annual constraint coefficient of the annual constraint having a high priority. In FIG. 7, the annual constraint coefficient updating unit 2622 updates the annual constraint coefficient related to electric power with priority over the annual constraint coefficient related to gas.

  The annual constraint coefficient update unit 2622 may update the annual constraint coefficient of the annual constraint to a greater extent as the energy demand is away from the annual constraint. As a result, even when a plurality of annual constraints are satisfied, the daily operation planning unit 264 shortens the convergence of the calculation result based on the updated annual constraint coefficient γ and performs a short time search without exhaustive search for the annual constraint coefficient γ. A daily operation plan can be created by calculating The annual operation plan unit 262 can make the calculation result converge quickly based on the updated annual constraint coefficient γ, and can create an annual operation plan in a short time without searching for the exhaustive number of the annual constraint coefficient γ. .

In FIG. 7, dots 300 to 330 indicate energy demands according to the annual constraint coefficient γ ₁ related to power. In FIG. 7, the dot 300 indicates the energy demand corresponding to the initial value of the annual constraint coefficient γ ₁ related to power. The dot 330 indicates the optimal solution of the annual demand energy demand.

In FIG. 7, the dot position indicating the energy demand changes in the order of dots 300 to 330 every time the annual constraint coefficient update unit 2622 updates the annual constraint coefficient γ ₁ related to power. The interval between the dot 300 and the dot 310 is longer than the interval between the dot 310 and the dot 320 because the position of the dot 300 is far from the optimal solution of the annual demand energy demand. The distance between the dots 310 and 320 is longer than the distance between the dots 320 and 330 because the position of the dots 310 is away from the position of the optimal solution.

FIG. 8 is a diagram illustrating the update of the annual constraint coefficient. The horizontal axis represents the annual constraint coefficient γ ₁ for power. The vertical axis represents the annual constraint coefficient γ ₂ for gas. The constraint range 340 indicates a range where the annual constraint is satisfied. The dots 350 to 380 are dots indicating an annual restriction coefficient γ ₁ and an annual restriction coefficient γ ₂ . In FIG. 8, the position of the dot 350 indicates the position corresponding to the initial value of the annual constraint coefficient γ _{1 and} the initial value of the annual constraint coefficient γ ₂ . The position of the dot 380 indicates the annual constraint coefficient γ ₁ and the annual constraint coefficient γ ₂ corresponding to the optimal solution of the energy demand of the annual constraint.

In FIG. 8, the dot position changes in the order of dots 350 to 380 every time the annual constraint coefficient update unit 2622 updates the annual constraint coefficient γ ₁ and the annual constraint coefficient number γ ₂ . The interval between the dot 350 and the dot 360 is longer than the interval between the dot 360 and the dot 370 because the position of the dot 350 is far from the optimal solution of the annual demand energy demand. The distance between the dot 360 and the dot 370 is longer than the distance between the dot 360 and the dot 370 because the position of the dot 360 is away from the position of the optimum solution.

  The annual constraint coefficient update unit 2622 may update the annual constraint coefficient based on the priority (weighted value) of the annual constraint and the equation (24). Expression (24) represents a first update example of the annual constraint coefficient.

  In the formula (24), a is a constant. The annual constraint coefficient updating unit 2622 may update the annual constraint coefficient based on the priority (weighted value) of the annual constraint and the equation (25). Equation (25) represents a second update example of the annual constraint coefficient.

  In formula (25), b and c are constants. The annual constraint coefficient update unit 2622 may update the annual constraint coefficient based on the priority (weighted value) of the annual constraint and the equation (26).

  Equation (26) represents a third update example of the annual constraint coefficient (step S204). The annual constraint coefficient update unit 2622 returns the process to step S107.

  When the annual constraint coefficient converges (step S202: YES), the annual constraint priority calculation unit 260 transmits the converged annual constraint coefficient and the annual operation plan data 272 to the annual constraint priority calculation unit 260 (step S205). ).

FIG. 9 is a diagram illustrating an example of display of an annual operation plan. The graph representing the annual operation plan may be displayed on the display device. The horizontal axis in the lower part of FIG. 9 shows the annual constraint coefficient γ ₂ of gas. The horizontal axis in the lower part of FIG. 9 may indicate an annual constraint coefficient γ ₁ of power. The vertical axis in the lower part of FIG. 9 indicates the annual energy cost. The annual energy cost may decrease as the gas annual constraint factor increases. The horizontal axis in the middle of FIG. 9 shows the annual constraint coefficient γ ₂ of gas. The vertical axis in the middle of FIG. 9 shows the annual gas demand. The annual gas demand increases as the annual constraint factor of gas increases. The horizontal axis in the upper part of FIG. 9 shows the annual constraint coefficient γ ₂ of gas. The vertical axis in the upper part of FIG. 9 indicates the annual demand amount of the external power supply. The annual power demand of the external power source decreases as the annual constraint factor of the gas increases.

  The annual constraint priority calculation unit 260 calculates an annual constraint coefficient γ (optimal solution) that minimizes the annual energy cost within a range that satisfies the annual constraint on the power of the external power source and the annual constraint on the gas. Even when a plurality of annual constraints are satisfied, the annual constraint priority calculation unit 260 accelerates the convergence of the calculation result based on the annual constraint coefficient γ, and the energy can be calculated in a short time without performing an exhaustive search for the annual constraint coefficient γ. Cost can be reduced.

  FIG. 10 is a diagram illustrating an example of the configuration of the daily operation planning unit 264. The daily operation plan unit 264 includes an annual constraint coefficient acquisition unit 2640, a power supply device operation plan unit 2641, a cold heat source device operation plan unit 2642, a heat source device operation plan unit 2643, a steam heat source device operation plan unit 2644, And an energy storage equipment operation planning unit 2645.

  The annual constraint coefficient acquisition unit 2640 acquires the annual constraint coefficient data 270 that is initialized by the annual constraint coefficient initialization unit 2620 of the annual operation planning unit 262. The power equipment operation planning unit 2641 creates a power equipment operation plan based on the annual restriction coefficient γ included in the annual restriction coefficient data 270. The power supply device is, for example, a cogeneration system that can generate power.

  The cold heat source equipment operation planning unit 2642 creates a cold heat source equipment operation plan such as the water-cooled chiller 403 based on the annual constraint coefficient γ. The heat source equipment operation plan unit 2643 creates an operation plan for heat source equipment such as the air-cooled HP chiller 404, the heat recovery HP chiller 405, the boiler 407, and the CGS 406 based on the annual constraint coefficient γ. The steam heat source equipment operation planning unit 2644 creates an operation plan for the steam heat source equipment based on the annual constraint coefficient γ. The energy storage equipment operation plan unit 2645 creates an operation plan for the energy storage equipment.

FIG. 11 is a flowchart showing an example of the operation (step S107) of the daily operation planning unit 264. When the daily operation plan unit 264 creates a daily operation plan (step S107), the annual constraint coefficient acquisition unit 2640 of the daily operation plan unit 264 acquires the annual constraint coefficient. For example, the annual constraint coefficient acquisition unit 2640 acquires the annual constraint coefficient data 270 with the annual constraint coefficient γ _i ⁰ included in the model parameter data 252 (step S301).

  The power supply device operation planning unit 2641 is based on the annual constraint coefficient included in the annual constraint coefficient data 270 and the daily demand forecast data 273, and the day of the hour unit in the power supply equipment such as the power receiving equipment 400, the PV 401, and the storage battery 402. Create an operation plan.

  For example, the power device operation planning unit 2641 calculates a marginal cost. The marginal cost is a unit price required to supply a unit amount of energy to the energy supply device. The unit price required to supply the unit amount of energy to the energy supply device is determined based on the result of dividing the unit price of the supplied energy by the energy conversion efficiency. The energy conversion efficiency is determined based on input / output characteristics of an energy supply device for which an operation plan is to be created. The power equipment operation planning unit 2641 determines the priority of the power equipment operation based on the marginal cost.

  For example, the power supply device operation plan unit 2641 may create an operation plan for preferentially operating a power supply device having high energy conversion efficiency. For example, the power supply device operation planning unit 2641 may create an operation plan for preferentially operating a power supply device with a low energy unit price. The power supply device operation planning unit 2641 creates a daily operation plan for the hourly unit of the power supply device based on the determined priority order so as to supply an amount of energy that satisfies the energy demand of the consumer 500 (step S302). ).

  The cold heat source equipment operation planning unit 2642 creates a daily operation plan for each hour of the cold heat source equipment based on the annual restriction coefficient included in the annual restriction coefficient data 270 and the daily demand prediction data 273. The cold heat source equipment operation planning unit 2642 determines the priority order of the operation of the cold heat source equipment based on the marginal cost.

  For example, the cold heat source equipment operation planning unit 2642 may create an operation plan for preferentially operating the cold heat source equipment having high energy conversion efficiency. For example, the cold heat source equipment operation plan unit 2642 may create an operation plan for preferentially operating the cold heat source equipment having a low energy unit price. The cold heat source equipment operation planning unit 2642 creates a daily operation plan for each hour of the cold heat source equipment based on the predetermined priority order so as to supply an amount of energy that satisfies the energy demand of the customer 500 (step). S303).

  Based on the annual constraint coefficient included in the annual constraint coefficient data 270 and the daily demand forecast data 273, the heat source equipment operation planning unit 2643 creates a daily operation plan for each hour of the cold heat source equipment. The heat source equipment operation planning unit 2643 determines the priority of the operation of the heat source equipment based on the limit cost.

  For example, the heat source equipment operation planning unit 2643 may create an operation plan for preferentially operating a heat source equipment having high energy conversion efficiency. For example, the heat source equipment operation planning unit 2643 may create an operation plan for preferentially operating a heat source equipment with a low energy unit price. The heat source equipment operation planning unit 2643 creates a daily operation plan for each hour of the heat source equipment based on the predetermined priority order so as to supply an amount of energy that satisfies the energy demand of the customer 500 (step) S304).

  The steam heat source equipment operation planning unit 2644 creates a daily operation plan for each hour of the steam heat source equipment based on the annual restriction coefficient included in the annual restriction coefficient data 270 and the daily demand prediction data 273. The steam heat source equipment operation planning unit 2644 determines the priority of the operation of the steam heat source equipment based on the marginal cost.

  For example, the steam heat source equipment operation planning unit 2644 may create an operation plan for preferentially operating steam heat source equipment with high energy conversion efficiency. For example, the steam heat source equipment operation planning unit 2644 may create an operation plan for preferentially operating steam heat source equipment with a low energy unit price. The steam heat source equipment operation planning unit 2644 creates an hourly daily operation plan of the steam heat source equipment based on the predetermined priority order so as to supply an amount of energy that satisfies the energy demand of the consumer 500 (step S305).

  The power device operation planning unit 2641 calculates the energy demand (energy consumption amount) of each power device. The power supply device operation planning unit 2641 may calculate the amount of received system power for each power supply device based on the balance of energy supply and demand of each power supply device. The cold heat source equipment operation planning unit 2642 calculates the energy demand of each cold heat source equipment. The cold heat source equipment operation planning unit 2642 may calculate the amount of power received by the system power for each cold heat source equipment based on the balance of energy supply and demand of each cold heat source equipment. The heat source equipment operation planning unit 2643 calculates the energy demand of each heat source equipment. The heat source device operation planning unit 2643 may calculate the amount of power received by the system power for each heat source device based on the balance of energy supply and demand of each heat source device. The steam heat source device operation planning unit 2644 calculates the energy demand of the steam heat source device (step S306-1).

  The energy storage equipment operation plan unit 2645 creates an operation plan for the energy storage equipment. For example, the energy storage device operation planning unit 2645 creates an operation plan for storing or releasing heat so that the energy cost can be further reduced based on the limit cost of the energy storage device and the energy conversion efficiency ( Step S307).

  The power device operation planning unit 2641 calculates the energy demand (energy consumption amount) of each power device. The power supply device operation planning unit 2641 may calculate the amount of received system power for each power supply device based on the balance of energy supply and demand of each power supply device. The cold heat source equipment operation planning unit 2642 calculates the energy demand of each cold heat source equipment. The cold heat source equipment operation planning unit 2642 may calculate the amount of power received by the system power for each cold heat source equipment based on the balance of energy supply and demand of each cold heat source equipment. The heat source equipment operation planning unit 2643 calculates the energy demand of each heat source equipment. The heat source device operation planning unit 2643 may calculate the amount of power received by the system power for each heat source device based on the balance of energy supply and demand of each heat source device. The steam heat source device operation planning unit 2644 calculates the energy demand of the steam heat source device (step S306-2).

  The power supply device operation planning unit 2641 transmits the daily operation plan data 274 of the power supply device to the annual operation plan unit 262. The cold heat source device operation planning unit 2642 transmits the daily operation plan data 274 of the cold heat source device to the annual operation plan unit 262. The heat source device operation planning unit 2643 transmits the daily operation plan data 274 of the heat source device to the annual operation plan unit 262. The steam heat source equipment operation planning unit 2644 transmits the daily operation plan data 274 of the steam heat source equipment to the annual operation planning unit 262 (step S308).

  FIG. 12 is a diagram illustrating a display example of the daily operation plan. A graph representing the daily operation plan is displayed on the display device. Each horizontal axis of the graph shown in FIG. 12 indicates time. The vertical axis | shaft of the graph shown in the upper stage of FIG. 12 shows electric power energy. The upper part of FIG. 12 represents a daily operation plan for energy supply equipment such as the storage battery 402 to supply energy to the customer 500. The graph shown in the upper part of FIG. 12 represents a daily operation plan for the external power source of the external energy source 3 to supply energy to the customer 500. The graph shown in the upper part of FIG. 12 represents the supply and demand balance in the customer 500. That is, the graph shown in the upper part of FIG. 12 shows the energy demand amount (total power load) of the customer 500, the energy supply amount of the energy supply device of the energy supply plant 4, the grid power of the external energy source 3, and This represents the balance with the amount of energy supplied by the external power supply.

  The vertical axis | shaft of the graph shown in the middle stage of FIG. 12 shows cold energy. The middle part of FIG. 12 represents a daily operation plan for energy supply equipment such as the water-cooled chiller 403 to supply energy to the customer 500. The graph shown in the middle part of FIG. 12 represents a daily operation plan for the ABR 408 to supply energy to the customer 500. The graph shown in the middle part of FIG. 12 represents the supply and demand balance in the customer 500. That is, the graph shown in the middle part of FIG. 12 represents the balance between the cold energy demand (total cold load), the energy supply amount of the water-cooled chiller 403, and the energy supply amount of the ABR 408 for the customer 500. The vertical axis of the graph shown in the lower part of FIG. 12 indicates the energy unit price. The lower part of FIG. 12 represents the daily operation plan regarding the energy unit price for the grid power, the external power source, and the gas.

  The daily operation plan unit 264 creates a daily operation plan for preferentially supplying the power from the external power source to the customer 500 in a time zone where the energy unit price of the external power source is lower than the energy unit price of the system power.

  For power energy, the daily operation plan unit 264 creates a daily operation plan for storing the power of the external power source in a time zone where the energy unit price of the power of the external power source is low. The daily operation plan unit 264 creates a daily operation plan for discharging from the storage battery 402 to the customer 500 in a time zone in which the energy demand in the customer 500 exceeds the upper limit of the power energy (kWh) of the external power source. Thereby, the daily operation planning unit 264 can reduce the energy cost.

  Regarding the cold energy, the daily operation planning unit 264 prioritizes the ABR 408 driven using gas over the water-cooled chiller 403 driven using electric power in a time zone in which the energy unit price of electric power is higher than the energy unit price of gas. Then, a daily operation plan for operating the ABR 408 is created. The unit price of gas energy may be constant throughout the day.

  As described above, the energy management apparatus 2 according to the first embodiment includes the annual demand prediction unit 261, the annual operation planning unit 262, the daily demand prediction unit 263, and the daily operation planning unit 264. The annual demand prediction unit 261 predicts an energy demand amount of a load to which energy is supplied from the energy supply device over a predetermined long period. The long-term load energy demand is, for example, annual demand forecast data 271. The predetermined long period is, for example, one year. The annual operation plan unit 262 determines an operation plan for the energy supply device for a long period of time within a range that satisfies a plurality of constraints based on the prediction result of the energy demand for the long period of time. The operation plan of the energy supply device in the long term is, for example, annual operation plan data 272. The daily demand prediction unit 263 predicts the load energy demand for a short period included in the long period. The energy demand of the load for a short period is, for example, daily demand forecast data 273. The short period is, for example, one day. The daily operation planning unit 264 determines an operation plan for the energy supply device in a short period within a range that satisfies a plurality of constraints based on the operation plan for the energy supply device in the long period and the prediction result of the energy demand in the short period. . The operation plan of the energy supply device in a short period is, for example, daily operation plan data 274.

  Thereby, the energy management device 2 of the first embodiment can reduce the energy cost even when a plurality of annual constraints are satisfied.

  The daily operation planning unit 264 multiplies the energy demand p in a short period by the energy unit price (virtual energy unit price) changed using a coefficient such as the annual constraint γ. The energy cost is expressed as, for example, “(demand amount of power × virtual energy unit price of power) + (demand amount of gas × virtual energy unit price of gas)”. The daily operation planning unit 264 determines an operation plan for the energy supply device in a short period according to the energy cost based on the multiplication result. The operation plan of the energy supply device in a short period is, for example, daily operation plan data 274.

(Second Embodiment)
The second embodiment is different from the first embodiment in that the energy management system further includes a monitoring control server and the like. In the second embodiment, only differences from the first embodiment will be described.

  FIG. 13 is a diagram illustrating an example of the configuration of the energy management system 1b. The energy management system 1b is a system for managing energy in a consumer group. The energy management system 1 b includes an energy management device 2, an external energy source 3, an energy supply plant 4, and a customer group 5. The energy management system 1b further includes a monitoring control server 6, a weather server 7, a DR server 8, and an external communication server 9. The external network 200 is a communication line. The external network 200 is, for example, an optical fiber or a coaxial cable.

  The monitoring control server 6 is an information processing device such as a server device. The monitoring control server 6 communicates with the energy management device 2, the energy supply plant 4, and the customer group 5 via the internal network 100. The monitoring control server 6 may communicate with the external communication server 9 via the internal network 100 and the external network 200. The monitoring control server 6 transmits monitoring data of the energy supply equipment of the energy supply plant 4 to the energy management device 2. The monitoring data includes, for example, operation data of energy supply equipment of the energy supply plant 4. The operation data includes, for example, an actual measurement value of the energy supply amount of the energy supply device of the energy supply plant 4.

  The weather server 7 is an information processing device such as a server device. The weather server 7 transmits weather data to the external communication server 9 via the external network 200. The DR server 8 is an information processing apparatus such as a server apparatus. The DR server 8 transmits data related to demand response (hereinafter referred to as “DR data”) to the external communication server 9 via the external network 200.

  The external communication server 9 acquires weather data from the weather server 7 via the external network 200. The external communication server 9 acquires DR data from the DR server 8 via the external network 200.

  FIG. 14 is a diagram illustrating an example of the configuration of the energy management device 2. The energy management device 2 includes a process data acquisition unit 21, a process data storage unit 22, a setting data acquisition unit 23, an acquisition control unit 24, a setting data storage unit 25, a calculation processing unit 26, and a calculation result storage unit. 27, a display control unit 28, and a display unit 29.

  The process data storage unit 22 stores process data 220, weather data 221 and DR data 222 in association with the date and time. The weather data 221 is data representing, for example, temperature and humidity. The weather data 221 is data provided from the Japan Meteorological Agency, for example.

  The DR data 222 is data related to demand response. The DR data 222 is data representing, for example, the amount of incentive for each time, a time zone for issuing a demand response signal, a time limit for bidding for a demand response signal, and the like. The DR data 222 is transmitted from the DR server 8 of the negative watt aggregator, for example.

  The arithmetic processing unit 26 includes an annual constraint priority calculation unit 260, an annual demand prediction unit 261, an annual operation planning unit 262, a daily demand prediction unit 263, a daily operation planning unit 264, a performance evaluation unit 265, and a device. A control unit 266 and a DR operation unit 267 are provided.

  The annual demand prediction unit 261 calculates the annual energy conversion efficiency of each energy supply device by applying a prediction method such as a neural network or a pattern matching method to the weather data 221 including the outside air temperature data.

  The daily demand prediction unit 263 calculates the energy conversion efficiency and the energy demand amount of each energy supply device for each day by applying a prediction method such as a neural network or a pattern matching method to the weather data 221 including the outside air temperature data.

  The performance evaluation unit 265 (evaluation unit) determines whether the energy cost determined by the created operation plan can be achieved with respect to the annual constraint based on the actual measurement value of the energy demand and the actual measurement value of the energy supply amount. Evaluate each energy supply device. The performance evaluation unit 265 transmits performance evaluation data 275 representing an energy cost evaluation result to the annual operation planning unit 262. The performance evaluation unit 265 stores the performance evaluation data 275 in the calculation result storage unit 27.

  For example, the device control unit 266 creates device control data 276 for controlling the energy supply device based on the plant model data 251, the model parameter data 252, and the daily operation plan data 274. The device control data 276 includes a set value in a range that satisfies the operation constraint condition. The operation constraint condition is, for example, a constraint condition for the maximum output of energy supplied by the energy supply device. The device control unit 266 transmits device control data 276 to each energy supply device. The device control unit 266 stores the device control data 276 in the calculation result storage unit 27.

  The DR calculation unit 267 calculates a virtual energy unit price for each time zone based on the DR data 222. The DR calculation unit 267 updates the daily operation plan data 274 based on the virtual energy unit price. The DR calculation unit 267 (determination unit) determines whether there is a merit of energy cost by bidding a demand response based on the daily operation plan data 274. When there is a merit of energy cost, the DR calculation unit 267 selects a demand response to be bid. When there is a merit of energy cost, the DR operation unit 267 (bid execution unit) executes a bid process for the selected demand response. The DR calculation unit 267 causes the calculation result storage unit 27 to store DR bid data 277 including information indicating a demand response to be bid.

  The calculation result storage unit 27 includes annual constraint coefficient data 270, annual demand forecast data 271, annual operation plan data 272, daily demand forecast data 273, daily operation plan data 274, performance evaluation data 275, and device control. Data 276 and DR bid data 277 are stored.

  The display control unit 28 includes annual constraint coefficient data 270, annual demand forecast data 271, annual operation plan data 272, daily demand forecast data 273, daily operation plan data 274, performance evaluation data 275, device control data 276, and DR bid data 277. Are obtained from the calculation result storage unit 27. The display control unit 28 causes the display unit 29 to display images representing various data.

  For example, the display control unit 28 includes the annual constraint coefficient data 270, the annual demand forecast data 271, the annual operation plan data 272, the daily demand forecast data 273, the daily operation plan data 274, the performance evaluation data 275, the device control data 276, and the DR bid. At least one of the data 277 may be displayed on the display unit 29.

  For example, the display control unit 28 may display the annual demand forecast data 271 of the hourly unit of the energy supply plant 4 on the display unit 29 in a table format or a graph format. For example, the display control unit 28 may cause the display unit 29 to display the annual operation plan data 272 for each hour of the energy supply plant 4 in a table format or a graph format. For example, the display control unit 28 may cause the display unit 29 to display the daily demand forecast data 273 for each hour of the energy supply plant 4 in a table format or a graph format. For example, the display control unit 28 may display the daily operation plan data 274 for each hour of the energy supply plant 4 on the display unit 29 in a table format or a graph format.

  For example, the display control unit 28 may display the device control data 276 on the display unit 29 in a table format or a graph format. For example, the display control unit 28 may display the DR bid data 277 on the display unit 29 in a table format or a graph format. For example, the display control unit 28 may display the web page on the display unit 29.

  The display unit 29 is a display device. The display unit 29 may be an information processing device including a display device. For example, the display unit 29 may be a tablet terminal or a smartphone terminal. The display unit 29 includes a display device such as a liquid crystal display or an organic EL (Electro-Luminescence) display. The display unit 29 displays images representing various data in accordance with control by the display control unit 28. The display unit 29 may include an operation unit for receiving an operation. The operation unit is, for example, a touch panel, a mouse, or a keyboard.

  FIG. 15 is a diagram illustrating an example of the configuration of the performance evaluation unit 265. The performance evaluation unit 265 includes a monitoring data acquisition unit 2650 and an annual constraint performance evaluation unit 2651. The monitoring data acquisition unit 2650 acquires monitoring data of the energy supply device of the energy supply plant 4 from the monitoring control server 6 via the internal network 100.

  The annual constraint performance evaluation unit 2651 determines whether or not the energy cost has been achieved with respect to the annual constraint when a certain time has elapsed from the start time of the evaluation period, and whether or not the actual measured value of the energy demand and the actual measured value of the energy supply amount. Based on the above, each energy supply device is evaluated. The annual constraint performance evaluation unit 2651 transmits the performance evaluation data 275 to the annual operation planning unit 262.

  The annual operation planning unit 262 minimizes the energy cost based on the performance evaluation data 275 within a range that satisfies a plurality of constraints such as the annual fuel constraint and the operation constraint of the energy supply plant 4, thereby performing the annual operation of the energy supply plant 4. Update the plan.

  FIG. 16 is a flowchart illustrating an example of the operation (step S105) of the annual operation planning unit 262. The operator of the energy management apparatus 2 may cause the annual operation planning unit 262 to execute the operation illustrated in FIG. 16 at an arbitrary timing or periodically. When the annual operation plan unit 262 updates the annual operation plan (step S105), the monitoring data acquisition unit 2650 of the performance evaluation unit 265 acquires monitoring data from the monitoring control server 6 (step S401).

  The annual constraint performance evaluation unit 2651 determines whether or not the energy cost has been achieved with respect to the annual constraint when a certain time has elapsed from the start time of the evaluation period, and whether or not the actual measured value of the energy demand and the actual measured value of the energy supply amount. Based on the above, each energy supply device is evaluated.

Annual constraint performance evaluation unit 2651, for the evaluation start date d = 1 subject of annual limitations to the current day d = d _now, and calculates the measured value of the energy supply of the energy supply equipment energy supply plant 4.

Hereinafter, a symbol written on a character in an expression is written immediately before the character. Formula (27) represents the actual value (^ E _e ^out ) of the annual power supply amount of the external power source. Equation (28) represents the actual value of the amount of gas supplied per year the (^ _{E e)} (step S402).

  The annual operation planning unit 262 acquires an actual measured value of the energy supply amount of the energy supply device of the energy supply plant 4 from the monitoring control server 6 as the actual value of the energy supply amount of the external energy source 3 with respect to the annual constraint (step S403). ).

  The annual constraint coefficient initialization unit 2620 of the annual operation planning unit 262 initializes the annual constraint coefficient data 270. For example, the annual constraint coefficient initialization unit 2620 initializes the annual constraint coefficient data 270 based on the equations (29) and (30).

  Expression (29) is an annual external power demand constraint expression that represents the result of updating Expression (2) based on the actual measurement value of the power supply amount of the external power supply. Equation (30) is an annual gas demand constraint equation representing the result of updating Equation (3) based on the actual measured gas supply amount (step S201).

  The daily operation planning unit 264 determines the remaining number of days (N months) after the present in the evaluation period of one year as the updated evaluation period. The daily operation plan unit 264 creates an updated daily operation plan for the energy supply plant 4 for the updated evaluation period based on the updated annual constraint coefficient data 270 and the annual demand prediction data 271 (step S107). ).

  The convergence determination unit 2621 determines whether or not the annual constraint coefficient has converged. For example, the convergence determination unit 2621 satisfies the formula (21) representing the absolute error and the formulas (29) and (30) representing the annual constraint based on the setting contents of the annual constraint included in the evaluation period data 250. It is determined whether or not (step S202).

  When the annual constraint coefficient has not converged (step S202: NO), the annual constraint priority calculation unit 260 calculates the priority of the annual constraint based on the setting content of the annual constraint and the setting content of the objective function ( Step S203).

  The annual constraint coefficient update unit 2622 updates the annual constraint coefficient based on the priority of the annual constraint (step S204). The annual constraint coefficient update unit 2622 returns the process to step S107.

  When the annual constraint coefficient converges (step S202: YES), the annual constraint priority calculation unit 260 transmits the converged annual constraint coefficient and the updated annual operation plan data 272 to the annual constraint priority calculation unit 260. (Step S205).

  The annual constraint priority calculation unit 260 may notify the operator of the energy management apparatus 2 of a request for approval to update the annual operation plan data 272. The annual constraint priority calculation unit 260 may store the updated annual operation plan data 272 in the calculation result storage unit 27 when the approval of the operator of the energy management apparatus 2 is obtained via the setting data acquisition unit 23. Good.

  FIG. 17 is a diagram illustrating an example of the configuration of the DR operation unit 267. The DR calculation unit 267 includes a DR data acquisition unit 2670, a DR hourly unit price calculation unit 2671, a DR bid determination unit 2672, and a DR bid output unit 2673.

  The DR data acquisition unit 2670 acquires the DR data 222 from the process data storage unit 22. Based on the DR data 222, the DR hourly unit price calculation unit 2671 calculates the virtual energy unit price at the time of executing the demand response for each time zone. The daily operation plan unit 264 creates an updated daily operation plan for the energy supply plant 4 for the updated evaluation period based on the updated annual constraint coefficient data 270 and the annual demand prediction data 271.

  The DR bid determination unit 2672 determines whether there is a merit of energy cost by bidding a demand response based on the DR data 222 and the daily operation plan data 274. When there is a merit of energy cost, the DR bid determination unit 2672 creates DR bid data 277 by selecting a demand response to be bid. The DR bid output unit 2673 causes the calculation result storage unit 27 to store DR bid data 277 including information indicating a demand response to be bid.

  FIG. 18 is a flowchart illustrating an example of the operation (step S107) of the daily operation planning unit 264. When the daily operation plan unit 264 creates a daily operation plan (step S107), the DR data 222 is acquired from the process data storage unit 22 (step S501).

  The DR hourly unit price calculation unit 2671 calculates the virtual energy unit price at the time of executing the demand response for each time zone based on the DR data 222 and the equation (31).

Here, p _A ^DR (t) represents a virtual energy unit price [yen / kWh] at time t when the energy supply device A executes a demand response. p _DR ^A (t) represents the expected incentive acquisition amount [yen / kWh] at the time t when the energy supply device A executes the demand response. The expected incentive acquisition amount p _DR ^A (t) is determined in advance based on an operation on the setting data acquisition unit 23. The expected incentive acquisition amount p _DR ^A (t) may be calculated based on the DR data 222, the daily demand prediction data 273, and the daily operation plan data 274 (step S502).

  Steps S301 to S306-1 are the same as steps S301 to S306-1 shown in FIG. Steps S307 to S306-2 are the same as steps S307 to S306-2 shown in FIG.

  The DR bid determination unit 2672 determines whether there is a merit of energy cost by bidding a demand response based on the DR data 222 and the daily operation plan data 274. For example, the DR bid determination unit 2672 creates a daily operation plan when bidding for a demand response and a daily operation plan when not bidding for a demand response. The DR bid determination unit 2672 determines that there is a merit of the energy cost in the daily operation plan in which the energy cost is lower in one day (step S503).

  If there is a merit of energy cost by bidding for the demand response (step S503: YES), the DR bid determination unit 2672 selects the demand response to be bid, if there is a merit of energy cost. 277 is created. The DR bid output unit 2673 stores the DR bid data 277 including information indicating the demand response to be bid in the calculation result storage unit 27 (step S504).

  The device control unit 266 creates device control data 276 for each energy supply device (step S505). The device control unit 266 transmits device control data to each energy supply device (step S506).

  As described above, the daily demand prediction unit 263 according to the second embodiment predicts the load energy demand for a short period based on the weather data. Thereby, the energy management device 2 of the second embodiment can efficiently reduce the energy cost even when a plurality of annual constraints are satisfied.

  The daily operation plan unit 264 updates the operation plan of the energy supply device in a short period when it is evaluated that the energy cost cannot be achieved due to the constraint. The daily operation plan unit 264 updates the operation plan of the energy supply device in a short period to the operation plan selected from a plurality of operation plan candidates.

(Third embodiment)
In the third embodiment, the point that the energy management system includes an energy center and the configuration of the customer group 5 are different from those in the first embodiment. In the third embodiment, only differences from the first embodiment will be described.

  FIG. 19 is a diagram illustrating an example of the configuration of the energy management system 1c. The energy management system 1 c includes an energy management device 2, an external energy source 3, a customer group 5, and an energy center 10.

  The external energy source 3 supplies energy to the consumer 500 of the consumer group 5 and the equipment of the energy center 10. The energy is, for example, power such as grid power, external power supply power, and market power.

  The customer group 5 includes a customer 500 and a shared portion load 510. The consumer group 5 may include a plurality of consumers 500. The shared part load 510 is a load in the shared part of the customer group 5. Shared portion load 510 is, for example, an electric power load, a cold load, a hot load, and a steam load. The consumer 500 includes a consumer EMS 505, an energy supply device 506, and a load. The loads are, for example, an electric power load 501, a cold load 502, a thermal load 503, and a steam load 504.

  The customer EMS 505 includes an EMS (hereinafter referred to as “customer EMS”) operated by an operator of the customer 500. The location where the customer EMS 505 is provided is not limited to a specific location. The customer EMS 505 is the customer 500. May be provided outside the site of the customer 500. The customer EMS 505 is, for example, BEMS, FEMS, HEMS, MEMS, etc. The customer EMS 505 is the energy supply device 506. By controlling the operation, the energy supply amount of the energy supply device 506 is managed.

  The customer EMS 505 may acquire the annual operation plan data 272 and the daily operation plan data 274 from the device control unit 266 (communication unit) of the arithmetic processing unit 26 of the energy management device 2. The customer EMS 505 may control the operation of the energy supply device 506 based on the annual operation plan data 272 and the daily operation plan data 274.

  The energy supply device 506 is a device that supplies energy to a load. The energy supply device 506 includes, for example, an emergency generator, an uninterruptible power supply (UPS), a power receiving facility 400, a PV 401, a storage battery 402, a water-cooled chiller 403, an air-cooled HP chiller 404, and heat recovery. They are an HP chiller 405, a CGS 406, a boiler 407, an ABR 408, a cooling / heating tank 409, and a heating / heating tank 410. The energy supply device 506 acquires energy from the external energy source 3. The energy supply device 506 supplies energy to the electric load 501, the cold load 502, the hot load 503, and the steam load 504 according to control by the customer EMS 505.

  The equipment of the energy center 10 is equipment for supplying energy such as electric power, cold heat, heat, and steam to the consumer group 5 according to the energy supplied from the external energy source 3. The equipment of the energy center 10 communicates with the energy management apparatus 2 via the internal network 100. The energy center 10 supplies energy such as electric power, cold heat, heat, and steam generated using the energy supplied from the external energy source 3 to the consumer group 5 based on control by the energy management device 2. In FIG. 19, the equipment of the energy center 10 supplies energy to the electric power load 501, the cold load 502, the hot load 503, the steam load 504, and the common use load 510.

  FIG. 20 is a diagram illustrating an example of the configuration of the energy management device 2. The energy management device 2 includes a process data acquisition unit 21, a process data storage unit 22, a setting data acquisition unit 23, an acquisition control unit 24, a setting data storage unit 25, a calculation processing unit 26, and a calculation result storage unit. 27, a display control unit 28, and a display unit 29.

  The calculation processing unit 26 includes an annual constraint priority calculation unit 260, an annual demand prediction unit 261, an annual operation planning unit 262, a daily demand prediction unit 263, a daily operation planning unit 264, a device control unit 266, and distribution. And an arithmetic unit 268.

  The distribution calculation unit 268 determines the distribution between the energy supply amount of the energy center 10 and the energy supply amount of the energy supply device 506. For example, the distribution calculation unit 268 includes the energy demand amount in each load of the consumer 500, the energy demand amount in the shared portion load 510 of the consumer group 5, the upper limit of the energy supply amount of the energy center 10, and the energy supply device 506. Distribution of the energy supply amount of the energy center 10 and the energy supply amount of the energy supply device 506 is determined based on the upper limit of the energy supply amount.

  The distribution calculation unit 268 stores the distribution data 278 in the calculation result storage unit 27. The distribution data 278 is data representing the distribution of the energy supply amount. For example, the distribution data 278 is data representing the distribution between the energy supply amount of the energy center 10 and the energy supply amount of the energy supply device 506. For example, the distribution data 278 may be data representing the distribution of energy demand in each load of the customer 500.

  The annual operation planning unit 262 acquires the distribution data 278 from the calculation result storage unit 27. The annual operation plan unit 262 determines the annual operation plan data 272 of the energy center 10 based on the distribution data 278 indicating the distribution of the determined energy supply amount. The annual operation plan unit 262 determines the annual operation plan data 272 of the energy supply device 506 based on the distribution data 278 representing the distribution of the determined energy supply amount.

  The daily operation planning unit 264 acquires the distribution data 278 from the calculation result storage unit 27. The daily operation plan unit 264 determines the daily operation plan data 274 of the energy center 10 based on the distribution of the determined energy supply amount. The daily operation plan unit 264 determines the daily operation plan data 274 of the energy supply device 506 based on the distribution of the determined energy supply amount.

  The equipment control unit 266 controls the energy center 10 based on the equipment control data 276 based on the annual operation plan data 272 and the daily operation plan data 274. The device control unit 266 may control the energy supply device 506 via the customer EMS 505 based on the device control data 276 based on the annual operation plan data 272 and the daily operation plan data 274.

  The calculation result storage unit 27 includes annual constraint coefficient data 270, annual demand forecast data 271, annual operation plan data 272, daily demand forecast data 273, daily operation plan data 274, device control data 276, and distribution data. 278 is stored. The display control unit 28 may cause the display unit 29 to display an image representing the distribution data.

  FIG. 21 is a diagram showing an example of energy distribution display. A graph representing energy distribution is displayed on the display unit 29. The display unit 29 displays a graph representing the energy supply amount of the external energy source 3, the energy supply amount of the energy supply device 506, and the energy demand amount in the consumer group 5 in the energy management system 1 c. The horizontal axis of the graph shown in FIG. 21 indicates time. The vertical axis | shaft of the graph shown in FIG. 21 shows electric power energy. The display unit 29 may display the energy demand (total load) in the customer group 5 and the energy demand in the customer 500 in a table format for each time zone.

  The display unit 29 may accept a selection operation via an operation unit provided in the display unit 29. The display unit 29 may switch the target consumer 500 to be displayed in the graph and the table in accordance with an instruction to select the consumer 500. That is, the display unit 29 may display a graph representing the energy supply amount of the external energy source 3, the energy supply amount of the energy supply device 506, and the energy demand amount of the customer group 5 in the consumer 500. . The display unit 29 may switch the type of energy load to be displayed in the graph and the table in accordance with an instruction to select the type of energy load.

  The operator of the energy management apparatus 2 confirms by a graph that the energy supply device 506 preferentially obtains the power of the external power source during a time period when the energy unit price of the power of the external power source is lower than the energy unit price of the system power. be able to. The operator of the energy management device 2 confirms by a graph that the photovoltaic power generation facility (PV) of the energy center 10 supplies energy in a time zone in which the energy unit price of power is higher than the energy unit price of gas. Can do. The operator of the energy management apparatus 2 may confirm by a graph that the cogeneration system (CGS) of the customer 500 supplies energy in a time zone in which the energy unit price of power is higher than the energy unit price of gas. it can.

  As described above, the daily operation planning unit 264 of the third embodiment relates to the energy supply device of the customer 500 having a load, the device of the energy center that supplies energy to the load, and the load of the customer 500. Establish a short-term operation plan. The operation plan in a short period is, for example, daily operation plan data 274. Thereby, the distribution calculation unit 268 of the third embodiment can reduce the energy cost based on the energy supply-demand balance in the energy center 10 and the customer group 5 and the like.

  According to at least one embodiment described above, the energy supply device in a short period within a range satisfying a plurality of constraints based on the operation plan of the energy supply device in the long period and the prediction result of the energy demand in the short period. By having a short-term planning section that determines the operation plan, energy costs can be reduced even when a plurality of annual constraints are satisfied.

  As mentioned above, although some embodiment of this invention was described, these embodiment is shown as an example and is not intending limiting the range of invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

DESCRIPTION OF SYMBOLS 1a-1c ... Energy management system, 2 ... Energy management apparatus, 3 ... External energy source, 4 ... Energy supply plant, 5 ... Consumer group, 6 ... Monitoring control server, 7 ... Weather server, 8 ... DR server, 9 ... External communication server, 10 ... energy center, 20 ... communication unit, 21 ... process data acquisition unit, 22 ... process data storage unit, 23 ... setting data acquisition unit, 24 ... acquisition control unit, 25 ... setting data storage unit, 26 ... Arithmetic processing unit, 27 ... Calculation result storage unit, 28 ... Display control unit, 29 ... Display unit, 30 ... Electric power company, 31 ... New electric power company, 32 ... Electric power market, 33 ... Gas company, 34 ... Fuel company, 100 ... Internal network 200 ... External network 220 ... Process data 221 ... Meteorological data 222 ... DR data 250 ... Evaluation period data 251 ... Plan Model data 252 ... Model parameter data 260 ... Annual constraint priority calculation unit 261 ... Annual demand forecasting unit 262 ... Annual operation planning unit 263 ... Daily demand forecasting unit 264 ... Daily operation planning unit 265 ... Performance evaluation , 266... Equipment control unit, 267. DR calculation unit, 268... Distribution calculation unit, 270... Annual constraint coefficient data, 271... Annual demand forecast data, 272. Daily operation plan data, 275 ... performance evaluation data, 276 ... device control data, 277 ... DR bid data, 278 ... distribution data, 300 ... dot, 310 ... dot, 320 ... dot, 330 ... dot, 340 ... restricted range, 350 ... dots, 360 ... dots, 370 ... dots, 380 ... dots, 400 ... power receiving equipment, 401 ... PV, 4 2 ... Storage battery, 403 ... Water-cooled chiller, 404 ... Air-cooled HP chiller, 405 ... Heat recovery HP chiller, 406 ... CGS, 407 ... Boiler, 408 ... ABR, 409 ... Cold-heat tank, 410 ... Hot-heat tank, 501 ... Power load, 502 ... Refrigeration load, 503 ... Thermal load, 504 ... Steam load, 505 ... Consumer EMS, 506 ... Energy supply equipment, 510 ... Common use load, 2620 ... Annual constraint coefficient initialization part, 2621 ... Convergence determination part, 2622 ... Annual Constraint coefficient update unit, 2640 ... Annual constraint coefficient acquisition unit, 2641 ... Power supply device operation planning unit, 2642 ... Cold heat source device operation planning unit, 2643 ... Thermal source device operation planning unit, 2644 ... Steam heat source device operation planning unit, 2645 ... Energy storage device operation planning unit, 2650 ... monitoring data acquisition unit, 2651 ... annual constraint performance evaluation unit, 2670 ... DR data acquisition unit, 2 671 ... DR hourly unit price calculation unit, 2672 ... DR bid determination unit, 2673 ... DR bid output unit

Claims (18)

A long-term prediction unit that predicts the energy demand of a load to which energy is supplied from an energy supply device for a predetermined long period;
Based on the prediction result of the amount of energy demand in the long term, a long-term plan unit that determines an operation plan of the energy supply device in the long term within a range that satisfies a plurality of constraints;
A short-term prediction unit that predicts the energy demand of the load for a short period included in the long period;
Based on the operation plan of the energy supply device in the long period and the prediction result of the energy demand in the short period, a short period of time for determining the operation plan of the energy supply device in the short period in a range satisfying the plurality of constraints An energy management device comprising a planning department.   The short-term planning unit defines an operation plan for the energy supply device in the short period based on a result of multiplying the energy demand in the short period by an energy unit price changed using a coefficient. The energy management device described.   The energy management device according to claim 1, wherein the short-term planning unit determines an operation plan of the energy supply device in the short period within a range satisfying a plurality of the constraints. A data acquisition unit for acquiring data representing the evaluation period;
The energy management device according to any one of claims 1 to 3, wherein the short-term planning unit determines an operation plan of the energy supply device in the short period included in the evaluation period. A priority determination unit that determines a priority for achieving the constraint for each constraint;
A constraint coefficient updating unit that prioritizes the coefficient of the constraint with the higher priority and updates the coefficient of the constraint more largely as the energy demand in the long term is farther from the constraint. The energy management device described in 1.   The energy management device according to any one of claims 1 to 5, wherein the short-term prediction unit predicts an energy demand of the load for the short period based on weather data. The energy management apparatus according to any one of claims 1 to 6, further comprising: a device control unit that controls an operation of the energy supply device based on an operation plan of the energy supply device in the short period. Based on the measured value of the energy demand in the short period and the measured value of the energy supply in the short period, the energy cost determined by the operation plan of the energy supply device in the short period can be achieved with respect to the constraint The energy management device according to any one of claims 1 to 7, further comprising: an evaluation unit that evaluates whether or not there is.   The energy management device according to claim 8, wherein the short-term planning unit updates an operation plan of the energy supply device in the short period when it is evaluated that the energy cost cannot be achieved with respect to the constraint.   The energy management device according to claim 9, wherein the short-term planning unit updates an operation plan of the energy supply device in the short period to the operation plan selected from a plurality of operation plan candidates.   The energy management device according to claim 10, wherein when the update of the operation plan is approved, the short-term planning unit updates the operation plan of the energy supply device in the short period. The determination unit according to claim 1, further comprising: determining whether there is a merit of energy cost by bidding for a demand response based on an operation plan of the energy supply device in the short period. The energy management device according to item. The energy management device according to claim 12, further comprising: a bid execution unit that executes a bid process for the selected demand response when there is a merit of the energy cost.   The said short-term plan part determines the said operation plan in the said short period about the said energy supply apparatus of the consumer provided with the said load, the apparatus of the energy center which supplies energy to the said load, and the said load. Item 14. The energy management device according to any one of items 13. The energy management apparatus according to claim 14, further comprising: a communication unit that transmits data representing the operation plan in the short period to the energy supply device of the consumer. The energy management device according to any one of claims 1 to 15, further comprising a display unit that displays an image representing an operation plan of the energy supply device in the short period. A method performed by an energy management device, comprising:
Predicting the energy demand of a load to which energy is supplied from an energy supply device for a predetermined long period of time;
A step of determining an operation plan of the energy supply device in the long term within a range satisfying a plurality of constraints based on a prediction result of the energy demand in the long term;
Predicting the energy demand of the load for a short period included in the long period;
The step of determining the operation plan of the energy supply device in the short period within a range satisfying the plurality of constraints based on the operation plan of the energy supply device in the long period and the prediction result of the energy demand in the short period And energy management methods. On the computer,
A procedure for predicting an energy demand of a load to which energy is supplied from an energy supply device over a predetermined long period;
A procedure for determining an operation plan of the energy supply device in the long term within a range satisfying a plurality of constraints based on the prediction result of the energy demand in the long term;
A procedure for predicting the energy demand of the load for a short period included in the long period;
A procedure for determining an operation plan of the energy supply device in the short period within a range satisfying the plurality of constraints based on the operation plan of the energy supply device in the long period and the prediction result of the energy demand in the short period An energy management program to execute and.

Images