Energy management system, energy management method, and program

Abstract

To enable optimization of an operating plan of a microgrid with a small amount of computation.SOLUTION: An energy management system for managing a microgrid is provided, comprising an optimization unit configured to iteratively optimize an operating plan of a microgrid for each of multiple time periods of a given length, and a combination unit for combining operating plans optimized for respective time periods.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present disclosure relates to an energy management system, an energy management method, and a program. [Background technology]

[0002] In recent years, the introduction of energy supply systems such as microgrids has progressed. In microgrids, energy generation devices that generate multiple types of energy and energy storage devices that store multiple types of energy are sometimes used in combination for the purpose of reducing energy costs or carbon dioxide emissions. Examples of energy generation devices include power generation devices that generate electric power and hydrogen production devices that generate hydrogen. Examples of energy storage devices include power storage devices that store electric power and hydrogen storage devices that store hydrogen.

[0003] There is known an energy management system that creates an operation plan for an electric power demand facility by solving a combinatorial optimization problem. For example, Patent Document 1 discloses a power control system that creates a planning problem under a power receiving point and assigns the planning problem to a solver selected from a plurality of solvers. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2023-108365 Summary of the Invention [Problem to be solved by the invention]

[0005] However, conventional technologies have room for reducing the amount of calculation required for optimization calculations. For example, an energy management system is required to create an operation plan for a certain period of time, but the amount of calculation increases as the period to be optimized becomes longer, increasing the probability that the optimization calculation will fail due to timeouts or other reasons.

[0006] One aspect of the present disclosure aims to optimize the operation plan of a microgrid with a small amount of calculation. [Means for solving the problem]

[0007] An energy management system according to one aspect of the present disclosure is an energy management system that manages a microgrid, and includes an optimization unit that repeatedly optimizes the operation plan of the microgrid for a time interval of a predetermined length for each of a plurality of time intervals, and a combination unit that combines the operation plans optimized for each of the plurality of time intervals. [Effects of the Invention]

[0008] According to one aspect of the present disclosure, the operation plan of a microgrid can be optimized with a small amount of calculation. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a block diagram showing an example of the overall configuration of a microgrid. [Figure 2] FIG. 2 is a block diagram illustrating an example of a hardware configuration of a computer. [Figure 3] FIG. 2 is a block diagram illustrating an example of a functional configuration of the energy management system. [Figure 4] FIG. 10 is a diagram showing an example of a lower limit value of electric power of a hydrogen production device. [Figure 5] FIG. 10 is a diagram illustrating an example of a method for combining optimization results. [Figure 6] 1 is a flowchart illustrating an example of an energy management method. [Figure 7] FIG. 1 is a block diagram showing an example of the overall configuration of a microgrid. [Figure 8] FIG. 2 is a block diagram illustrating an example of a functional configuration of the energy management system. [Figure 9] FIG. 10 is a diagram illustrating an example of maximum energy storage amount control. [Figure 10] FIG. 10 is a diagram illustrating an example of energy supply amount leveling control. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. In this specification and drawings, components having substantially the same functional configurations are designated by the same reference numerals, and redundant description will be omitted.

[0011] [First embodiment] One embodiment of the present disclosure is an energy management system for managing a microgrid. In this embodiment, the microgrid includes a plurality of energy generation devices that generate a plurality of types of energy and a plurality of energy storage devices that store each type of energy, with the aim of achieving self-sufficiency with renewable energy.

[0012] The energy generation device may include a power generation device that generates electric power and a hydrogen production device that generates hydrogen. Examples of power generation devices include a solar power generation device equipped with solar panels that converts sunlight into electric power, a wind power generation device that converts wind power into electric power, a fuel cell that generates electric power using hydrogen as a raw material, a fuel cell vehicle, etc. Examples of hydrogen production devices include a water electrolysis device that generates hydrogen by electrolyzing water. Examples of destinations for the hydrogen produced by the hydrogen production device include a hydrogen power generation device that generates electric power using hydrogen, and a hydrogen boiler, hydrogen furnace, etc. that directly use hydrogen.

[0013] The energy storage device may include a power storage device that stores electric power and a hydrogen storage device that stores hydrogen. Examples of the power storage device include a storage battery. Examples of the hydrogen storage device include a hydrogen tank.

[0014] In this embodiment, the energy management system has a function of creating an operation plan for the microgrid. The operation plan for the microgrid is information for controlling the operation of the energy generation device and the energy storage device in a time interval of a predetermined length (hereinafter also referred to as a "planned interval"). The operation plan for the microgrid may include an operation plan for each device included in the microgrid. The length of the planned interval may be, for example, about one week to ten days.

[0015] In this embodiment, the energy management system optimizes the operation plan of each device included in the microgrid through optimization calculations in order to operate each device efficiently. Because some devices included in the microgrid deteriorate over time, the optimization calculations incorporate logic to suppress the deterioration of each device. Furthermore, because a microgrid operation plan needs to be created for a planning period of, for example, several days or more, logic is incorporated to reduce the amount of calculation required for the optimization calculations and enable optimization without failure in a reasonable amount of time even on a computer with limited computing resources.

[0016] <Overall configuration of microgrid> The overall configuration of a microgrid in this embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing an example of the overall configuration of a microgrid.

[0017] As shown in FIG. 1, the microgrid 1 includes an energy management system 10, solar panels 11, a power conditioner 12, a storage battery 13, a water electrolysis device 14, a hydrogen tank 15, and a fuel cell 16. The solar panels 11 are an example of a solar power generation device. The storage battery 13 is an example of a power storage device. The water electrolysis device 14 is an example of a hydrogen production device. The hydrogen tank 15 is an example of a hydrogen storage device. The fuel cell 16 is an example of a hydrogen power generation device.

[0018] The microgrid 1 is connected to a power grid 2. The power grid 2 is a different power system from the microgrid 1. The power grid 2 is managed by an energy supplier different from the operator of the microgrid 1. The power grid 2 supplies a forward power flow to the microgrid 1 and accepts a reverse power flow from the microgrid 1. Note that the power grid 2 does not necessarily have to accept a reverse power flow.

[0019] The microgrid 1 may further include a consumer 3. The consumer 3 is a facility to which energy is supplied, such as a factory or a building. The consumer 3 consumes the electricity or hydrogen generated in the microgrid 1 by supplying the electricity or hydrogen to devices installed within the facility. The fuel cell 16 may be included in the consumer 3.

[0020] The solar panel 11 is an example of a power generation device that generates power using sunlight and supplies the power to the microgrid 1. The power generated by the solar panel 11 is supplied to the power conditioner 12.

[0021] The power conditioner 12 is a device that converts power. The power conditioner 12 converts input DC power into AC power and outputs it. The power conditioner 12 receives power from the solar panel 11, the fuel cell 16, and the power grid 2. The power conditioner 12 supplies power to the storage battery 13, the water electrolysis device 14, and the consumer 3.

[0022] The storage battery 13 is an example of an electricity storage device that repeatedly stores electricity through an electrochemical reaction and discharges the stored electricity. In a charging mode, the storage battery 13 stores electricity supplied from the power conditioner 12. In a discharging mode, the storage battery 13 supplies electricity to the power conditioner 12.

[0023] The water electrolysis device 14 is an example of a hydrogen production device that produces hydrogen by electrolyzing water. The hydrogen produced by the water electrolysis device 14 can be used to generate electricity in a fuel cell 16. The hydrogen produced by the water electrolysis device 14 is supplied to a hydrogen tank 15.

[0024] The hydrogen tank 15 is an example of a hydrogen storage device that stores hydrogen. The hydrogen tank 15 stores hydrogen supplied from the water electrolysis device 14. The hydrogen tank 15 supplies hydrogen to the fuel cell 16 or the consumer 3.

[0025] The fuel cell 16 is an example of a power generation device that generates electricity using chemical energy of fuel through an electrochemical reaction. The fuel cell 16 may be a hydrogen fuel cell that generates electricity using hydrogen as a raw material. The fuel cell 16 generates electricity using hydrogen produced by the water electrolysis device 14 and stored in the hydrogen tank 15. The electricity generated by the fuel cell 16 is supplied to the power conditioner 12.

[0026] The energy management system 10, solar panels 11, power conditioner 12, storage battery 13, water electrolysis device 14, hydrogen tank 15, and fuel cell 16 are connected to a communication network such as a LAN (Local Area Network). The energy management system 10 can communicate with the solar panels 11, power conditioner 12, storage battery 13, water electrolysis device 14, hydrogen tank 15, and fuel cell 16 via the communication network.

[0027] The energy management system 10 collects measurement data at predetermined time intervals from each device included in the microgrid 1. The energy management system 10 also creates an operation plan for the microgrid 1 based on the collected measurement data and provides it to each device included in the microgrid 1. Each device connected to the microgrid 1 operates according to the operation plan provided by the energy management system 10.

[0028] <Hardware configuration of the energy management system> The hardware configuration of the energy management system 10 will be described with reference to Fig. 2. The energy management system 10 is realized by, for example, a computer. Fig. 2 is a block diagram showing an example of the hardware configuration of a computer.

[0029] As shown in FIG. 2, the computer 500 includes a CPU (Central Processing Unit) 501, a ROM (Read Only Memory) 502, a RAM (Random Access Memory) 503, a data storage device (e.g., an SSD (Solid State Drive) or an HDD (Hard Disk Drive)) 504, an input device 505, a display device 506, a communication I / F (Interface) 507, and an external I / F 508. The CPU 501, the ROM 502, and the RAM 503 form a so-called computer. The hardware components of the computer 500 are connected to each other via a bus line 509. The input device 505 and the display device 506 may be connected to the external I / F 508 for use.

[0030] The CPU 501 is a computing device that controls the entire computer 500 and realizes its functions by reading programs and data from a storage device such as the ROM 502 or HDD 504 onto the RAM 503 and executing the processes.

[0031] The ROM 502 is an example of a non-volatile semiconductor memory (storage device) that can retain programs and data even when the power is turned off. The ROM 502 functions as a main storage device that stores various programs, data, etc. required for the CPU 501 to execute various programs installed in the HDD 504. Specifically, the ROM 502 stores boot programs such as a Basic Input / Output System (BIOS) and an Extensible Firmware Interface (EFI) that are executed when the computer 500 starts up, as well as data such as OS (Operating System) settings and network settings.

[0032] The RAM 503 is an example of a volatile semiconductor memory (storage device) in which programs and data are erased when the power is turned off. The RAM 503 is, for example, a dynamic random access memory (DRAM) or a static random access memory (SRAM). The RAM 503 provides a working area in which various programs installed in the HDD 504 are expanded when executed by the CPU 501.

[0033] The HDD 504 is an example of a non-volatile storage device that stores programs and data. The programs and data stored in the HDD 504 include an OS, which is basic software that controls the entire computer 500, and applications that provide various functions on the OS. Note that the computer 500 may use a storage device that uses flash memory as a storage medium (e.g., an SSD (Solid State Drive)) instead of the HDD 504.

[0034] The input device 505 includes a touch panel, operation keys and buttons, a keyboard and mouse, a microphone for inputting sound data such as voice, and the like, which are used by the user to input various signals.

[0035] The display device 506 is configured with a display such as a liquid crystal display or organic EL (Electro-Luminescence) display for displaying a screen, a speaker for outputting sound data such as voice, and the like.

[0036] The communication I / F 507 is an interface that connects to a communication network and enables the computer 500 to perform data communication.

[0037] The external I / F 508 is an interface with external devices, such as a drive device 510.

[0038] The drive device 510 is a device for loading a recording medium 511. The recording medium 511 here includes media that record information optically, electrically, or magnetically, such as a CD-ROM, a flexible disk, or a magneto-optical disk. The recording medium 511 may also include semiconductor memories that record information electrically, such as ROMs and flash memories. This allows the computer 500 to read from and / or write to the recording medium 511 via the external I / F 508.

[0039] The various programs to be installed in the HDD 504 are installed, for example, by setting the distributed recording medium 511 in a drive device 510 connected to the external I / F 508 and reading out the various programs recorded on the recording medium 511 by the drive device 510. Alternatively, the various programs to be installed in the HDD 504 may be installed by being downloaded via the communication I / F 507 from a network different from the communication network.

[0040] <Functional configuration of the energy management system> The functional configuration of the energy management system 10 will be described with reference to Fig. 3. Fig. 3 is a block diagram showing an example of the functional configuration of the energy management system.

[0041] As shown in FIG. 3, the energy management system 10 includes an acquisition unit 110, a determination unit 120, an optimization unit 130, a combination unit 140, an adjustment unit 150, and an output unit 160.

[0042] The acquisition unit 110, determination unit 120, optimization unit 130, combination unit 140, adjustment unit 150, and output unit 160 are realized by processing that is executed by the CPU 501 according to a program expanded from the HDD 504 shown in FIG. 2 onto the RAM 503.

[0043] The acquisition unit 110 acquires information to be used in the optimization calculation. The acquisition unit 110 may acquire the information by collecting measurement data from each device included in the microgrid 1. The acquisition unit 110 may acquire the information by reading electronic data input to the input device 505 of the energy management system 10 or a terminal device connected to the energy management system 10.

[0044] The acquisition unit 110 acquires at least the deterioration rate of the water electrolysis device 14 , the remaining capacity of the storage battery 13 , the remaining capacity of the hydrogen tank 15 , the amount of power generated by the solar panel 11 , and the operation plan of the fuel cell 16 .

[0045] The acquisition unit 110 may calculate the deterioration rate of the water electrolysis device 14 based on the current and voltage of the water electrolysis cells included in the water electrolysis device 14. The deterioration rate of the water electrolysis device 14 may be calculated by comparing the current current and voltage of the water electrolysis cells with the current and voltage of water electrolysis cells that are not degraded. The current and voltage of water electrolysis cells that are not degraded may be values ​​measured when the water electrolysis device 14 is first used, or may be catalog values ​​published by the manufacturer of the water electrolysis device 14. The deterioration rate of the water electrolysis device 14 may be calculated taking into account the water temperature.

[0046] The acquisition unit 110 may receive, from the storage battery 13, measurement data indicating the remaining capacity of the storage battery 13 measured by a sensor installed in the storage battery 13. The acquisition unit 110 may acquire the remaining capacity of the storage battery 13 input to the energy management system 10 by a user operation.

[0047] The acquisition unit 110 may acquire measurement data indicating the remaining amount of hydrogen in the hydrogen tank 15, measured by a sensor installed in the hydrogen tank 15, from the hydrogen tank 15. The acquisition unit 110 may also acquire the remaining amount of hydrogen in the hydrogen tank 15 that is input to the energy management system 10 by a user operation.

[0048] The acquisition unit 110 may predict the amount of power generated by the solar panel 11 based on a trained model. The trained model may be a learning model that uses weather forecast data as an explanatory variable and the amount of power generated by the solar panel 11 as a target variable. The weather forecast data may include, for example, weather, amount of sunlight, temperature, and amount of cloud cover. The trained model may be a learning model that predicts the amount of power generated by the solar panel 11 on a specific day based on training data that includes past weather forecast data and actual values ​​of the amount of power generated by the solar panel 11. Note that other learning models may be selected as the trained model as needed. For example, a learning model consisting of a newly developed algorithm or a learning model that can shorten processing time may be selected.

[0049] In this specification, a learning model refers to a method of data analysis that involves a process of obtaining output from input data through a model. Specifically, a computer receives input data, extracts insights, and the model evaluates the data to provide final output. A trained model refers to a model that has been trained using a dataset for a specific purpose. A trained model is used to make predictions or judgments for specific tasks, and for example, highly accurate results can be obtained by utilizing a trained model in tasks such as speech recognition and image classification.

[0050] The operation plan for the fuel cell 16 is time-series data indicating the power generation time of the fuel cell 16 and the amount of hydrogen consumed during power generation. In other words, the operation plan for the fuel cell 16 is data indicating the amount of hydrogen consumed produced by the water electrolysis device 14. The operation plan for the fuel cell 16 may be created by a user of the energy management system 10. The acquisition unit 110 may acquire the operation plan for the fuel cell 16 input to the energy management system 10 by a user operation.

[0051] The determination unit 120 determines the lower power limit of the water electrolysis device 14 based on the deterioration rate of the water electrolysis device 14 acquired by the acquisition unit 110. The determination unit 120 may determine, as the lower power limit of the water electrolysis device 14, the electrolysis power of the water electrolysis device 14 at which a predetermined minimum hydrogen production efficiency can be maintained at the deterioration rate acquired by the acquisition unit 110. The electrolysis power of the water electrolysis device 14 refers to the power used by the water electrolysis device 14 to electrolyze water (in other words, the total amount of power applied to the water electrolysis cells by the water electrolysis device 14).

[0052] <Lower power limit considering deterioration rate> The hydrogen generation efficiency of the water electrolysis device 14 is the amount of hydrogen that can be generated per unit of power. In this embodiment, the hydrogen generation efficiency according to the deterioration rate of the water electrolysis device 14 is defined by equation (1).

[0053]

number

[0054] However, Conversion Hydrogen is the hydrogen production efficiency (unit: Nm3 / kWh), and p WE required is the lower limit of power (unit: kW), and Required Hydrogen is the minimum hydrogen production efficiency (unit: Nm3 / kWh), and α DET is a coefficient according to the deterioration rate, and β DET is an intercept corresponding to the deterioration rate. In this embodiment, the relationship of the deterioration rate is expressed by the right side of equation (1), but it is not limited to this equation and may be another equation or may be derived from experimental results.

[0055] Hydrogen generation efficiency Conversion Hydrogen Minimum hydrogen generation efficiency required Hydrogen The power lower limit p WE required can be calculated using equation (2).

[0056]

number

[0057] Therefore, the electrolysis power p WE The range of is defined by equation (3), where [·] is a closed interval.

[0058]

number

[0059] 4 is a diagram showing an example of the lower limit of the power of the hydrogen production device. As shown in FIG. 4, the relationship between the electrolysis power (horizontal axis) and the hydrogen generation efficiency (vertical axis) of the water electrolysis device 14 varies depending on the deterioration rate. In the example shown in FIG. 4, at the current deterioration rate, the hydrogen generation efficiency Conversion Hydrogen Minimum hydrogen generation efficiency required Hydrogen The electrolysis power exceeding the power lower limit p WE required is decided.

[0060] In the example shown in FIG. 4, when determining the lower limit of power, the deterioration rate is rounded off to the nearest one, and the electrolysis power is rounded off to the nearest tenth. As shown in FIG. 4, as an example, the minimum hydrogen generation efficiency Required Hydrogen is 1.1 Nm3 / kWh and the deterioration rate is 30%, the power lower limit p WE required is 7kW.

[0061] The optimization unit 130 optimizes the operation plan of the microgrid 1 based on the information acquired by the acquisition unit 110 and the power lower limit value determined by the determination unit 120. The operation plan of the microgrid 1 includes at least an operation plan of the water electrolysis device 14. The operation plan of the water electrolysis device 14 includes at least the electrolysis power of the water electrolysis device 14. The operation plan of the microgrid 1 may further include an operation plan of the storage battery 13. The operation plan of the storage battery 13 includes at least the charging power of the storage battery 13 and the discharging power of the storage battery 13.

[0062] The optimization unit 130 may optimize the operation plan of the microgrid 1 so as to maximize the electrolysis power of the water electrolysis device 14. In other words, the optimization unit 130 may optimize the operation plan of the microgrid 1 so as to maximize the amount of hydrogen produced by the water electrolysis device 14 during the planning period. The optimization unit 130 may optimize the operation plan of the microgrid 1 so as to minimize the amount of power purchased from and sold to the power grid 2.

[0063] The optimization unit 130 may optimize the operation plan of the microgrid 1 so as to minimize the penalty related to the deterioration of the water electrolysis device 14 and the penalty related to the deterioration of the storage battery 13. The penalty related to the deterioration of the water electrolysis device 14 may take a larger value as the amount of change or the number of changes in the electrolysis power of the water electrolysis device 14 increases. The penalty related to the deterioration of the storage battery 13 may take a larger value when the remaining charge of the storage battery 13 is outside a predetermined range.

[0064] The optimization unit 130 may optimize the operation plan of the microgrid 1 so as to satisfy a constraint on the amount of change in the electrolysis power of the water electrolysis device 14. The optimization unit 130 may optimize the operation plan of the microgrid 1 so as to further satisfy constraints on the change range and change frequency of the electrolysis power of the water electrolysis device 14. The constraint on the change range may include an upper power limit lower than the rated power of the water electrolysis device 14 and a lower power limit determined by the determination unit 120. The constraint on the change frequency may be that the number of changes in the electrolysis power per unit time is equal to or less than a predetermined threshold. The constraint on the change amount may be that the amount of change in the electrolysis power per unit time is equal to or less than a predetermined threshold.

[0065] The optimization unit 130 optimizes the operation plan of the microgrid 1 in the planning interval. The optimization unit 130 may repeatedly optimize the operation plan of the microgrid 1 in a time interval (referred to as an optimization interval) that is shorter than the planning interval. The time length of the optimization interval may be, for example, about one or two days. The optimization unit 130 may repeatedly optimize the operation plan of the microgrid 1 in each optimization interval until the combined time length of multiple optimization intervals is equal to or greater than the time length of the planning interval.

[0066] When repeatedly performing optimization calculations for multiple optimization intervals that are consecutive in the time direction, the optimization unit 130 may set initial values ​​of variables in the optimization calculations for the subsequent optimization interval based on the optimization results of the preceding optimization interval. Specifically, the optimization unit 130 may set variables at the last time of the preceding optimization interval to variables at the time immediately before the subsequent optimization interval.

[0067] In the present embodiment, the variables for which the optimization unit 130 sets initial values ​​include the resolution of the water electrolysis device 14, the remaining capacity of the storage battery 13, and the remaining capacity of the hydrogen tank 15. When optimizing the operation plan of the microgrid 1 in the first optimization section included in the planning section, the optimization unit 130 may set a predetermined initial value as the initial value of the resolution of the water electrolysis device 14. In this case, the optimization unit 130 may set the remaining capacity of the storage battery 13 acquired by the acquisition unit 110 as the initial value of the remaining capacity of the storage battery 13. Furthermore, the optimization unit 130 may set the remaining capacity of the hydrogen tank 15 acquired by the acquisition unit 110 as the initial value of the remaining capacity of the hydrogen tank 15.

[0068] The operation plan for the microgrid 1 needs to be created for a period of time, for example, one week to ten days. However, if long-term operation plans are optimized at once, the amount of calculation required becomes enormous, increasing the possibility that the optimization calculation will fail due to inability to execute or a timeout. Dividing the period targeted for the optimization calculation into shorter periods reduces the amount of calculation required for each optimization calculation, and reduces the possibility of the optimization calculation failing.

[0069] In this embodiment, when performing optimization calculations for multiple optimization sections that are consecutive in the time direction, the optimization results at the end of the preceding optimization section are set as the initial values ​​of the variables of the subsequent optimization section, which makes it possible to combine the optimization results in chronological order of the optimization sections.

[0070] <<Formulation of optimization calculations>> The formulation of the optimization calculation performed by the optimization unit 130 will now be described in detail.

[0071] (constraints) The constraints used in the optimization calculation include (1) a constraint on the amount of change in the water electrolysis device, (2) prohibition of simultaneous accounting of charging and discharging, (3) prohibition of simultaneous accounting of discharged electricity for sale, (4) a formula for calculating the remaining capacity of the hydrogen tank, (5) a formula for calculating the remaining capacity of the storage battery, (6) a formula for calculating the electrolysis power of the water electrolysis device, and (7) a formula for the relationship between charging and discharging.

[0072] (1) The change amount constraint of the water electrolysis device is defined by equation (4).

[0073]

number

[0074] where t is a time index (0 to t max (or less), and t max is the number of time points included in the optimization interval (e.g., 48), and p SWITCH is the operation switch of the water electrolysis device (0 = off, 1 = on), and p resolution is the output resolution of the water electrolysis device (unit: %), and p resolution limit is the control constraint (unit: %) of the water electrolysis device 14. The time t is set at a predetermined time interval. The time interval Δt may be, for example, 30 minutes or 1 hour.

[0075] (2) The prohibition of simultaneous charging and discharging is defined by equation (5).

[0076]

number

[0077] However, q CHARGE is the charging power (unit: kW), and q DISCHARGE is the discharge power (unit: kW).

[0078] (3) The prohibition of simultaneous accounting of discharged electricity sales is defined by equation (6).

[0079]

number

[0080] However, q DISCHARGE is the discharge power (unit: kW), and p SELL is the power sold (unit: kW).

[0081] (4) The formula for calculating the remaining capacity of the hydrogen tank is defined by equation (7).

[0082]

number

[0083] However, v tank is the remaining amount of hydrogen in the tank (unit: Nm3), and p WE is the electrolysis power of the water electrolysis device (unit: kW), and Conversion Hydrogen is the hydrogen production efficiency of the water electrolysis device (unit: Nm3 / kWh), and v fuelcell is the fuel cell operation plan (unit: Nm3). In this embodiment, the remaining amount of hydrogen in the hydrogen tank v tank There is no need to set a lower limit for

[0084] (5) The formula for calculating the remaining battery capacity is defined as equation (8).

[0085]

number

[0086] However, q SB is the remaining capacity of the storage battery (unit: kWh), and q DISCHARGE is the discharge power (unit: kW), and Efficiency DISCHARGE is the discharge conversion efficiency, and q CHARGE is the charging power (unit: kW), and Efficiency CHARGE is the charge conversion efficiency.

[0087] (6) The calculation formula for the electrolysis power of the water electrolysis device is defined by equation (9).

[0088]

number

[0089] However, p WE is the electrolysis power of the water electrolysis device (unit: kW), and p max WE is the rated power of the water electrolysis device (unit: kW), and p resolution is the output resolution of the water electrolysis device (unit: %), and p SWITCH is the operation switch for the water electrolysis device (0 = off, 1 = on).

[0090] A water electrolysis device is prone to deterioration when operated at its rated power. According to the constraints in equation (9), the upper limit of the electrolysis power of the water electrolysis device can be maintained lower than the rated output, enabling control that suppresses deterioration of the water electrolysis device.

[0091] (7) The charge / discharge relationship is defined by equation (10).

[0092]

number

[0093] However, p WE is the electrolysis power of the water electrolysis device (unit: kW), and p SELL is the power sold (unit: kW), and p BUY is the purchased power (unit: kW), and p PV is the amount of power generated by the solar panel (unit: kW), and qDISCHARGE is the discharge power (unit: kW), and q CHARGE is the charging power (unit: kW).

[0094] (Objective function) The objective function used in the optimization calculation is defined by equation (11).

[0095]

number

[0096] However, p WE is the electrolysis power of the water electrolysis device (unit: kW), and p SWITCH is the operation switch of the water electrolysis device (0 = off, 1 = on), and p BUY is the purchased power (unit: kW), and p SELL is the power sold (unit: kW), and q SB is the remaining capacity of the storage battery (unit: kWh), and q SB max is the rated capacity of the battery (unit: kWh).

[0097] The first and second terms of the objective function shown in equation (11) are terms for maximizing the electrolysis power of the water electrolysis device. Maximizing the electrolysis power of the water electrolysis device maximizes the amount of hydrogen produced by the water electrolysis device, and maximizes the amount of hydrogen available to the fuel cell.

[0098] The third and fourth terms of the objective function shown in equation (11) are terms for minimizing the power sold. Power sold indicates that surplus power is generated within the microgrid, so it is more efficient to keep the power sold as small as possible. However, if the power sold is not optimized, the constraints will not be satisfied when surplus power is generated, and there is a possibility that no solution will be found.

[0099] The fifth term of the objective function shown in equation (11) is a penalty related to deterioration of the water electrolysis device. The penalty increases as the amount of change or the number of changes in the electrolysis power of the water electrolysis device increases. Optimization to minimize this penalty reduces the amount of change or the number of changes in the electrolysis power of the water electrolysis device.

[0100] A large change in the electrolysis power or a large number of changes in the electrolysis power increases the load on the water electrolysis device, making it more susceptible to deterioration. By including a penalty related to deterioration of the water electrolysis device in the objective function, control that suppresses deterioration of the water electrolysis device becomes possible.

[0101] The sixth term of the objective function shown in equation (11) is a penalty related to the deterioration of the power storage device. This penalty takes a large value when the remaining charge of the power storage device is outside a predetermined range. By optimizing to minimize this penalty, the remaining charge of the power storage device is more likely to fall within the predetermined range.

[0102] A power storage device is prone to deterioration when its remaining capacity remains close to 0% or 100%. By including a penalty related to the deterioration of the power storage device in the objective function, it becomes possible to control the power storage device so as to suppress the deterioration.

[0103] (Initial value) After calculating the optimization result for the first optimization section, when performing optimization calculation for the second optimization section that is continuous in the time direction, the initial values ​​of the variables in the optimization calculation for the second optimization section are set based on the optimization result for the first optimization section. The variables for which the initial values ​​are set are the remaining capacity q of the storage battery, SB , remaining hydrogen tank volume v tank and the output resolution of the water electrolysis device p resolution Specifically, the optimization unit 130 calculates the formula (12).

[0104]

number

[0105] The combining unit 140 combines the operation plans of the microgrid 1 for the multiple optimization intervals optimized by the optimizing unit 130. The combining unit 140 may combine the operation plans of the microgrid 1 in chronological order of the optimization intervals. In this way, an operation plan of the microgrid 1 for the planning interval is generated.

[0106] 5 is a diagram showing an example of a method for combining optimization results. As shown in FIG. 5, the optimization results for each optimization section are max is an integer less than t max On the other hand, the planned section contains d times. In the example shown in Figure 5, d = n × t max Therefore, the optimization unit 130 repeatedly performs optimization calculations for n optimization intervals, and the combining unit 140 combines the n optimization results in chronological order. As a result, an operation plan for the microgrid 1 in a planning interval including d times is generated.

[0107] The adjusting unit 150 adjusts the operation plan of the fuel cell 16 based on the operation plan of the microgrid 1 connected by the connecting unit 140. The adjusting unit 150 may adjust the operation plan of the fuel cell 16 based on the operation plan of the water electrolysis device 14 included in the operation plan of the microgrid 1.

[0108] In this embodiment, the remaining amount v of the hydrogen tank 15 tank Therefore, in the operation plan for Microgrid 1, the remaining amount of hydrogen in the hydrogen tank 15, v tank can be a negative value. By adjusting the operation plan of the fuel cell 16 using the adjustment unit 150, it is possible to control the operation of the fuel cell 16 so as to maximize it within the capacity of the hydrogen tank 15.

[0109] <Fuel cell operation adjustment> The total amount of hydrogen produced by the water electrolysis device 14 is defined by equation (13).

[0110]

number

[0111] However, v WEsum is the total amount of hydrogen produced by the water electrolysis device (unit: Nm3), and t start is the time when the fuel cell starts to operate, and t end is the time when the fuel cell stops operating, and p WE is the electrolysis power of the water electrolysis device (unit: kW), and Conversion Hydrogen is the hydrogen production efficiency of the water electrolysis device (unit: Nm3 / kWh).

[0112] The amount of hydrogen that can be used by the fuel cell 16 to generate electricity is defined by equation (14).

[0113]

number

[0114] However, v availablefuel is the amount of hydrogen (unit: Nm3) that the fuel cell can use to generate electricity, and v tank initial is the initial value of the remaining amount of hydrogen in the hydrogen tank (unit: Nm3), and v WEsum is the total amount of hydrogen produced by the water electrolysis device (unit: Nm3).

[0115] If the fuel cell 16 is operated so as to satisfy the operating condition defined by equation (15), operation can be maximized within the capacity of the hydrogen tank 15.

[0116]

number

[0117] However, v availablefuel is the amount of hydrogen (unit: Nm3) that the fuel cell can use to generate electricity, and t optimized is the time when the fuel cell stops operating after the operation adjustment, and v fuelcell is the fuel cell operation plan (unit: Nm3).

[0118] The adjustment unit 150 adjusts the operation plan v of the fuel cell 16 so as to satisfy the formula (15). fuelcell Specifically, the adjustment unit 150 updates the start From time t optimized The operation plan of the fuel cell 16 is set so that it operates within the range up to and stops in other ranges. fuelcell In addition, the adjustment unit 150 updates the operation plan v of the fuel cell 16 after the operation adjustment. fuelcell Based on this, the remaining volume of hydrogen in the tank is v tank Specifically, the adjustment unit 150 calculates the equation (16).

[0119]

number

[0120] The output unit 160 outputs the operation plan of the microgrid 1. The output unit 160 may output the operation plan of the microgrid 1 to the display device 506 of the energy management system 10 or a terminal device connected to the energy management system 10. The output unit 160 may transmit the operation plan of the microgrid 1 to each device included in the microgrid 1.

[0121] The output unit 160 may transmit an operation plan for the water electrolysis device 14 included in the operation plan for the microgrid 1 to the water electrolysis device 14. The output unit 160 may transmit an operation plan for the storage battery 13 included in the operation plan for the microgrid 1 to the storage battery 13. The output unit 160 may transmit an operation plan for the fuel cell 16 adjusted by the adjustment unit 150 to the fuel cell 16.

[0122] <Energy management method processing procedure> An energy management method executed by the energy management system 10 will be described with reference to Fig. 6. Fig. 6 is a flowchart showing an example of the energy management method. The energy management method shown in Fig. 6 is repeatedly executed for the immediately succeeding planned section at predetermined time intervals while the microgrid 1 is in operation.

[0123] In step S1, the acquisition unit 110 of the energy management system 10 acquires the deterioration rate of the water electrolysis device 14, the remaining capacity of the storage battery 13, the remaining capacity of the hydrogen tank 15, the power generation amount of the solar panel 11, and the operation plan of the fuel cell 16. The acquisition unit 110 sends the deterioration rate of the water electrolysis device 14 to the determination unit 120. The acquisition unit 110 sends the remaining capacity of the storage battery 13, the remaining capacity of the hydrogen tank 15, the power generation amount of the solar panel 11, and the operation plan of the fuel cell 16 to the optimization unit 130.

[0124] In step S2, the determination unit 120 of the energy management system 10 receives the deterioration rate of the water electrolysis device 14 from the acquisition unit 110. The determination unit 120 determines a lower power limit value for the water electrolysis device 14 based on the deterioration rate of the water electrolysis device 14. The determination unit 120 sends the lower power limit value for the water electrolysis device 14 to the optimization unit 130.

[0125] In step S3, the optimization unit 130 of the energy management system 10 receives the remaining charge of the storage battery 13, the remaining charge of the hydrogen tank 15, the power generation amount of the solar panel 11, and the operation plan of the fuel cell 16 from the acquisition unit 110. The optimization unit 130 also receives the lower limit power value of the water electrolysis device 14 from the determination unit 120.

[0126] The optimization unit 130 optimizes the operation plan of the microgrid 1 in the current optimization section based on the lower power limit of the water electrolysis device 14, the remaining charge of the storage battery 13, the remaining charge of the hydrogen tank 15, the power generation amount of the solar panel 11, and the operation plan of the fuel cell 16. The operation plan of the microgrid 1 includes the operation plan of the water electrolysis device 14 and the operation plan of the storage battery 13.

[0127] In step S4, the optimization unit 130 of the energy management system 10 determines whether the combined time length of the optimized optimization sections is equal to or greater than the time length of the planned section. Specifically, the optimization unit 130 calculates the sum of the number of times included in the optimized optimization sections, and determines whether the sum of the number of times is equal to or greater than a predetermined threshold. The threshold is the number of times included in the planned section.

[0128] If the combined time length of the optimized optimization sections is less than the time length of the planned section (NO), the optimization unit 130 proceeds to step S5. On the other hand, if the combined time length of the optimized optimization sections is equal to or greater than the time length of the planned section (YES), the optimization unit 130 proceeds to step S6.

[0129] In step S5, the optimization unit 130 of the energy management system 10 sets initial values ​​of the variables of the optimization section to be next optimized based on the optimization results of the optimization section optimized in the most recent step S3. Then, the optimization unit 130 returns the process to step S3.

[0130] Returning to step S3, the optimizer 130 optimizes the operation plan of the microgrid 1 for the next optimization interval based on the initial value set in step S5. In this way, the optimizer 130 repeatedly optimizes the operation plan of the microgrid 1 for multiple optimization intervals that are consecutive in the time direction until the combined time length of the optimization intervals optimized in step S4 is equal to or greater than the time length of the planned interval.

[0131] In step S6, the combining unit 140 of the energy management system 10 combines the operation plans of the microgrid 1 in the multiple optimization sections optimized in step S3 in the chronological order of the optimization sections. The combining unit 140 sends the combined operation plan of the microgrid 1 to the adjusting unit 150 and the output unit 160.

[0132] In step S7, the adjustment unit 150 of the energy management system 10 receives the operation plan of the microgrid 1 from the connection unit 140. The adjustment unit 150 adjusts the operation plan of the fuel cell 16 based on the operation plan of the microgrid 1. The adjustment unit 150 sends the operation plan of the fuel cell 16 after the operation adjustment to the output unit 160.

[0133] In step S8, the output unit 160 of the energy management system 10 receives the operation plan of the microgrid 1 from the coupling unit 140. The output unit 160 also receives the operation plan of the fuel cell 16 from the adjustment unit 150.

[0134] The output unit 160 transmits the operation plan of the water electrolysis device 14, which is included in the operation plan of the microgrid 1, to the water electrolysis device 14. The output unit 160 transmits the operation plan of the storage battery 13, which is included in the operation plan of the microgrid 1, to the storage battery 13. The output unit 160 transmits the operation plan of the fuel cell 16 after the operation adjustment to the fuel cell 16.

[0135] The water electrolysis device 14 receives an operation plan for the water electrolysis device 14 from the energy management system 10. The operation plan for the water electrolysis device 14 indicates the electrolysis power of the water electrolysis device 14 at multiple times included in the planned interval. The water electrolysis device 14 electrolyzes water to generate hydrogen in accordance with the electrolysis power indicated in the operation plan received from the energy management system 10. The hydrogen generated by the water electrolysis device 14 is stored in the hydrogen tank 15.

[0136] The storage battery 13 receives an operation plan for the storage battery 13 from the energy management system 10. The operation plan for the storage battery 13 indicates the charging power and discharging power of the storage battery 13 at multiple times included in the planned interval. The storage battery 13 charges or discharges in accordance with the charging power and discharging power indicated in the operation plan received from the energy management system 10.

[0137] The fuel cell 16 receives an operation plan for the fuel cell 16 from the energy management system 10. The operation plan for the fuel cell 16 indicates the power generation time and hydrogen consumption amount at multiple times included in the planned section. The fuel cell 16 generates electricity using hydrogen stored in the hydrogen tank 15 in accordance with the power generation time and hydrogen consumption amount indicated in the operation plan received from the energy management system 10.

[0138] <Effects of the first embodiment> An energy management system 10 according to this embodiment manages a microgrid 1 that includes solar panels 11 that generate electric power, a storage battery 13 that stores the electric power, and a water electrolysis device 14 that uses the electric power to generate hydrogen. The energy management system 10 optimizes an operation plan for the water electrolysis device 14 based on the amount of power generated by the solar panels 11 and the amount of hydrogen consumed by the water electrolysis device 14. The energy management system 10 can optimize the operation plan for the water electrolysis device 14 while taking into account the charging power and discharging power of the storage battery 13. In one aspect, this embodiment enables the water electrolysis device 14 to be operated efficiently.

[0139] The operation plan for the water electrolysis device 14 may include the electrolysis power of the water electrolysis device 14. The energy management system 10 may optimize the operation plan for the water electrolysis device 14 so as to maximize the electrolysis power of the water electrolysis device 14. The energy management system 10 may optimize the operation plan for the water electrolysis device 14 so as to satisfy a constraint on the amount of change in the electrolysis power of the water electrolysis device 14. In one aspect, according to the present embodiment, the amount of hydrogen produced by the water electrolysis device 14 can be maximized.

[0140] The energy management system 10 may optimize an operation plan for the storage battery 13. The operation plan for the storage battery 13 may include charging power and discharging power of the storage battery 13. According to one aspect, the present embodiment allows the storage battery 13 to be operated efficiently.

[0141] The energy management system 10 may be connected to the power grid 2. The energy management system 10 may optimize the operation plan of the water electrolysis device 14 so as to minimize the amount of power purchased from and sold to the power grid 2. According to one aspect, the present embodiment minimizes surplus power in the microgrid 1, thereby enabling efficient use of power generated by the solar panel 11.

[0142] The microgrid 1 may include a fuel cell 16 that generates power using hydrogen. The energy management system 10 may obtain the consumption amount of hydrogen produced by the water electrolysis device 14 based on the operation plan of the fuel cell 16. The energy management system 10 may adjust the operation plan of the fuel cell 16 based on the operation plan of the water electrolysis device 14. In one aspect, according to the present embodiment, hydrogen demand can be obtained with high accuracy, and therefore the operation plan of the water electrolysis device 14 can be optimized with high accuracy.

[0143] The energy management system 10 according to this embodiment optimizes the operation plan for the water electrolysis device 14 so that the electrolysis power of the water electrolysis device 14 satisfies constraints related to the amount, range, and frequency of change. Deterioration of the water electrolysis device 14 can be suppressed by operating within a margin from the upper or lower limit of the electrolysis power. Furthermore, sudden or frequent changes in the electrolysis power make the water electrolysis device 14 more susceptible to deterioration. In one aspect, this embodiment enables efficient suppression of deterioration of the water electrolysis device 14.

[0144] The constraints on the range of change may include an upper power limit that is lower than the rated power of the water electrolysis device 14, and a lower power limit that ensures that the hydrogen production efficiency of the water electrolysis device 14 is equal to or greater than a predetermined value. The energy management system 10 may determine the lower power limit of the water electrolysis device 14 based on the deterioration rate of the water electrolysis device 14. In one aspect, according to the present embodiment, a constant hydrogen production efficiency can be maintained in consideration of the deterioration rate of the water electrolysis device 14.

[0145] The energy management system 10 may optimize the operation plan for the water electrolysis device 14 so as to minimize the penalty associated with the deterioration of the water electrolysis device 14. The penalty associated with the deterioration of the water electrolysis device 14 may take a larger value as the amount of change or the number of changes in the electrolysis power of the water electrolysis device 14 increases. The water electrolysis device 14 is more likely to deteriorate as the amount of change or the number of changes in the electrolysis power increases. In one aspect, according to the present embodiment, deterioration of the water electrolysis device 14 can be suppressed.

[0146] The microgrid 1 may include a storage battery 13 that stores power. The energy management system 10 may further optimize an operation plan for the storage battery 13. The energy management system 10 may optimize the operation plan for the storage battery 13 so as to minimize a penalty related to deterioration of the storage battery 13. The penalty related to deterioration of the storage battery 13 may take a large value when the remaining charge of the storage battery 13 is outside a predetermined range. The storage battery 13 is more likely to deteriorate when the remaining charge fluctuates within a range close to 0% or 100%. In one aspect, according to this embodiment, deterioration of the storage battery 13 can be suppressed.

[0147] The energy management system 10 according to this embodiment optimizes the operation plan of the microgrid 1 in an optimization interval of a predetermined time length, repeatedly executing the optimization for each of multiple optimization intervals, and combines the operation plans of the microgrid 1 optimized for each of the multiple time intervals. If the time interval targeted by the optimization calculation is long, the amount of calculation becomes enormous, increasing the possibility of the optimization calculation failing due to inability to execute or a timeout. By combining the results of optimization calculations performed over short time intervals, the amount of calculation required for a single optimization calculation can be reduced, and the possibility of the optimization calculation failing can be reduced. In one aspect, according to this embodiment, the operation plan of the microgrid 1 can be optimized with a small amount of calculation.

[0148] The energy management system 10 may repeatedly optimize operation plans in successive optimization intervals in the time direction until the combined time length of a plurality of optimization intervals becomes equal to or greater than a threshold. When optimizing an operation plan in an optimization interval successive to a preceding optimization interval, the energy management system 10 may set an initial value of the operation plan in the subsequent optimization interval based on the operation plan in the preceding optimization interval. In one aspect, according to this embodiment, an operation plan in a planning interval longer than an optimization interval can be optimized with a small amount of calculation.

[0149] The microgrid 1 may include a water electrolysis device 14 that generates hydrogen using electric power. The operation plan of the microgrid 1 may include the electrolysis power of the water electrolysis device 14 at multiple times included in the optimization interval. The energy management system 10 may set the electrolysis power at the last time of the preceding optimization interval to the electrolysis power at the time immediately before the subsequent optimization interval. In one aspect, according to the present embodiment, the operation plan of the water electrolysis device 14 in the plan interval can be optimized with a small amount of calculation.

[0150] The microgrid 1 may include a storage battery 13 that stores power. The operation plan of the microgrid 1 may include the remaining capacity of the storage battery 13 at multiple times included in the optimization interval. The energy management system 10 may set the remaining capacity at the last time of the preceding optimization interval to the remaining capacity at the time immediately before the subsequent optimization interval. In one aspect, according to the present embodiment, the operation plan of the water electrolysis device 14 in the planned interval can be optimized with a small amount of calculation.

[0151] The microgrid 1 may include a hydrogen tank 15 that stores hydrogen. The operation plan for the microgrid 1 may include the remaining amount of hydrogen in the hydrogen tank 15 at multiple times included in the optimization interval. The energy management system 10 may set the remaining amount at the end of the preceding optimization interval to the remaining amount at the time immediately before the subsequent optimization interval. In one aspect, according to this embodiment, the operation plan for the water electrolysis device 14 in the planned interval can be optimized with a small amount of calculation.

[0152] [Second embodiment] In the second embodiment, the hydrogen production device may include a plurality of water electrolysis devices 14. In such a case, current is supplied from the power conditioner 12 to each of the plurality of water electrolysis devices 14.

[0153] When the deterioration rates of the water electrolysis devices 14 are different, the determination unit 120 may perform control to prioritize the water electrolysis device with the least deterioration and increase the production amount. Alternatively, the amount of hydrogen supplied from each water electrolysis device 14 may be made approximately the same by setting the electrolysis power of each water electrolysis device 14 so that all water electrolysis devices 14 satisfy the minimum hydrogen production efficiency.

[0154] The optimization unit 130 may optimize the operation plan of the microgrid 1 based on the lower power limit value of each water electrolysis device 14, etc. In such a case, the amount of hydrogen to be supplied from each water electrolysis device 14 may be set to a value obtained by dividing the remaining capacity of the hydrogen tank 15 by the number of water electrolysis devices 14. The optimization unit 130 also receives the remaining capacity of the storage battery 13, the remaining capacity of the hydrogen tank 15, the amount of power generated by the solar panel 11, and the operation plan of the fuel cell 16 from the acquisition unit 110.

[0155] Furthermore, in another new embodiment, the microgrid 1 may include a plurality of sets, each set being a combination of a water electrolysis device 14, a hydrogen tank 15, a fuel cell 16, a solar panel 11, and a storage battery 13. In such a case, the optimization unit 130 of the energy management system 10 receives from the acquisition unit 110 the remaining charge of each storage battery 13, the remaining charge of each hydrogen tank 15, the power generation amount of each solar panel 11, and the operation plan of each fuel cell 16. The optimization unit 130 also receives the lower limit power value of each water electrolysis device 14 from the determination unit 120.

[0156] The optimization unit 130 then optimizes the operation plan of the microgrid 1 in the current optimization section based on the lower limit power value of each water electrolysis device 14, the remaining charge of each storage battery 13, the remaining charge of each hydrogen tank 15, the power generation amount of each solar panel 11, and the operation plan of each fuel cell 16. If the remaining charge of each storage battery 13, the remaining charge of each hydrogen tank 15, the power generation amount of each solar panel 11, the lower limit power value of each water electrolysis device 14, etc. are approximately the same, the average value of each may be calculated, and the operation plan of the microgrid 1 may be optimized based on each average value, etc. This method reduces the amount of data, thereby shortening the time required for optimization.

[0157] In the second embodiment described above, the data storage device 504 (SSD, HDD, etc.) that stores the measurement data and calculation result data, and the CPU 501 that performs the optimization calculation are implemented by local hardware, but this is not limited to this and may also be provided on the cloud side.

[0158] [Third embodiment] The energy management system 1000 according to the third embodiment optimally operates the microgrid 100 based on the priority of devices determined from the responsiveness and evaluation index of the devices.

[0159] The microgrid in this embodiment includes multiple types of energy storage devices and hydrogen-related equipment. Focusing on responsiveness as an operating characteristic of the energy storage devices, the microgrid can be optimally operated based on various evaluation indices. For example, when multiple types of energy storage devices with different responsiveness are included, an operation plan can be developed taking into account constraints arising from the differences in responsiveness, enabling efficient operation of the microgrid. Furthermore, when multiple types of energy storage devices with different characteristics are included, an operation plan can be developed taking into account constraints arising from the differences in characteristics, enabling optimal operation of the microgrid based on various evaluation indices. More specifically, assuming linkage with the wholesale electricity market, various energy storage devices and hydrogen-related equipment are used to minimize the cost of electricity trading for the building's energy load (electricity and heat). Alternatively, the cost of received power over a certain period of time can be minimized. Furthermore, the degree of deterioration of each component device is quantified as a cost, and a control plan that minimizes the degree of deterioration is implemented. Furthermore, if it is desired to set priorities among identical element devices (such as storage batteries) and if the priorities are not reflected in the above-mentioned costs, the priorities of each device are set as constraints. In this embodiment, an optimal energy management system is realized based on the above-mentioned concept.

[0160] <Overall configuration of microgrid> The overall configuration of the microgrid in this embodiment will be described with reference to Fig. 7. Fig. 7 is a block diagram showing an example of the overall configuration of the microgrid in this embodiment.

[0161] 7, the microgrid 100 in this embodiment is connected to a grid 200 via a power distribution line E. The grid 200 is a power system different from the microgrid 100, and is managed by an energy supplier different from the operator of the microgrid 100.

[0162] The microgrid 100 in this embodiment includes a consumer 300, an energy management system 1000, a solar power generation system 1100, a biomass power generation system 1200, a plurality of storage batteries 1300 (a first storage battery 1300-1 and a second storage battery 1300-2), a power storage control device 1400, a heat storage device 1500, a water electrolysis device 1600, a fuel cell 1700, a hydrogen storage device 1800, a hydrogen boiler 1900, and a heat source device 2000.

[0163] The solar power generation system 1100, the biomass power generation system 1200, the storage battery 1300, the water electrolysis system 1600, the fuel cell 1700, and the heat source system 2000 are connected to a power distribution line E. The heat storage system 1500 and the hydrogen boiler 1900 are connected to a heat transfer line H. The consumer 300, the biomass power generation system 1200, the fuel cell 1700, and the heat source system 2000 are connected to the power distribution line E and the heat transfer line H. The microgrid 100 supplies electric power and thermal energy to the consumer 300 through the power distribution line E and the heat transfer line H.

[0164] The consumer 300 is a facility to which energy is supplied, such as a factory or a building. The consumer 300 consumes electric power and thermal energy by supplying the electric power supplied through the power distribution line E and the thermal energy supplied through the heat transfer line H to devices installed within the facility.

[0165] The energy management system 1000, the solar power generation system 1100, the biomass power generation system 1200, the power storage control device 1400, the heat storage device 1500, the water electrolysis device 1600, the fuel cell 1700, the hydrogen storage device 1800, and the heat source device 2000 are connected to a communication network N100 such as a LAN (Local Area Network). The first storage battery 1300-1, the second storage battery 1300-2, and the power storage control device 1400 are connected to a communication network N200. The communication network N100 and the communication network N200 may be two mutually closed networks, two networks that can communicate with each other, or the same network.

[0166] The energy management system 1000, the solar power generation system 1100, the biomass power generation system 1200, the power storage control device 1400, the heat storage device 1500, the water electrolysis device 1600, the fuel cell 1700, the hydrogen storage device 1800, and the heat source device 2000 can communicate with each other via a communication network N100. The first storage battery 1300-1, the second storage battery 1300-2, and the power storage control device 1400 can communicate with each other via a communication network N200.

[0167] The solar power generation plant 1100, biomass power generation plant 1200, power storage control device 1400, heat storage device 1500, water electrolysis device 1600, fuel cell 1700, hydrogen storage device 1800, and heat source device 2000 provide operating data to the energy management system 1000. The energy management system 1000 formulates an operating plan based on the operating data provided by each device. The solar power generation plant 1100, biomass power generation plant 1200, power storage control device 1400, heat storage device 1500, water electrolysis device 1600, fuel cell 1700, hydrogen storage device 1800, and heat source device 2000 operate in accordance with the operating plan formulated by the energy management system 1000. The power storage control device 1400 controls the operation of the first storage battery 1300-1 and the second storage battery 1300-2 in accordance with the operating plan formulated by the energy management system 1000.

[0168] The solar power generation device 1100 is a renewable energy power generation device that generates electric power using sunlight and supplies the electric power to the microgrid 100 through the power distribution line E. The electric power generated by the solar power generation device 1100 is supplied to the power distribution line E.

[0169] The biomass power generation plant 1200 is a renewable energy power generation plant that generates power using biomass as fuel. The biomass power generation plant 1200 is also a cogeneration system that supplies heat generated during power generation. The power generated by the biomass power generation plant 1200 is supplied to a power distribution line E. The heat recovered by the biomass power generation plant 1200 is supplied to a heat transfer line H.

[0170] The storage battery 1300 is an energy storage device that repeatedly stores electricity through an electrochemical reaction and discharges the stored electricity. The first storage battery 1300-1 and the second storage battery 1300-2 are storage batteries with different characteristics. In this embodiment, the characteristics of the storage batteries include, for example, the type (material), storage capacity, years of use, or number of charge / discharge cycles. Examples of different types of storage batteries are a lithium-ion battery and a sodium-sulfur battery (NAS battery).

[0171] The storage battery 1300 stores or discharges electricity according to the balance between supply and demand of electricity in the microgrid 100. When the amount of electricity generated in the microgrid 100 exceeds the amount of electricity consumed, causing surplus electricity, the storage battery 1300 stores the electricity supplied from the electricity distribution line E. When the amount of electricity consumed exceeds the amount of electricity generated, causing a shortage of electricity consumed by the consumers 300, the storage battery 1300 releases the stored electricity to the electricity distribution line E.

[0172] The power storage control device 1400 controls the amounts of stored and discharged power in the first storage battery 1300-1 and the second storage battery 1300-2 in accordance with an operation plan formulated by the energy management system 1000. The power storage control device 1400 in this embodiment performs priority control to determine which storage battery to use with priority from the first storage battery 1300-1 and the second storage battery 1300-2 in power storage or discharge.

[0173] The thermal storage device 1500 is an energy storage device that alternates between storing thermal energy generated in a heat source facility and discharging the stored thermal energy. The thermal storage device 1500 stores thermal energy in a thermal storage layer filled with water, ice, steam, a thermal storage material, or the like. For example, an adsorbent called HASClay, which is disclosed in Reference 1 below, can be used as the thermal storage material.

[0174] [Reference 1] Yoshishi Kamata, Risuke Kawakami, Takamasa Oyama, Satoshi Matsuda, Masaya Suzuki, Kenji Maruge, Kazumasa Yamauchi, Hidetaka Miyahara, Katsuya Matsunaga, Masayuki Tanino, "Development of an open-type adsorbent thermal storage heat pump system using HASClay (Part 1) Experimental results of a small-scale device and a calculation model for the adsorbent thermal storage tank," Transactions of the Society of Heating, Air-Conditioning and Sanitary Engineers of Japan, No. 281, pp. 9-16, 2020.

[0175] The thermal storage device 1500 stores or releases heat depending on the balance between supply and demand of thermal energy in the microgrid 100 and the remaining capacity of the storage battery 1300. When the amount of heat generated in the microgrid 100 exceeds the amount of heat consumed and surplus heat is generated, the thermal storage device 1500 stores the thermal energy of the heat medium in the pipes connected to the biomass power generation plant 1200 and the fuel cell 1700. When the amount of heat consumed in the microgrid 100 exceeds the amount of heat generated and the thermal energy consumed by the consumer 300 is insufficient, the thermal storage device 1500 releases the stored thermal energy to the heat transfer line H.

[0176] The thermal storage device 1500 uses an evaluation index that prioritizes power storage over heat storage, and when the amount of power generated in the microgrid 100 exceeds the amount of power consumed, surplus power is generated, and the capacity of the storage battery reaches its maximum, the thermal storage device 1500 stores thermal energy generated from the heat source device 2000 operated by the surplus power. When the amount of power generated in the microgrid 100 falls below the amount of power consumed and it is predicted that the received power will increase, for example, during a time period when electricity rates are high, the thermal storage device 1500 operates the heat source device 2000 to store thermal energy in advance.

[0177] The water electrolysis device 1600 is an energy conversion device that produces hydrogen by electrolyzing water. The hydrogen produced by the water electrolysis device 1600 can be used to generate electricity in a fuel cell 1700. The hydrogen produced by the water electrolysis device 1600 is stored in a hydrogen storage device 1800.

[0178] The fuel cell 1700 is a power generation device that generates electricity using chemical energy of fuel through an electrochemical reaction. The fuel cell 1700 in this embodiment is a hydrogen fuel cell that generates electricity using hydrogen as fuel. The fuel cell 1700 generates electricity using hydrogen produced by the water electrolysis device 1600 and stored in the hydrogen storage device 1800. The fuel cell 1700 also functions as a cogeneration system that recovers waste heat generated during the electrochemical reaction. The electricity generated by the fuel cell 1700 is supplied to a power distribution line E. The heat recovered by the fuel cell 1700 is supplied to a heat transfer line H.

[0179] In this embodiment, the storage battery 1300 and the hydrogen storage device 1800 are energy storage devices with different responsiveness. The responsiveness in this embodiment includes the processing time required for planned or unexpected start-up and shutdown of the energy storage device. For example, the water electrolysis device 1600 requires time after start-up until it can stably produce hydrogen. Therefore, the hydrogen storage device 1800, which stores the hydrogen produced by the water electrolysis device 1600, has a slower responsiveness than the storage battery 1300.

[0180] The energy management system 1000 collects operation data at predetermined time intervals (hereinafter also referred to as "measurement intervals") from each device connected to the microgrid 100. The energy management system 1000 also transmits an operation plan generated based on the collected operation data to each device at predetermined time intervals (hereinafter also referred to as "control intervals").

[0181] The energy management system 1000 collects the amount of power generated and controls the output for the solar power generation system 1100. The energy management system 1000 collects the amount of power generated and the amount of recovered heat and controls the output for the biomass power generation system 1200 and the fuel cell 1700. The energy management system 1000 collects the amount of stored power for the power storage control device 1400 and controls the input / output power of the storage battery.

[0182] The energy management system 1000 collects the amount of heat stored and controls the amount of heat stored and released for the heat storage device 1500. The energy management system 1000 collects the amount of hydrogen produced and controls the input power for the water electrolysis device 1600. The energy management system 1000 collects the amount of hydrogen stored for the hydrogen storage device 1800. The energy management system 1000 collects the output and controls the amount of heat released for the heat source device 2000.

[0183] When controlling input / output power (controlling the amount of stored power), the energy management system 1000 controls the storage device with high responsiveness to store power preferentially. A storage battery 1300 with high responsiveness and a water electrolysis device 1600 with low responsiveness are connected to the microgrid 100 in this embodiment. Therefore, the energy management system 1000 controls the water electrolysis device 1600 to produce hydrogen preferentially when an evaluation index that prioritizes hydrogen production is used and the water electrolysis device 1600 is capable of producing hydrogen, and controls the storage battery 1300 to be charged preferentially when the water electrolysis device 1600 is not capable of producing hydrogen. Note that the energy management system 1000 may also control the storage battery 1300 to be charged preferentially and hydrogen to be produced by the water electrolysis device 1600 using surplus power, even when an evaluation index that prioritizes hydrogen production is used and the water electrolysis device 1600 is capable of producing hydrogen.

[0184] <Hardware configuration of the energy management system> The hardware configuration of the energy management system according to this embodiment will be described.

[0185] <Computer hardware configuration> The energy management system 1000 in this embodiment is realized by, for example, a computer.

[0186] The computer 500 includes a CPU (Central Processing Unit) 501, a ROM (Read Only Memory) 502, a RAM (Random Access Memory) 503, an HDD (Hard Disk Drive) 504, an input device 505, a display device 506, a communication I / F (Interface) 507, and an external I / F 508. The CPU 501, the ROM 502, and the RAM 503 form a so-called computer. The hardware components of the computer 500 are connected to each other via a bus line 509. The input device 505 and the display device 506 may be connected to the external I / F 508 for use.

[0187] The CPU 501 is a computing device that controls the entire computer 500 and realizes its functions by reading programs and data from a storage device such as the ROM 502 or HDD 504 onto the RAM 503 and executing the processes.

[0188] The ROM 502 is an example of a non-volatile semiconductor memory (storage device) that can retain programs and data even when the power is turned off. The ROM 502 functions as a main storage device that stores various programs, data, etc. required for the CPU 501 to execute various programs installed in the HDD 504. Specifically, the ROM 502 stores boot programs such as a Basic Input / Output System (BIOS) and an Extensible Firmware Interface (EFI) that are executed when the computer 500 starts up, as well as data such as OS (Operating System) settings and network settings.

[0189] The RAM 503 is an example of a volatile semiconductor memory (storage device) in which programs and data are erased when the power is turned off. The RAM 503 is, for example, a dynamic random access memory (DRAM) or a static random access memory (SRAM). The RAM 503 provides a working area in which various programs installed in the HDD 504 are expanded when executed by the CPU 501.

[0190] The HDD 504 is an example of a non-volatile storage device that stores programs and data. The programs and data stored in the HDD 504 include an OS, which is basic software that controls the entire computer 500, and applications that provide various functions on the OS. Note that the computer 500 may use a storage device that uses flash memory as a storage medium (e.g., an SSD (Solid State Drive)) instead of the HDD 504.

[0191] The input device 505 includes a touch panel, operation keys and buttons, a keyboard and mouse, a microphone for inputting sound data such as voice, and the like, which are used by the user to input various signals.

[0192] The display device 506 is configured with a display such as a liquid crystal display or organic EL (Electro-Luminescence) display for displaying a screen, a speaker for outputting sound data such as voice, and the like.

[0193] The communication I / F 507 is an interface that connects to a communication network and enables the computer 500 to perform data communication.

[0194] The external I / F 508 is an interface with external devices, such as a drive device 510.

[0195] The drive device 510 is a device for loading a recording medium 511. The recording medium 511 here includes media that record information optically, electrically, or magnetically, such as a CD-ROM, a flexible disk, or a magneto-optical disk. The recording medium 511 may also include semiconductor memories that record information electrically, such as ROMs and flash memories. This allows the computer 500 to read from and / or write to the recording medium 511 via the external I / F 508.

[0196] The various programs to be installed in the HDD 504 are installed, for example, by setting the distributed recording medium 511 in a drive device 510 connected to the external I / F 508 and reading out the various programs recorded on the recording medium 511 by the drive device 510. Alternatively, the various programs to be installed in the HDD 504 may be installed by being downloaded via the communication I / F 507 from a network different from the communication network.

[0197] <Functional configuration of the energy management system> The functional configuration of the energy management system in this embodiment will be described with reference to Fig. 8. Fig. 8 is a block diagram showing an example of the functional configuration of an energy management system 1000 in this embodiment.

[0198] <Functional configuration of the energy management system> As shown in FIG. 8 , the energy management system 1000 in this embodiment includes an operation data collection unit 10100, a status acquisition unit 10200, a demand prediction unit 10300, a characteristic acquisition unit 10400, a supply prediction unit 10500, an optimization unit 10600, and an operation planning unit 10700.

[0199] The operation data collection unit 10100, status acquisition unit 10200, demand forecasting unit 10300, characteristic acquisition unit 10400, supply forecasting unit 10500, optimization unit 10600, and operation planning unit 10700 are realized by processing executed by the CPU 501 using a program expanded from the HDD 504 onto the RAM 503.

[0200] The operation data collection unit 10100 collects operation data from each device connected to the microgrid 100. The devices from which the operation data collection unit 10100 acquires operation data include at least the solar power generation device 1100, the biomass power generation device 1200, the power storage control device 1400, the heat storage device 1500, the water electrolysis device 1600, the fuel cell 1700, and the heat source device 2000.

[0201] The driving data collection unit 10100 collects driving data at a predetermined measurement interval. The predetermined measurement interval may be, for example, one minute. The measurement interval may vary depending on the device from which the data is collected.

[0202] The status acquisition unit 10200 acquires the operating status of each device connected to the microgrid 100 based on the operating data collected by the operating data collection unit 10100. The devices from which the status acquisition unit 10200 acquires the operating status include at least the water electrolysis device 1600.

[0203] The operating data collected from the solar power generation plant 1100 includes the amount of power generated by the solar power generation plant 1100. The operating data collected from the biomass power generation plant 1200 includes the amount of power generated and the amount of heat recovered by the biomass power generation plant 1200. The operating data collected from the power storage control device 1400 includes the amount of power stored and discharged by the first storage battery 1300-1 and the second storage battery 1300-2. The operating data collected from the heat storage device 1500 includes the amount of heat stored and the amount of heat released by the heat storage device 1500.

[0204] The operating data collected from the water electrolysis device 1600 includes the input power and hydrogen production amount of the water electrolysis device 1600. The operating data collected from the fuel cell 1700 includes the power generation amount and heat recovery amount of the fuel cell 1700. The operating data collected from the hydrogen storage device 1800 includes the hydrogen storage amount of the hydrogen storage device 1800. The operating data collected from the heat source device 2000 includes the input power and heat release amount of the heat source device 2000.

[0205] The demand forecasting unit 10300 forecasts the power demand, heat demand, and hydrogen demand in the microgrid 100 based on the operation data collected by the operation data collecting unit 10100 .

[0206] The demand prediction unit 10300 predicts the electricity demand, heat demand, and hydrogen demand of the consumer 300 for a predetermined prediction period based on the operation data collected by the operation data collection unit 10100. The prediction of the electricity demand, heat demand, and hydrogen demand may be calculated based on actual measured values ​​from sensors or the like possessed by each device, or may be performed based on a regression model based on past operation data. The structure of the regression model may be a machine learning model, a neural network, or a deep neural network.

[0207] The supply prediction unit 10500 predicts the amount of power supply, the amount of thermal energy supply, and the amount of hydrogen supply in the microgrid 100 based on the operation data collected by the operation data collection unit 10100 .

[0208] The supply prediction unit 10500 predicts the amount of power supply, amount of thermal energy supply, and amount of hydrogen supply to the consumer 300 for a predetermined prediction period based on the operation data collected by the operation data collection unit 10100. The prediction of the amount of power supply, amount of thermal energy supply, and amount of hydrogen supply may be calculated based on actual measured values ​​from sensors or the like possessed by each device, or may be based on a regression model based on past operation data. The structure of the regression model may be a machine learning model, a neural network, or a deep neural network.

[0209] The characteristic acquisition unit 10400 acquires the characteristics of each device connected to the microgrid 100. The devices from which the characteristic acquisition unit 10400 acquires the characteristics include at least the first storage battery 1300-1 and the second storage battery 1300-2. Information indicating the characteristics of each device connected to the microgrid 100 may be set in advance by an operator or manager of the microgrid 100, or may be included in the operation data.

[0210] The optimization unit 10600 creates an operation plan for each device that best satisfies the preset evaluation indexes based on the operating status of each device acquired by the status acquisition unit 10200, the power demand, heat demand, and hydrogen demand of the consumer 300 predicted by the demand prediction unit 10300, the characteristics of each device acquired by the characteristics acquisition unit 10400, and the power supply, thermal energy supply, and hydrogen supply of each device predicted by the supply prediction unit 10500.

[0211] The operation planner 10700 transmits the operation plan generated by the optimizer 10600 to each device connected to the microgrid 100. The devices to which the operation planner 10700 transmits the operation plan include at least the solar power generation device 1100, the biomass power generation device 1200, the power storage control device 1400, the heat storage device 1500, the water electrolysis device 1600, the fuel cell 1700, and the heat source device 2000.

[0212] The operation plan unit 10700 transmits the operation plan at a predetermined control interval. The predetermined control interval may be, for example, 10 minutes. The control interval may vary depending on the destination device.

[0213] <Energy management system processing procedure> The processing procedure of the energy management method executed by the energy management system 1000 in this embodiment will be described.

[0214] In step S1, the operating data collection unit 10100 of the energy management system 1000 collects operating data from the power storage control device 1400 and the water electrolysis device 1600. The operating data collection unit 10100 stores the collected operating data in a storage device such as the HDD 504.

[0215] In step S2, the status acquisition unit 10200 of the energy management system 1000 reads out the operating data stored in the storage device. Based on the read out operating data, the status acquisition unit 10200 acquires the operating status of the water electrolysis apparatus 1600. The status acquisition unit 10200 sends the acquired operating status of the water electrolysis apparatus 1600 to the optimization unit 10600.

[0216] The operating state of the water electrolysis apparatus 1600 is information that can be used to determine whether the water electrolysis apparatus 1600 is in a state where it can produce hydrogen. The operating state of the water electrolysis apparatus 1600 can be determined based on the amount of change in the amount of hydrogen produced in the operating data collected from the water electrolysis apparatus 1600. If the operating data collected from the water electrolysis apparatus 1600 includes information indicating the operating state, that information can be acquired.

[0217] In step S3, the optimization unit 10600 of the energy management system 1000 receives the operation status of the water electrolysis device 1600 from the status acquisition unit 10200. The optimization unit 10600 determines the operation priority order between the storage battery 1300 and the water electrolysis device 1600 based on the operation status of the water electrolysis device 1600.

[0218] The operation priority is information that indicates the order of priority for use in charging and discharging at each time. That is, when charging, the power storage device with the highest operation priority is charged first, and when it is fully charged, the power storage device with the next highest operation priority is charged. When discharging, the power storage device with the highest operation priority is discharged first, and when sufficient output cannot be obtained, the power storage device with the next highest operation priority is discharged.

[0219] When an evaluation index that prioritizes hydrogen production is used and the water electrolysis apparatus 1600 is in an operating state where hydrogen can be produced, the optimization unit 10600 increases the operating priority of the water electrolysis apparatus 1600. When the water electrolysis apparatus 1600 is not in an operating state where hydrogen can be produced, the optimization unit 10600 increases the operating priority of the storage battery 1300. Since the water electrolysis apparatus 1600 takes longer to start and stop than the storage battery 1300, it is efficient to prioritize the storage battery 1300 for charging and discharging when the water electrolysis apparatus 1600 is not in an operating state where hydrogen can be produced.

[0220] The optimization unit 10600 may set the operation priority of the storage battery 1300 higher than that of the water electrolysis device 1600, regardless of the operating state of the water electrolysis device 1600. The storage battery 1300 has a characteristic that the amount of stored electricity gradually decreases due to self-discharge. For example, the amount of stored electricity of the storage battery 1300 decreases by 5% over the course of one month from a fully charged state. On the other hand, the amount of hydrogen produced by the water electrolysis device 1600 does not decrease over time. Therefore, it may be efficient to set the operation priority of the storage battery 1300 higher in order to preferentially use the electricity stored in the storage battery 1300.

[0221] In step S4, the optimization unit 10600 of the energy management system 1000 creates an operation plan including a charge / discharge plan for each of the storage battery 1300 and the water electrolysis device 1600, based on the operation priority order determined in step S3. The charge / discharge plan is information that indicates the amount of electricity to be stored and discharged in a predetermined time interval. The operation plan unit 10700 transmits the operation plan created by the optimization unit 10600 to the electricity storage control device 1400 and the water electrolysis device 1600.

[0222] According to this operation plan, when an evaluation index that prioritizes hydrogen production is used and the water electrolysis apparatus 1600 is in an operating state where hydrogen can be produced, control is performed to preferentially charge the water electrolysis apparatus 1600. Conversely, when the water electrolysis apparatus 1600 is not in an operating state where hydrogen can be produced, control is performed to preferentially charge the storage battery 1300. Note that when charging the storage battery 1300, whether the first storage battery 1300-1 or the second storage battery 1300-2 is to be preferentially charged may be determined by any method.

[0223] There may be a case where the charge / discharge plan included in the operation plan cannot be achieved, and even though the water electrolysis device 1600 is in an operating state where it can produce hydrogen, the power required for hydrogen production cannot be supplied to the water electrolysis device 1600. In this case, the energy management system 1000 may increase the discharge rate of the storage battery 1300 so that the power required for hydrogen production is supplied to the water electrolysis device 1600.

[0224] <Effects of the third embodiment> The energy management system of this embodiment determines an operation priority order according to the type of energy storage device in a microgrid including multiple types of energy storage devices, and creates an operation plan for each energy storage device according to the operation priority order. Therefore, the energy management system of this embodiment can efficiently operate a microgrid including multiple energy storage devices of different types.

[0225] The energy management system of this embodiment determines an operational priority based on the operational status of a water electrolysis device that produces hydrogen in a microgrid that includes a hydrogen storage device that stores hydrogen as fuel for fuel cells and a power storage device that stores surplus power. Specifically, an evaluation index that prioritizes hydrogen production is used, and when the water electrolysis device is in an operational state where it can produce hydrogen, the operational priority of the water electrolysis device is increased, and when it is not in an operational state where it can produce hydrogen, the operational priority of the power storage device is increased. Therefore, the energy management system of this embodiment enables efficient operation of a microgrid that includes a hydrogen storage device and a power storage device.

[0226] [Fourth embodiment] A microgrid according to a fourth embodiment of the present disclosure includes an energy generation facility including a renewable energy power generation device and a cogeneration system, and an energy storage facility including multiple types of energy storage devices. The energy storage devices according to this embodiment include, for example, a power storage device that stores electric power and a heat storage device that stores thermal energy. That is, the microgrid according to this embodiment has the functions of generating, storing, and supplying multiple types of energy.

[0227] In the microgrid of this embodiment, the energy demand side includes devices that use electric power and devices that use thermal energy. On the energy supply side, there are devices that generate electric power (for example, a solar power generation system 1100 and a fuel cell 1700) and devices that generate electric power and thermal energy (for example, a biomass power generation system 1200). Furthermore, as energy storage facilities, there are devices that store electric power (a storage battery 1300 and a hydrogen storage system 1800) and devices that store thermal energy (a heat storage system 1500). In this embodiment, an energy management system is realized that can efficiently operate a microgrid where there is demand and supply for multiple types of energy.

[0228] <Energy management system processing procedure> The processing procedure of the energy management method executed by the energy management system 1000 in this embodiment will be described.

[0229] In step S11, the operating data collection unit 10100 of the energy management system 1000 collects operating data from the solar power generation plant 1100, the biomass power generation plant 1200, the power storage control device 1400, the heat storage plant 1500, the water electrolysis plant 1600, and the fuel cell 1700. The operating data collection unit 10100 stores the collected operating data in a storage device such as the HDD 504.

[0230] In step S12, the demand forecasting unit 10300 of the energy management system 1000 reads out the operation data stored in the storage device. Based on the read out operation data, the demand forecasting unit 10300 predicts the power demand in the microgrid 100. The demand forecasting unit 10300 sends the power demand in the microgrid 100 to the operation planning unit 10700.

[0231] In step S13, the demand forecasting unit 10300 of the energy management system 1000 forecasts the heat demand in the microgrid 100 based on the operation data read in step S12. The demand forecasting unit 10300 sends the heat demand in the microgrid 100 to the operation planning unit 10700.

[0232] In step S14, the demand forecasting unit 10300 of the energy management system 1000 forecasts the hydrogen demand in the microgrid 100 based on the operation data read out in step S12. The demand forecasting unit 10300 sends the hydrogen demand in the microgrid 100 to the operation planning unit 10700.

[0233] In step S15, the operation planner 10700 of the energy management system 1000 reads out the operation data stored in the storage device. The operation planner 10700 also receives the power demand, heat demand, and hydrogen demand in the microgrid 100 from the demand forecaster 10300.

[0234] The operation planner 10700 creates an operation plan for each of the power storage control device 1400 and the water electrolysis device 1600 so as to satisfy the power demand in the microgrid 100. Specifically, the operation planner 10700 creates an operation plan including a charge / discharge plan for each of the storage battery 1300 and the water electrolysis device 1600 so as to satisfy the difference between the total amount of power generated by the photovoltaic power generation device 1100, the biomass power generation device 1200, and the fuel cell 1700 included in the operation data and the power demand in the microgrid 100. The operation planner 10700 transmits the created operation plans to the power storage control device 1400 and the water electrolysis device 1600.

[0235] The operation planner 10700 may create an operation plan for the water electrolysis device 1600 so as to satisfy the hydrogen demand in the microgrid 100. Specifically, the operation planner 10700 creates an operation plan including a hydrogen production plan for the water electrolysis device 1600 so as to satisfy the difference between the amount of hydrogen produced by the water electrolysis device 1600 included in the operation data and the hydrogen demand in the microgrid 100. The operation planner 10700 transmits the created operation plan to the water electrolysis device 1600.

[0236] The operation planning unit 10700 creates an operation plan for the heat storage device 1500 so as to satisfy the heat demand in the microgrid 100. Specifically, the operation planning unit 10700 creates an operation plan including a heat storage plan for the heat storage device 1500 so as to satisfy the difference between the heat generation amount of the biomass power generation plant 1200 included in the operation data and the heat demand in the microgrid 100. The heat storage plan is information that indicates the amount of heat storage and the amount of heat release in a specified time interval. The operation planning unit 10700 transmits the created operation plan to the heat storage device 1500.

[0237] According to this operation plan, the first storage battery 1300-1, the second storage battery 1300-2, and the water electrolysis device 1600 can be controlled to meet the power demand in the microgrid 100. In addition, the heat storage device 1500 can be controlled to meet the heat demand in the microgrid 100.

[0238] <Effects of the Fourth Embodiment> The energy management system of this embodiment creates operation plans for the water electrolysis device and the power storage device so as to satisfy the power demand of the microgrid, and creates an operation plan for the heat storage device so as to satisfy the heat demand of the microgrid, in a microgrid including a water electrolysis device, a heat storage device, and a power storage device. Therefore, the energy management system of this embodiment enables efficient operation of the microgrid including the water electrolysis device, the heat storage device, and the power storage device.

[0239] [Fifth embodiment] A microgrid according to a fifth embodiment of the present disclosure includes a power storage facility including a plurality of types of power storage devices. The power storage devices according to this embodiment include, for example, a plurality of lithium-ion batteries and NAS batteries.

[0240] Energy storage devices have operating characteristics that depend on the materials used to store power and their implementation. Even for the same type of energy storage device, there are cases where it is desirable to operate it differently depending on its characteristics, such as the number of charge / discharge cycles and capacity. This embodiment realizes an energy management system that can efficiently operate a microgrid that includes multiple types of energy storage devices.

[0241] <Energy management system processing procedure> The processing procedure of the energy management method executed by the energy management system 1000 in this embodiment will be described.

[0242] In step S21, the operating data collection unit 10100 of the energy management system 1000 collects operating data from the solar power generation plant 1100, the biomass power generation plant 1200, the power storage control device 1400, the water electrolysis plant 1600, and the fuel cell 1700. The operating data collection unit 10100 stores the collected operating data in a storage device such as the HDD 504.

[0243] In step S22, the characteristic acquisition unit 10400 of the energy management system 1000 acquires the characteristics of each of the first storage battery 1300-1 and the second storage battery 1300-2. The characteristic acquisition unit 10400 sends the acquired characteristics of each of the first storage battery 1300-1 and the second storage battery 1300-2 to the optimization unit 10600.

[0244] The characteristic acquisition unit 10400 can read out characteristics that are set in advance by an operator or the like of the microgrid 100. If the operation data collected from the power storage control device 1400 includes information that indicates the characteristics of each of the first storage battery 1300-1 and the second storage battery 1300-2, that information can be acquired.

[0245] In step S23, the optimization unit 10600 of the energy management system 1000 receives the characteristics of the first storage battery 1300-1 and the second storage battery 1300-2 from the characteristics acquisition unit 10400. The optimization unit 10600 determines the operation priority of the first storage battery 1300-1 and the second storage battery 1300-2 based on the characteristics of the first storage battery 1300-1 and the second storage battery 1300-2. The optimization unit 10600 sends the determined operation priority to the operation plan unit 10700.

[0246] For example, different types of storage batteries 1300 have different responsiveness and operating environments. NAS batteries have a low self-discharge rate but need to be heated to 300°C or higher during operation. On the other hand, lithium-ion batteries have a relatively high self-discharge rate but are subject to fewer operating environment restrictions. In this case, the optimization unit 10600 sets the operating priority of the lithium-ion battery higher than that of the NAS battery.

[0247] For example, even if the storage batteries 1300 are made of the same material, the storage battery 1300 that is preferred for use may change depending on the available storage capacity, the number of years of use, or the number of charge / discharge cycles. For example, the utilization efficiency of a lithium-ion battery decreases if the amount of change in capacity during a single charge / discharge is small compared to the maximum storage capacity. In an environment where charging / discharging is frequently repeated, this problem can be alleviated by preferentially using lithium-ion batteries with smaller available storage capacities for charging / discharging. In this case, the optimization unit 10600 sets the operation priority of lithium-ion batteries with smaller available storage capacities higher than that of lithium-ion batteries with larger available storage capacities.

[0248] Furthermore, for example, a storage battery that has been in use for a long time or that has been charged and discharged many times is likely to have a short remaining lifespan. Therefore, by preferentially using a storage battery that has been in use for a long time or that has been charged and discharged many times for charging and discharging, it is possible to realize an operation in which the storage battery is used up and then replaced with a new storage battery. In this case, the optimization unit 10600 sets the operating priority of a storage battery that has been charged and discharged many times higher than the operating priority of a storage battery that has been charged and discharged few times.

[0249] In step S24, the operation planner 10700 of the energy management system 1000 receives the priorities from the optimizer 10600. The operation planner 10700 creates an operation plan including a charge / discharge plan for the first storage battery 1300-1 and the second storage battery 1300-2 based on the priorities. The operation planner 10700 transmits the created operation plan to the power storage control device 1400.

[0250] According to this operation plan, control is performed to preferentially charge or discharge either the first storage battery 1300-1 or the second storage battery 1300-2 according to the respective characteristics. For example, in a microgrid including lithium-ion batteries and NAS batteries, it is possible to preferentially use the lithium-ion batteries for charging or discharging. For example, in a microgrid including multiple rechargeable batteries with different storage capacities, it is possible to preferentially use the rechargeable batteries with smaller storage capacities for charging or discharging. For example, in a microgrid including multiple rechargeable batteries with different ages, it is possible to preferentially use the rechargeable batteries with longer ages for charging or discharging.

[0251] <Effects of the Fifth Embodiment> The energy management system of this embodiment determines the operation priority of a microgrid including multiple types of power storage devices based on the characteristics of each power storage device. Specifically, the operation priority of the power storage devices is determined based on the available storage capacity, years of use, number of charge / discharge cycles, or material. Therefore, the energy management system of this embodiment can efficiently operate a microgrid including multiple types of power storage devices.

[0252] [supplement] The storage battery 1300 and the power storage control device 1400 in the above embodiment are an example of a power storage system. The heat storage device 1500 is an example of a heat storage system. The water electrolysis device 1600 and the hydrogen storage device 1800 are an example of a hydrogen storage system.

[0253] In the above embodiment, heat is transferred through the heat transfer line H, but a medium such as water, air, or a heat medium is required to transfer the heat. The heat storage device 1500 may be configured with two types of heat storage devices: a type that directly stores heat in a medium flowing through the heat transfer line H (for example, a type that stores hot water, cold water, ice, or steam), and a type that stores heat in a heat storage material (such as zeolite, HASClay, or a chemical heat storage material) and exchanges heat with the medium when used. In this case, the type that directly stores heat in a medium is characterized by a relatively high natural heat release rate, so the stored heat amount is easily attenuated (a 20 to 50% decrease over a few days), while the type that stores heat in a heat storage material is characterized by a relatively low natural heat release rate, so the stored heat amount is not easily attenuated (a 10% decrease over a year or more). Under these assumptions, if it is predicted that there will be a demand for heat, prioritizing a type of heat storage device that directly stores heat in a medium will reduce heat conversion losses and allow for a quick response to heat demand, and if it is predicted that there will be no heat demand, prioritizing a heat storage material type heat storage device for storing heat will allow for a relatively long-term heat storage capacity.

[0254] Furthermore, in the above embodiment, the biomass power generation apparatus 1200 is both a power generation apparatus and a heat generation apparatus. When operating an energy generation apparatus that generates multiple types of energy (electricity, heat, and hydrogen) in this way, it is preferable to operate a corresponding type of energy storage apparatus as a set. When operating the biomass power generation apparatus 1200 or the fuel cell 1700, it is desirable to control the operation of the heat storage apparatus 1500 and the storage battery 1300. Conversely, if there is limited capacity in both the heat storage apparatus 1500 and the storage battery 1300, it is possible to suppress the operation of the apparatus that generates multiple types of energy and prioritize the operation of the apparatus that generates a single type of energy.

[0255] Furthermore, in the above embodiment, hydrogen can meet hydrogen demand, electricity demand (conversion by fuel cell 1700), and heat demand (conversion by hydrogen boiler 1900), but for energy with low conversion efficiency, it is desirable to prioritize direct use.

[0256] [Sixth embodiment] The energy management system 1000 in the sixth embodiment employs model predictive control (MPC) as a means for appropriately controlling the microgrid 100 with respect to various objective functions and constraints based on the prediction results of the energy demand and power generation amount of the consumers 300. The energy management system 1000 in this embodiment formulates two types of model predictive control. The first model predictive control aims to control the maximum storage amount (SOE; State of Energy) of the power storage device 1300, minimize the amount of suppression of the power generation device, and maintain the upper limit of the amount of power sold by the grid 200 to the consumers 300. The second model predictive control aims to minimize the peak of power received from the grid 200, assuming a pricing structure in which a base fee is set according to the maximum power received within a certain period in the past.

[0257] Here, a calculation model of the power storage system in this embodiment and its operation method will be described. As described above, the power storage device 1300 includes a power conditioner and auxiliary equipment in addition to a storage battery. The auxiliary equipment includes a temperature adjustment function and a control power supply within the power storage device 1300.

[0258] In this embodiment, the following preconditions are set. First, energy loss of the power storage device 1300 occurs only in the power conditioner, and the ratio of the amount of power input and output by the power conditioner is constant. Second, the power consumption of the auxiliary devices is constant. Third, the amount of power input and output by the storage battery is equal to the amount of change in the maximum amount of power stored in the power storage device 1300.

[0259] Based on the above preconditions, the following equations (101) to (301) hold.

[0260]

number

[0261] However, P Systemis the system output (the output of the power storage device 1300), and P Battery is the battery output, and P AUX is the auxiliary power, and E Battery,t is the amount of stored energy at time t, and η PCS is the effectiveness factor of the power conditioner.

[0262] Auxiliary power P AUX and the effectiveness coefficient η PCS is the system output P System and storage capacity E Battery,t Specifically, the amount of stored energy E at each time t can be estimated based on Battery,t The auxiliary power P that minimizes the residual between the difference between the actual measured value and the difference between the storage amount estimated based on equations (101) to (301) AUX and the effectiveness coefficient η PCS can be calculated.

[0263] (Constant power receiving control) The power storage device 1300 in this embodiment employs constant power reception control (CPR), which determines the system output when the upper limits of the amount of power purchased from and sold to the grid 200 are the same and constant, i.e., so that the received power always approaches a set value. In constant power reception control, an output value that brings the received power closest to a set value is determined within the constraints of the system output that are determined based on the amount of stored power at each time and the rated output value. Hereinafter, the set value of the received power is also referred to as the "target power reception value." The target power reception value may be determined taking into consideration the fee structure of the grid 201 and control errors due to response delays, etc. The constant power reception control is disclosed in Reference 2 below.

[0264] [Reference 2] Y Matsunami, et al., "Development of a grid independent energy system using energy supply and demand prediction (Part 1) Concept and problem identification from operational data", Vol.9, pp.1-4, Technical papers of annual meeting, The Society of Heating, Air-Conditioning and Sanitary Engineers of Japan, 2021.

[0265] (formulation) In model predictive control, an objective function is defined within a given prediction period, and an optimization problem with the manipulated variable at each time point is sequentially solved. Below, we will explain in detail the first model predictive control, maximum energy storage control, and the second model predictive control, energy supply leveling control.

[0266] ((Maximum energy storage control)) Maximum energy storage control (MCC; Maximum Capacity Control) is a model predictive control that controls the maximum storage capacity of the energy storage device 1300 in order to prevent reverse power flow. FIG. 9 is a diagram showing an example of maximum energy storage control. The objective function and constraints of the maximum energy storage control are expressed by equation (401). Note that "^" is a symbol that should normally be written directly above the character immediately following it, but due to limitations in text notation, it is written immediately before it in the main text. In mathematical expressions, it is written directly above the actual character.

[0267]

number

[0268] However, ^E Battery_max is the predicted maximum storage capacity, and E Battery_setis the threshold for the maximum charge amount. Load is the predicted power consumption, and ^P PV_MAX is the predicted maximum power generation amount of the solar power generation device 1100, and ^P CHP is the predicted value of the power generation amount of the biomass power generation device 1200, and ^P System is the predicted value of the system output, and ^P Grid is the predicted value of the received power, and ^r PV is the output rate of the solar power generation device 1100, and f CPR is a function of constant power receiving control.

[0269] In the maximum energy storage control, the predicted value of the maximum storage amount in the prediction period Tw is Battery_max and the preset maximum storage threshold E Battery_set The squared residual between and the objective function obj MCC and the objective function obj MCC The output rate r of the photovoltaic power generation device at each time that minimizes PV The optimal solution is the maximum storage capacity ^E during the forecast period Tw. Battery_max is the maximum storage threshold E Battery_set If it is predicted that the output of the solar power generation device 1100 in the prediction period Tw will exceed the output rate r PV This makes it possible to avoid full charging of the power storage device 1300 and prevent reverse power flow to the grid 200.

[0270] ((Energy supply leveling control)) Energy supply leveling control (ESL) is a model predictive control that controls the set value of constant power reception control with the aim of lowering the peak of received power to a target power reception value. Fig. 10 is a diagram showing an example of energy supply leveling control. The objective function and constraint conditions of the energy supply leveling control are expressed by equation (501).

[0271]

number

[0272] However, ^PGrid_max is the predicted maximum received power, and P Grid_target is the target value of the received power.

[0273] In the energy supply leveling control, the maximum value P of the received power in the prediction period Tw is Grid_max and the target value of the received power P Grid_target The squared residual between and the objective function obj ESL The set value P of the constant power receiving control in the prediction period Tw is Grid_set is a variable, and the objective function obj ESL The predicted value of the maximum receiving power ^P Grid_max The set point P of the constant power receiving control is the lowest. Grid_set Explore.

[0274] <Long-term solar radiation forecast> The energy management system 1000 in this embodiment calculates the maximum power generation amount P PV_MAX In order to predict the long-term solar radiation amount, a long-term solar radiation amount prediction is adopted in the model predictive control. The energy management system 1000 in this embodiment uses an advanced deep learning model to deal with the uncertainty of the long-term solar radiation amount.

[0275] The use of solar radiation forecasting in model predictive control has been widely studied. Traditional model predictive control requires a longer prediction period to obtain an optimal solution, but the accuracy of the prediction affects the final optimization result. A common approach is to iterate predictions using a regression model and achieve the goal through multiple-step predictions. However, due to uncertainty in solar radiation, the accuracy of the prediction tends to decrease as the prediction horizon widens. One reason for this is that prediction errors at each step accumulate, resulting in large errors in the final result.

[0276] To avoid the error accumulation problem caused by regression models, this embodiment utilizes an advanced deep learning model to process and learn long-term time series data. Conventional deep neural networks use multi-layer feedforward neural networks. The nonlinear activation function between each layer of the neural network is a key feature that characterizes deep neural networks. However, in this type of network, the computational process of the entire network is parallel and not time-dependent. Therefore, it is difficult to effectively process and learn time series data.

[0277] Considering the drawbacks of conventional deep neural networks, this embodiment uses long short-term memory (LSTM) as a basic unit for constructing a model. Long short-term memory has unique advantages in terms of network structure in time series processing.

[0278] [supplement] Each function of the above-described embodiments can be realized by one or more processing circuits. Here, the term "processing circuit" in this specification includes a processor programmed to execute each function by software, such as a central processing unit (CPU) or a graphics processing unit (GPU) implemented by an electronic circuit, as well as devices such as an application specific integrated circuit (ASIC), a digital signal processor (DSP), a field programmable gate array (FPGA), and conventional circuit modules designed to execute each of the above-described functions.

[0279] Although the embodiments of the present disclosure have been described in detail above, the embodiments disclosed herein are illustrative in all respects and are not limiting. The embodiments can be modified and improved in various ways without departing from the scope and spirit of the appended claims. The matters described in the above embodiments can be configured in other ways as long as they are not inconsistent, and can be combined as long as they are not inconsistent. [Explanation of symbols]

[0280] 1: Microgrid 2: Power grid 3: Consumer 10: Energy management system 11: Solar panels 12: Power conditioner 13: Storage battery 14: Water electrolysis device 15: Hydrogen tank 16: Fuel cell 110: Acquisition Department 120: Decision section 130: Optimization section 140:Joining part 150: Adjustment section 160: Output section

Claims

1. An energy management system for managing a microgrid, comprising: an optimization unit configured to repeatedly optimize an operation plan of the microgrid in a time interval having a predetermined time length for each of a plurality of time intervals; a combining unit configured to combine the operation plans optimized for each of the plurality of time intervals; An energy management system equipped with:

2. 2. The energy management system according to claim 1, the optimization unit is configured to repeatedly optimize the operation plan for the time intervals that are consecutive in a time direction until a time length obtained by combining the plurality of time intervals becomes equal to or greater than a threshold. Energy management system.

3. 3. The energy management system according to claim 2, the optimization unit is configured to, when optimizing the operation plan for a second time interval subsequent to a first time interval, set an initial value of the operation plan for the second time interval based on the operation plan for the first time interval. Energy management system.

4. 4. The energy management system according to claim 3, the microgrid includes a hydrogen production device that produces hydrogen using electric power; the operation plan includes electrolysis power of the hydrogen production device at a plurality of times included in the time interval, the optimization unit is configured to set the electrolysis power at the last time of the first time interval to the electrolysis power at the time immediately before the second time interval. Energy management system.

5. 4. The energy management system according to claim 3, the microgrid includes a power storage device that stores power; the operation plan includes remaining amounts of the power storage device at a plurality of times included in the time period; the optimization unit is configured to set a remaining capacity of the power storage device at a last time of the first time interval to a remaining capacity of the power storage device at a time immediately before the second time interval. Energy management system.

6. 4. The energy management system according to claim 3, The microgrid includes a hydrogen storage device that stores hydrogen; the operation plan includes a remaining amount of hydrogen in the hydrogen storage device at a plurality of times included in the time interval, the optimization unit is configured to set the remaining amount of hydrogen in the hydrogen storage device at the last time of the first time interval to the remaining amount of hydrogen in the hydrogen storage device at the time immediately before the second time interval. Energy management system.

7. The computer that manages the microgrid a step of repeatedly optimizing an operation plan of the microgrid in a time interval of a predetermined time length for each of a plurality of time intervals; a step of combining the operation plans optimized for each of the plurality of time intervals; Energy management method that implements the above.

8. The computer that manages the microgrid a step of repeatedly optimizing an operation plan of the microgrid in a time interval of a predetermined time length for each of a plurality of time intervals; a step of combining the operation plans optimized for each of the plurality of time intervals; A program to execute.

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