Server, power management method

Abstract

A server (100) for implementing energy management of a power grid (MG) using a plurality of energy storage resources, has a loss acquisition section (111) and a selection section (112). The loss acquisition section acquires, for each of the plurality of energy storage resources, an energy loss including a storage loss and an input / output loss that occurs when energy is stored in the energy storage resource. The selection section selects, from among the plurality of energy storage resources, one or more energy storage resources for storing surplus power using the energy loss that occurs when surplus power is stored, when surplus power is generated in the power grid.

Description

Technical Field

[0001] This invention relates to a server that uses multiple energy storage resources to implement energy management and a power management method. Background Technology

[0002] Japanese Patent Application Publication No. 2020-089147 discloses a method for managing electricity by charging facilities with surplus electricity (the unused electricity generated).

[0003] In the power management method described in Japanese Patent Application Publication No. 2020-089147, when selecting facilities that request suppression of charging power through DR (demand response), facilities with small suppression capacity are excluded from the selected candidates. Summary of the Invention

[0004] However, when surplus electricity is stored in energy storage resources (e.g., batteries), energy loss occurs during electricity storage. For example, during the period when electricity is stored in a battery, electricity is gradually released from the battery due to self-discharge. Hereinafter, the energy loss that occurs when storing energy in energy storage resources is also referred to as "storage loss".

[0005] Furthermore, energy losses occur both when energy is input into energy storage resources and when energy is output from energy storage resources. For example, when converting electricity into hydrogen for storage, energy loss occurs during the conversion. Similarly, when converting hydrogen into electricity for use, energy loss also occurs during the conversion. Hereinafter, the energy loss incurred when inputting energy into energy storage resources will be referred to as "input loss." Furthermore, the energy loss incurred when outputting energy from energy storage resources will be referred to as "output loss." The sum of input and output losses will be called "input-output loss." Additionally, the sum of storage losses and input-output losses will be called "overall loss."

[0006] According to the electricity management method described in Japanese Patent Application Publication No. 2020-089147, storing surplus electricity in a facility (energy storage resource) may increase the overall loss in that facility.

[0007] This invention was made to solve the above-mentioned problems, and its purpose is to store surplus electricity in a way that reduces energy loss.

[0008] The server of this invention is configured to implement power grid energy management using multiple energy storage resources. The server has a loss acquisition unit and a selection unit. The loss acquisition unit acquires, for each of the multiple energy storage resources, the energy loss generated during energy storage in that energy storage resource, including storage losses and input / output losses. When surplus power is generated in the power grid, the selection unit uses the energy loss generated during the storage of the surplus power to select one or more energy storage resources from the multiple energy storage resources for storing the surplus power.

[0009] The server selects energy storage resources for storing surplus power based on the energy losses (including storage losses and input / output losses) incurred when storing surplus power. According to the server, surplus power can be stored in a manner that minimizes energy loss.

[0010] Energy storage resources are configured to store electricity. The storage method is arbitrary. Energy storage resources can directly store electricity (electrical energy) or be converted into other forms of energy (e.g., liquid or gaseous fuels as energy sources) for storage.

[0011] The loss acquisition unit is configured to, when surplus power is generated in the power grid, predict the storage period (i.e., the period during which the surplus power is stored in the energy storage resource) for each of a plurality of energy storage resources, and obtain the storage loss using the predicted storage period.

[0012] Regarding storage losses (i.e., energy losses incurred when storing energy in energy storage resources), these losses increase with longer storage periods. Based on the described structure, storage losses can be easily calculated with high accuracy.

[0013] The plurality of energy storage resources may include at least one of stationary energy storage devices and stationary fuel cells. The loss acquisition unit predicts a sufficient supply period (i.e., the period from the generation of surplus power in the grid to the point where the grid's demand for power exceeds the grid's supply of power) and uses the predicted sufficient supply period to acquire the storage period of at least one of the stationary energy storage devices and stationary fuel cells.

[0014] The energy stored in stationary energy storage devices and stationary fuel cells can be released to meet demand when the grid's power demand exceeds its supply. Therefore, regarding the storage period of each of the stationary energy storage devices and stationary fuel cells, it can be considered that the longer the sufficient supply period, the longer the energy storage period. Based on this structure, the storage period of at least one of the stationary energy storage devices and stationary fuel cells can be easily calculated with high accuracy.

[0015] The power grid can also be configured to supply electricity to multiple residences. The power grid can also be configured to receive power from naturally fluctuating power sources (i.e., power sources whose output varies according to weather conditions). The loss acquisition unit can also be configured to use weather forecast information to predict the power demand and supply of the power grid.

[0016] The power demand of the power grid varies depending on the operating status of air conditioning equipment in residences. The loss acquisition unit can easily predict the power demand of the power grid with high accuracy by using meteorological forecast information (e.g., predicted temperature information). Furthermore, the power supply of the power grid varies according to meteorological conditions. The loss acquisition unit can easily predict the power supply of the power grid with high accuracy by using meteorological forecast information (e.g., weather forecast information).

[0017] Examples of naturally occurring power sources include solar power and wind power. Because naturally occurring power sources use renewable energy to generate electricity, ensuring at least a portion of the grid's power supply can reduce carbon dioxide emissions.

[0018] The plurality of energy storage resources may include vehicles equipped with energy storage devices capable of connecting to external power supply equipment. The loss acquisition unit may also be configured to predict the vehicle's storage period using the vehicle's driving schedule.

[0019] The electricity stored in the vehicle's energy storage device can be released for driving when the vehicle begins to move. According to this structure, the storage period in a vehicle with an energy storage device can be easily predicted with high accuracy. Examples of vehicles with such energy storage devices include BEVs (Battery Electric Vehicles) and PHEVs (Plug-in Hybrid Electric Vehicles).

[0020] The plurality of energy storage resources may also include hydrogen stations configured to supply hydrogen to fuel cell vehicles. The loss acquisition unit may also be configured to predict the hydrogen refueling time of the fuel cell vehicle using the remaining hydrogen supply and driving plan, and to predict the storage period of the hydrogen station using the predicted hydrogen refueling time.

[0021] FCEVs (Fuel Cell Electric Vehicles) consume hydrogen while driving and replenish it at hydrogen stations when the remaining hydrogen supply is low. Based on this structure, the storage period at the hydrogen station can be easily predicted with high accuracy.

[0022] The selection unit can also be configured to sequentially select one or more energy storage resources for storing surplus power, starting with energy storage resources that have the smallest energy losses (including storage losses and input / output losses) when storing surplus power. According to this structure, surplus power is stored in a manner that minimizes energy losses.

[0023] When there is an energy storage resource with insufficient remaining energy among multiple energy storage resources, the selection unit selects the energy storage resource with insufficient remaining energy as the energy storage resource for storing surplus electricity. When there is no energy storage resource with insufficient remaining energy among multiple energy storage resources, starting from the energy storage resource with the smallest energy loss when storing surplus electricity, one or more energy storage resources are selected sequentially for storing surplus electricity.

[0024] Depending on the energy storage resources, when the remaining energy becomes too low, functionality may degrade and degradation may occur. In this server, it is possible to prioritize storing remaining power in energy storage resources with insufficient remaining energy. This prevents the remaining energy in energy storage resources from becoming too low. Furthermore, in the absence of energy storage resources with insufficient remaining energy, the server can prioritize storing remaining power in energy storage resources with minimal energy loss (including storage loss and input / output loss) during storage.

[0025] The selection unit can also be configured to obtain the energy surplus of each region. The selection unit can also be configured to, in the case of regions with insufficient energy surplus, limit the candidates for energy storage resources used to store surplus electricity to energy storage resources present in those regions with insufficient energy surplus.

[0026] In case of emergencies (e.g., disasters), the amount of reserve energy (i.e., the amount of energy that is always pre-stored) can be determined based on the region. According to the server, surplus power is preferentially stored in energy storage resources existing in areas with insufficient energy reserves. Thus, it is possible to prevent the energy reserves in a region from becoming too low.

[0027] Each of the aforementioned servers also has a storage control unit that controls multiple energy storage resources in a manner that allows surplus electricity to be stored in one or more energy storage resources selected by a selection unit. A server with such a storage control unit selects an energy storage resource when surplus electricity is generated on the power grid and stores the surplus electricity in the selected energy storage resource.

[0028] The power management method of the present invention is a method for implementing power grid power management using multiple energy storage resources that can be electrically connected to the power grid, comprising: when surplus power is generated in the power grid, for each of the multiple energy storage resources, obtaining the energy loss generated when storing energy in the energy storage resource, including storage loss and input / output loss; and using the obtained energy loss, selecting one or more energy storage resources from the multiple energy storage resources for storing surplus power.

[0029] According to the power management method, similar to the server, it is also possible to store surplus power in a way that reduces energy loss.

[0030] The above and other objects, features, aspects and advantages of the present invention will become apparent from the following detailed description of the invention, which is understood in conjunction with the accompanying drawings. Attached Figure Description

[0031] Figure 1 This is a diagram showing a schematic structure of a power system according to an embodiment of the present invention.

[0032] Figure 2 This is a functional block diagram illustrating the constituent elements of a server according to an embodiment of the present invention.

[0033] Figure 3 This is a diagram illustrating the energy management method of an embodiment of the present invention.

[0034] Figure 4 It is used to explain by Figure 2 The flowchart shown illustrates the energy management-related processes performed by the server.

[0035] Figure 5 It means by Figure 2 The flowchart shown illustrates the processes performed by the server related to the selection of energy storage resources.

[0036] Figure 6 It is used to explain by Figure 2 The diagram shows the processing performed by the server during the prediction storage period.

[0037] Figure 7 This is a diagram illustrating the overall loss of each DER when the weather is sunny the following day.

[0038] Figure 8 This is a diagram illustrating the overall loss of each DER when the weather is cloudy the following day.

[0039] Figure 9 It means Figure 5 The flowchart shows a variation of the processing.

[0040] Figure 10It is used to explain in Figure 9 The diagram shows a series of processes that select energy storage resources with insufficient energy reserves.

[0041] Figure 11 It is used to explain in Figure 9 The diagram shows a series of processes in which the selected candidates are limited to DER processes in regions with insufficient energy reserves. Detailed Implementation

[0042] Embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the drawings, the same or corresponding parts are labeled with the same symbols, and their descriptions will not be repeated. Hereinafter, the Energy Management System will be referred to as "EMS". Furthermore, Distributed Energy Resource will be referred to as "DER".

[0043] Figure 1 This is a diagram illustrating a schematic structure of a power system according to an embodiment of the present invention. (Refer to...) Figure 1 Power system 1 includes power system PG, microgrid MG, server 100, 200, DER group 500, and receiving substation equipment 501.

[0044] Server 100 is a computer that manages the supply and demand of a microgrid MG. Server 100 is the administrator of the microgrid MG. Server 100 corresponds to a CEMS (Community EMS) server. A microgrid MG is a power grid that supplies electricity to an entire city (e.g., a smart city). The power lines used in the microgrid MG to network multiple DERs can also be self-operated power lines. The microgrid MG is configured to be able to connect in parallel and disconnect from the power system PG. The microgrid MG corresponds to an example of the "power grid" of this invention.

[0045] The receiving transformer 501 is located at the linkage point (power receiving point) of the microgrid MG, and can switch the parallel (connection) / disconnection (shutdown) of the power system PG and the microgrid MG. When the microgrid MG operates in a linked state with the power system PG, the receiving transformer 501 receives AC power from the power system PG, steps down the received power, and supplies it to the microgrid MG. When the microgrid MG operates independently with its power system PG disconnected, no power supply is implemented from the power system PG to the microgrid MG. The receiving transformer 501 comprises switching devices (e.g., section switches, circuit breakers, breaker switches, and load switches) on the high-voltage side (primary side), a transformer, protective relays, measuring equipment, and control devices. The server 100 is configured to receive information related to the microgrid MG (e.g., power waveforms) from the receiving transformer 501 and instruct the receiving transformer 501 to connect / disconnect.

[0046] Server 200 is a computer that manages the supply and demand of the power system PG. The power system PG is a power grid constructed from power plants and transmission and distribution equipment (not shown). The power company corresponds to the typical transmission and distribution enterprise and maintains and manages the power system PG (commercial power source). The power company is the manager of the power system PG. Server 200 belongs to the power company.

[0047] Server 100 is configured to communicate with each of server 200 and DER group 500. The communication protocol may be OpenADR. DER group 500 contains multiple DERs that can be electrically connected to the microgrid MG. Server 100 manages the multiple DERs contained in DER group 500. Server 100 can also implement DR (demand response) to DER group 500 when requesting supply and demand regulation of the power system PG from server 200. In addition, server 100 can also implement DR to DER group 500 based on requests from the supply and demand regulation market. Furthermore, server 100 can also implement DR to DER group 500 for supply and demand regulation of the microgrid MG.

[0048] Multiple DERs within DER group 500 are electrically interconnected via a microgrid MG. DER group 500 includes EVSE (Electric Vehicle Supply Equipment) 20, residential 30, commercial facilities 40, factories 50, ESS (Energy Storage System) 60, FCS (Fuel Cell System) 70, hydrogen stations 80, natural variable power sources 91, and generators 92. Each of these can function as a DER.

[0049] DER group 500 further includes BEV (Battery Electric Vehicle) 11 and FCEV (Fuel Cell Electric Vehicle) 12. EVSE 20 functions as a DER in a state of electrical connection with a vehicle (e.g., BEV 11). For example, the charging connector of EVSE 20 is inserted into the inlet of BEV 11, thereby electrically connecting EVSE 20 to BEV 11. Figure 1 The diagram shows only one BEV11 and one FCEV12, but the number of vehicles included in DER Group 500 is arbitrary, ranging from more than 10 to more than 100. DER Group 500 can include POV or MaaS vehicles. POVs are privately owned vehicles. MaaS vehicles are vehicles managed by MaaS (Mobility as a Service) operators.

[0050] The number of EVSE20, residential 30, commercial facilities 40, factories 50, ESS60, FCS70, hydrogen stations 80, natural variable power sources 91, and generators 92 included in DER group 500 is also arbitrary. In this embodiment, multiple EVSE20, residential 30, commercial facilities 40, factories 50, ESS60, FCS70, hydrogen stations 80, natural variable power sources 91, and generators 92 are respectively set up in a city.

[0051] BEV11 has an energy storage device B1. The energy storage device B1 is configured to connect to an external power supply device (e.g., EVSE20). The electricity stored in the energy storage device B1 is used to power the BEV11's drive motor (not shown) and consumed by devices mounted on the BEV11. FCEV12 has a power generation device H2 and an energy storage device B2. The power generation device H2 includes a hydrogen tank for storing hydrogen and a fuel cell (neither shown) that generates electricity through the chemical reaction of hydrogen and oxygen. The fuel cell uses hydrogen supplied from the hydrogen tank to generate electricity. The electricity generated by the power generation device H2 is used to power the FCEV12's drive motor (not shown), consumed by devices mounted on the FCEV12, and stored in the energy storage device B2. FCEV12 users can refill hydrogen at hydrogen stations 80 located in cities. Furthermore, BEV11 and FCEV12 each have ECU (Electronic Control Unit) 11a and 12a, and communication devices 11b and 12b for wireless communication with a server 100.

[0052] The ESS60 is a stationary energy storage device configured to charge and discharge to a microgrid (MG). The ESS60 can be equipped with lithium-ion batteries, lead-acid batteries, nickel-metal hydride batteries, redox flow batteries, or NAS (sodium-sulfur) batteries.

[0053] The FCS70 includes a stationary fuel cell 71, a hydrogen tank 72, and a hydrogen generation device 73, which generate electricity through the chemical reaction of hydrogen and oxygen. The fuel cell 71 is connected to the hydrogen tank 72, and the hydrogen tank 72 is connected to the hydrogen generation device 73. The fuel cell 71 is configured to generate electricity using hydrogen supplied from the hydrogen tank 72 and to supply the generated electricity to the microgrid MG. The hydrogen generation device 73 generates hydrogen and supplies the generated hydrogen to the hydrogen tank 72. Any method can be used as the hydrogen generation method. For example, in the hydrogen generation device 73, known methods such as by-product hydrogen production, water splitting, fossil fuel modification, biomass modification, or the IS (iodine / sulfur) process can be used. The hydrogen generation device 73 is configured to generate hydrogen using electricity supplied from the microgrid MG.

[0054] The DER group 500 comprises multiple EVSE20s and multiple hydrogen stations 80 as infrastructure provided in cities. The microgrid MG and EVSE20s are connected in a manner capable of power exchange. The hydrogen stations 80, in principle, have the same structure as the FCS70. That is, the hydrogen station 80 includes stationary fuel cells, hydrogen tanks, and hydrogen generation devices. Furthermore, the hydrogen station 80 is configured to generate hydrogen using electricity supplied from the microgrid MG. However, the hydrogen station 80 is also capable of supplying hydrogen to FCEV12s.

[0055] EVSE20 and hydrogen station 80 are public facilities that vehicle users can access by implementing prescribed authentication. Authentication can be via a charging card or communication-based authentication (e.g., Plug and Charge). After a BEV11 user connects BEV11 to EVSE20 via cable, power can be supplied to BEV11 from EVSE20 by operating at least one of BEV11 and EVSE20. After FCEV12 connects to hydrogen station 80 via cable, a FCEV12 user can receive hydrogen from hydrogen station 80 by operating at least one of FCEV12 and hydrogen station 80. Server 100, EVSE20, and hydrogen station 80 can communicate with each other. Server 100 can identify users of EVSE20 and hydrogen station 80 through the aforementioned authentication.

[0056] DER group 500 comprises multiple residences 30 (e.g., homes of people living in a city). A microgrid MG is configured to supply electricity to the multiple residences 30. Each residence 30 contains various household electrical appliances (e.g., lighting fixtures, air conditioning equipment, cooking appliances, information equipment, televisions, refrigerators, and washing machines). Furthermore, each residence 30 may also have at least one of the following: a power supply (e.g., a home electric energy store), a natural variable power source (e.g., solar panels mounted on a roof), an energy storage and power supply (ESS), an electric power system (FCS), or a combined heat and power system (e.g., a water heater or heat pump water heater that uses heat generated during home power generation). Energy supply and demand in each residence 30 are managed, for example, by a HEMS (Home EMS) not shown. In this embodiment, server 100 and each residence 30 communicate via HEMS. The microgrid MG is electrically exchangeable with each residence 30.

[0057] DER group 500 includes commercial facilities 40. Commercial facilities 40 include, for example, office buildings and shops. Examples of shops include department stores, shopping malls, supermarkets, or convenience stores. The energy supply and demand of the various facilities included in commercial facility 40 are managed, for example, by a BEMS (Building EMS) not shown. The BEMS can also manage the energy supply and demand separately for each facility, or it can aggregate and manage the energy supply and demand of multiple facilities. In this embodiment, server 100 communicates with commercial facility 40 via BEMS. The various facilities included in commercial facility 40 are connected to the microgrid MG in a power-swappable manner.

[0058] DER group 500 comprises multiple plants 50. Plant 50 may be, for example, an automobile manufacturing plant or other types of plants. Plant 50 includes, for example, a production line and a centralized heat source for air conditioning. Furthermore, plant 50 may also have at least one of the following: a natural variable power source (e.g., solar or wind power generation equipment), a generator (e.g., a gas turbine generator or diesel generator), or a combined heat and power (CHP) system. Energy supply and demand in plant 50 are managed, for example, by a FEMS (Factory EMS) not shown. In this embodiment, server 100 and each plant 50 communicate via FEMS. Microgrid MG and each plant 50 are electrically exchangeable.

[0059] DER group 500 includes multiple variable power sources 91. Each variable power source 91 generates electricity whose output varies according to weather conditions and supplies the generated power to a microgrid MG. The microgrid MG receives power from the variable power sources 91. The electricity generated by the variable power sources 91 corresponds to variable renewable energy (VRE). Variable power sources 91 may include, for example, solar power generation equipment and wind power generation equipment.

[0060] DER group 500 contains multiple generators 92. Generators 92 are stationary generators that generate electricity using fossil fuels. Generators 92 can be, for example, gas turbine generators or diesel generators. Generators 92 can be used as emergency power sources.

[0061] Server 100 includes a processor 110, a storage device 120, and a communication device 130. The processor 110 may be a CPU (Central Processing Unit). The storage device 120 is configured to store various types of information. In addition to the program executed by the processor 110, the storage device 120 also stores information used in the program (e.g., mappings, mathematical formulas, and various parameters). The communication device 130 includes various communication I / F (interfaces). Server 100 is configured to communicate with the outside world via the communication device 130.

[0062] Server 100 controls DER group 500, which is connected to the microgrid MG, enabling DER group 500 to function as a VPP (virtual power plant). More specifically, server 100 uses IoT (Internet of Things) energy management technology to remotely and comprehensively control DER group 500, thus allowing it to function like a power plant.

[0063] Figure 2 This is a functional block diagram representing the constituent elements of server 100. (Refer to...) Figure 1 and Figure 2 The server 100 includes a loss acquisition unit 111, a selection unit 112, a storage control unit 113, and an information management unit 114. For example, through... Figure 1 The processor 110 shown and the program in the storage device 120 executed by the processor 110 implement the above-described components. However, this is not a limitation; these components may also be embodied in dedicated hardware (electronic circuitry). The server 100 of this embodiment corresponds to an example of the "server" of the present invention.

[0064] Server 100 is configured to communicate with portable terminal 10 and each DER via communication device 130.

[0065] Users of each vehicle (including BEV11 and FCEV12) carry a portable terminal 10. Figure 2Only one portable terminal 10 is shown, which is carried by each vehicle user. In this embodiment, the portable terminal 10 is a smartphone with a touch panel display. However, it is not limited to this; any portable terminal, such as a tablet, wearable device (e.g., a smartwatch), or electronic key, can be used as the portable terminal 10. A pre-defined application software (hereinafter referred to as the "application") is installed on the portable terminal 10, and the portable terminal 10 is configured to exchange information with the server 100 through the application. By operating the portable terminal 10, the user can send the vehicle's driving plan to the server 100. Examples of vehicle driving plans include the operation plan of a POV (e.g., departure time, destination, and arrival time) or the operation plan of a MaaS vehicle.

[0066] The DERs included in DER group 500 are roughly divided into power generation DERs, energy storage DERs, and load DERs.

[0067] In a power generation DER, the generator uses natural energy (such as solar or wind power) or fuel (such as light oil, natural gas, or hydrogen) to generate electricity, which is then output to the microgrid MG via a power conversion circuit. In a storage DER, power exchange between the storage device and the microgrid MG is performed via a power conversion circuit. The power conversion circuit in each DER operates according to control signals from server 100, performing a prescribed power conversion. The power conversion circuit may include at least one of an inverter and a converter. Furthermore, the power conversion circuit may also include a relay for switching the connection / disconnection between the DER and the microgrid MG.

[0068] For example, in Figure 1 In the DER group 500 shown, ESS60 functions as a storage-type DER. Additionally, FCS70, natural variable power source 91, and generator 92 each function as a power generation-type DER. The power output of natural variable power source 91 is determined in principle by weather conditions, but its output can be limited.

[0069] BEV11 functions as a storage-type DER. BEV11 functions as a storage-type DER by charging and discharging the storage device B1 connected to the microgrid MG. FCEV12 functions as a generation-type DER. FCEV12 functions as a generation-type DER by outputting power generated by the generation device H2 to the microgrid MG. Furthermore, FCEV12 can also be configured to function as a storage-type DER. FCEV12 can also function as a storage-type DER if the capacity and charging / discharging performance of the storage device B2 are sufficient. The power conversion circuit can be installed on the vehicle (BEV11, FCEV12) or on the EVSE20. For example, DC power can be output from the vehicle to the DC-mode EVSE20, and DC / AC conversion can be performed by the inverter built into the EVSE20. Alternatively, an on-board inverter can perform DC / AC conversion on power released from the vehicle's storage device, and the converted AC power can be output from the vehicle to the AC-mode EVSE.

[0070] Although Figure 2 Not shown, but electrical equipment consuming power from the microgrid MG can also function as a load-type DER. The larger the power load of the electrical equipment connected to the microgrid MG, the greater the power consumption of the microgrid MG. For example, Figure 1 The users of the residential buildings 30, commercial facilities 40, and factories 50 shown can regulate the supply and demand of the microgrid MG by adjusting the power load of their electrical equipment. When the power consumption of the electrical equipment connected to the microgrid MG is suppressed, the electrical equipment acts as a generator for the microgrid MG. That is, the electrical equipment (load-type DER) can function as a hypothetical generator (power source).

[0071] The Information Management Department 114 manages the information of each user registered in the server 100 (hereinafter also referred to as "user information"), the information of each vehicle registered in the server 100 (hereinafter also referred to as "vehicle information"), and the information of each fixed DER registered in the server 100 (hereinafter also referred to as "resource information"). The user information, vehicle information, and resource information are distinguished by identification information (ID) for each user, each vehicle, and each DER, respectively, and are stored in the storage device 120.

[0072] Vehicle information includes vehicle specifications, vehicle location, input and output power, remaining energy, and driving plan. The remaining energy for BEV11 includes the State of Charge (SOC) of the energy storage unit B1. The remaining energy for FCEV12 includes the remaining hydrogen in the hydrogen tank of the power generation unit H2.

[0073] The vehicle information also includes loss information for calculating energy loss. The loss information for BEV11 includes the self-discharge rate of the energy storage device B1 (i.e., information representing the amount of electricity released per unit time from the stored energy storage device) and the SOC / temperature / resistance mapping diagram of the energy storage device B1 (i.e., a mapping diagram representing the relationship between SOC, temperature, and resistance). Details will be described later. The loss acquisition unit 111 refers to the SOC / temperature / resistance mapping diagram of the energy storage device B1 to predict the input / output losses generated when storing remaining electricity in BEV11. Furthermore, the self-discharge rate of the energy storage device B1 is used to calculate the storage loss of BEV11. The loss information for FCEV12 includes the hydrogen / electricity conversion efficiency of FCEV12 (i.e., information representing the proportion of energy lost when generating electricity from hydrogen). In the case where the power system 1 includes multiple FCEVs of different vehicle types, the hydrogen / electricity conversion efficiency of each FCEV can be the average hydrogen / electricity conversion efficiency of the multiple FCEVs included in the power system 1. Details will be described later. The loss acquisition unit 111 refers to the hydrogen / electricity conversion efficiency of FCEV12 to predict the output loss that will occur when the remaining electricity is stored in the hydrogen station 80.

[0074] The location and status of the vehicles (e.g., temperature of the energy storage device, input / output power, and remaining energy) are acquired by various sensors mounted on each vehicle and transmitted from each vehicle to server 100. Each vehicle may also transmit its latest location and status sequentially at predetermined intervals, or transmit the stored data centrally at predetermined times (e.g., at the end of a journey). The driving plan is transmitted from portable terminal 10 to server 100. However, server 100 can also predict the vehicle's driving plan based on historical vehicle data. The self-discharge rate, SOC / temperature / resistance mapping, and hydrogen / electricity conversion efficiency described above can also be calculated in advance through experiments or simulations and stored in storage device 120.

[0075] Server 100 registers EVSE20, residential 30, commercial facility 40, factory 50, ESS60, FCS70, hydrogen station 80, natural variable power source 91, and generator 92 as fixed DERs. Resource information includes the location, specifications, and input / output power of each fixed DER. The resource information for EVSE20 and hydrogen station 80 also includes whether or not a vehicle is connected. Furthermore, the remaining energy is included in the resource information for EVSE20, ESS60, FCS70, and hydrogen station 80 connected to BEV11. The remaining energy of EVSE20 connected to BEV11 is the SOC of the energy storage device B1. The remaining energy of ESS60 is the SOC of ESS60. The remaining energy of FCS70 and hydrogen station 80 is the remaining hydrogen in their hydrogen tanks. Server 100 can obtain the status (e.g., input / output power and remaining energy) of each fixed DER through communication with them.

[0076] The resource information for ESS60, FCS70, and hydrogen station 80 also includes loss information for calculating energy loss. The loss information for ESS60 includes its self-discharge rate and its SOC / temperature / resistance mapping. Furthermore, the loss information for FCS70 includes the hydrogen leakage rate of hydrogen tank 72 (i.e., information converting the amount of hydrogen released from the tank per unit time into electrical energy), the power / hydrogen conversion efficiency of hydrogen generation device 73 (i.e., information representing the proportion of energy lost when generating hydrogen from electricity), and the hydrogen / electricity conversion efficiency of fuel cell 71. The loss information for hydrogen station 80 includes the hydrogen leakage rate of hydrogen tanks and the power / hydrogen conversion efficiency of hydrogen generation device.

[0077] The user information includes the communication address of the portable terminal 10 carried by the user, the vehicle ID of the vehicle belonging to the user, and the resource ID of the fixed DER belonging to the user.

[0078] Furthermore, the information management unit 114 manages information related to energy management (hereinafter also referred to as "EM information"). EM information is time-separated and stored in the storage device 120. In this embodiment, the EM information includes meteorological data and historical demand data as described below.

[0079] Meteorological data includes both predicted and measured values ​​of meteorological information for each region. Meteorological information includes, for example, weather conditions, temperature, sunshine intensity, and wind speed. Weather is categorized as, for example, sunny / cloudy / rainy / snowy. Information Management Department 114 can also obtain predicted and measured values ​​of meteorological information using publicly available meteorological services (e.g., services provided by meteorological bureaus, information technology companies, or telecommunications companies). Information Management Department 114 manages meteorological data by distinguishing between target areas and times (measurement time or prediction time).

[0080] Historical demand data may include daily power demand curves (power demand shifts) of the microgrid MG measured in the past. Power demand may also be stored in storage device 120 in association with the measurement time and meteorological data (e.g., temperature). Information management unit 114 may also obtain power demand curves from receiving transformer 501. Power demand of the microgrid MG may also be measured by a power meter (not shown) installed in receiving transformer 501 and stored in storage device 120 in association with the measurement time. The data interval for the power demand curves may be less than 10 minutes, approximately 30 minutes, or 1 to 3 hours. Historical demand data may include, for example, data from the past three years, or data from longer periods.

[0081] Server 100 is configured to use DER group 500 for energy management of the microgrid MG. Figure 1 and Figure 2 and Figure 3 This is a diagram illustrating the energy management method of this embodiment. (Refer to...) Figure 3 When, for example, surplus electricity is generated in the microgrid MG due to power generation from the naturally fluctuating power source 91, server 100 selects a storage destination for the surplus electricity from EVSE20, ESS60, FCS70, and hydrogen station 80 connected to BEV11. Hereinafter, EVSE20 connected to BEV11 is sometimes referred to as "BEV-EVSE". In DER group 500, BEV-EVSE can store the electricity received from the microgrid MG by EVSE20 in the energy storage device B1 of BEV11. ESS60 can store electricity supplied from the microgrid MG. Each of FCS70 and hydrogen station 80 can convert the electricity supplied from the microgrid MG into hydrogen and store it in a hydrogen tank. In this embodiment, each of the EVSE20, ESS60, FCS70, and hydrogen station 80 connected to BEV11 included in DER group 500 corresponds to an example of the "energy storage resources" of the present invention.

[0082] Refer again Figure 1 and Figure 2 The loss acquisition unit 111 acquires the energy loss incurred during energy storage in each of the BEV-EVSE, ESS60, FCS70, and hydrogen station 80 included in the DER group 500. The energy loss acquired by the loss acquisition unit 111 is the total loss. When energy is stored in the DER, energy loss occurs during energy storage in the DER (i.e., storage loss). In addition, energy loss occurs during the input and output of energy stored in the DER (i.e., input and output loss). The total loss is the sum of the storage loss and the input and output loss.

[0083] In this embodiment, when the loss acquisition unit 111 generates surplus power in the microgrid MG, it predicts the storage period for each of the BEV-EVSE, ESS60, FCS70, and hydrogen station 80 included in the DER group 500. The storage period predicted by the loss acquisition unit 111 is the period during which the surplus power is stored in the DER if it is stored in the DER. The longer the storage period, the greater the storage loss.

[0084] The loss acquisition unit 111 uses the predicted storage period to acquire the storage losses of each of the BEV-EVSE, ESS60, FCS70, and hydrogen station 80. The loss acquisition unit 111 also uses the loss information within the storage device 120 to acquire the input / output losses of each of the BEV-EVSE, ESS60, FCS70, and hydrogen station 80. Furthermore, the loss acquisition unit 111 calculates the overall loss of each of the BEV-EVSE, ESS60, FCS70, and hydrogen station 80 by adding the storage losses to the input / output losses.

[0085] The selection unit 112 uses the overall loss predicted as described above to select a DER for storing surplus power from the DER group 500. More specifically, the selection unit 112 selects DERs for storing surplus power sequentially, starting with the DERs with the smallest overall loss.

[0086] The storage control unit 113 controls the DER group 500 in such a way that the remaining power is stored in one or more DERs selected by the selection unit 112. The storage control unit 113 controls the power conversion circuit of each DER included in the DER group 500 in such a way that the remaining power of the microgrid MG is stored only in the DERs selected by the selection unit 112.

[0087] Figure 4 This is a flowchart illustrating the energy management-related processes performed by server 100. The processes shown in the flowchart are executed repeatedly, for example, at a predetermined period.

[0088] Reference Figure 1 and Figure 2 as well as Figure 4 In step (hereinafter referred to as "S") 11, the selection unit 112 determines whether surplus power has been generated in the microgrid MG. For example, when the power output of the naturally fluctuating power source 91, which depends on weather conditions, increases, the power supplied by the microgrid MG may sometimes exceed the power demand of the microgrid MG. During the period when it is determined in S11 that no surplus power has been generated, the process of S11 is repeated. On the other hand, when it is determined in S11 that yes (surplus power has been generated), the process proceeds to the next step (S12).

[0089] In S12, the following instructions are executed. Figure 5 The processing is shown. Figure 5 This is a flowchart illustrating the processes related to DER selection performed by server 100. (See reference...) Figure 1 and Figure 2 as well as Figure 5 The loss acquisition unit 111, through processing in S21 to S24, acquires the overall losses of BEV-EVSE, ESS60, FCS70 and hydrogen station 80 included in DER group 500.

[0090] In S21, the loss acquisition unit 111 predicts the storage period of each of the BEV-EVSE, ESS60, FCS70 and hydrogen station 80 included in DER group 500. Figure 6 This is a diagram used to illustrate the processing (S21) during the prediction storage period.

[0091] Reference Figure 1 and Figure 2 as well as Figure 6 The loss acquisition unit 111 uses the driving plan of the BEV11 to predict the storage period of the BEV-EVSE. Regarding the electricity stored in the energy storage device B1 of the BEV11, since the BEV11 begins driving, there is a high probability that it will be released for driving. In this embodiment, the loss acquisition unit 111 will use the period from the current time (i.e., the time when remaining electricity is generated in the microgrid MG) to the start of driving of the BEV11 as the storage period of the BEV-EVSE.

[0092] The loss acquisition unit 111 uses the remaining hydrogen amount of FCEV12 and the driving plan to predict the hydrogen refueling time of FCEV12, and uses the predicted hydrogen refueling time to predict the storage period of hydrogen station 80. FCEV12 consumes hydrogen due to driving, and when the remaining hydrogen amount in the hydrogen tank of the power generation unit H2 decreases, hydrogen is refueled at hydrogen station 80. Therefore, the loss acquisition unit 111 can predict the hydrogen refueling time of FCEV12 (i.e., the timing of FCEV12 refueling at hydrogen station 80) using the remaining hydrogen amount of FCEV12 and the driving plan. The hydrogen stored in hydrogen station 80 is released to supply hydrogen to FCEV12. In this embodiment, the loss acquisition unit 111 uses the period from the current timing to the hydrogen refueling time of FCEV12 as the storage period of hydrogen station 80.

[0093] The loss acquisition unit 111 predicts the sufficient supply period of the microgrid MG (i.e., the period from the generation of surplus power in the microgrid MG to the point where the demand for power in the microgrid MG exceeds the supply power), and uses the predicted sufficient supply period to obtain the storage periods of ESS60 and FCS70 respectively. The energy stored in ESS60 and FCS70 is likely to be released to meet demand when the demand for power in the microgrid MG exceeds the supply power. Therefore, regarding the storage periods of ESS60 and FCS70, it is considered that the longer the sufficient supply period, the longer the energy storage period. In this embodiment, ESS60 and FCS70 correspond to an example of the "stationary energy storage device" and "stationary fuel cell" of the present invention, respectively.

[0094] The loss acquisition unit 111 uses meteorological data and historical demand data to predict the next day's electricity demand curve (the shift in electricity demand) of the microgrid MG. For example, the loss acquisition unit 111 can use historical demand data (e.g., electricity demand during the same period of the previous year) to predict the next day's electricity demand curve of the microgrid MG. Furthermore, the loss acquisition unit 111 can also use meteorological data (e.g., predicted temperature) to predict the operating status of air conditioning equipment. Moreover, the loss acquisition unit 111 can also revise the predicted next day's electricity demand curve of the microgrid MG based on historical demand data according to the predicted operating status of air conditioning equipment. For example, if the temperature is expected to be higher the next day than the temperature during the same period of the previous year, and more residences 30, commercial facilities 40, and factories 50 are operating air conditioning equipment, the loss acquisition unit 111 can also revise the predicted value of the next day's electricity demand of the microgrid MG to the larger side. The loss acquisition unit 111 can also use at least one of a weekly meteorological forecast (e.g., the end of the rainy season) and a multi-month meteorological forecast (e.g., a cold summer) to perform demand forecasting.

[0095] The loss acquisition unit 111 uses meteorological data (e.g., weather, solar radiation intensity, and wind speed) to predict the power generation curve (power generation shift) of the naturally fluctuating power source 91 for the following day. For example, the loss acquisition unit 111 can predict the solar power generation curve based on the naturally fluctuating power source 91 for the following day using weather forecasts and predicted solar radiation intensity. Furthermore, the loss acquisition unit 111 can predict the wind power generation curve based on the naturally fluctuating power source 91 for the following day using weather forecasts and predicted wind speed.

[0096] The loss acquisition unit 111 can also use the demand power curve and power generation curve for the next day, as described above, to predict the timing when the demand power of the microgrid MG will exceed the supply power. If the state of the power supply of the microgrid MG exceeding the demand power continues until the next day, the loss acquisition unit 111 can also use more future forecast data (e.g., the demand power curve and power generation curve for the next day) to predict the timing when the demand power of the microgrid MG will exceed the supply power.

[0097] The loss acquisition unit 111 uses the period during which the microgrid MG is adequately supplied, as predicted above, as the storage period for ESS60 and FCS70 respectively.

[0098] Refer again Figure 1 and Figure 2 as well as Figure 5In S22, the loss acquisition unit 111 uses the storage period predicted in S21 and the loss information within the storage device 120 to acquire the storage loss Ra for each of the BEV-EVSE, ESS60, FCS70, and hydrogen station 80. In S23, the loss acquisition unit 111 uses the loss information within the storage device 120 to acquire the input / output loss Rb for each of the BEV-EVSE, ESS60, FCS70, and hydrogen station 80. In S24, the loss acquisition unit 111 adds the storage loss Ra and the input / output loss Rb to acquire the overall loss Rt for each of the BEV-EVSE, ESS60, FCS70, and hydrogen station 80.

[0099] More specifically, the loss acquisition unit 111 obtains loss information (including the self-discharge rate of the energy storage device B1) from the storage device 120 and predicts the storage loss Ra (S22) as the product of the self-discharge rate of the energy storage device B1 and the storage period of BEV11, which is BEV-EVSE. The loss acquisition unit 111 obtains loss information (including a SOC / temperature / resistance mapping) from the storage device 120 and uses the SOC / temperature / resistance mapping of the energy storage device B1 to calculate the resistance of the energy storage device B1 corresponding to its SOC and temperature. The loss acquisition unit 111 calculates the resistance of the energy storage device B1 according to the formula "Input Loss = I in ×I in ×R in (I) in Input current, R in Calculate the input loss of BEV-EVSE based on the input resistance, and then calculate the output loss according to the formula "output loss I". out ×I out ×R out (Iout: output current, Rout: resistance at output), calculate the output loss of BEV-EVSE. in and I out Each can be a predetermined value or the average value of past input and output data. The loss acquisition unit 111 predicts that the sum of the input loss and output loss obtained above is the input-output loss Rb of BEV-EVSE (S23). Then, the loss acquisition unit 111 predicts that the sum of the storage loss Ra and the input-output loss Rb of BEV-EVSE obtained above is the overall loss Rt of BEV-EVSE (S24).

[0100] Similar to the BEV-EVSE described above, the loss acquisition unit 111 predicts that the product of the self-discharge rate of ESS60 and the storage period of ESS60 is the storage loss Ra of ESS60 (S22). Furthermore, the loss acquisition unit 111 calculates the input loss and output loss of ESS60 using the same method as BEV-EVSE. The loss acquisition unit 111 predicts that the sum of the obtained input loss and output loss is the input-output loss Rb of ESS60 (S23). Then, the loss acquisition unit 111 predicts that the sum of the obtained storage loss Ra and input-output loss Rb of ESS60 is the overall loss Rt of ESS60 (S24).

[0101] The loss acquisition unit 111 obtains loss information (including hydrogen leakage rate) from the storage device 120 and predicts that the product of the hydrogen leakage rate of the hydrogen tank 72 and the storage period of the FCS70 is the storage loss Ra of the FCS70 (S22). Furthermore, the hydrogen leakage rate is smaller than the self-discharge rate. The loss acquisition unit 111 uses the power / hydrogen conversion efficiency of the hydrogen generation device 73 to calculate the input loss of the FCS70. The loss acquisition unit 111 uses the hydrogen / power conversion efficiency of the fuel cell 71 to calculate the output loss of the FCS70. The loss acquisition unit 111 predicts that the sum of the obtained input loss and output loss is the input-output loss Rb of the FCS70 (S23). Then, the loss acquisition unit 111 predicts that the sum of the obtained storage loss Ra of the FCS70 and the input-output loss Rb is the overall loss Rt of the FCS70 (S24). Furthermore, the input-output loss Rb of the FCS70 is larger than the input-output loss Rb of the ESS60.

[0102] Similar to the FCS70 described above, the loss acquisition unit 111 predicts the storage loss of hydrogen station 80 as the product of the hydrogen leakage rate of the hydrogen tank and the storage period of hydrogen station 80 (S22). The loss acquisition unit 111 calculates the input loss of hydrogen station 80 using the power / hydrogen conversion efficiency of the hydrogen generation device of hydrogen station 80. The loss acquisition unit 111 calculates the output loss of hydrogen station 80 using the hydrogen / power conversion efficiency of FCEV12. The loss acquisition unit 111 predicts that the sum of the obtained input loss and output loss is the input-output loss Rb of hydrogen station 80 (S23). Then, the loss acquisition unit 111 predicts that the sum of the obtained storage loss Ra and input-output loss Rb of hydrogen station 80 is the overall loss Rt of hydrogen station 80 (S24). Furthermore, the input-output loss Rb of hydrogen station 80 is larger than the input-output loss Rb of BEV-EVSE.

[0103] The formulas used to calculate storage loss and input / output loss are not limited to those described above. The loss acquisition unit 111 can also modify the formulas based on past realities. The loss acquisition unit 111 can also use machine learning to update the formulas sequentially based on statistical data (e.g., big data).

[0104] In S25, selection unit 112 selects the number of DERs required to store the remaining electricity from the BEV-EVSE, ESS60, FCS70, and hydrogen station 80 included in DER group 500. Selection unit 112 selects sequentially from the DERs with the smallest predicted overall loss Rt from the processing in S21 to S24. The overall loss Rt of ESS60 and FCS70 is affected by the weather the following day. Hereinafter, using... Figure 7 and Figure 8 This describes the processing selected by DER.

[0105] Figure 7 This is a graph representing an example of the overall loss Rt for each DER when the weather is sunny the following day. (See reference...) Figure 7 If the weather is clear the following day, the power supplied to the microgrid MG increases due to solar power generation from the natural variable power source 91, and the storage periods of ESS60 and FCS70 tend to lengthen. Because ESS60 has a high self-discharge rate, storing surplus power in ESS60 for an extended period tends to result in significant energy loss due to self-discharge. On the other hand, because FCS70 has a low hydrogen leakage rate, even with long-term storage of surplus power in FCS70, energy loss during storage is less likely to increase. Based on this tendency, in Figure 7 In the example shown, the overall loss Rt of ESS60 is larger than that of FCS70.

[0106] Figure 8 This is a graph illustrating an example of the overall loss Rt of each DER when the weather is cloudy the following day. When the weather is cloudy the following day, the storage period for both ESS60 and FCS70 tends to be shorter than when the weather is sunny. Therefore, the energy loss in storage when storing surplus electricity in ESS60 tends to decrease. On the other hand, the input-output loss Rb of FCS70 is larger than that of ESS60. Therefore, in Figure 8 In the example shown, the overall loss Rt of FCS70 is greater than that of ESS60.

[0107] Figure 7 The overall losses Rt for each DER shown, from smallest to largest, are: BEV-EVSE, FCS70, hydrogen station 80, and ESS60. Therefore, in Figure 7 In the example shown, the selection priority in S25, from highest to lowest, is: BEV-EVSE, FCS70, hydrogen station 80, and ESS60. Therefore, in S25, BEV-EVSE is selected before FCS70, FCS70 is selected before hydrogen station 80, and hydrogen station 80 is selected before ESS60.

[0108] Figure 8 The overall losses Rt for each DER shown, from smallest to largest, are: ESS 60, BEV-EVSE, FCS 70, and hydrogen station 80. Therefore, in Figure 8 In the example shown, the selection priority in S25, from highest to lowest, is ESS60, BEV-EVSE, FCS70, and hydrogen station 80. Therefore, in S25, ESS60 is selected before BEV-EVSE, BEV-EVSE is selected before FCS70, and FCS70 is selected before hydrogen station 80.

[0109] Figure 7 and Figure 8 The overall loss Rt is shown for only one BEV-EVSE, but power system 1 contains multiple BEV-EVSEs. The overall loss Rt varies for each BEV-EVSE. BEV-EVSEs with smaller overall loss Rts have a higher selection priority in S25, while BEV-EVSEs with larger overall loss Rts have a lower selection priority in S25.

[0110] When processing S25 is executed, Figure 5 The series of processes shown ( Figure 4 S12) ends. Then, processing enters... Figure 4 S13. Refer again. Figure 1 and Figure 2 as well as Figure 4 In S13, the storage control unit 113 controls the DER group 500 to store the remaining power in the DERs selected in S12 (more specifically, the remaining power determined to be "generated" in S11). The storage control unit 113, for example, controls the power conversion circuits of each DER, connecting the selected DERs to the microgrid MG and disconnecting the unselected DERs from the microgrid MG. Thus, the remaining power of the microgrid MG is stored only in the DERs selected in S12. The storage amount for each selected DER can be equal or different. The storage control unit 113 can preferentially store power in the selected DERs with higher priority (i.e., DERs with smaller overall loss Rt). To prevent excessive power storage in a single DER, an upper limit can be set for the storage amount. When the processing in S13 is executed, the process returns to the initial step (S11).

[0111] As described above, the power management method of this embodiment is a method of managing the power of the microgrid MG using multiple DERs that can be electrically connected to the microgrid MG, and includes... Figure 5S21 to S25 are shown. In S21 to S24, when surplus power is generated in the microgrid MG, the server 100 obtains the total loss Rt (i.e., energy loss including storage loss and input / output loss) generated when storing energy in each of the plurality of DERs. In S25, the server 100 uses the obtained total loss Rt to select one or more DERs from the plurality of DERs for storing surplus power.

[0112] In step S25 above, server 100 selects an energy storage resource for storing the remaining power, taking into account the energy losses (including storage losses and input / output losses) incurred when storing the remaining power. Therefore, according to the power management method described above, it is possible to store the remaining power in a manner that minimizes energy losses.

[0113] Server 100 can also be used as a substitute. Figure 5 The process shown is executed. Figure 9 The processing shown. Figure 9 It means Figure 5 The flowchart shows a variation of the processing. Figure 9 S21 to S25 and Figure 5 S21 to S25 are the same.

[0114] Reference Figure 1 and Figure 2 and Figure 9 In step S31, the selection unit 112 determines whether there are any DERs in the DER group 500 with insufficient energy reserves. The selection unit 112 determines whether each DER has insufficient energy reserves, for example, based on whether the energy reserves of each DER are less than a predetermined lower limit. The predetermined lower limit values ​​for each DER may be different.

[0115] If the condition is determined to be present in S31, then in S32, the selection unit 112 selects the DER with insufficient remaining energy as the DER for storing remaining power. If multiple DERs with insufficient remaining energy exist, all of these DERs are selected. Figure 10 This is a diagram illustrating the treatment (S32) for DERs with insufficient selected energy reserves. (See reference...) Figure 10 In this example, among BEV-EVSE, ESS60, FCS70, and hydrogen station 80, the energy surplus of ESS60 is below the specified lower limit. Therefore, in Figure 9 In S32, select ESS60.

[0116] Refer again Figure 1 and Figure 2 as well as Figure 9Following S32, the process proceeds to S33. In S33, the selection unit 112 determines whether the selection of the DER for storing remaining power has been completed. If the remaining power can be stored using only the DER with insufficient remaining energy, the determination is made as yes in S33. Figure 9 The series of processes shown ( Figure 4 End of S12). Then, in Figure 4 In S13, the remaining power is stored equally for DERs with insufficient remaining energy.

[0117] On the other hand, if the remaining power cannot be stored by the DER alone due to insufficient remaining energy, the process is determined to be negative in S33, and proceeds to S34. Furthermore, if the process is determined to be negative (does not exist) in S31, the process also proceeds to S34.

[0118] In S34, the selection unit 112 determines whether there are areas with insufficient energy surplus in the cities that receive power from the microgrid MG. If the determination is yes (exists) in S34, in S35, the selection unit 112 limits the candidates for DERs used to store surplus power to DERs that exist in areas with insufficient energy surplus. Then, the process proceeds to S21.

[0119] Figure 11 This diagram illustrates the process (S34 and S35) of limiting selected candidates to DERs within regions with insufficient energy reserves. (See also...) Figure 1 and Figure 2 as well as Figure 11 In this example, the city receiving power from the microgrid MG is divided into four regions A to D. Then, the information management unit 114 manages the energy surplus of each region. In this example, the energy surplus of a region means the sum of the energy surplus of all DERs existing in that region. The selection unit 112... Figure 9 In S34, the energy surplus of each region is determined to be insufficient based on whether it is less than a specified lower limit. The specified lower limit can also vary for each region. Figure 11 In the example shown, the energy surplus in regions B and D within regions A–D is below the specified lower limit. Therefore, in Figure 9 In S34, it is determined that it exists. Figure 9 In S35, the selected candidates (i.e., candidates for DERs to store surplus power) are limited to DERs existing in regions B and D. That is, DERs existing in regions A and C are excluded from the candidate selection. Thus, in Figure 9 From S21 to S25, a DER for storing surplus electricity is selected from BEV-EVSE, ESS60, FCS70 and hydrogen station 80 that exist in regions B and D.

[0120] Furthermore, if the total remaining energy in regions A through D is above the specified lower limit, the condition is determined as no (does not exist) in S34. In this case, the selected candidate is not limited, and the process proceeds to S21.

[0121] The selected part 112 of the above-described modified example is used when there is a DER with insufficient energy remaining in the DER group 500. Figure 9 In S31, the DER with insufficient remaining energy is selected as the DER for storing the remaining power. Figure 9 S32), in the case that there are no DERs with insufficient energy reserves in DER group 500 ( Figure 9 (In S31, if not), starting with the DER that has the smallest overall loss Rt (i.e., energy loss including storage loss and input / output loss) when storing surplus power, one or more DERs are selected sequentially for storing surplus power. Figure 9 (S21 to S25). Based on this structure, it is possible to suppress the insufficient energy surplus of the DER.

[0122] The selected section 112 in the above-described modified example obtains the energy surplus of each region. Then, in the case where there are regions with insufficient energy surplus (in... Figure 9 In S34, the selection unit 112 limits the candidate DER for storing surplus power to DERs that exist in areas with insufficient energy reserves. Figure 9 (S35). According to this structure, surplus electricity can be preferentially stored in the DER that exists in areas with insufficient energy surplus. Thus, it is possible to suppress areas with insufficient energy surplus.

[0123] In the above embodiments, when the remaining electricity stored in the vehicle is used during vehicle operation, the energy lost during operation is also treated as energy loss. However, this is not a limitation; the energy lost during vehicle operation may also be treated as usable energy rather than energy loss. That is, energy loss can also be calculated by removing the energy lost during vehicle operation.

[0124] In the above implementation, considering individual differences among vehicles, loss information for each vehicle is prepared in server 100, but such a structure is not mandatory. For example, the average data for each vehicle type can also be used as the loss information for the corresponding vehicle type. Server 100 can also use machine learning to update the average data for each vehicle type sequentially based on statistical data (e.g., big data).

[0125] Server 100 can collaboratively control DER group 500 with other servers. Alternatively, DERs included in DER group 500 can be grouped, with a server set up for each group (e.g., a server managing the DERs within the group). For example, a server can be set up to control each EMS. Server 100 can then control DER group 500 via the server in each group.

[0126] The structure of the vehicle used as an energy storage resource is not limited to the structure shown in the above embodiments. For example, the vehicle does not need to have a communication device for wireless communication with server 100. Furthermore, a PHEV (Plug-in Hybrid Electric Vehicle) can also be used as an energy storage resource. The vehicle can also be configured to be able to charge without contact. The vehicle is not limited to a passenger car; it can also be a bus or a truck. The vehicle can be configured to be capable of autonomous driving and may also have flight capabilities. The vehicle can be a driverless vehicle (e.g., an automated guided vehicle (AGV) or agricultural machinery).

[0127] In the above embodiments, the server and power management method are applicable to the energy management of AC (alternating current) power grids, but the above server and power management method can also be applied to the energy management of DC (direct current) power grids.

[0128] While embodiments of the invention have been described, they should be considered illustrative rather than restrictive in all respects. The scope of the invention is defined by the claims, which include all modifications within the meaning and scope equivalent to those claims.

Claims

1. A server that implements power grid energy management using multiple energy storage resources, having: The loss acquisition unit acquires, for each of the plurality of energy storage resources, the energy loss generated during the storage of energy in that energy storage resource, including storage loss and input / output loss; When a selected unit generates surplus electricity in the power grid, it utilizes the energy loss incurred during the storage of the surplus electricity to select one or more energy storage resources from a plurality of energy storage resources for storing the surplus electricity. in, When there is an energy storage resource with insufficient remaining energy among the plurality of energy storage resources, the selection unit selects the energy storage resource with insufficient remaining energy as the energy storage resource for storing the remaining electricity. When there is no energy storage resource with insufficient remaining energy among the plurality of energy storage resources, starting from the energy storage resource with the smallest energy loss when storing the remaining electricity, one or more energy storage resources are selected sequentially for storing the remaining electricity.

2. The server according to claim 1, wherein, When the residual power is generated in the power grid, the loss acquisition unit predicts, for each of the plurality of energy storage resources, the period during which the residual power is stored in that energy storage resource, i.e., the storage period, and uses the predicted storage period to acquire the storage loss.

3. The server according to claim 2, wherein, The plurality of energy storage resources include at least one of stationary energy storage devices and stationary fuel cells. The loss acquisition unit predicts the period from the generation of the surplus power in the power grid to the point where the power demand of the power grid exceeds the power supply, i.e., the sufficient supply period, and uses the predicted sufficient supply period to obtain the storage period of at least one of the stationary energy storage device and the stationary fuel cell.

4. The server according to claim 3, wherein, The power grid is configured to supply electricity to multiple residences. The power grid is configured to receive power from naturally varying sources of electricity that change according to weather conditions. The loss acquisition unit uses meteorological forecast information to predict the power demand and power supply of the power grid.

5. The server according to any one of claims 2 to 4, wherein, The plurality of energy storage resources include vehicles, which have energy storage devices capable of connecting to external power supply equipment. The loss acquisition unit uses the vehicle's driving plan to predict the vehicle's storage period.

6. The server according to any one of claims 2 to 4, wherein, The aforementioned energy storage resources include hydrogen stations capable of supplying hydrogen to fuel cell vehicles. The loss acquisition unit uses the remaining hydrogen amount and driving plan of the fuel cell vehicle to predict the hydrogen refueling time of the fuel cell vehicle, and uses the predicted hydrogen refueling time to predict the storage period of the hydrogen station.

7. The server according to any one of claims 1 to 4, wherein, When there is a region with insufficient remaining energy, the selection unit limits the candidates for energy storage resources used to store the remaining electricity to energy storage resources that exist in the region with insufficient remaining energy.

8. The server according to any one of claims 1 to 4, wherein, It also includes a storage control unit that controls the plurality of energy storage resources in such a way that the remaining electricity is stored in one or more energy storage resources selected by the selection unit.

9. A power management method, comprising using multiple energy storage resources capable of being electrically connected to a power grid to implement power management of the power grid, including: When surplus power is generated in the power grid, for each of the plurality of energy storage resources, the step of obtaining the energy loss generated when storing energy in that energy storage resource, including storage loss and input / output loss; The step of selecting one or more energy storage resources from the plurality of energy storage resources to store the surplus electricity using the obtained energy loss. in, If there is an energy storage resource with insufficient remaining energy among the plurality of energy storage resources, the energy storage resource with insufficient remaining energy is selected as the energy storage resource for storing the remaining electricity. If there is no energy storage resource with insufficient remaining energy among the plurality of energy storage resources, one or more energy storage resources are selected sequentially for storing the remaining electricity, starting from the energy storage resource with the smallest energy loss when storing the remaining electricity.

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