JP7736207B2 - Power management method and power management system - Google Patents

Description

The present invention relates to a power management method and a power management system.

Patent Literature 1 describes an electric power management system that appropriately manages the charging and discharging of secondary batteries in electric vehicles to level the balance of power supply and demand in multiple adjacent microgrids. The electric power management system described in Patent Literature 1 predicts changes in the supply and demand gap, which is the difference between the amount of power generated by power generation equipment and the amount of power consumed by power consumption equipment, for each microgrid. Then, for electric vehicles located within the area corresponding to each microgrid, the remaining charge of the secondary battery is obtained, and information is distributed to the electric vehicles to encourage them to charge and discharge the secondary battery based on the predicted supply and demand gap and the remaining charge.

Japanese Patent Application Laid-Open No. 2020-114090

The power management system described in Patent Document 1 transmits information to electric vehicles with surplus power, encouraging them to supply the surplus power they have stored in a microgrid where the power supply-demand gap is below a predetermined value, i.e., a microgrid where power shortages are predicted. However, electric vehicles that are not scheduled to operate in an area corresponding to a microgrid where power shortages are predicted are likely not permitted to supply surplus power. Therefore, even if information encouraging them to supply the surplus power is transmitted to all electric vehicles with surplus power, it is not possible to efficiently resolve the supply-demand gap in a microgrid where power shortages are predicted.

The present invention has been made in consideration of the above-mentioned problems, and its purpose is to provide a power management method and a power management system that can efficiently eliminate the supply-demand gap in a microgrid where power shortages are predicted.

A power management method according to one aspect of the present invention is a power management method for a power management system that manages the balance of power supply and demand in a plurality of microgrids in which power generation facilities that generate power using natural energy and power consumption facilities that consume power supplied from the power generation facilities are connected, the method comprising:
For each of the multiple microgrids, a change in the supply-demand gap, which is the amount of power generated by the power generation equipment minus the amount of power consumed by the power consumption equipment, is predicted;
identifying a second region having the largest number of electric vehicles moving to a first region corresponding to a first microgrid predicted to have a supply-demand gap smaller than a threshold, based on first data indicating inter-regional dynamics of electric vehicles located in each region corresponding to each of the plurality of microgrids;
First information is distributed to an electric vehicle located in the second area, prompting the electric vehicle to move to the first area and discharge the secondary battery.

According to the present invention, it is possible to efficiently eliminate the supply-demand gap in a microgrid where power depletion is predicted.

FIG. 1 is a block diagram showing an example of the configuration of a power management system according to an embodiment of the present invention. FIG. 2 is a diagram illustrating an example of the configuration of a power management system according to an embodiment of the present invention. FIG. 3 is a diagram illustrating an example of the first data. FIG. 4 is a flowchart showing an example of the operation of the central management device. FIG. 5 is a flowchart showing an example of the operation of the electric vehicle. FIG. 6 is a flowchart showing an example of the process of step S13 in FIG.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the description of the drawings, the same parts are designated by the same reference numerals and the description thereof will be omitted.

[Configuration of the power management system]
An example configuration of a power management system 1 according to this embodiment will be described with reference to FIGS. 1 and 2. As shown in FIG. 1, the power management system 1 is mainly composed of a central management device 10, multiple microgrids 20A to 20D, and multiple electric vehicles 30. As shown in FIG. 2, the power management system 1 has multiple regions A to D obtained by dividing an electric power demand area. Region A corresponds to microgrid 20A, region B corresponds to microgrid 20B, region C corresponds to microgrid 20C, and region D corresponds to microgrid 20D. The number of regions into which the supply and demand area is divided is not particularly limited, and may be three or less, or five or more. Each of regions A to D is assumed to be a small area that can be traveled by vehicle in a relatively short time.

As shown in FIG. 1, each of the microgrids 20A to 20D is connected to a power generation facility 21, a power storage facility 22, and a plurality of power consumption facilities (power consumption loads: consumers) 23.

The power generation facility 21 is, for example, a solar power generation facility equipped with solar panels. However, the power generation facility 21 does not need to be limited to solar power generation, and other power generation methods may be used as long as the facility generates power using natural energy. For example, the colored areas in Figure 2 are areas where the natural energy generation situation is poor (for example, cloudy weather and weak sunlight).

The power storage facility 22 stores the power generated by the power generation facility 21. The plurality of power consumption facilities 23 consume the power supplied from the power generation facility 21 (and the power storage facility 22).

Each of the microgrids 20A to 20D is configured to supply power to secondary batteries equipped in electric vehicles such as electric cars and hybrid cars, and to discharge power from the secondary batteries equipped in the electric vehicles to the power grid. Charging and discharging equipment (not shown) is connected to the power grid, and the secondary batteries of the electric vehicles can be charged or discharged via this charging and discharging equipment. Basically, power is not exchanged between the microgrids 20A to 21D, and each of the microgrids 20A to 21D independently manages its own power supply and demand.

Each of the microgrids 20A to 20D is connected to a central management device (server) 10 that manages the supply and demand of power for each of the microgrids 20A to 20D via a wireless or wired network.

The central management device 10 is a controller that performs processing to manage the balance of power supply in the multiple microgrids 20A to 20D.

The central management device 10 is connected to each of the microgrids 20A to 20D via a wireless or wired network. The central management device 10 also communicates with each of the electric vehicles 30 via the wireless network. The network may be, for example, the Internet, or may utilize a mobile communication function such as 4G/LTE or 5G.

The central management unit 10 can be realized using a microcomputer equipped with a CPU (Central Processing Unit), memory, and input/output units. A computer program for causing the microcomputer to function as the central management unit 10 is installed and executed on the microcomputer. This allows the microcomputer to function as the multiple information processing units (11-16) included in the central management unit 10. While an example of implementing the central management unit using software is shown here, it is of course also possible to configure the central management unit 10 by providing dedicated hardware for executing each information processing unit. Dedicated hardware includes devices such as application-specific integrated circuits (ASICs) and conventional circuit components arranged to perform the functions described in the embodiments. Alternatively, the multiple information processing units (11-16) may be configured as separate hardware.

The central management device 10 has multiple information processing units (11 to 16), including a vehicle information acquisition unit 11, a supply and demand gap prediction unit 12, a region identification unit 13, a vehicle identification unit 14, an information distribution unit 15, and a power sales price setting unit 16.

The vehicle information acquisition unit 11 acquires, via the network, vehicle information of the electric vehicles 30 located in each of the areas A to D corresponding to each of the microgrids 20A to 20D. The vehicle information includes information indicating the current location of the electric vehicles 30, the remaining charge of the secondary batteries mounted on the electric vehicles 30, and the destination of the electric vehicles 30. The vehicle information acquisition unit 11 acquires the vehicle information of each electric vehicle 30 at a predetermined timing. In addition, the vehicle information acquisition unit 11 receives, via the network, responses to a cooperation request, which will be described later, from the electric vehicles 30.

The supply and demand gap predictor 12 acquires power generation amount information by the power generation facilities 21 of each of the microgrids 20A to 20D via a network or the like. The power generation amount information is, for example, information (weather information, etc.) on the generation status of natural energy in each of the regions A to D. For example, in the example shown in FIG. 2 , the supply and demand gap predictor 12 can predict changes in the power generation amount by the power generation facilities 21 of each of the microgrids 20A to 20D up to a predetermined time ahead based on the acquired power generation amount information.

The supply and demand gap prediction unit 12 also acquires historical demand data of the power consumption facilities 23 of each of the microgrids 20A to 20D via a network or the like. Based on the acquired historical demand data, the supply and demand gap prediction unit 12 can predict changes in the power consumption of each of the microgrids 20A to 20D up to a predetermined time ahead. The historical demand data may be data accumulated in the central management device 10. There are no particular limitations on the method for predicting the amount of power generated by the power generation facilities 21 and the amount of power consumed by the power consumption facilities 23, and as any known technology may be used, detailed description thereof will be omitted.

Based on the predicted values, the supply and demand gap prediction unit 12 predicts a change in the supply and demand gap, which is the amount of power generated by the power generation equipment 21 minus the amount of power consumed by the power consumption equipment, for each of the microgrids 20A to 20D. For example, in the example shown in Fig. 2, the weather in area C is sunny, and the supply and demand gap in microgrid 20C is larger than the threshold value. In other words, the supply and demand gap predicted by the supply and demand gap prediction unit 12 for the predetermined time ahead is larger than the threshold value.

The supply and demand gap prediction unit 12 determines whether or not there is a gap closure-requiring grid (first microgrid) that needs to close the supply and demand gap, based on the supply and demand gap predicted by the supply and demand gap prediction unit 12 for each of the microgrids 20A to 20D. The supply and demand gap prediction unit 12 determines a microgrid whose supply and demand gap is smaller than a threshold value as a gap closure-requiring grid. For example, the supply and demand gap prediction unit 12 determines a microgrid whose supply and demand gap is smaller than 0 as a gap closure-requiring grid. The supply and demand gap prediction unit 12 determines that a gap closure-requiring grid exists if there is even one microgrid whose supply and demand gap is smaller than the threshold value.

Furthermore, the supply and demand gap prediction unit 12 determines whether or not the power supply and demand gap in the gap elimination-requiring grid is expected to be eliminated after a predetermined time has elapsed since the information distribution unit 15, which will be described later, distributed a request for cooperation to eliminate the power supply and demand gap in the gap elimination-requiring grid to a predetermined electric vehicle 30. A method for determining whether or not the power supply and demand gap in the gap elimination-requiring grid is expected to be eliminated will be described later with reference to FIG.

The region specifying unit 13 specifies a region corresponding to the gap elimination grid as a first region. Then, the region specifying unit 13 specifies a second region having the largest number of electric vehicles moving to the first region based on first data indicating inter-region dynamics of electric vehicles 30 located in each of regions A to D corresponding to each of microgrids 20A to 20D.

The first data indicating the inter-regional dynamics of the electric vehicles 30 located in each of the regions A to D is specifically data indicating the OD traffic volume of the electric vehicles 30 located in each of the regions A to D corresponding to each of the microgrids 20A to 20D. The OD traffic volume is the number of electric vehicles 30 moving from an origin region to a destination region of the movement. The first data may be stored in advance in the memory of the central management device 10, for example, or may be acquired via a network or the like.

The first data may be, for example, an OD table showing the OD traffic volume of electric vehicles 30 located in each of areas A to D, as shown in FIG. 3. In FIG. 3, it is assumed that microgrid 20A is a gap elimination required grid, and area A corresponding to microgrid 20A is identified as the first area. As shown in FIG. 3, the OD traffic volume of electric vehicles 30 traveling from area B to area A is 10 vehicles. The OD traffic volume of electric vehicles 30 traveling from area C to area A is 30 vehicles. The OD traffic volume of electric vehicles 30 traveling from area D to area A is 10 vehicles. In this case, the area identification unit 13 identifies area C, which has the highest OD traffic volume of electric vehicles 30 traveling to area A identified as the first area, among areas A to D, as the second area.

The vehicle identification unit 14 identifies an electric vehicle 30 located in the second area from among the electric vehicles 30 located in each of areas A to D, based on information on the current location of the electric vehicle 30 included in the vehicle information. In the example shown in Fig. 3, the vehicle identification unit 14 identifies an electric vehicle 30 located in area C, which has been identified as the second area.

The information distribution unit 15 distributes a cooperation request (first information) to the electric vehicles 30 located in the second area identified by the vehicle identification unit 14, urging them to move to the first area and discharge their secondary batteries. In the example shown in Fig. 3 , the information distribution unit 15 distributes the cooperation request to all electric vehicles 30 located in area C identified as the second area. That is, the information distribution unit 15 distributes the cooperation request to a total of 120 vehicles 30 whose "current location" is area C, regardless of their "destination."

The information distribution unit 15 may also distribute the cooperation request together with information on the remuneration amount set by the power selling price setting unit 16, which will be described later. Furthermore, if the supply-demand gap in the gap elimination required grid is not resolved even after a predetermined time has elapsed since the information distribution unit 15 distributed the cooperation request, the information distribution unit 15 distributes a cooperation request (second information) together with information on the remuneration amount per unit amount of power to all electric vehicles 30 located in each of the regions A to D. The remuneration amount per unit amount of power is set by the power selling price setting unit 16, which will be described later.

The power selling price setting unit 16 sets a remuneration amount to be paid to the occupant of the electric vehicle 30 that discharged its secondary battery in the gap elimination required grid in proportion to the amount of power discharged from the secondary battery. Furthermore, if the supply-demand gap in the gap elimination required grid is not resolved even after a predetermined time has elapsed since the information distribution unit 15 distributed the cooperation request, the power selling price setting unit 16 executes a power selling price hike process to set a remuneration amount per unit amount of power to be paid to the occupant of the electric vehicle 30 that discharged its secondary battery in the gap elimination required grid. Details of the power selling price hike process will be described later with reference to FIG. 6 .

As shown in FIG. 1 , the electric vehicle 30 includes a vehicle state acquisition device 31 , a notification determination device 32 , an input reception device 33 , and an information transmission device 34 .

The vehicle state acquisition device 31 acquires information indicating the current position of the electric vehicle 30 and the destination of the electric vehicle 30 from a navigation device (not shown) mounted on the electric vehicle 30. The vehicle state acquisition device 31 also acquires information indicating the remaining charge of a secondary battery (not shown) mounted on the electric vehicle 30 from the secondary battery.

When the notification determination device 32 receives a cooperation request from the information distribution unit 15, it calculates a predicted State of Charge (SOC), which is the remaining charge of the secondary battery of the electric vehicle 30 at the time when the electric vehicle 30 moves to the first area and starts discharging the secondary battery, based on the current remaining charge of the secondary battery of the electric vehicle 30. The notification determination device 32 calculates, for example, the traveling distance from the current location of the electric vehicle 30 to a location where the electric vehicle 30 can move to the first area and start discharging the secondary battery, i.e., the location of a charging/discharging facility that can discharge to the gap elimination grid. Then, it calculates the predicted SOC based on the current remaining charge of the secondary battery and the calculated traveling distance.

When the predicted SOC is equal to or greater than the first predetermined value, the notification determination device 32 notifies the occupant of the electric vehicle 30 of the cooperation request received from the information distribution unit 15. The notification determination device 32 may notify the occupant of the electric vehicle 30 of the cooperation request by, for example, displaying the cooperation request on a display device such as a display mounted on the electric vehicle 30, or may notify the occupant of the electric vehicle 30 of the cooperation request via a mobile terminal carried by the occupant of the electric vehicle 30. Note that the method of notifying the cooperation request is not particularly limited.

The input receiving device 33 receives a response to the cooperation request from the occupant of the electric vehicle 30. The input receiving device 33 receives information from the occupant of the electric vehicle 30 as to whether or not the occupant accepts the cooperation request.

The information transmitting device 34 transmits vehicle information of the electric vehicle 30 to the central management device 10 via the network. The vehicle information includes information indicating the current position of the electric vehicle 30, the destination of the electric vehicle 30, and the remaining charge of the secondary battery mounted on the electric vehicle 30, which are acquired by the vehicle state acquisition device 31. The information transmitting device 34 also transmits a response to the cooperation request accepted by the input accepting device 33 to the central management device 10 via the network.

Next, an example of the operation of the power management system 1 according to the embodiment will be described with reference to Figures 4 to 6. Figure 4 is a flowchart showing an example of the operation of the central management unit 10. Figure 5 is a flowchart showing an example of the operation of the electric vehicle 30. When the electric vehicle 30 receives a signal requesting vehicle information from the central management unit 10, it starts the process of Figure 5.

First, in step S1 of FIG. 4 , the vehicle information acquisition unit 11 of the central management unit 10 acquires, via the network, vehicle information of the electric vehicles 30 located in each of the areas A to D corresponding to each of the microgrids 20A to 20D. At this time, in step S21 of FIG. 5 , the vehicle state acquisition device 31 of the electric vehicle 30 acquires information indicating the current position and destination of the electric vehicle 30 from a navigation device (not shown) mounted on the electric vehicle 30. The vehicle state acquisition device 31 also acquires information indicating the remaining charge of a secondary battery (not shown) mounted on the electric vehicle 30. The process proceeds to step S22, and the information transmission device 34 transmits the information indicating the current position of the electric vehicle 30, the destination of the electric vehicle 30, and the remaining charge of the secondary battery mounted on the electric vehicle 30, acquired by the vehicle state acquisition device 31, to the central management unit 10 as vehicle information.

The process proceeds to step S2 in Fig. 4, where the supply and demand gap prediction unit 12 acquires information on the amount of power generated by the power generation facilities 21 of each of the microgrids 20A to 20D via a network, etc. Based on the acquired information on the amount of power generated, the supply and demand gap prediction unit 12 predicts changes in the amount of power generated by the power generation facilities 21 of each of the microgrids 20A to 20D for a predetermined time period ahead.

The process proceeds to step S3, where the supply and demand gap prediction unit 12 acquires historical demand data of the power consumption facilities 23 of each of the microgrids 20A to 20D via a network, etc. Based on the acquired historical demand data, the supply and demand gap prediction unit 12 predicts changes in the power consumption of each of the microgrids 20A to 20D up to a predetermined time ahead.

The processing proceeds to step S4, where the supply and demand gap prediction unit 12 predicts the change in the supply and demand gap, which is the amount of power generated by the power generation equipment 21 minus the amount of power consumed by the power consumption equipment, for each of the microgrids 20A to 20D based on the values predicted in steps S2 and S3.

The process proceeds to step S5, where the supply and demand gap predictor 12 determines whether or not there is a gap closure-requiring grid that needs to close the supply and demand gap, based on the supply and demand gap predicted for each of the microgrids 20A to 20D in step S4. The supply and demand gap predictor 12 determines that there is a gap closure-requiring grid if there is even one microgrid whose supply and demand gap is smaller than the threshold. If there is a gap closure-requiring grid (YES in step S5), the process proceeds to step S6. On the other hand, if there is no gap closure-requiring grid (NO in step S5), the process returns to step S1.

In step S6, the region identification unit 13 identifies a region corresponding to the gap elimination grid as a first region. Then, the region identification unit 13 identifies a second region having the largest number of electric vehicles moving to the first region based on first data indicating the inter-regional dynamics of electric vehicles 30 located in each of regions A to D corresponding to each of the microgrids 20A to 20D. For example, the region identification unit 13 identifies the second region having the largest number of electric vehicles moving to the first region based on an OD table indicating the OD traffic volume of electric vehicles 30 located in each of regions A to D.

The processing proceeds to step S7, where the vehicle identification unit 14 identifies the electric vehicles 30 located in the second region from among the electric vehicles 30 located in each of regions A to D based on the information on the current location of the electric vehicles 30 included in the vehicle information.

The process proceeds to step S8, where the information distribution unit 15 distributes a cooperation request to the electric vehicles 30 located in the second area identified in step S7, urging them to move to the first area and discharge their secondary batteries.

5, if the electric vehicle 30 receives a cooperation request from the information distribution unit 15 (YES in step S23), the process proceeds to step S24. On the other hand, if the electric vehicle 30 does not receive a cooperation request from the information distribution unit 15 (NO in step S23), the electric vehicle 30 ends the process in FIG.

In step S24, the notification determination device 32 of the electric vehicle 30 calculates a predicted SOC (predicted remaining charge), which is the remaining charge of the secondary battery of the electric vehicle 30 when the electric vehicle 30 moves to the first area and starts discharging the secondary battery, based on the current remaining charge of the secondary battery of the electric vehicle 30. The notification determination device 32 calculates, for example, the traveling distance from the current location of the electric vehicle 30 to a location where the electric vehicle 30 can move to the first area and start discharging the secondary battery, i.e., the location of a charging/discharging facility that can discharge to the gap elimination grid. The notification determination device 32 then calculates the predicted SOC based on the current remaining charge of the secondary battery and the calculated traveling distance.

The process proceeds to step S25, where notification determination device 32 determines whether the predicted SOC is equal to or greater than a first predetermined value. If the predicted SOC is equal to or greater than the first predetermined value (YES in step S25), the process proceeds to step S26. On the other hand, if the predicted SOC is smaller than the first predetermined value (NO in step S25), electric vehicle 30 ends the process of FIG. 5.

In step S26, the notification determination device 32 notifies the occupant of the electric vehicle 30 of the cooperation request received from the information distribution unit 15. The process proceeds to step S27, where the input reception device 33 receives a response to the cooperation request from the occupant of the electric vehicle 30. The process proceeds to step S28, where the information transmission device 34 transmits the response to the cooperation request received by the input reception device 33 to the central management device 10 via the network.

The process proceeds to step S9 in FIG. 4, where the vehicle information acquisition unit 11 receives a response to the cooperation request from the electric vehicle 30 via the network.

The process proceeds to step S10, where the supply-demand gap prediction unit 12 calculates the total amount of power that can be supplied by the vehicles that have accepted the cooperation request, at a predetermined time after the information distribution unit 15 has distributed the cooperation request. For example, the power that can be supplied by the vehicles that have accepted the cooperation request can be determined by calculating a predicted remaining charge, which is the remaining charge of the secondary battery when the occupants of the vehicles that have accepted the cooperation request move to the first area and start discharging the secondary battery, using the current remaining charge of the secondary battery as a base point. In other words, the power that can be supplied by the vehicles that have accepted the cooperation request is the amount of power that is predicted to be supplied from the secondary battery of the vehicles that have accepted the cooperation request in the gap elimination grid.

The processing proceeds to step S11, where the supply and demand gap prediction unit 12 determines whether the supply and demand gap in the gap elimination-requiring grid is likely to be eliminated. The supply and demand gap prediction unit 12 determines that the supply and demand gap is likely to be eliminated if the value obtained by adding the total supplyable power of the agreed-upon vehicles calculated in step S10 to the supply and demand gap in the gap elimination-requiring grid predicted in step S4 is greater than a threshold. For example, the supply and demand gap prediction unit 12 determines that the supply and demand gap is likely to be eliminated if the value obtained by adding the total supplyable power of the agreed-upon vehicles to the supply and demand gap is greater than 0.

If it is determined that the supply-demand gap is likely to be resolved (YES in step S11), the process returns to step S1. On the other hand, if it is determined that the supply-demand gap is not likely to be resolved (NO in step S11), the process proceeds to step S12.

In step S12, the electricity selling price setting unit 16 executes the electricity selling price increase process to set the remuneration amount per unit amount of electricity.

[Power selling price hike processing]
An example of the electricity selling price increase process in step S12 in Fig. 4 will be described below with reference to Fig. 6. In step S121 in Fig. 6, the electricity selling price setting unit 16 calculates the urgency indicating the degree of the amount of electricity required to eliminate the supply and demand gap, based on the supply and demand gap in the gap elimination required grid predicted in step S4 in Fig. 4 and the total amount of supplyable electricity of the approved vehicles calculated in step S10 in Fig. 4. For example, the urgency is calculated by multiplying a value obtained by adding the supply and demand gap to the total amount of supplyable electricity of the approved vehicles by a predetermined coefficient.

The processing proceeds to step S122, where the electricity selling price setting unit 16 sets the remuneration amount per unit amount of electricity to be paid to the occupant of the electric vehicle 30 that discharged its secondary battery in the gap elimination required grid, based on the second data indicating the remuneration amount per unit amount of electricity according to the degree of urgency. The second data may be, for example, data in which the remuneration amount per unit amount of electricity increases as the degree of urgency increases. The second data may be, for example, data in which the remuneration amount per unit amount of electricity increases stepwise as the degree of urgency increases. For example, the second data may be stored in advance in the memory of the central management device 10, or may be acquired via a network, etc.

The process proceeds to step S123, where the power selling price setting unit 16 updates the second data by multiplying the second data by a predetermined correction value. In subsequent processes, the power selling price setting unit 16 sets the remuneration amount per unit amount of power based on the updated second data. The predetermined correction value may be set to a value greater than 1, such as 1.1.

The process proceeds to step S13 in FIG. 4, where the information distribution unit 15 distributes a request for cooperation to all electric vehicles 30 located in each of areas A to D, including information regarding the remuneration amount per unit amount of electricity calculated in step S13, and the process returns to step S10 in FIG. 4.

[Action and effect]
As described above, according to this embodiment, the following advantageous effects can be obtained.

The power management method of the power management system 1 according to this embodiment manages the balance between supply and demand of power in multiple microgrids 20A-20D, each of which is connected to a power generation facility 21 that generates power using natural energy and a power consumption facility 23 that consumes the power supplied from the power generation facility 21. A change in the supply-demand gap, calculated by subtracting the amount of power consumed by the power consumption facility 23 from the amount of power generated by the power generation facility 21, is predicted for each of the multiple microgrids 20A-20D. Based on first data indicating the inter-regional dynamics of electric vehicles 30 located in regions A-D corresponding to each of the multiple microgrids 20A-20D, a second region is identified that has the largest number of electric vehicles moving to a first region corresponding to a first microgrid for which a supply-demand gap smaller than a threshold is predicted. First information is distributed to electric vehicles 30 located in the second region, prompting them to move to the first region and discharge their secondary batteries.

The central management device 10 of the power management system 1 according to this embodiment identifies a second region where the supply-demand gap is smaller than a threshold and the number of electric vehicles moving to the first region corresponding to the first microgrid where power depletion is predicted is the largest, based on first data indicating the inter-regional dynamics of electric vehicles 30. The central management device 10 then transmits first information to electric vehicles 30 located in the second region, prompting them to move to the first region and discharge their secondary batteries. Electric vehicles 30 located in the second region where the number of electric vehicles moving to the first region is the largest are more likely to move to the first region than electric vehicles 30 located in other regions, and are therefore more likely to accept the request to move to the first region and discharge their secondary batteries. Therefore, by transmitting the first information only to electric vehicles 30 located in the second region where the number of electric vehicles moving to the first region is the largest, the power supply-demand gap in the first microgrid can be efficiently resolved. Furthermore, the amount of data transmitted is reduced.

In the power management method of the power management system 1 according to this embodiment, the first data is data indicating the on-demand traffic volume of electric vehicles 30 located in each of the areas A to D corresponding to each of the multiple microgrids 20A to 20D. By using data indicating the on-demand traffic volume as the first data, it is possible to identify a second area in which the largest number of electric vehicles are moving to the first area corresponding to the first microgrid for which a supply-demand gap smaller than a threshold is predicted. Therefore, by transmitting first information to the electric vehicles 30 located in this second area, encouraging them to move to the first area and discharge their secondary batteries, it becomes more likely that the supply-demand gap of the first microgrid can be resolved using the secondary batteries of the electric vehicles that are likely to comply with the request to move to the first area and discharge their secondary batteries.

The power management method of the power management system 1 according to this embodiment identifies, among the regions A to D corresponding to each of the multiple microgrids 20A to 20D, the region with the highest OD traffic volume of electric vehicles 30 moving to the first region as the second region. By transmitting first information to electric vehicles 30 located in the second region with the highest OD traffic volume, encouraging them to move to the first region and discharge their secondary batteries, it is possible to narrow down the regions and electric vehicles 30 to which the information is to be transmitted, thereby reducing the amount of data transmitted.

The power management method of the power management system 1 according to the present embodiment may set a reward amount to be paid to a driver of an electric vehicle 30 that discharges its secondary battery in the first microgrid in proportion to the amount of power discharged from the secondary battery, and may distribute the first information together with information about the reward amount. By distributing the first information together with information about the reward amount, which encourages the driver of the electric vehicle 30 to discharge the secondary battery, it is possible to motivate the driver of the electric vehicle 30 to comply with a request to encourage the driver to discharge the secondary battery.

In the power management method of the power management system 1 according to the present embodiment, when a supply-demand gap in a first microgrid is not resolved even after a predetermined time has elapsed since the distribution of first information, the power management method calculates a degree of urgency indicating the level of the amount of power required to resolve the supply-demand gap based on the supply-demand gap in the first microgrid and the total amount of power predicted to be supplied from electric vehicles 30 in the first microgrid. Then, based on second data indicating a remuneration amount per unit amount of power according to the degree of urgency, a remuneration amount per unit amount of power to be paid to an occupant of an electric vehicle 30 that discharges its secondary battery in the first microgrid is set. Then, second information, in which information regarding the remuneration amount per unit amount of power is added to the first information, is distributed to all electric vehicles 30 located in each of areas A to D corresponding to each of the multiple microgrids 20A to 20D.

The remuneration amount per unit amount of power to be paid to the occupants of electric vehicles 30 who discharge their secondary batteries can be set based on the difference between the supply-demand gap in the first microgrid and the total amount of power predicted to be supplied from the electric vehicles 30 in the first microgrid. The remuneration amount per unit amount of power can be set according to the amount of power required to eliminate the supply-demand gap. The greater the amount of power required to eliminate the supply gap, the higher the remuneration amount per unit amount of power can be set, which can motivate the occupants of all electric vehicles 30 to comply with a request to discharge their secondary batteries.

In the power management method of the power management system 1 according to this embodiment, if the supply-demand gap in the first microgrid is not resolved even after a predetermined time has elapsed since the second information was distributed, the method sets a remuneration amount per unit amount of power based on the second data updated by multiplying the second data by a predetermined correction value. If the amount of power required to resolve the supply-demand gap remains insufficient even after a predetermined period has elapsed since the second information was distributed, the method can set a remuneration amount per unit amount of power higher than the amount at the time of the previous distribution. This can further motivate occupants of all electric vehicles 30 to comply with a request to discharge their secondary batteries.

The power management method of the power management system 1 according to this embodiment calculates a predicted remaining charge, which is the remaining charge of the secondary battery of the electric vehicle 30 at the time when the electric vehicle 30 moves to a first area and starts discharging the secondary battery, based on the current remaining charge of the secondary battery of the electric vehicle 30. If the predicted remaining charge is equal to or greater than a first predetermined value, the first information or the second information is notified to the occupant of the electric vehicle 30. This makes it possible to prevent the occupant of the electric vehicle 30, whose predicted remaining charge of the secondary battery is low and who finds it difficult to move to the first microgrid to discharge the secondary battery, from being notified of a request to discharge the secondary battery, and thus to prevent the occupant from leaving the system due to the inconvenience of the notification.

Although the embodiments of the present invention have been described above, the descriptions and drawings that form part of this disclosure should not be understood to limit the present invention. Various alternative embodiments, examples, and operating techniques will become apparent to those skilled in the art from this disclosure.

For example, the information distribution unit 15 of the central management device 10 may distribute the first information encouraging the electric vehicles 30 located in the second area to move to the first area and discharge their secondary batteries only to those electric vehicles 30 that have a destination set within the first area. The information encouraging the electric vehicles 30 located in the second area to move to the first area and discharge their secondary batteries can be distributed only to those electric vehicles 30 that have a destination set within the first area, and the number of electric vehicles 30 to which the first information is distributed can be further narrowed down, thereby reducing the amount of data transmitted.

Furthermore, the information distribution unit 15 may calculate a contribution level, which is the degree to which the occupant of the electric vehicle 30 has contributed to eliminating the supply-demand gap, based on acceptance history data, which is information on a history of acceptance by the occupant of the electric vehicle 30 of the first information, and generate contribution level information at predetermined intervals, which indicates the calculated contribution level as a relative index to the contribution levels of occupants of other electric vehicles 30. For example, the information distribution unit 15 may calculate the contribution level for each occupant of the electric vehicle 30 by dividing the number of times that the occupant of the electric vehicle 30 has accepted the first information received by the electric vehicle 30 in the past by the number of times that the electric vehicle 30 has received the first information in the past. Then, a graph showing the distribution of the calculated contribution levels of the occupants of the electric vehicle 30 may be created, and contribution level information indicated as a relative index to the contribution levels of occupants of other electric vehicles 30 may be generated. Furthermore, the acceptance history data may be stored in a storage device (not shown) of the central management unit 10.

The information distribution unit 15 may distribute the generated contribution information to all electric vehicles 30 located in each of the areas A to D corresponding to each of the plurality of microgrids 20A to 20D. By periodically notifying the occupants of the electric vehicles 30 of the contribution information of the occupants of the electric vehicles, it is possible to motivate the occupants of the electric vehicles to travel to the first area and discharge their secondary batteries.

Furthermore, the area identification unit 13 may identify a third area where the OD traffic volume of electric vehicles 30 moving within the same area is greater than a second predetermined value, based on the first data. The information distribution unit 15 may distribute third information to electric vehicles 30 located within the third area, encouraging them to charge their secondary batteries in the third area. Electric vehicles 30 located within a predetermined section where the OD traffic volume of electric vehicles 30 moving within the same area is greater than the second predetermined value can be encouraged to charge in the microgrid in the area where they are currently located. This makes it possible to encourage electric vehicles 30 that are unlikely to move to other areas to charge in the microgrid in the area where they are currently located, thereby preparing for a case where the power of the microgrid is depleted.

Furthermore, the area specifying unit 13 may specify a fourth area corresponding to a second microgrid predicted to have a supply-demand gap greater than the threshold. The information distribution unit 15 may distribute fourth information to electric vehicles 30 located in the fourth area, encouraging them to charge their secondary batteries in the fourth area. Electric vehicles 30 located in an area corresponding to a power surplus grid predicted to have a power surplus because the supply-demand gap is greater than the threshold, can be encouraged to charge in the power surplus grid. This makes it possible to prepare for a future power shortage in the microgrid. The supply-demand gaps of each microgrid 20A to 20D can be leveled.

1 Power management system 20A to 20D Multiple microgrids 21 Power generation equipment 23 Power consumption equipment 30 Electric vehicles A to D Region

Claims (13)

A power management method for a power management system that manages the balance of power supply and demand in a plurality of microgrids in which power generation facilities that generate power using natural energy and power consumption facilities that consume power supplied from the power generation facilities are connected, comprising:
predicting a change in a supply-demand gap obtained by subtracting an amount of power consumed by the power consumption equipment from an amount of power generated by the power generation equipment for each of the plurality of microgrids;
identifying a second region having the largest number of electric vehicles moving to a first region corresponding to a first microgrid for which the supply-demand gap is predicted to be smaller than a threshold, based on first data indicating inter-regional dynamics of electric vehicles located in each region corresponding to each of the plurality of microgrids;
transmitting first information to the electric vehicle located in the second area, prompting the electric vehicle to move to the first area and discharge the secondary battery;
Power management methods. The power management method according to claim 1 , wherein the first data is data indicating an on-demand (OD) traffic volume of electric vehicles located in each area corresponding to each of the plurality of microgrids. The power management method according to claim 2 , wherein an area corresponding to each of the plurality of microgrids has the highest OD traffic volume of electric vehicles moving to the first area, and the area is identified as the second area. setting a reward to be paid to a driver of the electric vehicle that discharges the secondary battery in the first microgrid in proportion to the amount of power discharged from the secondary battery;
The power management method according to claim 1 or 2, wherein the first information is distributed with information relating to the remuneration amount. when the supply and demand gap in the first microgrid is not resolved even after a predetermined time has elapsed since the distribution of the first information, calculates a degree of urgency indicating a degree of the amount of power required to resolve the supply and demand gap based on the supply and demand gap in the first microgrid and a sum of the amount of power predicted to be supplied from secondary batteries of the electric vehicles in the first microgrid;
The power management method according to claim 4, further comprising: setting a remuneration amount per unit amount of power to be paid to a driver of the electric vehicle that discharges the secondary battery in the first microgrid based on second data indicating a remuneration amount per unit amount of power according to the urgency. 6. The power management method according to claim 5, further comprising distributing second information, which is the first information plus information regarding a remuneration amount per unit amount of power, to all of the electric vehicles located in each area corresponding to each of the plurality of microgrids. 7. The power management method according to claim 6, wherein, if the supply-demand gap in the first microgrid is not resolved even after a predetermined time has elapsed since the second information was distributed, the remuneration amount per unit amount of power is set based on the second data updated by multiplying the second data by a predetermined correction value. calculating a predicted remaining charge amount, which is the remaining charge amount of the secondary battery at the time when the electric vehicle moves to the first area and starts discharging the secondary battery, using a current remaining charge amount of the secondary battery of the electric vehicle as a base point;
The power management method according to claim 7 , wherein when the predicted remaining charge amount is equal to or greater than a first predetermined value, the first information or the second information is notified to a driver of the electric vehicle. acquiring data indicating a destination of the electric vehicle that is set in a navigation device mounted on the electric vehicle or a mobile terminal owned by a passenger of the electric vehicle;
The power management method according to any one of claims 1 to 3, wherein the first information is distributed only to electric vehicles located in the second area that have the destination set within the first area. calculating a contribution level that is a degree to which the occupant of the electric vehicle has contributed to eliminating the supply-demand gap based on compliance history data that is information on a history of the occupant of the electric vehicle complying with the first information;
generating contribution information at predetermined intervals that indicates the calculated contribution as a relative index to the contribution of occupants of other electric vehicles;
The power management method according to any one of claims 1 to 3, wherein the generated contribution information is distributed to all of the electric vehicles located in each area corresponding to each of the plurality of microgrids. identifying a third area in which the OD traffic volume of electric vehicles moving within the same area is greater than a second predetermined value based on the first data;
The power management method according to claim 2 or 3, further comprising the step of: transmitting third information to electric vehicles located in the third area, the third information prompting the electric vehicles to charge the secondary battery in the third area. identifying a fourth region corresponding to a second microgrid in which the supply-demand gap is predicted to be greater than the threshold;
The power management method according to any one of claims 1 to 3, further comprising transmitting fourth information to electric vehicles located in the fourth area, the fourth information encouraging charging of the secondary battery in the fourth area. A power management system that manages the balance of power supply and demand in a plurality of microgrids in which power generation facilities that generate power using natural energy and power consumption facilities that consume power supplied from the power generation facilities are connected,
a prediction unit that predicts a change in a supply-demand gap obtained by subtracting an amount of power consumed by the power consumption equipment from an amount of power generated by the power generation equipment for each of the plurality of microgrids;
a memory that stores first data indicating a behavior of electric vehicles located in each area corresponding to each of the microgrids between the areas;
an identification unit that identifies, based on the first data, a second area having the largest number of electric vehicles moving to a first area corresponding to a first microgrid in which the supply-demand gap is predicted to be smaller than a threshold;
a distribution unit that distributes first information to the electric vehicle located in the second area, encouraging the electric vehicle to move to the first area and discharge a secondary battery.