130 illustrated in FIG. 2) to perform charging or discharging for electric power adjustment of the electric power system PG by remote control. For example, when an imbalance occurs, the server 600 controls the DER (for example, charge and discharge device 120 illustrated in FIG. 2) to eliminate the imbalance.

FIG. 3 is a diagram illustrating a detailed configuration of the server 300 and the server 600. With reference to FIG. 3, the servers 300, 600 respectively include processors 310, 610, storage devices 320, 620, communication devices 330, 630, and HMIs 340, 640. The communication device 630 acquires information on the market price of electric power by communication. The communication device 330 and the communication device 630 communicate with each other. The communication device 630 and the communication device 330 are examples of the “communication unit” of the present disclosure. Further, the processor 310 and the processor 610 are examples of the “control unit” of the present disclosure.

Each of the storage device 320 and the storage device 620 is configured to be able to save various information. In the storage devices 320, 620, in addition to the programs executed by the processors 310, 610, pieces of information (for example, maps, mathematical formulas, and various parameters) used in the programs are stored. Each of the communication device 330 and the communication device 630 includes various communication interfaces (I/Fs). Each of the HMI 340 and the HMI 640 includes an input device and a display device.

The server 300 is configured to manage information (hereinafter, also referred to as “vehicle information”) regarding each electric vehicle 100 included in the vehicle group VG. The vehicle information is stored in the storage device 320 of the server 300. Specifically, identification information (vehicle ID) for identifying the electric vehicle 100 is assigned to each electric vehicle 100, and the server 300 manages the vehicle information by distinguishing it by the vehicle ID. The vehicle ID may be a unique number (for example, vehicle identification number (VIN)) for each electric vehicle 100, or may be a communication address of the electric vehicle 100. The vehicle information includes, for example, the position of the electric vehicle 100, the state of charge (SOC) of the battery 130 included in the electric vehicle 100, the traveling plan of the electric vehicle 100, the system connection state (plug-in state/plug-out state), and the state (on/off) of the vehicle system. Further, the specifications (for example, the specifications related to charging and discharging) of the electric vehicle 100 may be registered in the server 300 in advance.

Further, the server 300 periodically communicates with each electric vehicle 100. Specifically, the server 300 repeatedly executes the process illustrated in FIG. 7 described below.

Further, the server 600 includes a vehicle management unit 611, a selection unit 612, a supply and demand management unit 613, a trading unit 614, an adjusting power calculation unit 615, and a market price prediction unit 616. Each of these units is embodied, for example, by the processor 610 and a program executed by the processor 610. However, the present disclosure is not limited to this, and each of the above units may be embodied by dedicated hardware (electronic circuit).

The vehicle management unit 611 acquires the data managed by the server 300 as needed. In addition, the vehicle management unit 611 predicts the future behavior of the electric vehicle 100 based on the data acquired from the server 300.

The vehicle management unit 611 operates the vehicle selected by the selection unit 612 as the adjusting power of the electric power system PG by remote control.

The supply and demand management unit 613 acquires the supply and demand information of the electric power system PG from the server 700. In addition, the supply and demand management unit 613 monitors the actual supply and demand of the electric power system PG. When an imbalance occurs with respect to the simultaneous equal amount of the electric power system PG, the supply and demand management unit 613 generates an adjusting power request for eliminating the imbalance.

The trading unit 614 conducts transactions in the electricity market. The trading unit 614 executes a bid in the electricity market and informs the supply and demand management unit 613 of the bid result. When the trading unit 614 makes a successful bid in the electricity market, the trading unit 614 generates an adjusting power request.

The adjusting power calculation unit 615 calculates a target adjusting power for the adjusting power request. The selection unit 612 selects the electric vehicle 100 to be operated as the adjusting power from the plurality of electric vehicles 100 included in the vehicle group VG in response to the adjusting power request described above. The selection unit 612 informs the vehicle management unit 611 of the selected electric vehicle 100.

The market price prediction unit 616 calculates a prediction value of the market price based on the market price information acquired by the communication device 630. In particular, the market price prediction unit 616 (processor 610) detects (calculates) the scheduled time when the next charge of the traveling electric vehicle 100 is performed, and calculates the prediction value of the market price at the detected (calculated) scheduled time. The graph illustrated in FIG. 4 shows a relationship between the annual prediction value predicted by the market price prediction unit 616 and the time. The process of detecting (calculating) the scheduled time when the next charge is performed may be performed by the processor 310 of the server 300.

The market price prediction unit 616 (processor 610) detects (calculates) the scheduled time for the next charge based on the future behavior of the electric vehicle 100 predicted by the vehicle management unit 611. Further, the market price prediction unit 616 (processor 610) may detect (calculate) the scheduled time when the next charge of the electric vehicle 100 selected by the selection unit 612 is performed.

Further, the server 300 includes an SOC adjustment processing unit 311. The SOC adjustment processing unit 311 is embodied by, for example, the processor 310 and a program executed by the processor 310. However, the present disclosure is not limited to this, and the SOC adjustment processing unit 311 may be embodied by dedicated hardware (electronic circuit).

The SOC adjustment processing unit 311 performs an SOC adjustment process for adjusting the SOC of the traveling electric vehicle 100. Here, when the SOC is adjusted without considering the market price of the electric power, for example, when the price of the electric power is high, the adjustment is made to lower the SOC of the electric power of the electric vehicle, and the cost for the next charging becomes large. Therefore, it is considered that the user of the electric vehicle 100 may feel financial anxiety (dissatisfaction) with respect to charging.

Therefore, in the present embodiment, the processor 310 (SOC adjustment processing unit 311) performs the SOC adjustment process based on the prediction value of the market price of the electric power calculated by the market price prediction unit 616. Specifically, the processor 310 (SOC adjustment processing unit 311) transmits a command signal to the electric vehicle 100 to perform the SOC adjustment process based on the prediction value of the market price of the electric power. The SOC of the electric vehicle 100 is adjusted between the start of the SOC adjustment process and the next charging.

Further, the processor 310 compares the prediction value of the market price of electric power calculated by the market price prediction unit 616 with a predetermined threshold price. Then, the SOC adjustment processing unit 311 (processor 310) performs the SOC adjustment process based on a magnitude correlation between the prediction value of the market price and the predetermined threshold price. The comparison between the prediction value of the market price and the predetermined threshold price may be performed by the processor 610.

The predetermined threshold price includes a threshold price A and a threshold price B. Here, FIG. 4 illustrates a graph showing the relationship between the prediction value of the market price and time. As illustrated in FIG. 4, the threshold price B is smaller than the threshold price A. Each of the threshold price A and the threshold price B is stored in the storage device 320 (or storage device 620) in advance. Further, each of the threshold price A and the threshold price B may be appropriately calculated based on predetermined information (for example, a transition of the market price of electric power), instead of a fixed value as described above. The threshold price A and the threshold price B are respectively examples of a “first threshold price” and a “second threshold price” of the present disclosure.

In the present embodiment, the SOC adjustment processing unit 311 (processor 310) performs an SOC reduction process for reducing a decrease in the SOC of the traveling electric vehicle 100 when the prediction value of the market price of electric power is equal to or higher than the threshold price A. As a result, it is possible to reduce the SOC from becoming relatively low at the time when the market price is expected to be relatively high. As a result, it is possible to reduce an increase in the cost for charging the electric vehicle 100, such that it is possible to easily reduce the amount of financial anxiety (dissatisfaction) the user feels. Further, as illustrated in FIG. 4, the threshold price A is smaller than, for example, ½ of the maximum value of the prediction values of the market price in one year. The example of the size of the threshold price A is not limited to this.

FIG. 5 illustrates a graph showing a relationship between the outside air temperature and the output upper limit value of the temperature controller 190 (cooling device 191 and heater 192). As illustrated in FIG. 5, the SOC reduction process includes, for example, a process (an example of the “first process” of the present disclosure) of lowering the output upper limit value of the temperature controller 190 of the electric vehicle 100 as compared with the case (the case where the prediction value of the market price of electric power is larger than the threshold price B and smaller than the threshold price A) where the prediction value of the market price of electric power is less than the threshold price A. In FIG. 5, the change in the output upper limit value after the SOC reduction process is shown by a solid line, and the change in the output upper limit value before the SOC reduction process is shown by a broken line.

Specifically, the SOC reduction process includes a process of lowering the output upper limit value of each of the cooling device 191 and the heater 192. The output upper limit value of the cooling device 191 may be controlled by the evaporator outlet temperature, and the output upper limit value of the heater 192 may be controlled by the supply electric power. The amount of decrease in the output upper limit value due to the SOC reduction process is, for example, a preset fixed value. The amount of decrease may be calculated based on, for example, the magnitude of a difference between the prediction value of the market price of electric power and the threshold price A.

Further, each of the cooling device 191 and the heater 192 changes the output upper limit value according to the outside air temperature. Specifically, the output upper limit value of the cooling device 191 increases as the outside air temperature increases. The output upper limit value of the heater 192 increases as the outside air temperature decreases. Here, the rate of change of the output upper limit value with respect to the outside air temperature may be the same or different before and after the SOC reduction process is performed. Further, the amount of decrease in the output upper limit value due to the SOC reduction process of each of the cooling device 191 and the heater 192 may be the same or different from each other. Further, only the output upper limit value of either the cooling device 191 or the heater 192 may be lowered by the SOC reduction process.

The SOC reduction process is not limited to the example described above. For example, the decrease in the SOC may be reduced by increasing the regenerative strength due to braking.

Further, the SOC adjustment process performs an SOC promotion process for promoting a decrease in the SOC of the traveling electric vehicle 100, for example, when the prediction value of the market price of electric power is equal to or less than the threshold price B (see the broken line in FIG. 5). For example, the threshold price B is smaller than ½ of the threshold price A. The example of the size of the threshold price B is not limited to this.

FIG. 6 is a graph showing a relationship between the outside air temperature and the output upper limit value of the temperature controller 190 (cooling device 191 and heater 192). As illustrated in FIG. 6, the SOC promotion process includes, for example, a process of increasing the output upper limit value of the temperature controller 190 of the electric vehicle 100 as compared with the case (the case where the prediction value of the market price of electric power is larger than the threshold price B and smaller than the threshold price A) where the prediction value of the market price of electric power is larger than the threshold price B. In FIG. 6, the change in the output upper limit value after the SOC promotion process is shown by a solid line, and the change in the output upper limit value before the SOC promotion process is shown by a broken line.

Specifically, the SOC promotion process includes a process of increasing the output upper limit value of each of the cooling device 191 and the heater 192