System, program, and method

Abstract

This system is connected to an electric power network and manages a plurality of charge / discharge stations that charge and discharge a mobile battery. The system comprises: an acquisition unit that acquires correlation of usage amounts of the plurality of charge / discharge stations between the plurality of charge / discharge stations; and a prediction unit that uses the present usage amounts of first and second charge / discharge stations and the correlation between the first and second charge / discharge stations as bases to predict a future power resource at the first charge / discharge station, said first charge / discharge station among the plurality of charge / discharge stations serving as a prediction target regarding a power resource thereof that will be available to the electric power network upon controlling the charging / discharging of the mobile battery, said second charge / discharge station among the plurality of charge / discharge stations being correlated with the first charge / discharge station.

Description

System, program and method

[0001] The present invention relates to a system, a program and a method.

[0002] Patent Documents 1 to 4 disclose technologies related to charging stations for charging batteries. [Prior art documents] [Patent documents] [Patent document 1] JP 2018-160364 A [Patent document 2] JP 2018-160073 A [Patent document 3] JP 2019-164989 A [Patent document 4] JP 2021-103549 A Problem to be solved

[0003] There are challenges in efficiently utilizing batteries and battery charging stations. General disclosure

[0004] In a first aspect of the present invention, there is provided a system. The system is connected to a power network and manages a plurality of charging / discharging stations that charge and discharge a mobile battery. The system includes an acquisition unit that acquires a correlation between the usage amounts of the plurality of charging / discharging stations. The system also includes a prediction unit that predicts future power resources at a first charging / discharging station based on a current usage amount of a first charging / discharging station among the plurality of charging / discharging stations that is a target for predicting power resources that can be provided to the power network by controlling charging / discharging of the mobile battery, a current usage amount of a second charging / discharging station among the plurality of charging / discharging stations that has the correlation with the first charging / discharging station, and the correlation between the first charging / discharging station and the second charging / discharging station.

[0005] If the correlation between the first charging / discharging station and the second charging / discharging station indicates a correlation in which the usage of the first charging / discharging station increases when the usage of the second charging / discharging station increases, the prediction unit may predict that the usage of the first charging / discharging station will increase within a predetermined time when the current usage of the second charging / discharging station increases, and may predict the power resources at the first charging / discharging station in the future based on the predicted usage of the first charging / discharging station.

[0006] If the correlation between the first charging / discharging station and the second charging / discharging station indicates a correlation in which the usage of the first charging / discharging station decreases when the usage of the second charging / discharging station increases, the prediction unit may predict that the usage of the first charging / discharging station will decrease within a predetermined time when the current usage of the second charging / discharging station increases, and may predict the power resources at the first charging / discharging station in the future based on the predicted usage of the first charging / discharging station.

[0007] If the correlation between the first charging / discharging station and the second charging / discharging station indicates that there is a correlation between the usage amount in a first time period at the second charging / discharging station and the usage amount in a second time period at the first charging / discharging station, the prediction unit may predict the usage amount at the first charging / discharging station based on the usage amount in the first time period at the second charging / discharging station and the correlation between the first charging / discharging station and the second charging / discharging station, and may predict the power resources at the first charging / discharging station in the future based on the predicted usage amount at the first charging / discharging station.

[0008] The first time period may be a different time period than the second time period.

[0009] The first time period and the second time period may comprise a common time period.

[0010] The acquisition unit may acquire a correlation of usage amounts between the plurality of charging / discharging stations based on a history of past usage amounts of each of the plurality of charging / discharging stations.

[0011] The system may further include a controller configured to control charging and discharging of the mobile battery connected to the first charging and discharging station in response to a demand for power in the power network.

[0012] The mobile battery may be a battery mounted on a vehicle.

[0013] The mobile battery may be a battery that is mounted on the vehicle and is replaceable at the plurality of charging / discharging stations.

[0014] In a second aspect of the present invention, there is provided a program that causes a computer to function as the above-described system.

[0015] In a third aspect of the present invention, there is provided a method for managing a plurality of charging / discharging stations connected to a power network for charging and discharging a mobile battery. The method includes a step of acquiring a correlation between utilization amounts of the plurality of charging / discharging stations. The method includes a step of predicting future power resources at a first charging / discharging station, the first charging / discharging station being a target for predicting power resources that can be provided to the power network by controlling charging / discharging of the mobile battery, based on a current utilization amount of a second charging / discharging station correlated with the first charging / discharging station, and the correlation between the first charging / discharging station and the second charging / discharging station.

[0016] The above summary of the invention does not list all of the features of the present invention, and subcombinations of these features may also constitute inventions.

[0017] 1 conceptually illustrates a usage pattern of a power system 5 in one embodiment. FIG. 2 illustrates an example of the system configuration of a system 100. FIG. 3 schematically illustrates historical information regarding the usage amount of a charging / discharging station 30. FIG. 4 schematically illustrates the strength of mutual correlation between charging / discharging stations 30 using the width of the arrows. FIG. 5 is a graph illustrating another example of historical information regarding the usage amount of a charging / discharging station 30. FIG. 6 illustrates a processing procedure for predicting power resources in a charging / discharging station 30. FIG. 7 schematically illustrates changes in the amount of power resources predicted in a charging / discharging station 30a over the course of a day. FIG. 8 illustrates an example of a computer 2000 in which multiple embodiments of the present invention may be embodied in whole or in part.

[0018] The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the scope of the invention as claimed. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0019] 1 conceptually illustrates a usage pattern of a power system 5 in one embodiment. The power system 5 includes a charging / discharging station 30a, a charging / discharging station 30b, a charging / discharging station 30c, a charging / discharging station 30d, and a charging / discharging station 30e, a power generation device 80, a system 100, a server 180, and a vehicle 20, a vehicle 10a, and a vehicle 10b. In this embodiment, the charging / discharging stations 30a, 30b, 30c, 30d, and 30e may be collectively referred to as "charging / discharging stations 30." The charging / discharging stations 30a, 30b, and 30c may be collectively referred to as "charging / discharging stations 30."

[0020] The system 100 is connected to a server 180 through a communication network 190. The server 180 is capable of communicating with the charging / discharging station 30 through the communication network 190. The system 100 manages the charging / discharging station 30.

[0021] The charging / discharging station 30, the power consumer 70, and the power generation device 80 are connected to a power network 90. ​​Electric power generated by the power generation device 80 can be supplied to the charging / discharging station 30 and the power consumer 70 through the power network 90. ​​The power network 90 is, for example, a power system.

[0022] The charging / discharging stations 30a, 30b, and 30c hold a plurality of batteries that can be mounted on the vehicle 20, and charge and discharge the plurality of batteries that they hold. The vehicle 20 is, for example, an electric motorcycle. The battery 22 used in the vehicle 20 is replaced at the charging / discharging station 30. As an example, the battery 22 that has been used to run the vehicle 20 is replaced with a charged battery 24 at the charging / discharging station 30a and attached to the vehicle 20. The batteries 22 and 24 are examples of movable batteries. The batteries 22 and 24 are movable when mounted on the vehicle 20.

[0023] The charging / discharging stations 30d and 30e can charge and discharge multiple batteries, including the battery 12a installed in the vehicle 10a and the battery 12a installed in the vehicle 10b. The vehicles 10a and 10b are, for example, electric vehicles. As an example, the vehicles 10a and 10b may be shared cars. A user of the shared car can return the vehicle to the charging / discharging station 30d and use a specific vehicle from multiple vehicles, including the vehicles 10a and 10b. The batteries 12a and 12b are examples of movable batteries. The batteries 12a and 12b are movable when installed in the vehicles 10a and 10b, respectively.

[0024] The charging / discharging stations 30a and 30b can charge the batteries held therein with power supplied from the power network 90. ​​The charging / discharging stations 30a and 30b can discharge the batteries held therein and supply the power to the power network 90. ​​The charging / discharging stations 30d and 30e can charge the batteries mounted on vehicles connected thereto with power supplied from the power network 90. ​​The charging / discharging stations 30d and 30e can discharge the batteries mounted on vehicles connected thereto and supply the power to the power network 90.

[0025] The system 100 controls the charging / discharging stations 30. When a power shortage occurs in the power network 90, the system 100 can cause the charging / discharging stations 30 to discharge their batteries and supply power to the power network 90. ​​When a power surplus occurs in the power network 90, the system 100 can cause the charging / discharging stations 30 to charge their batteries and receive power from the power network 90. ​​The system 100 can provide primary regulation power, secondary regulation power, and tertiary regulation power in the power network 90 using the charging / discharging stations 30. In this way, the system 100 can aggregate the charging / discharging stations 30 and preserve power resources for the power network 90.

[0026] The server 180 is a server used by, for example, a power aggregator. The server 180 performs power transactions in the power market. The system 100 can provide the power resources it holds by aggregating the charging / discharging stations 30 to the server 180. The system 100 controls the charging / discharging of batteries by the charging / discharging stations 30 to provide the power agreed upon by the server 180. For example, the system 100 controls the charging / discharging of batteries by the charging / discharging stations 30 in response to a demand from the server 180 to provide power according to the demand.

[0027] 2 shows an example of the system configuration of the system 100. The system 100 includes a processing unit 200, a storage unit 280, and a communication device 290.

[0028] The processing unit 200 controls the communication device 290. The communication device 290 is responsible for communication between the charge / discharge station 30a and the server 180. The processing unit 200 is realized by an arithmetic processing device including a processor. The storage units 280 are each realized by including a non-volatile storage medium. The processing unit 200 performs processing using information stored in the storage units 280. The processing unit 200 may be realized by a microcomputer including a CPU, ROM, RAM, I / O, a bus, etc. The system 100 may be realized by a computer.

[0029] In this embodiment, the system 100 is implemented by a single computer. However, in other embodiments, the system 100 may be implemented by multiple computers. At least some of the functions of the system 100 may be implemented by one or more servers, such as a cloud server.

[0030] The processing unit 200 includes an acquisition unit 210 , a prediction unit 220 , and a control unit 240 .

[0031] The acquisition unit 210 acquires the correlation of the usage amounts of each of the plurality of charge / discharge stations 30 among the plurality of charge / discharge stations 30. For example, the acquisition unit 210 acquires the correlation of the usage amounts among the plurality of charge / discharge stations 30 based on the history of the past usage amounts of each of the plurality of charge / discharge stations 30.

[0032] The prediction unit 220 predicts the future power resources at the first charging / discharging station based on the current usage of a first charging / discharging station that is a target of prediction of power resources that can be provided to the power network 90 by controlling battery charging / discharging among the multiple charging / discharging stations 30, the current usage of a second charging / discharging station that is correlated with the first charging / discharging station among the multiple charging / discharging stations 30, and the correlation between the first charging / discharging station and the second charging / discharging station. The power resources may be represented, for example, by the number or capacity of batteries that are held in the charging / discharging station 30 and can supply or receive power in response to the power demand of the power network 90.

[0033] Here, the first charging / discharging station is assumed to be the charging / discharging station 30a, and the second charging / discharging station is assumed to be the charging / discharging station 30b. If the correlation between the charging / discharging station 30a and the charging / discharging station 30b indicates that an increase in the usage of the charging / discharging station 30a will result in an increase in the usage of the charging / discharging station 30a, the prediction unit 220 may predict that an increase in the current usage of the charging / discharging station 30b will occur within a predetermined time period, and may predict the future power resources of the charging / discharging station 30a based on the predicted usage of the charging / discharging station 30a.

[0034] If the correlation between charging / discharging station 30a and charging / discharging station 30b indicates a correlation in which the usage of charging / discharging station 30a decreases when the usage of charging / discharging station 30b increases, the prediction unit 220 may predict that the usage of charging / discharging station 30a will decrease within a predetermined time when the current usage of charging / discharging station 30b increases, and may predict the future power resources at charging / discharging station 30a based on the predicted usage of charging / discharging station 30a.

[0035] If the correlation between charging / discharging station 30a and charging / discharging station 30b indicates that there is a correlation between the usage amount during a first time period at charging / discharging station 30b and the usage amount during a second time period at charging / discharging station 30a, the prediction unit 220 may predict the usage amount during the second time period at charging / discharging station 30a based on the usage amount during the first time period at charging / discharging station 30b and the correlation between charging / discharging station 30a and charging / discharging station 30b, and may predict the future power resources during the second time period at charging / discharging station 30a based on the predicted usage amount during the second time period at charging / discharging station 30a.

[0036] The first time period may be a different time period than the second time period. The first time period and the second time period may comprise a common time period.

[0037] The control unit 240 controls the charging and discharging of the battery connected to the charging and discharging station 30 a in response to the power demand in the power network 90 .

[0038] Control of the charge / discharge stations 30a, 30b, and 30c will be described with reference to Figures 3 to 8. The charge / discharge stations 30a, 30b, and 30c are assumed to be located in the same area, for example, within a range that the vehicle 20 can travel. In Figures 3 to 8, the charge / discharge stations 30a, 30b, and 30c are collectively referred to as "charge / discharge stations 30."

[0039] 3 is a diagram illustrating history information relating to the amount of use of the charging / discharging station 30 during a certain time period. The history information illustrated in FIG. 3 is used to obtain the correlation of the amount of use at the charging / discharging station 30.

[0040] The history information shown in Fig. 3 is collected by tracking batteries held at the charging / discharging station 30 during a certain time period. For example, the charging / discharging station 30 reads identification information stored in the battery to be returned and the battery provided to the vehicle 20, and transmits the read identification information to the system 100 together with the timing at which the battery was returned and the timing at which the battery was provided to the vehicle 20. The acquisition unit 210 acquires information received from the charging / discharging station 30 within a predetermined aggregation period. Based on the information acquired from the charging / discharging station 30, the acquisition unit 210 identifies which battery was provided to the vehicle 20 at which charging / discharging station 30 and then returned to which charging / discharging station 30, thereby acquiring the history information shown in Fig. 3.

[0041] In Fig. 3, "Out" indicates batteries provided to vehicle 20 from charging / discharging station 30a, charging / discharging station 30b, and charging / discharging station 30c. In Fig. 3, "In" indicates batteries returned from vehicle 20 to charging / discharging station 30a, charging / discharging station 30b, and charging / discharging station 30c.

[0042] 3 , the numbers in the row for charging / discharging station 30a indicate that the next return destinations for a total of 170 batteries provided from charging / discharging station 30a to vehicle 20 were 100 to station 30a, 60 to station 30b, and 10 to station 30c. The numbers in the row for charging / discharging station 30b indicate that the next return destinations for a total of 200 batteries provided from charging / discharging station 30b to vehicle 20 were 80 to station 30a, 110 to station 30b, and 10 to station 30c. The numbers in the row for charging / discharging station 30c indicate that the next return destinations for a total of 125 batteries provided from charging / discharging station 30c to vehicle 20 were 20 to station 30a, 15 to station 30b, and 90 to station 30c.

[0043] In the example of Figure 3, it can be seen that the probability that a battery provided to vehicle 20 from charging / discharging station 30b will be returned to charging / discharging station 30a is eight times higher than the probability that it will be returned to charging / discharging station 30c. It can also be seen that the probability that a battery provided to vehicle 20 from charging / discharging station 30a will be returned to charging / discharging station 30b is six times higher than the probability that it will be returned to charging / discharging station 30c. Therefore, in the example of Figure 3, it can be seen that the correlation in usage between charging / discharging station 30a and charging / discharging station 30b is higher than the correlation in usage between charging / discharging station 30a and charging / discharging station 30c and the correlation in usage between charging / discharging station 30b and charging / discharging station 30c.

[0044] 4 schematically shows the strength of the correlation between charging / discharging stations 30 using the width of the arrows. As schematically shown in FIG. 4, when a battery is provided to vehicle 20 from charging / discharging station 30b, it can be seen that there is a relatively high possibility that it will be returned to charging / discharging station 30a. When a battery is provided to vehicle 20 from charging / discharging station 30a, it can be seen that there is a relatively high possibility that it will be returned to charging / discharging station 30b. Therefore, if, for example, the number of batteries provided to vehicle 20 from charging / discharging station 30b increases, prediction unit 220 predicts that the number of batteries returned to charging / discharging station 30a will increase based on the history information shown in FIG. 3.

[0045] Fig. 5 is a graph showing another example of history information regarding the usage of the charge / discharge station 30. Fig. 5 shows a conversion of the number of times the charge / discharge station 30 is used in a day. In the graph of Fig. 5, the horizontal axis represents time, and the vertical axis represents the number of times the charge / discharge station 30 is used for battery exchange.

[0046] Graph 500a shows the number of times charging / discharging station 30a has been used, graph 500b shows the number of times charging / discharging station 30b has been used, and graph 500c shows the number of times charging / discharging station 30a has been used. Each time a battery is returned from vehicle 20 and provided to vehicle 20, charging / discharging station 30 transmits usage information indicating that charging / discharging station 30 has been used to system 100. Acquiring unit 210 acquires history information represented as graphs 500a, 500b, and 500c by aggregating the number of pieces of usage information received from charging / discharging stations 30 by time period. Using the history information obtained by aggregating the number of pieces of usage information by time period over multiple different time periods, acquiring correlation between the increase / decrease in the number of times of use for each time period at each charging / discharging station 30.

[0047] 5, both the graph 500a and the graph 500b have a peak in the number of uses within the time period T1. Therefore, the acquisition unit 210 can determine that there is a correlation between the usage amount of the charging / discharging station 30a during the time period T1 and the usage amount of the charging / discharging station 30b during the time period T1, and can acquire correlation information indicating the strength of the correlation.

[0048] Both graph 500a and graph 500b have extreme values ​​of the number of uses within time period T2. Therefore, the acquisition unit 210 can determine that there is a correlation between the usage amount of charging / discharging station 30a during time period T2 and the usage amount of charging / discharging station 30b during time period T2, and can acquire correlation information indicating the strength of the correlation. Based on the correlation information acquired by the acquisition unit 210, the prediction unit 220 can predict how much the usage amount of charging / discharging station 30a will increase during time period T1 if the usage amount of charging / discharging station 30b increases during time period T1. Based on the correlation information acquired by the acquisition unit 210, the prediction unit 220 can predict how much the usage amount of charging / discharging station 30a will decrease during time period T1 if the usage amount of charging / discharging station 30b decreases during time period T1. Based on the correlation information acquired by the acquisition unit 210, the prediction unit 220 can predict how much the usage amount of charging / discharging station 30a will increase during time period T2 if the usage amount of charging / discharging station 30b increases during time period T2. Based on the correlation information acquired by the acquisition unit 210, the prediction unit 220 can predict how much the usage at the charging / discharging station 30a will decrease during time period T2 if the usage at the charging / discharging station 30b decreases during time period T2.

[0049] The acquisition unit 210 can determine that there is a correlation between the usage amount of the charging / discharging station 30a in time zone T2 and the usage amount of the charging / discharging station 30b in time zone T1, and can acquire correlation information indicating the strength of the correlation. Based on the correlation information acquired by the acquisition unit 210, the prediction unit 220 can predict how much the usage amount of the charging / discharging station 30a will increase in time zone T2 if the usage amount of the charging / discharging station 30b increases in time zone T1. Based on the correlation information acquired by the acquisition unit 210, the prediction unit 220 can predict how much the usage amount of the charging / discharging station 30a will decrease in time zone T2 if the usage amount of the charging / discharging station 30b decreases in time zone T1.

[0050] Furthermore, the acquisition unit 210 may determine that there is a negative correlation between the usage amount of the charging / discharging station 30a in time zone T1 and the usage amount of the charging / discharging station 30c in time zone T1, and may acquire correlation information indicating the strength of the negative correlation. Based on the correlation information acquired by the acquisition unit 210, the prediction unit 220 may predict how much the usage amount of the charging / discharging station 30a will increase in time zone T1 if the usage amount of the charging / discharging station 30c decreases in time zone T1. Based on the correlation information acquired by the acquisition unit 210, the prediction unit 220 may predict how much the usage amount of the charging / discharging station 30a will decrease in time zone T1 if the usage amount of the charging / discharging station 30c increases in time zone T1. The acquisition unit 210 may determine that there is a negative correlation between the usage amount of the charging / discharging station 30a in time zone T2 and the usage amount of the charging / discharging station 30c in time zone T2, and may generate correlation information indicating the strength of the negative correlation. Based on the correlation information acquired by the acquisition unit 210, the prediction unit 220 can predict how much the usage at the charge / discharge station 30a will decrease in time period T2 if the usage at the charge / discharge station 30c increases in time period T2. Based on the correlation information acquired by the acquisition unit 210, the prediction unit 220 can predict how much the usage at the charge / discharge station 30a will increase in time period T2 if the usage at the charge / discharge station 30c decreases in time period T2.

[0051] Fig. 6 shows a processing procedure for predicting power resources in the charge / discharge station 30. The processing in Fig. 6 may be started at a predetermined timing in a day. The processing in Fig. 6 may be started at a predetermined time in a day when resource prediction is to be started. A case of predicting power resources in the charge / discharge station 30a will be described with reference to Fig. 6.

[0052] In S602, the prediction unit 220 predicts the amount of power resources for one day at the charging / discharging station 30a that is the target of prediction based on the long-term prediction model. The long-term prediction model may be generated in advance based on history information collected by the acquisition unit 210 from the charging / discharging station 30a. For example, the acquisition unit 210 acquires, as the history information, the number of batteries that are in a charged state and that can provide power resources to the power network 90 and that are held by the charging / discharging station 30a, in association with time. The long-term prediction model may be generated based on the history information acquired by the acquisition unit 210. The long-term prediction model may be a model generated by machine learning, for example, with inputs of the season, day of the week, and time of day, and output of the amount of power resources at the charging / discharging station 30a.

[0053] In steps S604 to S620, the short-term prediction is repeatedly performed. In step S606, the acquisition unit 210 acquires the most recent usage information of the charge / discharge station 30. For example, the acquisition unit 210 acquires, from each charge / discharge station 30, the number of times the charge / discharge station 30 has been used within a predetermined time period.

[0054] In S608, the acquisition unit 210 acquires correlation information regarding the usage amounts between the charging / discharging station 30a and the other charging / discharging stations 30. For example, the acquisition unit 210 may acquire correlation information generated based on the history information described with reference to Figures 3 and 4. The acquisition unit 210 may acquire association information generated from the history information described with reference to Figure 5.

[0055] In S610, the prediction unit 220 calculates a correction value for the power resource based on the short-term prediction model and the correlation between the charging and discharging stations. The short-term prediction model may be generated in advance based on history information collected by the acquisition unit 210 from the charging and discharging station 30a. For example, the acquisition unit 210 acquires, as the history information, the number of batteries in a charged state that allows the charging and discharging station 30a to provide power resources to the power network 90 from the charging and discharging station 30. The short-term prediction model may be a model generated by machine learning that receives weather information and most recent usage information as input and outputs the amount of power resource at the charging and discharging station 30a after a predetermined time. When the charging and discharging station 30a is correlated with the charging and discharging station 30b, the prediction unit 220 predicts the number of uses at the charging and discharging station 30a after a predetermined time based on the most recent usage information at the charging and discharging station 30b and information on the correlation between the charging and discharging stations 30a and 30b. The prediction unit 220 calculates a correction value for the amount of power resources based on the amount of power resources calculated from the short-term prediction model and the number of uses predicted based on the correlation information.

[0056] In S612, the prediction unit 220 predicts the amount of power resources based on the amount of power resources predicted in S602 and the correction value of the amount of power resources calculated in S610. For example, the prediction unit 220 predicts the amount of power resources by adding the amount of power resources predicted in S602 and the correction value of the amount of power resources calculated in S610. The short-term prediction from S604 to S620 may be repeatedly performed at predetermined time intervals.

[0057] Fig. 7 schematically shows changes in the amount of power resources that can be provided as adjustment capability predicted by the charge / discharge station 30a over the course of a day. In Fig. 7, the amount of power resources is represented by the number of batteries that the charge / discharge station 30a holds as power resources for the power network 90. ​​The horizontal axis of Fig. 7 represents the time of day, and the vertical axis of Fig. 7 represents the number of batteries, which represents the amount of power resources. In Fig. 7, the maximum number of batteries that the charge / discharge station 30a can hold is 12, and the vehicle 20 uses two batteries.

[0058] As schematically shown by reference numeral 702, the amount of power resources is 12 between midnight and 6 o'clock. That is, in order to provide adjustment power to the power network 90 between midnight and 6 o'clock, the control unit 240 maintains the SOC (State of Charge) of all 12 batteries held in the charge / discharge station 30a at an intermediate value (e.g., equal to or greater than 40% and less than 60%).

[0059] Here, it is assumed that one vehicle 20 is predicted to use the charge / discharge station 30a at 10:00 and one vehicle 20 at 11:00. Therefore, in order to fully charge the two batteries by 10:00, the control unit 240 causes the two batteries to be charged from 6:00. As a result, as schematically shown by reference numeral 704, the amount of power resources that can be provided as adjustment capability between 6:00 and 7:00 is 10. Furthermore, in order to fully charge the two batteries by 11:00, the control unit 240 causes the two batteries to be charged from 7:00. As a result, as schematically shown by reference numeral 706, the amount of power resources that can be provided as adjustment capability between 7:00 and 10:00 is 8.

[0060] The charging / discharging station 30a is used by one vehicle 20 at 10:00, and the battery charged between 6:00 and 10:00 is exchanged for the battery installed in the vehicle 20. The battery returned from the vehicle 20 to the charging / discharging station 30a has a relatively low SOC and can therefore be used for the up-DR. As a result, the amount of power resources becomes 10, as schematically indicated by reference numeral 702.

[0061] Similarly, the charging / discharging station 30a is used by one vehicle 20 at 11:00, and the battery charged between 7:00 and 11:00 is exchanged for the battery installed in the vehicle 20. The battery returned from the vehicle 20 to the charging / discharging station 30a has a relatively low SOC and can therefore be used for the up-DR. As a result, the amount of power resources becomes 12.

[0062] Next, suppose that in the afternoon, one vehicle 20 is predicted to use the charging / discharging station 30a at each of 4:00 PM, 6:00 PM, and 7:00 PM. In this case, charging of two batteries each will start at 12:00 PM, 2:00 PM, and 3:00 PM. As a result, the amount of power resources from 12:00 PM to 2:00 PM will be 10, the amount of power resources from 2:00 PM to 3:00 PM will be 8, and the amount of power resources from 3:00 PM to 4:00 PM will be 6.

[0063] The charging / discharging station 30a is used by one vehicle 20 at 4:00 PM, and the battery charged between 12:00 PM and 4:00 PM is exchanged for the battery installed in the vehicle 20. The SOC of the battery returned from the vehicle 20 to the charging / discharging station 30a is relatively low, so it can be used for the up-DR. As a result, the amount of power resources between 4:00 PM and 6:00 PM is 8.

[0064] The charging / discharging station 30a is used by one vehicle 20 at 6:00 PM, and the battery charged between 2:00 PM and 6:00 PM is exchanged for the battery installed in the vehicle 20. The SOC of the battery returned from the vehicle 20 to the charging / discharging station 30a is relatively low, so it can be used for the up-DR. As a result, the amount of power resources becomes 10 between 6:00 PM and 7:00 PM.

[0065] The charging / discharging station 30a is used by one vehicle 20 at 7 PM, and the battery charged between 3 PM and 7 PM is exchanged for the battery installed in the vehicle 20. The SOC of the battery returned from the vehicle 20 to the charging / discharging station 30a is relatively low, so it can be used for the up-DR. As a result, the amount of power resources becomes 12 after 7 PM.

[0066] In response to a demand from the server 180, the control unit 240 controls charging and discharging of a battery that can provide a power resource held in the charging and discharging station 30a, thereby providing power according to the demand.

[0067] 3 to 7 , the control at charge / discharge stations 30a, 30b, and 30c has been described, but the entry (return) and exit of vehicles 10 at charge / discharge stations 30d and 30e can be handled in the same way as the return and provision of batteries at charge / discharge stations 30a, 30b, and 30c. Therefore, the amount of power resource can be predicted at charge / discharge stations 30d and 30e in the same way as the amount of power resource predicted at charge / discharge stations 30a, 30b, and 30c.

[0068] According to the system 100 of the present embodiment, it is possible to predict with high accuracy the amount of power resources at the charge / discharge stations 30 by using the correlation of usage amounts between the charge / discharge stations 30. It is also possible to robustly predict the amount of power resources. Furthermore, it is possible to appropriately charge the batteries held in the charge / discharge stations 30 in accordance with the prediction.

[0069] 8 shows an example of a computer 2000 in which multiple embodiments of the present invention may be embodied, in whole or in part. A program installed on the computer 2000 may cause the computer 2000 to function as a system or each part of a system according to an embodiment, or as a device such as various control devices or each part of the device, to perform operations associated with the system or each part of the system or the device or each part of the device, and / or to perform a process or steps of the process according to an embodiment. Such a program may be executed by the CPU 2012 to cause the computer 2000 to perform specific operations associated with some or all of the processing procedures and blocks of the block diagrams described herein.

[0070] The computer 2000 according to this embodiment includes a CPU 2012 and a RAM 2014, which are interconnected by a host controller 2010. The computer 2000 also includes a ROM 2026, a flash memory 2024, a communication interface 2022, and an input / output chip 2040. The ROM 2026, the flash memory 2024, the communication interface 2022, and the input / output chip 2040 are connected to the host controller 2010 via the input / output controller 2020.

[0071] The CPU 2012 operates according to programs stored in the ROM 2026 and RAM 2014, thereby controlling each unit.

[0072] The communication interface 2022 communicates with other electronic devices via a network. The flash memory 2024 stores programs and data used by the CPU 2012 in the computer 2000. The ROM 2026 stores a boot program or the like executed by the computer 2000 upon activation and / or programs dependent on the hardware of the computer 2000. The input / output chip 2040 may also connect various input / output units such as a keyboard, mouse, and monitor to the input / output controller 2020 via input / output ports such as a serial port, a parallel port, a keyboard port, a mouse port, a monitor port, a USB port, an HDMI port, etc.

[0073] The programs are provided via a computer-readable storage medium such as a CD-ROM, DVD-ROM, or memory card, or via a network. RAM 2014, ROM 2026, and flash memory 2024 are examples of computer-readable storage media. The programs are installed in flash memory 2024, RAM 2014, or ROM 2026 and executed by CPU 2012. Information processing described in these programs is read by computer 2000, and causes cooperation between the programs and the various types of hardware resources described above. An apparatus or method may be configured by implementing operations or processing of information in accordance with the use of computer 2000.

[0074] For example, when communication is performed between the computer 2000 and an external device, the CPU 2012 may execute a communication program loaded into the RAM 2014 and instruct the communication interface 2022 to perform communication processing based on the processing described in the communication program. Under the control of the CPU 2012, the communication interface 2022 reads transmission data stored in a transmission buffer processing area provided in a recording medium such as the RAM 2014 or flash memory 2024, transmits the read transmission data to a network, and writes received data received from the network to a reception buffer processing area or the like provided on the recording medium.

[0075] The CPU 2012 may also cause all or a necessary portion of a file or database stored on a recording medium such as the flash memory 2024 to be read into the RAM 2014, and may perform various types of processing on the data on the RAM 2014. The CPU 2012 then writes the processed data back to the recording medium.

[0076] Various types of information, such as various types of programs, data, tables, and databases, may be stored on the recording medium and subjected to information processing. The CPU 2012 may perform various types of processing on data read from the RAM 2014, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., as described herein and specified by the instruction sequences of the programs, and write the results back to the RAM 2014. The CPU 2012 may also search for information in a file, database, etc. on the recording medium. For example, if multiple entries each having an attribute value of a first attribute associated with an attribute value of a second attribute are stored on the recording medium, the CPU 2012 may search for an entry that matches a condition and specifies an attribute value of the first attribute from among the multiple entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0077] The above-described programs or software modules may be stored in a computer-readable storage medium on or near the computer 2000. A recording medium such as a hard disk or RAM provided in a server system connected to a dedicated communication network or the Internet can be used as the computer-readable storage medium. The programs stored in the computer-readable storage medium may be provided to the computer 2000 via a network.

[0078] A program installed in computer 2000 and causing computer 2000 to function as system 100 may act on CPU 2012 or the like to cause computer 2000 to function as each part of system 100. When the information processing described in these programs is read into computer 2000, it functions as each part of system 100, which is a specific means formed by the cooperation of software and the various hardware resources described above. These specific means then perform calculations or processing of information according to the intended use of computer 2000 in this embodiment, thereby constructing a specific system 100 according to the intended use.

[0079] Various embodiments have been described with reference to block diagrams. In the block diagrams, each block may represent (1) a stage of a process in which an operation is performed or (2) a portion of an apparatus responsible for performing the operation. Particular stages and portions may be implemented by dedicated circuitry, programmable circuitry provided with computer-readable instructions stored on a computer-readable storage medium, and / or a processor provided with computer-readable instructions stored on a computer-readable storage medium. Dedicated circuitry may include digital and / or analog hardware circuitry, and may include integrated circuits (ICs) and / or discrete circuits. Programmable circuitry may include reconfigurable hardware circuitry, including logical AND, OR, XOR, NAND, NOR, and other logic operations, flip-flops, registers, memory elements such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), and the like.

[0080] A computer-readable storage medium may include any tangible device capable of storing instructions that are executed by an appropriate device, such that the computer-readable storage medium having instructions stored thereon constitutes at least a portion of an article of manufacture containing instructions that can be executed to provide means for performing the operations specified in a process or block diagram. Examples of computer-readable storage media may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, etc. More specific examples of computer-readable storage media may include floppy disks, diskettes, hard disks, random access memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or flash memories), electrically erasable programmable read-only memories (EEPROMs), static random access memories (SRAMs), compact disc read-only memories (CD-ROMs), digital versatile discs (DVDs), Blu-ray (RTM) discs, memory sticks, integrated circuit cards, etc.

[0081] The computer readable instructions may include either assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk®, JAVA®, C++, etc., and conventional procedural programming languages ​​such as the “C” programming language or similar programming languages.

[0082] The computer-readable instructions may be provided to a processor or programmable circuitry of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, either locally or over a local area network (LAN), a wide area network (WAN) such as the Internet, etc., to execute the computer-readable instructions to provide means for performing the operations specified in the process steps or block diagrams described. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0083] Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various modifications and improvements can be made to the above embodiments. It is clear from the claims that such modifications and improvements can also be included within the technical scope of the present invention.

[0084] It should be noted that the execution order of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before," "prior to," etc., and that the processes can be performed in any order unless the output of a previous process is used in a subsequent process. Even if the operational flow in the claims, specifications, and drawings is described using "first," "next," etc. for convenience, this does not mean that the processes must be performed in this order.

[0085] 5 Power system 22 Battery 24 Battery 30 Charging / discharging station 70 Power consumer 80 Power generation device 90 Power network 180 Server 190 Communication network 200 Processing unit 210 Acquisition unit 220 Prediction unit 240 Control unit 280 Storage unit 290 Communication device 500 Graph 702 Code 704 Code 706 Code 100 System 2000 Computer 2010 Host controller 2012 CPU 2014 RAM 2020 Input / output controller 2022 Communication interface 2024 Flash memory 2026 ROM 2040 Input / output chip

Claims

1. A system for managing a plurality of charging and discharging stations connected to an electric power network for charging and discharging mobile batteries, comprising: an acquisition unit that acquires a correlation between the usage amounts of the plurality of charging and discharging stations; a prediction unit that predicts future power resources at a first charging / discharging station based on a current usage amount of a first charging / discharging station that is a prediction target of power resources that can be provided to the power network by controlling charging / discharging of the movable battery among the plurality of charging / discharging stations, a current usage amount of a second charging / discharging station that is correlated with the first charging / discharging station among the plurality of charging / discharging stations, and a correlation between the usage amount of the first charging / discharging station and the usage amount of the second charging / discharging station; A system comprising:

2. When the correlation between the usage amount of the first charging / discharging station and the usage amount of the second charging / discharging station indicates a correlation in which the usage amount of the first charging / discharging station increases when the usage amount of the second charging / discharging station increases, the prediction unit predicts that the usage amount of the first charging / discharging station will increase within a predetermined time when the current usage amount of the second charging / discharging station increases, and predicts the power resource at the first charging / discharging station in the future based on the predicted usage amount of the first charging / discharging station. The system of claim 1 .

3. When the correlation between the usage amount of the first charging / discharging station and the usage amount of the second charging / discharging station indicates a correlation in which the usage amount of the first charging / discharging station decreases when the usage amount of the second charging / discharging station increases, the prediction unit predicts that the usage amount of the first charging / discharging station will decrease within a predetermined time when the current usage amount of the second charging / discharging station increases, and predicts the power resource at the first charging / discharging station in the future based on the predicted usage amount of the first charging / discharging station.

3. The system according to claim 1 or 2.

4. When the correlation between the utilization amount of the first charging / discharging station and the utilization amount of the second charging / discharging station indicates that there is a correlation between the utilization amount of the second charging / discharging station in a first time slot and the utilization amount of the first charging / discharging station in a second time slot, the prediction unit predicts the utilization amount of the first charging / discharging station based on the correlation between the utilization amount of the second charging / discharging station in the first time slot and the utilization amount of the first charging / discharging station and the utilization amount of the second charging / discharging station, and predicts future power resources of the first charging / discharging station based on the predicted utilization amount of the first charging / discharging station.

3. The system according to claim 1 or 2.

5. The first time period is a different time period from the second time period. The system of claim 4.

6. The first time period and the second time period include a common time period. The system of claim 5.

7. The acquisition unit acquires a correlation of usage amounts between the plurality of charging / discharging stations based on a history of past usage amounts of each of the plurality of charging / discharging stations.

3. The system according to claim 1 or 2.

8. a control unit that controls charging and discharging of the mobile battery connected to the first charging and discharging station in response to a power demand in the power network; The system of claim 1 or 2, further comprising:

9. The mobile battery is a battery mounted on a vehicle.

3. The system according to claim 1 or 2.

10. The mobile battery is a battery mounted on the vehicle and replaceable at the plurality of charging / discharging stations. The system of claim 9.

11. A program for causing a computer to function as the system according to claim 1 or 2.

12. 1. A method for managing a plurality of charging and discharging stations connected to an electrical power network for charging and discharging mobile batteries, comprising: acquiring a correlation between the usage amounts of the plurality of charging / discharging stations; predicting future power resources at the first charging / discharging station based on a current usage amount of a first charging / discharging station among the plurality of charging / discharging stations that is a target for predicting power resources that can be provided to the power network by controlling charging / discharging of the mobile battery, a current usage amount of a second charging / discharging station among the plurality of charging / discharging stations that has the correlation with the first charging / discharging station, and a correlation between the usage amount of the first charging / discharging station and the usage amount of the second charging / discharging station; A method for providing