Electric power supply group control system, electric power supply group control method, and electric power supply group control program

Abstract

To provide an electric power group control system, a method thereof, and a program therefor for charing an EV through group control using information indicating whether a user is at home or out.SOLUTION: A power management apparatus has a data acquiring unit 12 for recording, as flag information, information including at least a position of each target vehicle, an actual demand predication unit 16 for, based on actual result information and the flag information, predicting a power required for charging and a time slot in which the charging is available, a prediction error calculating unit 192 for comparing an actual power supply amount supplied by a charging device with a power supply amount predication by the actual demand prediction unit 16 to calculate a predication error in prediction of power supply amounts for each charging device 43, a deviation tendency analysis unit 191 for analyzing, as deviation tendency information, power supply information and the prediction error of each charging device and correlation with external information, a group setting unit 19 for dividing a charging device group into a plurality of groups based on the deviation tendency information of each charging device, and a power supply control unit 15 for, based on the prediction by the actual demand prediction unit 16, controlling power supply to the charging device or charging to the target vehicle by a group unit.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a power supply group control system, a power supply group control method, and a power supply group control program for charging EVs (Electric Vehicles). [Background technology]

[0002] In recent years, the spread of EVs (Electric Vehicles) has been promoted in response to global environmental issues. In this case, the development of charging infrastructure for EVs is essential, and as part of this, in addition to conventional charging stations, systems are being developed to install charging stations in stores such as convenience stores, supermarkets, shopping centers, and facilities such as hospitals, and to charge EVs.

[0003] In the operation of a power grid, if the balance between power supply and demand deviates from the allowable range, a stable supply of power cannot be achieved. Furthermore, because electrical energy cannot be stored, it is necessary to maintain the balance between power demand and supply within an allowable range, known as "simultaneous and balanced supply."

[0004] Furthermore, in power grids, the balance between power supply and demand (power supply and demand balance) can be disrupted due to gaps between power demand forecasts and power supply plans (additional supply due to power source failures, an increase in demand, etc.) If the supply and demand balance is disrupted beyond a certain range, the frequency and voltage of the power grid will fluctuate, causing electrical equipment at power consumers to malfunction and, in extreme cases, causing a major power outage in the power grid, which will have a significant adverse effect on maintaining the quality of power in the power grid.

[0005] To solve this problem, a system has been proposed as a mechanism for formulating a plan to procure electricity for adjusting the power supply balance, such as the system disclosed in Patent Document 1. The system disclosed in Patent Document 1 matches demand and supply by creating a supply and demand adjustment plan that procures electricity in a real-time market according to the difference between actual demand and the supply adjustment plan, thereby achieving simultaneous equalization of supply and demand. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Publication No. 2018-139468 Summary of the Invention [Problem to be solved by the invention]

[0007] However, when charging an EV, power supply characteristics such as charging time, required time, and voltage vary depending on the location and time of day the EV is being charged, such as when the vehicle is being charged from a low-voltage charging device at the user's home or a high-voltage charging device installed at a business establishment, etc. For this reason, if information about the return location of each vehicle, such as whether they are at home or out, is not taken into consideration when supplying power for EV charging, problems such as increased peak loads on the power supply, reduced efficiency in power use, and increased energy costs may arise.

[0008] Specifically, for example, while many EVs charge at home using low-voltage charging during the evening and night, there is a tendency for demand for charging at high-voltage charging stations in commercial areas and near highways during the day. If power is supplied uniformly without considering the presence or absence of each vehicle, peak power loads will be concentrated during these times, placing a heavy burden on the power system. In particular, because the supply of renewable energy depends on the time of day and weather, depending on the season and region, charging may not occur during times when renewable energy is abundant, hindering the effective use of environmentally friendly energy sources. Concentrating charging during times of peak power demand could lead to soaring electricity prices. Since electricity prices fluctuate with supply and demand, this could result in higher electricity costs and unnecessarily higher EV operating costs.

[0009] Therefore, the present invention has been made to solve the conventional technical problems, and aims to provide an EV power supply group control system, a power supply group control method, and a power supply group control program that can suppress peaks in power demand and optimize energy use through group control that utilizes information on whether people are at home or away, thereby reducing the burden on the supply system and reducing the operating costs of EVs. [Means for solving the problem]

[0010] In order to solve the above problem, the present invention provides a power supply group control system that charges a target power storage device mounted on a target vehicle to be supplied with power, the system comprising: a charging device that charges the target power storage device; a data acquisition unit that records, for each charging device, the time, required time, and amount of power that was used to charge a target vehicle as actual performance information, and also records information including at least the location of each target vehicle as flag information; an actual demand prediction unit that predicts the power required for charging and a time period during which charging is possible for each charging device based on the performance information and flag information; a prediction error calculation unit that compares an actual amount of power supplied by the charging device with the power supply amount predicted by the actual demand prediction unit, and calculates a prediction error of the power generation amount prediction for each charging device; a deviation tendency analysis unit that analyzes a correlation between the power generation information and the prediction error of each of the charging devices and the external information as deviation tendency information; a group setting unit that divides the group of charging devices into a plurality of groups based on deviation tendency information of each of the charging devices; a power supply control unit that controls power supply to the charging devices or charging of the target vehicles on a group-by-group basis based on the prediction by the actual demand prediction unit; The present invention is characterized by comprising:

[0011] The present invention also provides a power supply group control method for charging a target power storage device mounted on a target vehicle to be supplied with power, the method comprising: (1) a data acquisition step in which a data acquisition unit records, for each charging device that charges the target power storage device, a time, a required time, and an amount of power that was used to charge the target vehicle as actual performance information, and records information including at least a position of each target vehicle as flag information; (2) an actual demand forecasting step in which an actual demand forecasting unit forecasts the power required for charging for each charging device and a time period during which charging is possible based on the performance information and flag information; (3) A deviation trend analysis step in which a deviation trend analysis unit compares the actual power supply amount of the charging device with the power supply amount predicted by the actual demand prediction unit to calculate a prediction error of the power generation amount prediction for each charging device, and a correlation between the power generation information of each charging device and the external information as deviation trend information; (4) a group setting step in which a group setting unit divides the group of charging devices into a plurality of groups based on deviation tendency information of each of the charging devices; (5) a power supply control step in which a power supply control unit controls power supply to the charging devices or charging of the target vehicles on a group-by-group basis based on the prediction by the actual demand prediction unit; Includes.

[0012] In the above invention, a connection detection unit that detects a connection state of the charging device to a charging plug of a target vehicle for each charging device; a flag information analysis unit that analyzes the usage status of each charging device, including an over-occupation state that is a difference between the duration of the connection state and the duration of the power supply state of the charging device, based on the flag information recorded by the data acquisition unit; and Furthermore, The actual demand forecasting unit forecasts the power required for charging and the time period during which charging is possible for each charging device based on the analysis result by the flag information analysis unit. It is preferable.

[0013] In the above invention, it is preferable that the device further comprises a notification unit that issues an alert when the duration of the excessive occupancy state exceeds a predetermined threshold based on the analysis by the flag information analysis unit.

[0014] In the above invention, the system further includes a map information storage unit that stores charging device map information in which the location information and charging capacity of each charging device are mapped, The flag information analysis unit analyzes the usage status by referring to the charging device map information. It is preferable.

[0015] The power supply group control system and power supply group control method according to the present invention can be realized by executing a power supply group control program written in a predetermined language on a computer. That is, by installing the power supply management program of the present invention in an IC chip or memory device of a general-purpose computer such as a portable terminal device, a smartphone, a wearable terminal, a mobile PC or other information processing terminal, a personal computer or a server computer, and executing it on the CPU, a power supply management system having the above-mentioned functions can be constructed, and the power supply management method according to the present invention can be implemented.

[0016] The power supply group control program of the present invention can be distributed, for example, via a communication line. It can also be transferred as a package application that runs on a standalone computer by recording it on a computer-readable recording medium. This recording medium can be recorded on a variety of recording media, including magnetic recording media such as flexible disks and cassette tapes, optical disks such as CD-ROMs and DVD-ROMs, and RAM cards. The computer-readable recording medium on which this program is recorded makes it possible to easily implement the above-described system and method using a general-purpose computer or a dedicated computer, and also makes it easy to store, transport, and install the program. [Effects of the Invention]

[0017] As described above, this invention enables EVs to be grouped and controlled based on flag information such as return (home / commute) and outing status, thereby suppressing peaks in power demand and reducing the burden on the power supply system. For example, it enables efficient charging planning, such as scheduling charging of vehicles that are out during low-load hours after returning home, and charging of vehicles that are at home or on the way to work during renewable energy peak times.

[0018] This will enable peak-off of power demand and optimization of renewable energy use, reducing charging costs, which will lead to lower charging costs for consumers and reduce power system operating costs for energy suppliers. Furthermore, smoothing out power demand through group control will ensure stable operation of the power system. In particular, this will enable us to respond to supply fluctuations that accompany the expansion of renewable energy adoption, and we can also expect to reduce environmental impact through the effective use of renewable energy. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 1 is a conceptual diagram illustrating an overview of a power supply management service according to an embodiment. [Figure 2] 1 is a block diagram showing an overall configuration of a power supply system according to an embodiment; [Figure 3] FIG. 2 is a block diagram showing the internal configuration of each device in the power supply system according to the embodiment. [Figure 4] 1 is a block diagram showing an internal configuration of a power management device according to an embodiment; [Figure 5] FIG. 2 is a block diagram showing the internal configuration of an intermediary server according to the embodiment. [Figure 6] FIG. 4 is a graph illustrating power control according to the embodiment. [Figure 7] FIG. 2 is a flowchart of an overall power supply process according to the embodiment. [Figure 8] FIG. 10 is a flow diagram of a data acquisition process according to the embodiment. [Figure 9] FIG. 10 is a flowchart of a predicted value calculation process according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0020] An embodiment of a power supply system, a power supply method, and a power supply program according to the present invention will be described below. In the following description, identical or equivalent parts and components are designated by the same or equivalent reference numerals throughout the drawings. Note that the embodiment described below exemplifies an apparatus for embodying the technical concept of the present invention, and the technical concept of the present invention does not limit the material, shape, structure, arrangement, etc. of each component to those described below. The technical concept of the present invention can be modified in various ways within the scope of the claims.

[0021] (Outline of power supply management service) An overview of the power supply management service according to this embodiment is shown in Figure 1. As shown in the figure, the power supply management service according to this embodiment provides a system for centrally managing both a low-voltage power supply device 431 installed in each user's home 4a and a high-voltage power supply device 432 at a commercial facility such as a charging station 4b. The home low-voltage power supply device 431 monitors power consumption through a control device such as a smart meter, and the charging station 4b has multiple high-voltage power supply devices 432 to handle large amounts of power demand.

[0022] Both the residential and commercial systems are integrated by a power management device 1, which operates an optimal power supply schedule based on power usage data and predictive analysis. This predictive model learns patterns of weather, time of day, and specific days, and adjusts the flow of power as needed. In particular, this service analyzes recorded power usage data and manages power supply based on flag information that defines the usage status of each charging device, including over-occupancy, or so-called "sitting state," which is the difference between the duration of the connected state and the duration of the power supply state for each charging device, thereby achieving stable power supply and efficient consumption and supporting sustainable energy consumption.

[0023] In more detail, in this embodiment, EV resources are grouped into area units and managed in groups for group control, enabling more effective control. To achieve this, an available capacity prediction method is used, and flag information such as "flags (away 0, feedback power supply 1, non-feedback power supply 2, away from home 3, over-occupancy 4, etc.)" and "at-home probability (probability 0-1)" are defined, making it possible to predict the available capacity of EV resources.

[0024] In this embodiment, in order to control the resources of each target vehicle, a BEV (electric vehicle), it is necessary to predict the "capacity (and remaining battery capacity)" and at the same time predict the "vehicle location information (= at-home flag, etc.)." At this time, the target vehicle is connected to a V2H (Vehicle-to-Home) device (a system that uses the EV battery at a specific location, such as a home or office, as power for the home or office), enabling resource control through charge / discharge instructions. As described above, in this embodiment, a bulk (area unit such as a city, ward, town, or village) capacity forecast is performed. This capacity forecast can be used to create plans for the following services in the future when EV penetration increases.

[0025] - Resource control of DER (Distributed Energy Resources) (participation in the supply and demand adjustment market through charge and discharge control) Arbitrage (profiting from price differences through charge / discharge control) - Distributing the charging timing of subordinate resources to prevent demand from concentrating in a certain time period Pre-charging as part of a BCP (Business Continuity Plan) (part of preparations for companies and organizations to ensure business continuity in the event of a disaster or emergency)

[0026] In addition, the specific method for predicting the BEV capacity is to calculate the following data based on actual and predicted values. - Possible increase amount (function of contracted power, demand, and charging output) -Possible reduction amount (function of demand and discharge output) SOE (State of Energy: Remote measurement and control of remaining battery capacity) Flag information (flag0~5) based on vehicle location information (time, latitude, longitude) More specifically, in this embodiment, the available capacity prediction for a low-voltage individual home is performed as follows.

[0027] -Charging and discharging control when the target vehicle is at home (return state). -SOE data can be obtained when a charger (V2H device) is connected. · Vehicle location information is defined by flag information (outside 0, return power supply 1, return power non-supply 2, outside power supply 3, over-occupancy 4, etc.). - Create and learn from actual results by base or area, and make predictions. For example, in the case of an area unit, set a target to control at about 80% of the predicted possible amount. ·Acquisition of area-based actual values ​​for data analysis.

[0028] In addition, in this embodiment, in order to prevent a decrease in power supply efficiency due to overuse (over-occupancy) of power supply stations, charging devices are classified into multiple groups and group control is performed on a group basis, and the bias in the decrease in power efficiency due to differences in the frequency and nature of overuse is leveled out based on characteristics rooted in the social, economic, and cultural background of each region. Specifically, grouping is performed according to the following criteria and rules.

[0029] Climatic conditions In cold or extremely hot climates, EV battery performance may be affected, requiring more frequent charging, which may lead to increased occupancy at charging stations. For this reason, the system uses the climate conditions of each region as a basis to group EVs to level out power consumption based on the seasons, regions, and time periods when power peaks are concentrated.

[0030] 〇 Charging infrastructure density and EV penetration rate in the region In areas where there are few charging stations and limited available charging points, users are more likely to stay where they want to charge, while in areas where the penetration rate of EVs is high, the demand for charging stations is high, which makes users more likely to stay where they want to charge.Therefore, based on the density of charging infrastructure in each area, the areas, time periods, and amount of electricity where peak power consumption is concentrated are grouped together to level out.

[0031] Economic situation and social customs In economically affluent areas, individuals are more likely to be able to install charging equipment at home, which tends to reduce the tendency for people to linger at public charging stations. Conversely, in economically disadvantaged areas, it is more difficult to invest in home charging equipment, which tends to increase the tendency for people to linger at public charging stations. Furthermore, depending on the region, social customs and norms regarding the use of public facilities and shared resources may differ, which may influence the occurrence of lingering. In areas where a spirit of sharing is deeply rooted, consideration for other users may be encouraged when using the facilities. For this reason, we group areas and time periods where peak power demand is concentrated, and aim to level out the amount of power consumed, based on the economic situation and social customs of each region.

[0032] Traffic patterns and travel distances, characteristics of tourist areas Commuting and daily travel distances vary by region, which means that the frequency and necessity of charging tend to vary. In areas with long travel distances, there is a tendency for charging stations to be overcrowded. Furthermore, in tourist areas, charging stations are used by both local residents and tourists, and during the tourist season in particular, charging stations tend to become overcrowded, resulting in a decline in power supply efficiency due to overcrowding. For this reason, the system groups areas based on the traffic patterns and travel distances of each region, as well as the characteristics of tourist areas, in order to level out areas, time periods, and power consumption where peak power consumption is concentrated.

[0033] (Overall configuration of the power supply system) 1 and 2 show the overall configuration of a power supply system according to this embodiment, and a schematic diagram of each device that constitutes the system, and FIG. 3 shows the internal configuration of each device in the power supply system. As shown in these figures, the power supply system according to this embodiment is generally composed of a plurality of charging devices 43 (including 43a and 43b) used to charge a target power storage device 71 mounted on an EV 7 that is to be charged, and a distribution power supply device 2 that can distribute power from a power supply source 3 to the plurality of charging devices 43. In this embodiment, a user's home 4a or a business 4c is a specific building or location that is registered and set as a return location unique to each vehicle, and each charging device 43 includes 43a-c installed at the user's home 4a, charging station 4b, or business 4c.

[0034] The power supply source 3 includes renewable energy power generation facilities such as solar power generation and wind power generation, thermal, hydroelectric, and nuclear power plants, as well as PPSs (Power Producers and Suppliers), and power prosumers or aggregators that purchase or sell power produced by households. The power from this power supply source 3 is first input to the distribution and power supply device 2, which then distributes the input power to each power supply facility such as the charging station 4b.

[0035] Charging station 4b is a facility or business that provides charging services, and includes conventional charging stations as well as those installed in private homes, stores such as convenience stores, supermarkets, and shopping centers, and facilities such as hospitals. Charging station 4b is equipped with a power control terminal 40 that controls power. This power control terminal 40 is, for example, an information processing terminal equipped with a CPU, and is a device that comprehensively controls each piece of equipment in the charging station. Equipment controlled by this power control terminal 40 includes a smart meter 41, a storage battery 42, a charging device 43, and the like, all of which are installed in charging station 4b, as well as devices that manage power generation, storage, and consumption as needed. Note that the various devices controlled by power control terminal 40 can be omitted as needed.

[0036] The user systems 4 (4a to 4c) are the general power facilities owned by each user's home or business, and are also units of power consumption, and may include power generation and storage facilities (such as storage batteries 42). Examples of power generation facilities include solar power generation and wind power generation. The user systems 4 include a power control terminal 40 and a smart meter 41 as a performance data generator. The power control terminal 40 installed in each user system is an information processing terminal equipped with a communication function and a CPU, and various functions can be implemented by installing an OS or firmware and various application software. In this embodiment, the power control terminal 40 functions as a power control terminal by installing and running an application.

[0037] (Configuration of an electricity trading system at an electricity supply source) In this embodiment, in the above-mentioned power supply source 3, tokens are issued according to the power generation method and power amount for sellable surplus power generated by solar power plants, wind power plants, power prosumers, and other consumers equipped with power generation facilities, and the power can be traded as tokens. These tokens are accumulated in various token pools of the token trading platform and can be used for token trading, liquidated and converted into cash, used for cashback, etc.

[0038] More specifically, an energy trading token is issued for sellable surplus electricity according to the amount of electricity generated, and together with this energy trading token, an environmental value token is issued, which is value information according to the degree of contribution to the environment of each electricity generation method and energy storage method. The environmental value token is a token that is calculated and issued according to the degree of contribution to the environment, such as the amount of electricity self-consumption or the amount of CO2 reduction. Furthermore, together with the energy trading token, an environmental value token is generated, which is value information according to the degree of contribution to the environment of each electricity generation method and energy storage method, and a DR control token is generated, which is value information as compensation for generating surplus electricity according to the economic effect of implementing power demand control (DR control).

[0039] Environmental value tokens are tokens that are calculated and issued according to the degree of contribution to the environment, such as the amount of electricity consumed by a household or the amount of CO2 reduction, and these environmental value tokens cannot be traded on the market or converted into cash in their current state. When these environmental value tokens are transferred, they are destroyed, and a transfer history is issued that records the transaction history describing the fact of the transfer, and the issued transfer history becomes the subject of transfer transactions. The transfer history of the destroyed environmental value tokens is recorded in an unalterable manner on the blockchain, a guarantee system, via the token trading platform.

[0040] In particular, in this embodiment, one of the methods for evaluating this environmental value token is to increase its value when electricity generated by a generation type with a high contribution to the environment is stored in a storage type with a high contribution to the environment, based on the method of generating electricity and the type of generation or storage related to the consumed or stored electricity. In the example shown in , electricity generated by renewable energy such as solar power generation is stored in the battery of an electric vehicle such as an EV truck of a transport company, and when it is consumed, a synergistic effect is achieved between the environmental contribution of the renewable energy and the environmental contribution of the use of the electric vehicle, so environmental value tokens are awarded as an evaluation, or their value is increased, or other processing is performed.

[0041] The energy trading tokens, environmental value tokens, and DR control tokens issued in this way will be given to solar power plants, wind power plants, businesses that have implemented DR control, etc., and can be converted into cash through settlement or used for cashback, etc., making energy management easier for each consumer and enabling optimal planned charging control such as peak cutting.

[0042] In this embodiment, a service for intermediating electricity trading using tokens is provided through an energy trading system built on a communication network 10. When the amount of power supply is adjusted through the above-mentioned power supply system, trading of the electricity related to that power supply is carried out through this energy trading system. Specifically, in this energy trading service, electricity trading is carried out by accessing a token trading platform through an energy control terminal provided in each facility (power plant, consumer, aggregator, etc.). When trading electricity, an energy trading token, which is value information of the electricity, is issued together with a DR control token and an environmental value token, which are value information related to DR (Demand Response: electricity demand) control and environmental value, and these tokens are exchanged between a seller and a buyer to complete a trading transaction of electricity and its added value.

[0043] Energy trading tokens are issued based on the amount and method of generated electricity. Salable electricity is stored in an energy trading token pool on a token trading platform as energy trading tokens equivalent to that amount of electricity, and is traded through this token pool. These energy trading tokens are ultimately purchased by consumers as the right to use (consume) electricity. The purchasing consumers can use electricity equivalent to the energy trading tokens, and by actually consuming electricity, the energy trading tokens equivalent to the consumed electricity are cancelled. The value of these energy trading tokens fluctuates depending on the supply and demand balance of trading transactions on the token trading platform. When generated, energy trading tokens are linked to origin information such as the amount of electricity, power generation method, power generation location, and power generation time. Additional information, such as related token information (e.g., environmental value tokens) derived from the energy trading tokens, and transaction history including transfer history through trading, are also associated and stored. Each accumulated token can be traded as an independent virtual currency.

[0044] In addition to the energy trading token for the generated electricity, an environmental value token is generated, which is value information according to the contribution to the environment of each power generation method and storage method, and a DR control token is generated, which is value information as compensation for generating surplus electricity according to the economic effect of implementing power demand control (DR control). The environmental value token is a token that is calculated and issued according to the contribution to the environment, such as the amount of electricity consumed by the home or the amount of CO2 reduction. In its current state, this environmental value token cannot be traded on the market or exchanged for cash.

[0045] This environmental value token is destroyed when it is transferred, and a transfer history is issued that records the date and time the transfer was executed, the transfer source (owner ID), the transfer destination (new owner ID), the value (value amount) at the time of the transfer, and other transaction history. The issued transfer history is the subject of the transfer transaction. The transfer history of this environmental value token records the value and issuer of the destroyed environmental value token, and the transfer destination in a transfer transaction is added to the transaction history each time a transfer is made. Here, destroying a token refers to a process that eliminates its exchange value as currency, such as setting its value to zero or storing it in an account that has its private key erased or made unknown and cannot be rewritten by the owner. The transfer history of the destroyed environmental token may be recorded in an unalterable manner on the blockchain, which is a guarantee system, via a token trading platform.

[0046] One method of evaluating this environmental value token is to increase the value of electricity generated by a generation type with a high environmental contribution when it is stored in a storage type with a high environmental contribution, based on the method of generating electricity and the type of generation or storage related to the consumed or stored electricity. For example, when electricity generated by renewable energy such as solar power generation is stored in a battery for an electric vehicle such as an EV truck and consumed, a synergistic effect is achieved between the environmental contribution of the renewable energy and the environmental contribution of the use of the electric vehicle, and therefore environmental value tokens can be awarded as an evaluation, or their value can be increased.

[0047] (Configuration of each device) (1)EV7 EV 7 is a passenger vehicle such as an EV, a hybrid vehicle (HV), a plug-in hybrid vehicle (PHV), etc. Specifically, EV 7 includes, as components related to the power supply system, a target power storage device 71, a charger 72, a vehicle control unit 73, and a target vehicle communication unit 74. Charger 72 is a device connected to target power storage device 71 and converts charging power supplied from charging device 43 into power suitable for charging, and is a wireless or wired communication device that communicates with charging device 43. Furthermore, vehicle control unit 73 is a control device that controls charger 72 and target vehicle communication unit 74.

[0048] The specific configuration of charger 72 is not limited, but for example, in a configuration in which AC power is supplied to EV 7 from charging device 43 as charging power, charger 72 can be provided with a function as an AC / DC converter that converts AC power to DC power. When supplying power to target power storage device 71, charger 72 is physically connected to charging device 43 via power receiving port 75 on the vehicle side and power supply plug 43f on the charging device 43 side. Power supply plug 43f includes multiple pins that fit into power receiving port 75, and these pins ensure the transmission of power, the exchange of communication signals (such as authentication between the vehicle and the charging station and management of the charging state), and a safety ground fault function.

[0049] (2) Charging device 43 Regarding the charging device 43, the charging device 43 is a device installed in a charging station that provides charging services, and is a device that charges the communication network 10 by being electrically connected to an EV 7, and is equipped with a power supply switch 43a, a charging device control unit 43b, a charging device notification unit 43c, and a charging device communication unit 43d.

[0050] The power supply switch 43a is provided on the power line extending from the distribution and power supply device 2 to the EV 7. It is a switching device that turns the power supply on and off. The charging device control unit 43b is a control device that controls the ON / OFF state of the power supply switch 43a. By controlling the ON / OFF state of the power supply switch 43a, the charging device control unit 43b controls whether charging power supplied from the distribution and power supply device 2 is transmitted to the EV 7. The power supply switch 43a is initially in the OFF state, blocking power transmission from the distribution and power supply device 2 to the EV 7. In this embodiment, when the charging device 43 and the distribution and power supply device 2 are connected and the power supply switch 43a is ON, charging power is distributed from the distribution and power supply device 2 to the charging device 43. When the charging device 43 and the distribution and power supply device 2 are connected and the power supply switch 43a is OFF, charging power is not distributed from the distribution and power supply device 2 to the charging device 43.

[0051] The charging device communication unit 43d is a wired or wireless communication device capable of communicating with the target vehicle communication unit 74. The charging device control unit 43b and the vehicle control unit 73 can exchange information through communication between the charging device communication unit 43d and the target vehicle communication unit 74. The charging device notification unit 43c is an output interface that performs various notifications, and can use, for example, a monitor or an audio speaker, and notifies information related to charging by monitor display or audio output. In this embodiment, the charging device 43 is provided with a connection detection unit 43e that detects the power supply status from the power supply plug 43f. This connection detection unit 43e detects the electrical and physical connection status of the power supply plug 43f with the power receiving port 75, and detects the power supply status including whether power is being supplied or has been supplied, and inputs the detection results to the charging device control unit 43b.

[0052] (3) Distribution and Power Supply Equipment 2 Next, the distribution power supply device 2 will be described. As shown in FIG. 1, the distribution power supply device 2 includes a power conversion unit 21, a distribution power supply device control unit 22, a distribution power supply device communication unit 23, a location information acquisition unit 24, a wireless communication unit 25, and a distribution power supply device notification unit 26.

[0053] Power conversion unit 21 is a device that converts the power supplied from power supply source 3 into AC power as charging power used to charge EVs 7. Distribution and power supply device 2 is connected to multiple charging devices 43, and distributes the AC power converted by power conversion unit 21 to each charging device 43.

[0054] Distribution / power supply device communication unit 23 is a communication device that can communicate with both EV 7 and charging device communication unit 43d. Distribution / power supply device control unit 22 can exchange information with charging device control unit 43b on the charging device 43 side via communication between distribution / power supply device communication unit 23 and charging device communication unit 43d.

[0055] Furthermore, the location information acquisition unit 24 is a module that acquires information about the current location and has, for example, a GPS (Global Positioning System) function to acquire its own current location. The wireless communication unit 25 is a wireless communication device that performs wireless communication, and the distribution and power supply apparatus control unit 22 can access the Internet, a server, etc. via wireless communication by the wireless communication unit 25 and perform various types of distribution and power supply apparatus notification unit 26 is an output device that performs various types of notification, such as a monitor or audio speaker, and notifies information related to power supply. The distribution and power supply apparatus control unit 22 monitors the connection status of the distribution and power supply apparatus 2 and the multiple charging apparatuses 43, and performs a power supply availability notification indicating that power supply is available along with the location information, using the communication established between the distribution and power supply apparatus communication unit 23 and the charging apparatus communication unit 43d and the charging apparatus communication unit 43d, or the wireless communication unit 25.

[0056] Specifically, when an EV 7 is connected, charging device control unit 43b uses charging device communication unit 43d to send a new connection confirmation signal confirming the new connection to distribution / power supply device control unit 22. For example, when an EV 7 is connected to charging device 43, charging device control unit 43b of a certain charging device 43 uses charging device communication unit 43d to send a new connection confirmation signal to distribution / power supply device control unit 22 (specifically, distribution / power supply device communication unit 23) using the charging device communication unit 43d. Then, distribution / power supply device control unit 22 identifies an uncharged vehicle when the distribution / power supply device communication unit 23 receives the new connection confirmation signal. When the distribution / power supply device control unit 22 identifies an uncharged vehicle, it executes a charging start control process to start charging the newly connected EV 7 (i.e., the uncharged vehicle).

[0057] (4) Power management device 1 As shown in Figure 4, the power management device 1 is a server device that manages power supply at multiple charging stations 4b in order to charge the target power storage devices installed in the EVs 7 that are the target of power supply, and specifically includes a communication interface 11, a data acquisition unit 12, a database 13, a control instruction schedule management unit 14, a power supply control unit 15, an actual demand forecasting unit 16, a performance information analysis unit 17, a notification unit 18, and a group setting unit 19.

[0058] The communication interface 11 is a device for performing data communication, and has the function of performing contactless communication such as wireless communication, and contact (wired) communication using a cable, adapter means, or the like.

[0059] Data acquisition unit 12 is a module that records, for each charging device 43, the time, required time, and amount of power that an EV 7 is charged, as well as changes in the amount of power stored in the charged target power storage device 71, and records the time and location information of the connection state detected by the connection detection unit as flag information.Data acquisition unit 12 is a module that acquires and monitors the power supply status of each charging device 43 and inputs the current status to control instruction schedule management unit 14. The power supply status acquired by data acquisition unit 12 is provided to actual demand forecasting unit 16 for demand forecasting.

[0060] The data acquiring unit 12 also has a function of recording the time and location information of the connection state detected by the connection detecting unit 43e of each charging device 43 as flag information, and also has a function of collecting power source information related to the power supply source 3. The power source information includes, for a predetermined time unit, the market price of electricity at the time when electricity is received or stored in each power source, the amount of electricity received or stored, and information related to the storage equipment that stored the electricity. The electricity storage information (including electricity reception information) collected by this data acquiring unit 12 is stored in the database 13, and is also input to the performance information analyzing unit 17 and the control instruction schedule managing unit 14.

[0061] The data acquisition unit 12 also has a market information collection function that collects external information (such as price fluctuations in the electricity market, weather information, and other external environmental information) from external information sources distributed on the Internet. This market information collection function not only patrols external information sources on the Internet by a so-called crawling process to periodically collect predetermined information, but also has a function that searches information sources on the communication network using related keywords, collects sudden news and weather fluctuations, and stores them as big data.

[0062] The control instruction schedule management unit 14 is a module that manages control schedules such as general power supply services, power generation services, power procurement, charging and discharging at power storage facilities, power distribution and supply, and power adjustment (balancing) by planning reduction periods. The control instruction schedule management unit 14 receives the current power supply status and external information (price fluctuations in the electricity market, weather information, and other external environmental information) input from the data acquisition unit 12, as well as flag information for each vehicle in real time, and creates and manages schedules for power distribution and supply to each charging station 4b, power adjustment such as planning charging and discharging at power storage facilities, and other power procurement schedules based on the power supply and demand predicted by the actual demand prediction unit 16 based on this information.

[0063] The power supply control unit 15 is a module that controls power supply to the charging devices 43 or charging of the EVs 7 in accordance with a control schedule based on the predictions made by the actual demand prediction unit 16. The power supply control unit 15 controls the operation of the charging devices 43 in each charging station 4b in accordance with the control of the control instruction schedule management unit 14.

[0064] The performance information analysis unit 17 is a module that calculates the amount of power consumed in each station by acquiring and analyzing performance data from the smart meters 41 provided in each charging station 4b. The analysis results by this performance information analysis unit 17 are input to the actual demand forecasting unit 16 and used to generate a control schedule.

[0065] Furthermore, the performance information analysis unit 17 has a flag information analysis unit 17a. This flag information analysis unit 17a analyzes the usage status of each charging device, including an over-occupation state, which is the difference between the duration of the connected state and the duration of the power supply state for each charging device 43, based on performance data including flag information recorded by the data acquisition unit 12. Furthermore, the flag information analysis unit 17a analyzes the usage status by referring to charging device map information 13a stored in the database 13.

[0066] The charging device map information 13a is a map information storage unit that stores charging device map information that maps the location information and charging capacity of each charging device. The charging device map information 13a also maps the return location of each target vehicle, and the flag information analysis unit 17a assigns a return flag (1) to each target vehicle when it is located at the return location, and assigns an out-of-town flag (0) when it is located other than the return location, and calculates the excessive occupancy state when the out-of-town flag (0) is assigned to the target vehicle by referring to the charging device map information 13a, and analyzes the usage status.

[0067] The actual demand forecasting unit 16 is a module that predicts the power required for charging each charging device 43 and the time period when charging should be performed based on the information recorded by the data acquisition unit 12. Specifically, the actual demand forecasting unit 16 analyzes the correlation between past power supply and demand, external information, and over-occupancy states to predict future power supply and demand. This prediction analyzes the external information collected by the data acquisition unit 12 and past changes in power demand as big data, and uses machine learning functions of AI (artificial intelligence) such as deep learning to accumulate feature points from the analysis targets, extract correlations (trends) between each piece of information based on the commonality of the feature points, and predicts future power demand from the commonality of feature points that match current market information.

[0068] In addition, based on the analysis results by the flag information analysis unit 17a, the actual demand forecasting unit 16 calculates the remaining storage capacity of each target vehicle that has been assigned an out-of-home flag, and predicts the power required for charging each charging device and the time periods during which charging is possible.

[0069] Furthermore, the power management device 1 is provided with a notification unit 18. The notification unit 18 issues an alert when the duration of the excessive occupancy state exceeds a predetermined threshold based on the prediction by the actual demand prediction unit 16. The following mechanisms can be used as a means for issuing this alert. This alert is sent to the driver or owner of the target vehicle, or to staff at the charging station, and the following methods can be selected.

[0070] Smartphone app notifications When a certain time has passed since charging was completed, the smartphone app will output an alert notification to the driver or owner of the vehicle and charging station staff. This alert notification will include a message that the vehicle is over-occupied and a prompt to unplug the vehicle immediately to free up space. If the user does not respond, the app may be configured to send repeated reminder notifications or to issue instructions to charging station staff.

[0071] * SMS and email warnings The app may also have the ability to send alerts directly to drivers, owners, or staff via SMS or email, including the time since charging was completed and specific instructions for actions to take to free up the charging spot, ensuring that even infrequent app users receive the alerts.

[0072] 〇Display display A display may be installed on the charging station premises to display a warning message to staff and on-site users, clearly indicating which charging spots are over-occupied and that action is required, facilitating staff to take prompt action.

[0073] 〇 Voice alert Audio alerts from charging stations can also be output directly to drivers and staff in the vicinity of the station. If a specific charging port is over-occupied, an audio message will be sent out to inform drivers and staff that an immediate action is required, raising awareness in public places.

[0074] *Warning by car navigation system communication function When charging is completed and the vehicle is in an over-occupancy state, a warning message may be displayed to the driver through the car navigation system via the car navigation system's communication function. In this system, the car navigation system and the notification unit 18 of the power management device 1 work together to exchange charging status information in real time, and notifications of charging completion and alerts about over-occupancy can be confirmed directly on the car navigation screen, making it possible to provide a highly convenient and effective warning.

[0075] The group setting unit 19 is a module that divides (groups) the group of charging devices into multiple groups based on the deviation tendency information of each charging device. In this embodiment, the group setting unit 19 divides the charging devices into groups by combining charging devices whose prediction errors are equal to or less than a predetermined low threshold with charging devices whose prediction errors are equal to or greater than a predetermined high threshold, so that the prediction error of the entire group exceeds a predetermined average value. For example, the group setting unit 19 divides the group of charging devices into multiple groups so that the sum of the prediction errors of all group candidates divided by the simple sum of the absolute values ​​of the prediction errors of those charging devices is below a predetermined value.

[0076] In this embodiment, the group setting unit 19 includes a deviation tendency analysis unit 191 and a prediction error calculation unit 192. The deviation trend analysis unit 191 is a module that analyzes the correlation between the power generation information and prediction error of each charging device and external information as deviation trend information. The deviation trend analysis unit 191 also has a learning function that extracts the distribution of features related to the actual power generation amount corresponding to the power generation amount prediction with a prediction error equal to or greater than a predetermined reference value and the external information related to the power generation amount prediction, and forms a neural network as deviation trend information. On the other hand, the prediction error calculation unit 192 is a module that compares the actual power supply amount of the charging device with the demand prediction by the actual demand prediction unit 16, and calculates the error in the demand prediction for each charging device.

[0077] In this embodiment, the actual demand forecasting unit 16 queries the learning function to obtain candidates calculated by machine learning in the process of predicting the power supply amount, power consumption amount, and their standard deviation values. This learning function is a module that performs machine learning so that the deep learning recognition function, which is an artificial intelligence, can make appropriate judgments. In this embodiment, it generates training data from the performance data and external information collected by the data acquisition unit 12, and trains the deep learning recognition unit based on this training data. The learning function also serves as a comparison unit that compares the estimated history, which is the judgment result by deep learning recognition, with the performance data and external information input to the deep learning recognition.

[0078] Furthermore, the prediction error calculation unit 192 compares the judgment results for the same event (target charging device, target vehicle, target area, occurrence time, etc.) input as training data to the deep learning recognition function with the actual control data at that time, determines whether the comparison results match, and calculates the degree of match as a prediction error. The prediction error calculated by this prediction error calculation unit 74c is sent to the deviation trend analysis unit 191. The deviation trend analysis unit 191 analyzes the correlation between the power supply information and prediction error of each charging device or a group of charging devices belonging to the target area and external information as deviation trend information. Furthermore, by analyzing the prediction results and confirming which options were incorrect if they differ from reality, the prediction error rate of the prediction results by the actual demand prediction unit 16 is calculated, and the validity of the various options selected by the actual demand prediction unit 16 when executed is inductively verified and fed back to the deviation trend analysis unit 191.

[0079] The deviation trend analysis unit 191 is a module that makes judgments using so-called deep learning, and uses the analyzed deviation trends as learning data (teacher data) for function verification. Specifically, the deep learning recognition unit analyzes the correlation between each piece of forecast information and performance data, as well as external information and correlation information, according to a predetermined deep learning algorithm, and accumulates the deep learning recognition result (price prediction AI model), which is the analysis result, in a forecast result information database.

[0080] In this embodiment, the algorithm implemented in the learning function of the actual demand forecasting unit 16 is a multi-layered neural network, particularly one with three or more layers, and is a learning and recognition system that mimics the mechanisms of the human brain. When image data or other data is input to this recognition system, the data is propagated in order from the first layer, and learning is repeated in order at each subsequent layer. During this process, the feature values ​​within the image are automatically calculated.

[0081] These features are essential variables necessary for solving problems, and are variables that characterize specific concepts. The actual demand forecasting unit 16 also receives inputs of performance data, estimated history, external information, and correlation information, hierarchically extracts multiple feature points from these data, and recognizes patterns based on hierarchical combination patterns of the extracted feature points. The recognition function module of the actual demand forecasting unit 16 is a multi-class classifier, which is configured with multiple events and detects feature vectors (e.g., "weather at a specific time period") that are objects containing specific feature points from multiple objects. This recognition function module has an input unit (input layer), a first weighting coefficient, a hidden unit (hidden layer), a second weighting coefficient, and an output unit (output layer).

[0082] In this case, multiple feature vectors are input to the input unit. The first weighting coefficient weights the output from the input unit. The hidden unit performs a nonlinear transformation on the linear combination of the output from the input unit and the first weighting coefficient. The second weighting coefficient weights the output from the hidden unit. The output unit calculates the classification probability for each class (e.g., device used, usage state, etc.). Three output units are shown here, but this is not limited to this. The number of output units is the same as the number of events that the pattern classifier can detect. Increasing the number of output units increases the number of events that the event classifier can detect, such as recognizable device types.

[0083] The deviation trend analysis unit 191 has a function of referring to deviation trend information by having a neural network identify related information having features similar to the characteristics of each group based on the characteristics of the group, such as regionality, and calculating the prediction error in the construction candidate area as deviation trend forecast information. Also, the actual demand forecasting unit 16 refers to the deviation trend information based on the characteristic information of each group and calculates the prediction error in the construction candidate area as deviation trend forecast information.

[0084] (5) Mediation Server 8 The intermediary server 8 is a server device managed and operated by a provider of an energy trading intermediary service, and a user wishing to buy or sell energy can access the intermediary server 8 through a communication network 10 and execute an energy trading transaction via the token trading platform provided by the intermediary server 8. Specifically, as shown in FIG. 5 , the intermediary server 8 includes a communication interface 83, an authentication unit 82, an energy trading execution unit 85, a token management database 81a, a user database 81b, a performance management database 81c, an energy trading management database 81d, a token management unit 84, a performance data management unit 86, and a settlement unit 87.

[0085] The communication interface 83 is a module that transmits and receives data to and from other communication devices through the communication network 10, and in this embodiment, is connected to each power control terminal and the smart meter 41 in order to provide this service.

[0086] The authentication unit 82 is a computer or software having such functionality that verifies the legitimacy of an accessing party involved in energy trading, and performs authentication processing based on a user ID that identifies the user. In this embodiment, the authentication unit 82 obtains the user ID and password from the accessing party's terminal device via the communication network 10, and verifies them against the user database 81b to confirm whether the accessing party has the right to access the energy trading site and whether the accessing party is the person in question.

[0087] The energy trade execution unit 85 is a module that mediates energy trades through the communication network 10, and in this embodiment includes a contract data generation unit 85a and a data storage unit 85b.

[0088] The contract data generation unit 85a generates contract data for a concluded transaction based on the selling data and buying data. In more detail, the energy trading execution unit 85 collates the selling data and buying data, which are the demand conditions of the buyer and the supply availability conditions of the seller, and concludes a transaction by matching corresponding combinations, and generates contract data describing information on the demand conditions and supply availability conditions of the concluded transaction, such as the supply source, power generation method, supply availability period, and electricity price.

[0089] The data storage unit 85b is a module that requests processing required for energy trading, such as credit related to energy trading, security management, and storage of transaction records, from data storage systems such as cloud servers and blockchain systems on the network, and cooperates with them to carry out the processing. By linking with the data storage system through this data storage unit 85b, the energy trading execution unit 85 manages the exchange of various tokens, adds public addresses related to token acquirers, and transfers each ownership by changing the owner of the various rights proven by each token.

[0090] The token management unit 84 is a module that executes and manages the generation (issuance), transfer, and cancellation of various tokens, and updates the data in various tokens to execute the issuance, transfer, or cancellation of various tokens in cooperation with the data storage unit 85b of the energy trading execution unit 85. Specifically, the token management unit 84 includes a token issuing unit 84a, a token canceling unit 84b, and a token transfer unit 84c.

[0091] The token issuing unit 84a is a module that issues various coin tokens to users in response to their requests. For example, based on performance data, it issues energy trading tokens to users who have electricity that can be sold by the power generation facility, and by analyzing the performance data, it generates environmental value tokens, which are value information corresponding to the environmental contribution of each power generation method and power storage method, derived from the energy trading token of the generated electricity, and generates DR control tokens, which are value information corresponding to the economic effect of implementing power demand control (DR control).

[0092] In this embodiment, the token issuing unit 84a issues environmental value tokens based on the amount of CO2 reduction or the amount of self-consumption due to the power generation method included in the performance data. For example, if the power generation method included in the performance data is based on renewable energy such as solar power generation or wind power generation, the token issuing unit 84a holds CO2 reduction table data that lists the correspondence between the amount of power generated by that power generation method and the amount of CO2 reduced by that power generation method, and references the CO2 reduction table data based on the amount of power generated included in the performance data to determine the value and quantity of environmental value tokens, and issues environmental value tokens of the determined value or quantity. The issued environmental value tokens are accumulated in an environmental value token pool as property of the power generator included in the performance data.

[0093] Furthermore, for example, when the power generation method included in the performance data is based on renewable energy such as solar power generation or wind power generation, and that power is self-consumed, the token issuing unit 84a holds self-consumption table data that lists the amount of CO2 reduced by that self-consumption and its correspondence with energy loss due to power transmission and distribution, and references the self-consumption table data based on the amount of self-consumption included in the performance data to determine the value and quantity of environmental value tokens, and issues environmental value tokens of the determined value or quantity. The issued environmental value tokens are accumulated in an environmental value token pool as property of the user who self-consumed the power and included in the performance data.

[0094] Furthermore, the token issuing unit 84a according to this embodiment also functions as a renewable energy token issuing unit that acquires the amount of the donation, converts the environmental value tokens equivalent to the acquired amount into tradable renewable energy tokens, and cancels the converted environmental value tokens. Specifically, the amount of the donation, etc., and the power generation method to which the donation is made are input as search conditions to the token issuing unit 84a, and the token issuing unit 84a searches the environmental value token pool in the token management database 81a for environmental value tokens of power generation methods that meet the search conditions. The token issuing unit 84a then extracts the corresponding environmental value tokens, distributes the input donation amount among the corresponding number of environmental value tokens, and converts the environmental value tokens equivalent to the distributed amount into renewable energy tokens. The converted renewable energy tokens are issued to the owner of the original environmental value tokens, and the issued renewable energy tokens are accumulated in the renewable energy token pool as the property of the user who is the owner of the original environmental value tokens.

[0095] The token erasure unit 84b is a module that erases energy trading tokens based on performance data and erases environmental value tokens related to transfer requests. Here, erasing a token refers to a process that eliminates its exchange value as a currency, such as setting its value to 0, erasing or obscuring the private key, and storing it in an account that cannot be rewritten by the owner.

[0096] The token transfer unit 84c is a module that controls the transfer of tokens by rewriting the ownership of each token, and in this embodiment, a blockchain interface service is used for this rewriting. This token transfer is executed based on a transfer request that instructs the transfer. This transfer request is data that is input from the energy trading execution unit 85 when a token sale is concluded in the energy trading execution unit 85, or that is input directly from the energy control terminal by operation of each user, and includes the type of token to be transferred, account information regarding the transfer source and transfer destination, and the quantity.

[0097] In particular, when the input transfer request requests the transfer of an energy trading token or an environmental value token, the token transfer unit 84c has the function of transferring the energy trading token related to the request if the target of the transfer request is an energy trading token, or causing the token erasure unit 84b to erase the environmental value token related to the request if the target of the transfer request is an environmental value token, and generating information related to the transfer included in the transfer request related to the erased environmental value token as a transfer history. The transfer history related to this erased environmental token is recorded non-falsifiable in the blockchain, which is a guarantee system, via the token trading platform.

[0098] The token management database 81a is a storage device that accumulates information about issued and cancelled tokens, and accumulates information about the owner of each token, its type, and its value or quantity, linked to each other. Various tokens are classified and accumulated according to their type as an energy trading token pool, an environmental value token pool, a DR control token pool, and a renewable energy token pool. In addition, related information such as the transaction history of each token is also recorded linked to each token. For example, the transfer history issued when an environmental value token is transferred is also recorded linked to the original environmental value token that was transferred and whose value was set to 0.

[0099] The user database 81b is a storage device that stores information about each consumer user and businesses such as aggregators. In this embodiment, personal information that identifies the user is not stored in the user database 81b, and only public account information that identifies each resident and user is stored. The credit information required for energy trading is evaluated based on the response to a request for credit related to the public account belonging to each resident from the data storage system.

[0100] The performance management database 81c is a storage device that collects, accumulates, and manages performance data from parties involved in the exchange of electricity, such as power plants, consumers, and aggregators. Performance data received from each smart meter is accumulated in this performance management database and used for token issuance, cancellation, and value evaluation. The electricity trading management database 81d is a storage device that records token trading performance.

[0101] At least a portion of the data stored in each of these databases 81a-d is recorded in the data storage system via the data storage unit 85b. The data storage system aggregates and blocks at least a portion of the data stored in each of the databases 81a-d at a predetermined timing in the nodes, forms a blockchain using the blocks, and shares this blockchain among multiple nodes and stores it as a distributed ledger.

[0102] The performance data management unit 86 is a module that calculates the type and quantity of tokens to be issued by collecting and analyzing performance data from each user system, and the analysis results by this performance data management unit 86 are input to the token management unit 84 and used for issuing or canceling tokens. Specifically, the performance data management unit 86 includes a value evaluation unit 86a.

[0103] The value evaluation unit 86a analyzes the measured values ​​of the amount of electricity generated or consumed by each user during each electricity usage period, power generation data indicating the power generation method and the user who generated the electricity, or power storage data regarding the amount of electricity stored and its storage period, which are included in the performance data.The token management unit 84 issues or cancels energy trading tokens, or issues energy trading tokens and environmental value tokens, based on the analysis results by the value evaluation unit 86a of the performance data including the power generation data or power storage data.Furthermore, the token issuing unit 84a issues environmental value tokens or power demand control tokens as compensation for generating surplus electricity, based on the analysis results by the value evaluation unit 86a of the performance data including the power generation data or power storage data.

[0104] Furthermore, the performance data includes the type of power generation or storage related to the consumed power, and the value evaluation unit 86a analyzes the performance data to extract the state in which power from a power generation type that has a high degree of contribution to the environment is stored in a power storage type that has a high degree of contribution to the environment, calculates the amount of power and time period, and evaluates the value.The token issuing unit 84a increases the value of the environmental value token when power from a power generation type that has a high degree of contribution to the environment is stored in a power storage type that has a high degree of contribution to the environment, based on the analysis results of the performance data by the value evaluation unit 86a.

[0105] The settlement unit 87 is a module that converts various tokens into cash according to their current value, and acquires information on the current value of various tokens from the network and converts them into actual currency, virtual currency, points, or other value information having exchange value by settling the information. The settlement unit 87 also has a function to generate or acquire final data including the final values ​​of the amount of electricity generated or used by each user during each electricity usage period and the compensation amount for that amount of electricity, and to settle the compensation paid or received by each user based on the final data.

[0106] (Operation when powered) The power supply management method of the present invention can be implemented by operating the power supply management system described above. FIG. 7 shows the power supply process according to this embodiment, FIG. 8 shows the data acquisition process according to this embodiment, and FIG. 9 shows the predicted value calculation process according to this embodiment. Note that the processing procedures described below are merely examples, and each process may be modified as much as possible. Furthermore, steps in the processing procedures described below can be omitted, replaced, or added as appropriate depending on the embodiment.

[0107] As shown in FIG. 7, first, the location information of each EV 7 is measured, and for each target power storage device 71, the data acquisition unit 12 records the time when the EV 7 was charged, the required time, and the amount of power, as well as the change in the amount of power stored in the charged target power storage device 71. A data acquisition step is then performed in which past performance data (performance information) and flag information for each time period are compiled for each power facility (S101).

[0108] Step S101 includes a data acquisition step in which, for each charging device 43, data acquisition unit 12 records the time, required time, and amount of power at which the target vehicle was charged, and the change in the amount of power stored in the charged target power storage device 71, as performance information, and records the time and position information of the connection state detected by connection detection unit 43e as flag information. Step S101 also includes a connection detection step in which, for each charging device that charges the target power storage device 71, connection detection unit 43e detects the connection state with the charging plug of the target vehicle, and a flag information analysis step in which flag information analysis unit 17a analyzes the usage status of each charging device, including an overoccupancy state, which is the difference between the duration of the connection state with respect to the charging device and the duration of the power supply state, based on the flag information recorded in the data acquisition step.

[0109] In the flag information analysis step, based on the flag information recorded in the data acquisition step, flag information analysis unit 17a executes a process of analyzing the usage status of each charging device, including an over-occupancy state, which is the difference between the duration of the connection state and the duration of the power supply state for charging device 43. In this flag information analysis step, the usage status is analyzed by referring to charging device map information 13a, which maps the location information and charging capacity of each charging device. The charging device map information 13a also maps the return position of each target vehicle, and in the flag information analysis step, a return flag is assigned when each target vehicle is located at the return position.

[0110] On the other hand, if the target vehicle is located other than the return position, an out-of-town flag is set, and the usage status is analyzed by calculating the excessive occupancy state when the out-of-town flag is set for the target vehicle with reference to the charging device map information 13a. If the duration of the excessive occupancy state exceeds a predetermined threshold, a notification step is executed in which the notification unit 18 issues a predetermined alert.

[0111] 8, the current position of each target vehicle is acquired (S301), and it is determined whether the target vehicle is at a return position (at home) (S302). This determination is made by referring to map information and determining whether the target vehicle is located (parked) at a predetermined return position (home, office, etc.) registered for each target vehicle. If the target vehicle is located at the return position ("at home" in step S302), a home (return) flag is set (S303), and if the target vehicle is not located at the return position ("away" in step S302), a away flag is set (S311).

[0112] If it is determined in step S302 that the user is at home, it is determined whether the vehicle is in a power supply state or a power non-supply state (S304). In step S304, it is confirmed whether the power supply plug of the charging device installed at home or the like is electrically connected to the power receiving port 75 of the target vehicle, and if voltage is actually being applied, it is determined that power is being supplied ("power supply" in S304) and a power supply flag is set (S308). On the other hand, if voltage is not being applied, it is determined that power is being supplied ("power non-supply" in S304) and a power non-supply flag is set (S305).

[0113] The management device records the time and duration of the state as flag information set according to the power supply or non-power supply state (S306 or S309). When the vehicle is in the power supply state ("power supply" in S304), steps S304, S308, and S309 are repeated in a loop until power supply is completed. When charging is completed, the vehicle enters the non-power supply state ("non-power supply" in S304), and measurement of the duration of the power supply state is switched to measurement of the duration of the non-power supply state, and recording begins (S306). After charging at home is completed, the actual information at the return location is updated (S307).

[0114] On the other hand, if it is determined in step S302 that the EV 7 is out ("Out" in S302), the outgoing plug is set (S311) and then a determination is made as to whether it is in a connected state (S312). This connection state is determined by detecting whether the power supply plug 43f is electrically and physically connected to the power receiving port 75 of the EV 7. If it is not connected ("Not connected" in S302), the process proceeds directly to step S310, where the current amount of stored power in the target vehicle is acquired and recorded. In other words, if the power supply plug is not physically or electrically connected to the power receiving port 75 of the EV 7, this means that the EV 7 is not, at least, involved in power supply work, and only the amount of stored power in the target vehicle is recorded.

[0115] If it is determined in step S312 that the vehicle is in a connected state ("connected" in S312), it is then determined whether the vehicle is in a power supplying state or a non-power supplying state (S313). In step S313, it is confirmed whether the power supply plug 43f of the charging device installed at a power supply station or the like at the destination is electrically connected to the power receiving port 75 of the target vehicle, and if voltage is actually being applied, it is determined that power is being supplied ("power supplying" in S313) and a power supply flag is set (S318). On the other hand, if voltage is not being applied, it is determined that power is being supplied ("non-power supplying" in S313) and a non-power supply flag is set (S314).

[0116] The management device records flag information set according to the power supply or non-power supply state, along with the time and duration of the state (S315 or S319). At this time, the distribution / power supply device control unit 22 determines, among the multiple charging devices 43, the charging device 43 that transmitted the new connection confirmation signal that triggered the execution of the charging start control process as the target charging device. The distribution / power supply device control unit 22 then confirms the vehicle model of the target vehicle. Specifically, the vehicle control unit 73 of the target vehicle transmits its own vehicle model information to the charging device control unit 43b of the target charging device, and the charging device control unit 43b of the target charging device transmits the vehicle model information to the distribution / power supply device control unit 22. The distribution / power supply device control unit 22 identifies the vehicle model of the target vehicle (EV7) based on the vehicle model information of the target vehicle. Note that the specific content of the vehicle model information of EV7 is arbitrary as long as it can identify the vehicle model.

[0117] When the device is in a power supply state ("Power supply" in S313), steps S318 and S319 are repeated in a loop until power supply is completed. When charging is completed, the device enters a non-power supply state ("Non-power supply" in S313), and measurement of the duration of the power supply state is switched to measurement of the duration of the non-power supply state, and recording is started (S315).

[0118] Following step S315, in step S316, it is determined whether a predetermined time has elapsed, and if it is within the predetermined time ("N" in step S316), steps S312 to S316 are repeated in a loop, and if the connection state is released within the predetermined time ("disconnected" in S312), charging is completed and the amount of stored power of each target vehicle is acquired (S310). On the other hand, if it is determined in step S316 that the predetermined time has elapsed ("Y" in step S316), an over-occupancy notification process is executed (S317), and steps S312 to S316 are repeated in a loop ("Y" in step S316), and when the over-occupancy state is released ("disconnected" in S312), charging is completed and the amount of stored power of each target vehicle is acquired (S310).

[0119] In step 310, the distribution / power supply device control unit 22 derives the battery capacity and remaining amount of stored power of the target power storage device 71 of the target vehicle by referencing battery capacity data stored in the distribution / power supply device control unit 22. This battery capacity data is data that associates vehicle model information of the EV 7 with the battery capacity and remaining amount of stored power of the target power storage device 71. The distribution / power supply device control unit 22 derives the battery capacity and remaining amount of stored power corresponding to the current target vehicle by referencing the battery capacity data. Note that the battery capacity is the maximum amount of stored power of the target power storage device 71 and is a design value that is predetermined for each vehicle model, and the remaining amount of stored power is the amount of power remaining in the target power storage device 71. In this way, in step S101, the location information of each vehicle is monitored, the connection status of the EV 7 to each charging device 43 at a home, business, power supply station, etc. is detected, and the flag information is analyzed as needed and updated to the latest information.

[0120] 7, based on the aggregation result of the information recorded by the data acquisition unit 12, the actual demand prediction unit 16 predicts the power required for charging for each charging device 43 and the time period during which charging should be performed, and performs a demand prediction step of calculating a predicted value of power demand for each charging device (S102). Specifically, in this demand prediction step (S102), the data acquisition unit 12 analyzes the actual data collected, and calculates, for each demand unit, the predicted power consumption for each unit measurement period of power consumption in each time period and the reliability for each unit measurement period at which the actual power consumption becomes the predicted power consumption (S201) for each charging device.

[0121] Next, the analysis results of the actual data are compared with the predicted power supply calculated in the previous step, flag information, and connection information to perform grouping (S202). At this time, the charging device groups are set based on the deviation trends (deviation trends) analyzed in the previous step. After that, matching between charging devices such as low-voltage charging devices and high-voltage charging devices is performed based on the deviation trends to select combinations of charging devices, and the prediction error reduction effect of each combination is analyzed for the charging device group (S203). The combination with the greatest prediction error reduction effect is set as the optimal charging device group.

[0122] In this embodiment, the charging devices are grouped by appropriately selecting the following criteria and methods. Grouping criteria Taking into account the balance of electricity supply and demand by region, regions are divided into those with abundant electricity supply and those without, and grouped based on the region's specific electricity supply and demand conditions, such as the regional adoption rate of renewable energy and trends in electricity consumption. Furthermore, as consumption tends to be higher at night in residential areas and during the day in commercial areas, grouping is based on consumption patterns by time of day. Alternatively, grouping is done based on the frequency and purpose of EV use, such as users who mainly charge at home, businesses that use them for commercial purposes, and users who travel frequently.

[0123] Grouping methods and rules This can be done using a demand response method that introduces a notification system that prompts a preset group to delay or accelerate charging before peak power demand, or a dynamic pricing method that encourages users to charge during off-peak times by raising charging costs during peak power demand and lowering them during off-peak times. A prioritized charging scheduling method can also be used, which determines charging priorities based on pre-registered charging needs and the next time of use, and executes charging based on an efficient charging schedule.

[0124] In particular, in this embodiment, grouping may be performed taking into account so-called "staying at the power station" by monitoring the connection status between the power receiving port 75 and the power plug 43f. More specifically, in this embodiment, the decline in power supply efficiency due to "staying at the power station (excessive occupancy)" is reduced by grouping charging devices. For example, vehicles that need to be charged more frequently (e.g., vehicles that are planned to be reused in a short time, have a low remaining battery, etc.) may be prioritized and a priority charging group may be established according to the urgency of charging. Alternatively, vehicles that can be charged quickly may be distinguished from vehicles that require long charging times and grouped according to the charging time required. For example, separating EVs that can be fast-charged from EVs that can only be standard-charged can improve the turnover rate at charging stations. Furthermore, grouping may be performed according to users' schedules, such as collecting users' charging schedules (e.g., charging start time, planned charging end time) in advance through a reservation system and allocating charging slots based on this information.

[0125] The grouping rules in this case may include, for example, a time-of-day charging restriction system that restricts non-emergency charging during times of tight power supply and demand and allows only highly urgent charging, thereby reducing power consumption during peak hours; a reservation priority system that gives priority at charging stations to vehicles that have made reservations and encourages vehicles waiting to charge without a reservation to charge during non-peak hours; or grouping based on penalties and incentives, such as applying a penalty if charging continues beyond a specified time to prevent vehicles from staying at the station, while providing incentives such as discounts to vehicles that charge during non-peak hours.

[0126] Furthermore, customized grouping rules can be established that take into account regional characteristics (such as power supply conditions, traffic volume, and charging infrastructure density), and grouping can be done based on regional characteristics to target optimal power supply efficiency for each region, or by providing real-time information such as the current congestion status of charging stations, expected waiting times, and optimal charging time periods, allowing users to charge efficiently.

[0127] Next, the standard deviation per unit time is calculated from the load value of the charging device (S204). Specifically, the chargeable / dischargeable power range, with the contracted power as the upper limit, is ranked according to reliability based on the load value of the charging device, and a model is constructed by machine learning based on accumulated past data. The standard deviation per unit time is calculated based on the model and external conditions such as weather.

[0128] Then, a required adjustment amount is set for each charging device based on the calculated predicted value and the rank of reliability based on the standard deviation (S205). In setting this required adjustment amount, the amount of power accumulated based on the length of time during which the same power consumption continues is defined by varying each power consumption, time period, and time length. An optimal amount of power consumption, time period, and time length are calculated based on the predicted power consumption and reliability for each unit measurement period included in the defined time period and time length, and an amount of power exceeding the optimal amount of power consumption is set as the required adjustment amount. A charging schedule is generated for each charging device based on this set required adjustment amount (S206). In this charging schedule, the power supply or charging amount is scheduled to form reduction periods in which the power supply amount is intermittently reduced while each charging device is charging, according to the required adjustment amount and its rank of reliability, thereby adjusting the charging speed (charging amount per unit time).

[0129] 7, in a power supply control step (S103), power supply control unit 15 controls power supply to charging device 43 or charging of EV 7 according to the charging schedule generated based on the predicted value calculated in the demand prediction step. In this power supply control step, power supply control unit 15 controls the power supply or the charging amount based on the calculated predicted value so as to form reduction periods in which the amount of power supply is intermittently reduced while charging is being performed, thereby adjusting the charging speed (amount of charging per unit time).

[0130] In step S103, distribution / power supply device control unit 22 refers to the available power supply amount, which is the amount of power that can be supplied by EV 7 under the current circumstances. Specifically, distribution / power supply device control unit 22 refers to the current state of charge of power supply source 3 and the amount of power that can be supplied from power supply source 3.

[0131] Thereafter, while power feeding or charging is being performed in this manner, the charging results for each charging device are recorded as performance information (S104). Specifically, distribution and power supply device control unit 22 starts charging of the target vehicle. In more detail, distribution and power supply device control unit 22 distributes AC power from distribution and power supply device 2 to the target charging device used to charge the target vehicle, and power is supplied from the target charging device to the target vehicle. At this time, distribution and power supply device control unit 22 sends a charging start command to the charging device control unit 43b of the target charging device. Based on the reception of the charging start command by the charging device communication unit 43d, the charging device control unit 43b of the target charging device switches the power feeding switch 43a of the target charging device from the OFF state to the ON state. As a result, AC power from distribution and power supply device 2 is supplied to the target vehicle.

[0132] The charging device control unit 43b of the target charging device controls the charging device notification unit 43c of the target charging device to issue a notification that charging is in progress when the power supply switch 43a of the target charging device is switched from OFF to ON. On the other hand, when the amount of available power supply is equal to or less than the battery capacity of the target vehicle, the distribution and power supply device control unit 22 executes processing corresponding to not charging. Specifically, the distribution and power supply device control unit 22 controls the distribution and power supply device notification unit 26 to issue a charging impossible notification, which is a notification that charging is impossible. Furthermore, the distribution and power supply device control unit 22 uses the distribution and power supply device communication unit 23 to send a charging impossible notification to the charging device control unit 43b of the target charging device.

[0133] The charging device control unit 43b of the target charging device maintains the power supply switch 43a of the target charging device in the OFF state based on the reception of the charging impossible notification by the charging device communication unit 43d, and controls the charging device notification unit 43c of the target charging device to notify the charging impossible. Then, the distribution / power supply device control unit 22 executes a distribution stop process to stop the power supply possible distribution using the wireless communication unit 25.

[0134] When charging of the target vehicle begins, the charging device control unit 43b of the target charging device periodically determines whether a predetermined charging termination condition is met. The charging termination condition can be any condition, but could be, for example, the target power storage device 71 of the target vehicle reaching a fully charged state, or, in a configuration where the charging device 43 is equipped with a charging stop button, the charging device control unit 43b of the target charging device switches the power supply switch 43a of the target charging device from ON to OFF based on the fact that the charging termination condition is met. This terminates charging of the EV 7 that is the charging target.

[0135] Here, distribution / power supply device control unit 22 executes a charging end response process based on the completion of charging of the EV 7 that is the charging target. This charging end response process will be described in detail below.

[0136] First, in step S301, distribution / power supply device control unit 22 determines the amount of power used to charge EV 7, the EV to be charged this time. The amount of power used can be determined in any manner. For example, in a configuration where a current sensor is provided to detect the current flowing through target power storage device 71 of EV 7, distribution / power supply device control unit 22 can calculate the amount of power used from the detection results of the current sensor. Distribution / power supply device control unit 22 then updates the amount of available power supply. Distribution / power supply device control unit 22 determines the new amount of available power supply by subtracting the amount of power used from the available power supply before the update.

[0137] Next, distribution / power supply device control unit 22 updates the charging history, which is a record of charging of EVs 7. The charging history includes, for example, information on the amount of power used for each EV 7 that was charged. That is, distribution / power supply device control unit 22 stores the amount of power used to charge an EV 7 each time the EV 7 is charged.

[0138] (Power Supply Management Program) The power supply management system and power supply management method according to the above-described embodiment and modified examples can be realized by executing a power supply management program written in a predetermined language on a computer. That is, by installing the power supply management program on a dedicated device such as a server device, a smartphone, a tablet PC, or an in-vehicle terminal, or on an IC chip and executing it on the CPU of such a device, a system having the above-described functions can be easily constructed. This program can be distributed, for example, via a communication line, or transferred as a packaged application that runs on a standalone computer.

[0139] Such a program can be recorded on a recording medium readable by a personal computer, such as a magnetic recording medium such as a flexible disk or cassette tape, an optical disk such as a CD-ROM or DVD-ROM, a USB memory or a memory card, or any of a variety of other recording media.

[0140] (Example of change) The above-described embodiment is merely an example of the present invention, and therefore the present invention is not limited to the above-described embodiment, and various modifications can be made depending on the design, etc., as long as they do not deviate from the technical concept of the present invention.

[0141] In this embodiment, prediction is performed based on the at-home flag or the at-home probability (probability). Because the at-home flag has two states, 1 and 2, and is complicated, the SOE ratio (total SOE ÷ maximum SOE) is used to calculate / predict the available amount instead of the at-home flag.

[0142] Furthermore, by using machine learning Available supply volume = predicted available volume {total of individual home demand, total of individual home charger specifications}, SOE ratio (SOC) prediction value, SOE data for individual EVs (for correction) In this case, the possible amount may be calculated by adding up the values ​​calculated from the actual results of each individual home / EV.

[0143] (Actions and Effects) As described above, according to this embodiment, the EV charging system monitors the plug connection status and power supply status in addition to vehicle location information such as the "at-home flag," so that it can accurately predict the available capacity (or remaining battery charge) and more reliably issue EV discharge instructions, thereby enabling effective EV resource control. For example, this can be effectively used to mitigate the impact of increased power demand due to the widespread use of EVs, alleviate grid congestion through EV control, and perform DR control.

[0144] More specifically, in this embodiment, in the charging management of electric vehicles (EVs), each charging device detects the connection status with the vehicle, records the charging time, required time, and amount of power used, and also uses an "at home flag" and an "out of home flag" based on location information. This makes it possible to accurately grasp the current location and charging status of the vehicle in real time, and to perform detailed analysis of the usage status and excessive usage of the charging device.

[0145] Furthermore, according to this embodiment, by dividing EVs into groups and controlling them in groups based on flag information such as return (home / commute) and outing status, peak power demand can be suppressed and the burden on the power supply system can be reduced. For example, an efficient charging plan can be realized by scheduling charging of out-of-home vehicles during low-load hours after returning home, and charging of vehicles at home or commuting during peak renewable energy hours. As shown in Figure 6(a), prediction errors are large for changes in individual battery remaining capacity. However, by combining SOE (State Of Energy: remote measurement and control of remaining battery capacity) through group control, this is smoothed out as shown in Figure 6(b), improving prediction accuracy.

[0146] This will enable peak-off of power demand and optimization of renewable energy use, reducing charging costs, which will lead to lower charging costs for consumers and reduce power system operating costs for energy suppliers. Furthermore, smoothing out power demand through group control will ensure stable operation of the power system. In particular, this will enable us to respond to supply fluctuations that accompany the expansion of renewable energy adoption, and we can also expect to reduce environmental impact through the effective use of renewable energy.

[0147] Furthermore, this embodiment of the system detects excessive usage and issues an alert when the duration exceeds a predetermined threshold, promoting efficient use of charging spots and ensuring fair access for all users while preventing overloading of the charging infrastructure. Furthermore, the actual demand forecasting unit performs analysis to predict the amount of power required for each charging device and the time periods when charging is possible. Based on this information, the power supply control unit optimizes power supply to charging devices and charging of vehicles. This contributes to improving the stability of the power supply by distributing the load on the power grid and avoiding peak times.

[0148] Furthermore, in this embodiment, by utilizing the charging device map information, the location and charging capacity of the charging device become clear, and based on this, precise matching of charging demand and supply becomes possible. Depending on whether the vehicle is at the return location or out, the remaining storage capacity and charging demand can be predicted in different ways, which makes it possible to execute EV charging plans more flexibly and efficiently.

[0149] As a result, according to this embodiment, by optimizing the EV charging process and effectively distributing the load on the power grid, it is possible to improve the stability of the power grid while also enhancing the quality of service for EV users, which is an effective measure against increased electricity demand and grid congestion.

[0150] The present embodiment is not limited to the above-described embodiments, and the components can be modified and embodied in practice without departing from the spirit of the invention. Furthermore, various inventions can be created by appropriately combining the multiple components disclosed in the above-described embodiments. For example, some components may be omitted from all the components shown in the embodiments. [Explanation of symbols]

[0151] 1...Power management device 2...Distribution and power supply equipment 3…Power supply source 4. User system 4a...User's home 4b…Charging station 4c…Business office 7...EV 8...Intermediary server 10. Communication Network 11...Communication interface 12...Data acquisition section 13...Database 13a...Charging device map information 14...Control Instruction Schedule Management Department 15...Power supply control unit 16... Actual Demand Forecasting Department 17...Performance Information Analysis Department 17a...Flag information analysis section 18...Information Department 19...Group setting section 21...Power conversion section 22...Distribution power supply control unit 23...Distribution and power supply device communication section 24...Location information acquisition unit 25...Radio communication section 26...Distribution and power supply device notification section 40...Power control terminal 41...Smart meter 42...Storage battery 43...Charging device 43a...Power supply switch 43b...Charger control unit 43c...Charging device notification unit 43d…Charging device communication department 43e...Connection detection unit 43f...Power plug 71...Target storage device 72…Charger 73...Vehicle control unit 74...Target vehicle communication unit 74c...Prediction error calculation section 75...Power outlet 81a...Token Management Database 81a~d...Database 81b...User database 81c...Performance management database 81d...Electricity trading management database 82...Authentication Department 83...Communication interface 84...Token Management Department 84a…Token issuing department 84b...Token cancellation section 84c…Token Transfer Section 85...Electricity Trading Execution Department 85a...Contract data generation unit 85b...Data storage section 86... Performance Data Management Department 86a… Valuation Section 87…Payment Department 191…Divergence trend analysis department 192...Prediction error calculation unit

Claims

1. A power supply group control system that charges a target power storage device mounted on a target vehicle that is a target of power supply, a charging device that charges the target power storage device; a data acquisition unit that records, for each charging device, the time, required time, and amount of power that was used to charge a target vehicle as actual performance information, and also records information including at least the location of each target vehicle as flag information; an actual demand prediction unit that predicts the power required for charging and a time period during which charging is possible for each charging device based on the performance information and flag information; a prediction error calculation unit that compares an actual amount of power supplied by the charging device with the power supply amount predicted by the actual demand prediction unit, and calculates a prediction error of the power generation amount prediction for each charging device; a deviation tendency analysis unit that analyzes a correlation between the power generation information and the prediction error of each of the charging devices and the external information as deviation tendency information; a group setting unit that divides the group of charging devices into a plurality of groups based on deviation tendency information of each of the charging devices; a power supply control unit that controls power supply to the charging devices or charging of the target vehicles on a group-by-group basis based on the prediction by the actual demand prediction unit; A power supply group control system comprising:

2. a connection detection unit for detecting a connection state of the charging device to a charging plug of a target vehicle; a flag information analysis unit that analyzes the usage status of each charging device, including an over-occupation state that is a difference between the duration of the connection state and the duration of the power supply state of the charging device, based on the flag information recorded by the data acquisition unit; and Furthermore, The actual demand forecasting unit forecasts the power required for charging and the time period during which charging is possible for each charging device based on the analysis result by the flag information analysis unit.

2. The power supply group control system according to claim 1.

3. The power supply group control system according to claim 1, further comprising a notification unit that issues an alert when a duration of the excessive occupancy state exceeds a predetermined threshold based on the analysis by the flag information analysis unit.

4. a map information storage unit that stores charging device map information that maps the location information and charging capacity of each charging device; The flag information analysis unit analyzes the usage status by referring to the charging device map information.

2. The power supply group control system according to claim 1.

5. The charging device map information also maps the return location of each target vehicle, the flag information analysis unit assigns a return flag when each target vehicle is located at the return position, and assigns an out-of-town flag when each target vehicle is located at a position other than the return position, and calculates the excessive occupancy state when the out-of-town flag is assigned to the target vehicle by referring to the charging device map information, and analyzes the usage status; The actual demand forecasting unit calculates the remaining amount of stored power of each target vehicle to which an out-of-home flag has been assigned based on the analysis result by the flag information analysis unit, and forecasts the power required for charging and the time period during which charging is possible for each charging device.

5. The power supply group control system according to claim 4.

6. A power supply group control method for charging a target power storage device mounted on a target vehicle to be supplied with power, comprising: a data acquisition step in which a data acquisition unit records, for each charging device that charges the target power storage device, a time, a required time, and an amount of power that was used to charge the target vehicle as actual performance information, and records information including at least a position of each target vehicle as flag information; an actual demand forecasting step in which an actual demand forecasting unit forecasts the power required for charging for each charging device and a time period during which charging is possible based on the performance information and flag information; a deviation trend analysis step in which a deviation trend analysis unit compares an actual power supply amount by the charging device with the power supply amount predicted by the actual demand prediction unit to calculate a prediction error of the power generation amount prediction for each charging device, and a correlation between power generation information of each charging device and the external information, as deviation trend information; a group setting step in which a group setting unit divides the group of charging devices into a plurality of groups based on deviation tendency information of each of the charging devices; a power supply control step in which a power supply control unit controls power supply to the charging devices or charging of the target vehicles on a group-by-group basis based on the prediction by the actual demand prediction unit; A power supply group control method comprising:

7. The method further includes a flag information analysis step in which a flag information analysis unit analyzes the usage status of each charging device, including an over-occupation status that is a difference between the duration of the connection state and the duration of the power supply state, based on the connection state of the target vehicle to the charging plug detected for each charging device and the flag information recorded by the data acquisition unit, In the actual demand forecasting step, the power required for charging and the time period during which charging is possible for each charging device are predicted based on the analysis result by the flag information analysis unit.

7. The power supply group control method according to claim 6.

8. The power supply group control method according to claim 6, further comprising a notification step in which a notification unit issues an alert when the duration of the excessive occupancy state exceeds a predetermined threshold based on the analysis by the flag information analysis step.

9. The flag information analysis unit analyzes the usage status by referring to charging device map information in which location information and charging capacity of each charging device are mapped.

7. The power supply group control method according to claim 6.

10. The charging device map information also maps the return location of each target vehicle, In the flag information analysis step, a return flag is assigned to each target vehicle when the target vehicle is located at the return position, and an out-of-town flag is assigned to each target vehicle when the target vehicle is located at a position other than the return position. Furthermore, by referring to the charging device map information, the excessive occupancy state when the out-of-town flag is assigned to the target vehicle is calculated, and the usage status is analyzed. In the actual demand forecasting step, the remaining amount of stored power of each target vehicle to which an out-of-home flag is assigned is calculated based on the analysis result by the flag information analysis unit, and the power required for charging and the time period during which charging is possible for each charging device are forecast. The power supply group control method according to claim 9 .

11. A power supply group control program for charging a target power storage device mounted on a target vehicle to be supplied with power, the program comprising: a data acquisition unit that records, for each charging device that charges the target power storage device, a time, a required time, and an amount of power that was used to charge the target vehicle as actual performance information, and also records information including at least a position of each target vehicle as flag information; an actual demand prediction unit that predicts the power required for charging and a time period during which charging is possible for each charging device based on the performance information and flag information; a prediction error calculation unit that compares an actual amount of power supplied by the charging device with the power supply amount predicted by the actual demand prediction unit, and calculates a prediction error of the power generation amount prediction for each charging device; a deviation tendency analysis unit that analyzes a correlation between the power generation information and the prediction error of each of the charging devices and the external information as deviation tendency information; a group setting unit that divides the group of charging devices into a plurality of groups based on deviation tendency information of each of the charging devices; a power supply control unit that controls power supply to the charging devices or charging of the target vehicles on a group-by-group basis based on the prediction by the actual demand prediction unit; function as A power supply group control program characterized by:

12. The computer a connection detection unit for detecting a connection state of the charging device to a charging plug of a target vehicle; a flag information analysis unit that analyzes the usage status of each charging device, including an over-occupation state that is the difference between the duration of the connection state and the duration of the power supply state for the charging device, based on the flag information recorded by the data acquisition unit; It further functions as The actual demand forecasting unit forecasts the power required for charging and the time period during which charging is possible for each charging device based on the analysis result by the flag information analysis unit. The power supply group control program according to claim 11 .

13. The power supply group control program according to claim 11, further causing the computer to function as a notification unit that issues an alert when a duration of the excessive occupancy state exceeds a predetermined threshold based on the analysis by the flag information analysis unit.

14. The computer is further configured to function as a map information storage unit that stores charging device map information that maps the location information and charging capacity of each charging device, The flag information analysis unit analyzes the usage status by referring to the charging device map information. The power supply group control program according to claim 11 .

15. The charging device map information also maps the return location of each target vehicle, the flag information analysis unit assigns a return flag when each target vehicle is located at the return position, and assigns an out-of-town flag when each target vehicle is located at a position other than the return position, and calculates the excessive occupancy state when the out-of-town flag is assigned to the target vehicle by referring to the charging device map information, and analyzes the usage status; The actual demand forecasting unit calculates the remaining amount of stored power of each target vehicle to which an out-of-home flag has been assigned based on the analysis result by the flag information analysis unit, and forecasts the power required for charging and the time period during which charging is possible for each charging device. The power supply group control program according to claim 14 .

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