Charging management system and charging management method

Abstract

To predict a future total EV charging amount charged by a charger user, calculate the power upper limit that is able to ensure economic efficiency for a building providing a charging environment, and control a charging amount.SOLUTION: A charging management system having a processor and a storage apparatus. The storage apparatus holds delivery information including delivery plans by electric vehicles, electricity cost information for the electric vehicles, facility information about facilities included in an electric vehicle delivery route, and charger information about the specifications of chargers installed in the facility. The facility information includes a unit price of electricity supplied to the facility, a charging unit price that is a unit price of electricity provided by the charger installed in the facility, and a profit target value from the charger providing electricity. The processor estimates a charging amount by the charger for a predetermined period in the future based on the delivery information, the electricity cost information, and the charger information, and calculates the upper limit of power consumption of the facility in a predetermined time frame including the current time so that the profit target value is secured based on the estimated charging amount and the facility information.SELECTED DRAWING: Figure 1

Description

Technical Field

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[0001] The present invention relates to a charging management system that manages the power demand of a building and the charging amount of electric vehicles, and calculates an appropriate upper limit of power consumption for the building.

Background Art

[0002] As the background art in this technical field, Japanese Patent Application Laid-Open No. 2018-191471 (Patent Document 1) is known. This Patent Document 1 describes that while suppressing the power peak due to rapid charging, a plurality of electric vehicles can be efficiently and rapidly charged at a low cost Charging control method is described.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] According to the technology described in Patent Document , a charging control method for electric vehicles is provided that can efficiently and rapidly charge a plurality of electric vehicles at a low cost while suppressing the power peak due to rapid charging. However, in the technology described in Patent Document , since the contract power corresponding to the power peak is fixed, when the actual charging amount exceeds the assumed total charging amount at the initial design, it is not possible to increase the charging amount of electric vehicles by setting a higher power peak and improve the convenience for electric vehicle users. Conversely, when the actual charging amount is less than the assumed total charging amount, it is not possible to avoid the deterioration of the profitability of the charging service by reducing the power peak.

[0005] This invention has been made in view of the above problems, and aims to provide a system and method for predicting the total future electric vehicle (EV) charging amount of charger users when the power peak is expected to exceed an assumed value, calculating a power limit that ensures economic viability for the building providing the charging environment, and controlling the charging amount of the charger. [Means for solving the problem]

[0006] A representative example of the invention disclosed in this application is as follows: a charging management system comprising a processor and a memory device, wherein the memory device holds delivery information including a delivery plan by an electric vehicle, power consumption information of the electric vehicle, facility information relating to facilities included in the delivery route of the electric vehicle, and charger information relating to the specifications of a charger installed at the facility for charging the electric vehicle, wherein the facility information includes the unit price of the charge paid to the power supplier for the power supplied to the facility, the unit price of the charge received from the power provider for the power provided by the charger installed at the facility to charge the electric vehicle, and a target value of the profit from the charger providing power, wherein the processor estimates the amount of charging by the charger for a predetermined future period based on the delivery information, power consumption information and charger information, and calculates an upper limit on the power consumption of the facility in a predetermined time frame including the current time, based on the estimated amount of charging and the facility information, so as to ensure the target value of the profit. [Effects of the Invention]

[0007] According to one aspect of the present invention, a building owner providing a charging service can improve the convenience of users charging electric vehicles while ensuring the profitability of the service. Other issues, configurations, and effects will be clarified by the following description of the embodiments. [Brief explanation of the drawing]

[0008] [Figure 1] Block diagram showing an example of a charging management system according to Embodiment 1 of the present invention. [Figure 2] This is an explanatory diagram showing an example of the configuration of route delivery data in Embodiment 1 of the present invention. [Figure 3] This is an explanatory diagram showing an example of the configuration of the energy consumption data for Embodiment 1 of the present invention. [Figure 4] This is an explanatory diagram showing an example of the configuration of charger data for Embodiment 1 of the present invention. [Figure 5] This is an explanatory diagram showing an example of the configuration of facility data in Embodiment 1 of the present invention. [Figure 6] This is a flowchart showing the process in the charging management system of Embodiment 1 of the present invention. [Figure 7] This flowchart shows the details of the processing of the power consumption prediction unit in Embodiment 1 of the present invention. [Figure 8] This is an explanatory diagram showing an example of the trend of accumulated power consumption based on power consumption collected from the charger and power meter of Embodiment 1 of the present invention. [Figure 9] This flowchart shows the details of the processing of the total path charge amount estimation unit in Embodiment 1 of the present invention. [Figure 10] This flowchart shows the details of the processing of the power limit calculation unit in Embodiment 1 of the present invention. [Figure 11] This is an explanatory diagram showing an example of a comparison between the predicted power consumption and the power limit in Embodiment 1 of the present invention. [Figure 12] Block diagram showing an example of a charging management system according to Embodiment 2 of the present invention. [Figure 13] This is a flowchart showing the process in the charging management system of Embodiment 3 of the present invention. [Figure 14] This is an explanatory diagram showing an example of the information that the charging management system of Embodiment 3 of the present invention presents to the energy manager. [Modes for carrying out the invention]

[0009] Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. [Examples]

[0010] In this embodiment, an example of a charging management system that can provide a charging service without impairing the economic efficiency of the charging service by receiving a delivery plan from a logistics operator, estimating the future charging amount at the building of the delivery destination, and calculating an appropriate power upper limit value will be described.

[0011] FIG. 1 is a block diagram showing an example of a charging management system 100 according to Embodiment 1 of the present invention.

[0012] The charging management system 100 is connected via a network 400 to a delivery plan system 201 that manages the delivery plans of logistics trucks at a logistics base 200 of a logistics operator, a building 300 where a charger for an electric vehicle 202 is installed, a charger 301, and a power meter 302 that measures the total power consumption of the building 300 where the charger is installed. Note that at least a part of the logistics trucks used by the logistics operator in this embodiment is the electric vehicle 202.

[0013] The charging management system 100 collects the future delivery plan of the logistics operator and the electricity cost of the electric vehicle 202 from the delivery plan system 201, collects the charging amount from the charger 301 to the electric vehicle 202, and collects the total power consumption of the building 300 where the charger is installed from the power meter 302.

[0014] [[ID=Id17]]The route delivery data 104 stores the delivery plan collected from the logistics operator. The electricity cost data 105 stores information regarding the electricity cost of the electric vehicle 202 managed by the logistics base 200. The charger data 106 stores information regarding the specifications of the charger 301 installed in the building 300. The facility data 107 stores information regarding the power contract and charging service of the building 300 where the charger 301 is installed. The logistics base 200 and the building 300 may each be a plurality of operators and a plurality of buildings, respectively. There may be a plurality of chargers 301 in the building 300.

[0015] The charging management system 100 is a computer including a processor 1, a memory 2, a storage device 3, an input / output device 4, and a communication device 5.

[0016] Processor 1 is an arithmetic unit that executes programs stored in memory 2. Note that some of the processing performed by Processor 1 when executing programs may be performed by other arithmetic units (e.g., hardware such as ASICs or FPGAs). Processor 1 operates as a functional unit that provides predetermined functions by executing processing according to the programs of each functional unit. The same applies to other programs. The charging management system 100 is a computer and computer system that includes the functional units realized by Processor 1.

[0017] Memory 2 includes a non-volatile memory element called ROM and a volatile memory element called RAM. ROM stores immutable programs (e.g., BIOS). RAM is a high-speed, volatile memory element such as DRAM (Dynamic Random Access Memory) and temporarily stores programs executed by processor 1 and data used during program execution. For example, a power consumption prediction unit 101, a total path charge amount estimation unit 102, and a power limit calculation unit 103 are loaded as programs into memory 2 and executed by processor 1.

[0018] The storage device 3 is, for example, a high-capacity, non-volatile storage device such as a magnetic storage device (HDD) or flash memory (SSD). The storage device 3 stores data used by the processor 1 when executing a program (for example, route delivery data 104, charger data 106, energy consumption data 105, and facility data 107), and the program that the processor 1 executes. In other words, the program is read from the storage device 3, loaded into memory 2, and executed by the processor 1.

[0019] The power consumption prediction unit 101 receives the charge amount from the charger 301 and the total energy consumption of the building 300 from the power meter 302, and predicts the power consumption of the building 300 within a 30-minute timeframe including the current time. For example, if the current time is 9:10, it predicts the power consumption between 9:00 and 9:30. If the current time is 9:33, it predicts the power consumption between 9:30 and 10:00.

[0020] In this embodiment, a 30-minute time frame is shown as an example of a predetermined time frame, but this predetermined time frame may be a length other than 30 minutes (for example, 10 minutes or 1 hour).

[0021] The total route charge amount estimation unit 102 receives route delivery data and information on the electric vehicle 202's energy consumption from the delivery planning system 201 and estimates the total future charge amount at the building 300 where the charger 301 is installed. If there are multiple logistics bases 200 and multiple delivery planning systems 201, the total route charge amount estimation unit 102 receives route delivery data and information on the electric vehicle 202's energy consumption from each of them. If there are multiple buildings 300, the total route charge amount estimation unit 102 estimates the total charge amount from the chargers installed at each building.

[0022] The power limit calculation unit 103 receives the total future charge amount at the building 300 where the charger 301 is installed from the total path charge amount estimation unit 102, receives the charge amount of the electric vehicle 202 from the charger 301, and receives the power demand from the power meter 302 of the building 300 where the charger 301 is installed, and calculates the power limit value for the building 300 that can ensure the economic viability of the charging service. If there are multiple buildings 300, the power limit calculation unit 103 calculates the power limit value for each building.

[0023] The charging management system 100 may have input / output devices 4 as input and output interfaces. The input interface is an interface to which input devices such as a keyboard and a mouse (not shown) are connected and to which input is received from the operator. The output interface is an interface to which output devices such as a display device or a printer (not shown) are connected and to which the program execution results are output in a format that can be viewed by the operator. In addition, other devices connected to the charging management system 100 via the network 400 may provide input / output devices.

[0024] The program executed by processor 1 is provided to the charge management system 100 via removable media (e.g., CD-ROM or flash memory) or network 400, and stored in a non-volatile storage device 3, which is a non-temporary storage medium. For this reason, the charge management system 100 should have an interface for reading data from the removable media.

[0025] The charging management system 100 is a computer system that operates on a single physical computer or on multiple computers configured logically or physically, and may operate on a virtual computer built on multiple physical computer resources. For example, the subprograms constituting the total path charge amount estimation unit 102 may each operate on separate physical or logical computers, or multiple subprograms may be combined and operate on a single physical or logical computer.

[0026] Figure 2 is an explanatory diagram showing an example of the configuration of route delivery data 104 in Embodiment 1 of the present invention.

[0027] Route delivery data 104 includes the route name 1031, departure location 1032, departure time 1033, arrival location 1034, arrival time 1035, and distance traveled 1036 in a single record. Route delivery data 104 stores data representing the delivery route collected from the delivery planning system 201.

[0028] Route name 1031 1032 is a route identifier. 1032 is an identifier representing the departure location of the logistics truck. 1033 is the time of departure from 1032. 1034 is an identifier representing the arrival location of the logistics truck. 1035 is the time of arrival at 1034. 1036 is the distance traveled by the logistics truck from 1032 to 1034.

[0029] For example, according to the first four records in Figure 2, a logistics truck traveling on Route A first departs from its own base A at 9:00, travels 15 km, and arrives at customer building B at 10:00. After staying at customer building B for 15 minutes, the logistics truck departs customer building B at 10:15, travels 20 km, and arrives at customer building C at 12:00. After staying at customer building C for 30 minutes, the logistics truck departs customer building C at 12:30, travels 10 km, and arrives at the distribution center at 13:00. After staying at the distribution center for 60 minutes, the logistics truck departs the distribution center at 14:00, travels 25 km, and arrives back at its own base A at 16:00. In other words, Route A is a route that departs from the home base A at 9:00, travels through customer building B, customer building C, and the distribution center, and returns to the home base A at 16:00.

[0030] Figure 3 is an explanatory diagram showing an example of the configuration of the energy consumption data 105 of Embodiment 1 of the present invention.

[0031] The fuel consumption data 105 contains the electric vehicle ID 1041 and the fuel consumption 1042 in a single record. The fuel consumption data 105 stores data representing the fuel consumption of electric vehicle 202 running on the delivery route.

[0032] For example, the first record in Figure 3 shows that the energy consumption of electric vehicle 202, identified as "EV Truck A" among the logistics trucks, is 1.9 km / kWh (i.e., electric vehicle 202 travels 1.9 km per 1 kWh of electricity consumed).

[0033] Figure 4 is an explanatory diagram showing an example configuration of charger data 106 of Embodiment 1 of the present invention.

[0034] Charger data 106 contains the charger ID 1051, charger output 1052, and charger installation location 1053 in a single record. Charger data 106 stores data representing the charger's rated output value, the charger's installation location, and the contracted power of the building where it is installed. Charger ID 1051 is the identifier of the charger. Charger output 1052 is the rated output value of the installed charger. Charger installation location 1053 is an identifier representing the location where the charger is installed.

[0035] In the example in Figure 4, charger A is installed in customer building C and has a rated output of 100kW. Charger B is installed at the company's own site and has a rated output of 6kW.

[0036] Figure 5 is an explanatory diagram showing an example of the configuration of facility data 107 in Embodiment 1 of the present invention.

[0037] Facility data 107 includes facility ID 1061, contracted power 1062, CO2 intensity 1063, charging unit price 1064, contracted power unit price 1065, usage-based unit price 1066, and target profit 1067 in a single record. Facility data 107 stores information about the facility's (e.g., building 300) power contract, the target profit for charger installation, and data about the charging unit price for charger users.

[0038] Facility ID 1061 is the identifier for the facility. Contracted power 1062 is the upper limit of power consumption that the facility has contracted with the power company. CO2 intensity 1063 is a conversion factor for calculating CO2 emissions derived from the electricity consumed by the facility. Charging unit price 1064 is the charging unit price charged to users who use the charger 301 installed at the facility. Contracted power unit price 1065 is the unit price per kW of power consumption that the facility has contracted with the power company. Usage-based unit price 1066 is the unit price per kWh of power consumption that the facility has contracted with the power company. Target profit 1067 is the target profit that can be obtained from the charger 301 installed at the facility.

[0039] Figure 6 is a flowchart showing the process in the charging management system 100 of Embodiment 1 of the present invention. The charging management system 100 periodically executes the process shown in Figure 6 and manages the amount of charge from the charger 301.

[0040] In step S101, the power consumption prediction unit 101 predicts the power consumption of building 300 for a 30-minute window including the current time. For example, if the current time is 9:10, it predicts the power consumption between 9:00 and 9:30. If the current time is 9:33, it predicts the power consumption between 9:30 and 10:00. The power consumption predicted here is the sum of the power consumption of building 300 itself (i.e., the facility only) and the power consumption for charging by the charger 301 installed in building 300 for that 30-minute window.

[0041] In step S102, the contracted power 1062 of the facility data 107 is referenced to determine whether the amount of electricity consumed in a 30-minute window predicted in step S101 exceeds the contracted power of the building 300 where the charger 301 is installed. At this time, the amount of electricity consumed in a 30-minute window (kWh) is converted to electricity consumed (kW) for comparison with the contracted power. For example, if the amount of electricity consumed in a 30-minute window predicted in step S101 is 10kWh, then 10kWh / (30 minutes / 60 minutes) = 20kW is compared with the contracted power. If it exceeds the contracted power, the process proceeds to step S103. If it does not exceed the contracted power, the process ends. If the predicted amount of electricity consumed does not exceed the contracted power, the basic electricity charge will not increase, and therefore the expected balance will not be affected. If it does exceed the contracted power, the contracted electricity charge will increase, which may worsen the profitability of the charging service. Therefore, in order to secure the target profit, it is necessary to calculate an acceptable upper limit and control the amount of charging within the range that does not exceed the upper limit.

[0042] In step S103, the total route charge amount estimation unit 102 estimates the total charge amount from the chargers 301 installed in building 300. Specifically, the total route charge amount estimation unit 102 uses route delivery data 104 collected from the delivery planning system 201 to estimate the amount of charge to be charged in building 300 based on future delivery plans. For example, the total route charge amount estimation unit 102 estimates the total charge amount up to several months in advance.

[0043] In step S104, the power limit calculation unit 103 calculates the power limit value using the facility data 107 which stores the total charge amount estimated in step S103 and information regarding the power contract of building 300.

[0044] In step S105, it is determined whether the predicted power consumption of the facility (building 300) only, excluding the power consumption of charger 301 from the current time onward, exceeds the power limit. If it does, the process proceeds to step S106. If it does not exceed the limit, the process ends.

[0045] In step S106, the power supply from the charger 301 is stopped. That is, the charging management system 100 stops the power supply from the charger 301 so that the power consumption in the building 300 does not exceed the power limit calculated in step S104.

[0046] In step S107, if the power consumption during the 30-minute time slot exceeds the contracted power when the 30-minute time slot ends, the charging management system 100 updates the value of the contracted power 1062 by setting the power consumption to the new contracted power.

[0047] Figure 7 is a flowchart detailing the processing of the power consumption prediction unit 101 in Embodiment 1 of the present invention. The power consumption prediction unit 101 takes the charging power from the charger 301 and the total power consumption of the building from the power meter 302 as input and outputs a predicted value of the power consumption for a 30-minute period.

[0048] In step S1011, the power consumption prediction unit 101 obtains the current charging power value from the charger 301 and the power consumption value of the building 300 from the power meter 302.

[0049] In step S1012, the power consumption prediction unit 101 calculates the cumulative power consumption at the current time within a 30-minute timeframe.

[0050] In step S1013, the power consumption prediction unit 101 estimates the cumulative power consumption at the end of the 30-minute period based on the progress of the cumulative power consumption from the start of the 30-minute period to the present time, and the charging power of the charger 301. Here, the power consumption prediction unit 101 estimates the power consumption including the charging by the charger 301, and the power consumption of the facility only, excluding the charging by the charger 301.

[0051] Figure 8 is an explanatory diagram showing an example of the trend of accumulated power consumption based on power consumption collected from the charger 301 and power meter 302 of Embodiment 1 of the present invention.

[0052] The power consumption prediction unit 101 periodically executes the process shown in Figure 7 to manage the cumulative power consumption at the current time and its trend within a 30-minute timeframe, as shown in Figure 8, and calculates a predicted value for the final cumulative power consumption within the 30-minute timeframe. The example in Figure 8 shows the cumulative power consumption situation for a 30-minute timeframe from 9:00 to 9:30. Here, the power consumption prediction unit 101 estimates both the power consumption including the charger and the power consumption of the facility only, excluding the charger, for the time from the current time within the 30-minute timeframe onward.

[0053] Figure 9 is a flowchart detailing the processing of the total path charge amount estimation unit 102 in Embodiment 1 of the present invention. The total path charge amount estimation unit 102 calculates the future total charge amount of the charger 301 installed in building 300.

[0054] In step S1021, the total route charge amount estimation unit 102 acquires route delivery data 104, charger data 106, and energy consumption data 105.

[0055] In step S1022, the total route charging amount estimation unit 102 assigns EVs to travel along each route based on data such as driving distance, energy consumption, and CO2 intensity, in order to minimize the amount of charging or CO2 emissions, and also calculates the amount of charging for each charger 301.

[0056] In step S1023, the total path charge amount estimation unit 102 calculates the total charge amount of the chargers 301 installed in the relevant building 300.

[0057] Figure 10 is a flowchart detailing the processing of the power limit calculation unit 103 in Embodiment 1 of the present invention. The power limit calculation unit 103 uses the charge amount x estimated by the total path charge amount estimation unit 102 to calculate the excess limit when the contracted power is exceeded.

[0058] In step S1031, the power limit calculation unit 103 acquires facility data 107.

[0059] In step S1032, the power limit calculation unit 103 uses the future year's charging amount x estimated by the total path charging amount estimation unit 102, the value J of the metered unit price 1066 obtained from the facility data 107, the value C of the charging unit price 1064, the value R of the annual target profit 1067, and the value K of the contracted power unit price 1065 to calculate the contracted power excess limit a using formula (1). If charging continues beyond the current time and the accumulated power amount for the 30-minute window exceeds the accumulated power amount based on the current contracted power, and the excess amount is a or more, the revenue from the charging service will fall below the target profit 1067.

[0060]

number

[0061] The above calculation assumes that the contracted power unit price K is determined based on the maximum monthly power consumption over the past year. That is, if the power consumption in a given month exceeds the contracted power value of 1062 at that time, the contracted power value of 1062 will be raised to the value based on the power consumption of that month for the following year, even if the actual power consumption is lower, and the amount paid to the power company based on the contracted power unit price K will also increase. If there is another month with higher power consumption during that year, the contracted power value of 1062 for the following year will be raised to match the power consumption at that time. Note that one year is just one example of a predetermined period, and a period other than one year may be set by contract with the power company.

[0062] Even if a month's power consumption exceeds the contracted power at that time, resulting in higher payments to the power company for the following year, if the amount of electricity charged x over the following year is large, the profit based on the difference between the charging unit price C and the usage unit price J will increase, potentially allowing the target profit R to be secured. The above formula (1) is used to calculate the upper limit of the excess cumulative electricity amount that can secure the target profit R, based on the estimated future amount of electricity charged x at the present time. The larger the estimated future amount of electricity charged x, and the larger the difference between the charging unit price C and the usage unit price J, the higher the upper limit of the excess cumulative electricity amount.

[0063] Figure 11 is an explanatory diagram showing an example of a comparison between the predicted power consumption and the power limit in Embodiment 1 of the present invention.

[0064] Specifically, Figure 11 shows an example of a case where the power consumption forecast exceeds the power limit in step S105 within a 30-minute timeframe. That is, it shows a case where the power consumption forecast for the facility alone, excluding power consumption by charger 301 from the current time onward, reaches the power limit. In other words, this forecast result indicates that if charging by charger 301 continues from the current time onward, the power consumption for the 30-minute timeframe will exceed the power limit, but if charging by charger 301 is stopped at the current time, the power consumption for the 30-minute timeframe will not exceed the power limit even if power consumption by the facility continues during the remaining time. By anticipating the power consumption of the facility that cannot stop consuming power and determining whether the power limit will be exceeded, and stopping charging by charger 301, it is possible to prevent the final power consumption from exceeding the power limit (i.e., current contracted power + a), thereby preventing a deterioration in the profitability of the charging service.

[0065] Conversely, if the power consumption forecast, including that of charger 301, does not exceed the power limit (current contracted power + a), then charging beyond the contracted power will not impair the profitability of the charging service. Users of electric vehicles 202 using the charging service will be able to charge their vehicles as needed for driving, even if they exceed their contracted power, as long as they do not exceed the power limit required to ensure profitability, thus improving the convenience of electric vehicles 202. In order to maximize the convenience of electric vehicles 202 while ensuring a certain level of profitability, it is desirable to stop charging by charger 301 at the latest time possible, provided that the power consumption forecast using only the facility, excluding power consumption by charger 301 from the current time onward, does not exceed the power limit. [Examples]

[0066] Example 2 describes a case where an energy management system is installed in building 300. In Example 2, a configuration different from that of Example 1 described above will be explained, and the explanation of the same configuration as in Example 1 will be omitted.

[0067] Figure 12 is a block diagram showing an example of the charging management system 100 according to Embodiment 2 of the present invention.

[0068] As shown in Figure 12, if the energy management system 303 is installed in the building 300, the charging management system 100 collects data on the power consumption of the charger 301 and the entire building 300 from the charger 301 and the power meter 302 via the energy management system 303.

[0069] Furthermore, if the energy management system 303 has the same functionality as the power consumption prediction unit 101, the charging management system 100 may obtain a predicted value of power consumption from the energy management system 303. [Examples]

[0070] Example 3 describes a case where the building's energy manager is presented with the impact on revenue of continuing charging by the charger 301 beyond the current time, and the decision to stop power supply by the charger 301 is left to the energy manager. In Example 3, a configuration different from that of Example 1 described above will be explained, and the explanation of the same configuration as in Example 1 will be omitted.

[0071] Figure 13 is a flowchart showing the processing in the charging management system 100 of Embodiment 3 of the present invention. In this process, the energy manager is presented with the impact on revenue of continuing to charge with the charger 301 beyond the current time, specifically whether the amount of power consumed will exceed the power limit if charging with the charger 301 beyond the current time is continued, and whether the target profit will be secured.

[0072] Steps S101 to S107 in Figure 13 are the same as those shown in Figure 6, so their explanation is omitted. In the process in Figure 13, if in step S105 it is determined that the predicted power consumption of the facility (building 300) only, excluding the power consumption of charger 301 from the current time onward, exceeds the power limit, then step S108 is executed. In step S108, the charging management system 100 presents the energy manager with the predicted power consumption if charging continues and the corresponding change in revenue.

[0073] The energy manager decides whether or not to stop the power supply from charger 301 based on changes in revenue. For example, the energy manager may decide not to stop the power supply from charger 301 as long as it is determined from changes in revenue that stopping the power supply from charger 301 from the current time onward will ensure the target profit, or decide to stop the power supply from charger 301 if it is determined that the target profit cannot be ensured even if the power supply from charger 301 from the current time onward is stopped (or before such a determination is made). In order to maximize the convenience of the electric vehicle 202 while ensuring a predetermined profitability, it is desirable to decide to stop the power supply from charger 301 at the latest time possible, provided that the predicted power consumption of the facility alone, excluding power consumption from charger 301 from the current time onward, does not exceed the power limit.

[0074] If the energy manager decides to stop supplying power from the charger 301, step S106 is executed. On the other hand, if the energy manager decides not to stop supplying power from the charger 301, the process ends.

[0075] The revenue generated by continuing charging is calculated using formula (2). b is the value obtained by subtracting the current contracted power from the predicted power consumption, which includes the power consumption of charger 301.

[0076]

number

[0077] Figure 14 is an explanatory diagram showing an example of information that the charging management system 100 of Embodiment 3 of the present invention presents to the energy manager.

[0078] The charging management system 100 presents energy managers with the expected revenue if charging is stopped and the expected revenue if charging is continued, prompting them to decide whether to continue or stop charging. By presenting energy managers with quantitative changes in revenue, it becomes possible to make flexible decisions about continuing charging.

[0079] The system of the embodiment of the present invention may be configured as follows, for example.

[0080] (1) A charging management system (e.g., charging management system 100) comprising a processor (e.g., processor 1) and a storage device (e.g., memory 2 and storage device 3), wherein the storage device holds delivery information (e.g., route delivery data 104) including a delivery plan by an electric vehicle (e.g., electric vehicle 202), electric vehicle energy consumption information (e.g., energy consumption data 105), facility information (e.g., facility data 107) relating to facilities (e.g., building 300) included in the electric vehicle's delivery route, and charger information (e.g., charger data 106) relating to the specifications of a charger (e.g., charger 301) for charging electric vehicles installed at the facility, and the facility information includes the unit price of the charge paid to the power supplier for the power supplied to the facility ( The processor includes, for example, a contracted power unit price (1065 and a usage-based unit price (1066)), a charging unit price (e.g., a charging unit price 1064) which is the unit price of the charger installed at the facility that the charger receives from the recipient of the charging power for the power it provides to charge electric vehicles, and a target value of the profit that the charger will make from providing power (e.g., a target profit 1067). Based on the delivery information, energy consumption information and charger information, the processor estimates the amount of charging by the charger over a predetermined period in the future (e.g., step S103), and based on the estimated amount of charging and facility information, calculates an upper limit on the amount of power consumed by the facility in a predetermined time frame including the current time (e.g., cumulative power consumption in a 30-minute frame) so as to ensure that the target value of the profit is secured (e.g., step S104).

[0081] This allows building owners providing charging services to ensure the profitability of their services while improving convenience for users charging electric vehicles.

[0082] (2) In (1) above, the facility information includes the contracted power with the power supplier to the facility (e.g., contracted power 1062), and the processor predicts the power consumption of the facility, including the power consumption of the charger, within a predetermined time frame (e.g., step S101), and if the power consumption based on the predicted power consumption exceeds the contracted power (e.g., if Yes in step S102), it estimates the amount of charge and calculates the upper limit of the power consumption.

[0083] This allows building owners providing charging services to ensure the profitability of their services while improving convenience for users charging electric vehicles, even if they anticipate exceeding their contracted power capacity.

[0084] (3) In (2) above, the processor controls the charger to stop charging if it determines that the amount of power consumed by the facility within a predetermined time frame exceeds the upper limit, even if charging by the charger from the current time onward is stopped (for example, step S106 in step S105 in Figure 5 if Yes).

[0085] This will help prevent a decline in the profitability of the service.

[0086] (4) In (2) above, the processor calculates and outputs the amount of benefit that the charger will provide if charging by the charger is stopped and if it is not stopped from the current time onward (for example, step S108 in Figure 13), and controls the charger to stop charging when information is input to instruct the charger to stop charging (for example, step S106 in the case of "stop" in step S108 in Figure 13).

[0087] This allows for flexible decisions regarding the continuation of charging while providing information on the profitability of the service.

[0088] (5) In (2) above, the unit price of the charge paid to the power supplier for the power supplied to the facility includes a variable rate (e.g., variable rate 1066) for determining the charge according to the amount of power consumed by the facility and a contracted power rate (e.g., contracted power rate 1065) for determining the charge according to the contracted power, and the processor calculates the amount of profit the charger makes from providing power such that the larger the value obtained by multiplying the difference between the variable rate and the charging rate by the estimated amount of charge, the greater the profit, and the larger the contracted power rate, the smaller the profit (e.g., formula (1)).

[0089] This allows for the appropriate calculation of the upper limit on power consumption that does not impair the profitability of the service.

[0090] It should be noted that the present invention is not limited to the embodiments described above, and various modifications are included. For example, the embodiments described above are explained in detail for a better understanding of the present invention, and are not necessarily limited to those having all of the configurations described. Furthermore, it is possible to replace parts of the configuration of one embodiment with the configuration of another embodiment, and it is possible to add configurations from other embodiments to the configuration of one embodiment. In addition, it is possible to add, delete, or replace parts of the configuration of each embodiment with other configurations.

[0091] Furthermore, each of the above configurations, functions, processing units, and processing means may be implemented in hardware, either partially or entirely, by designing them as integrated circuits, for example. Alternatively, each of the above configurations and functions may be implemented in software by a processor interpreting and executing programs that implement each function. Information such as programs, tables, and files that implement each function can be stored in storage devices such as non-volatile semiconductor memory, hard disk drives, and SSDs (Solid State Drives), or in computer-readable non-temporary data storage media such as IC cards, SD cards, and DVDs.

[0092] Furthermore, the control lines and information lines shown are those deemed necessary for explanation purposes, and do not necessarily represent all control lines and information lines in the actual product. In practice, it can be assumed that almost all components are interconnected. [Explanation of Symbols]

[0093] 100 Charging Management System 101 Power Consumption Prediction Unit 102 Total path charge amount estimation unit 103 Power Limit Calculation Unit 104 Route Delivery Data 105 Fuel Consumption Data 106 Charger Data 107 Facility Data 200 logistics bases 201 Delivery Planning System 202 Electric vehicle 300 Building 301 charger 302 Electricity meter 303 Energy Management System

Claims

1. It is a charging management system, It has a processor and a memory device, The storage device holds delivery information including a delivery plan by electric vehicle, power consumption information of the electric vehicle, facility information relating to facilities included in the delivery route of the electric vehicle, and charger information relating to the specifications of chargers installed at the facilities for charging the electric vehicle. The facility information includes the unit price of the fee paid to the power supplier for the power supplied to the facility, the charging unit price which is the unit price of the fee received from the recipient of the charging power for the power that the charger installed at the facility provides to charge the electric vehicle, and the target value of the profit from the power provided by the charger. The aforementioned processor, Based on the delivery information, the power consumption information, and the charger information, the amount of charge generated by the charger over a predetermined period in the future is estimated. A charging management system characterized by calculating an upper limit on the power consumption of the facility within a predetermined time frame, including the current time, based on the estimated charging amount and the facility information, so as to ensure the target value of the profit.

2. A charging management system according to claim 1, The facility information includes the contracted power with the power supplier to the facility, The aforementioned processor, The power consumption of the facility, including the power consumption of the charger, is predicted within the predetermined time frame. A charging management system characterized by performing the estimation of the charging amount and the calculation of the upper limit of the power consumption when the power consumption based on the predicted power consumption exceeds the contracted power.

3. A charging management system according to claim 2, A charging management system characterized in that the processor controls the charger to stop charging if it determines that the power consumption of the facility within the predetermined time frame exceeds the upper limit, even if charging by the charger is stopped from the current time onward.

4. A charging management system according to claim 2, The processor calculates and outputs the amount of profit the charger would generate if it stopped charging from the current time onward, and if it did not stop charging, in each case. A charging management system characterized by controlling the charger to stop charging when information is input instructing it to stop charging by the charger.

5. A charging management system according to claim 2, The unit price of the charge payable to the power supplier for the electricity supplied to the facility includes a metered unit price for determining the charge according to the amount of electricity consumed by the facility, and a contracted power unit price for determining the charge according to the contracted power. A charging management system characterized in that the processor calculates the amount of profit the charger makes from providing power such that the larger the value obtained by multiplying the difference between the usage-based unit price and the charging unit price by the estimated amount of charge, the greater the profit, and the larger the contracted power unit price, the smaller the profit.

6. A charging management method performed by a charging management system, The charging management system comprises a processor and a storage device. The storage device holds delivery information including a delivery plan by electric vehicle, power consumption information of the electric vehicle, facility information relating to facilities included in the delivery route of the electric vehicle, and charger information relating to the specifications of chargers installed at the facilities for charging the electric vehicle. The facility information includes the unit price of the fee paid to the power supplier for the power supplied to the facility, the charging unit price which is the unit price of the fee received from the recipient of the charging power for the power that the charger installed at the facility provides to charge the electric vehicle, and the target value of the profit from the power provided by the charger. The aforementioned charging management method is, The first step involves the processor estimating the amount of charge the charger will provide over a predetermined period in the future, based on the delivery information, the power consumption information, and the charger information. A charging management method characterized in that the processor calculates an upper limit on the power consumption of the facility in a predetermined time frame including the current time, based on the estimated charge amount and the facility information, so as to ensure the target value of the profit.

7. A charging management method according to claim 6, The facility information includes the contracted power with the power supplier to the facility, The charging management method further includes a step in which the processor predicts the power consumption of the facility, including the power consumption of the charger, within the predetermined time frame. A charging management method characterized in that the processor executes the first and second steps when the power consumption based on the predicted power consumption exceeds the contracted power.

8. A charging management method according to claim 7, A charging management method further comprising a step of controlling the charger to stop charging if the processor determines that the power consumption of the facility within the predetermined time frame exceeds the upper limit, even if the charger stops charging from the current time onward.

9. A charging management method according to claim 7, The procedure for the processor to calculate and output the amount of profit that the charger will generate from providing power, in both cases where charging by the charger stops and where it does not stop, from the current time onward, A charging management method further comprising the steps of: when information is input instructing the charger to stop charging, the processor controls the charger to stop charging.

10. A charging management method according to claim 7, The unit price of the charge payable to the power supplier for the electricity supplied to the facility includes a metered unit price for determining the charge according to the amount of electricity consumed by the facility, and a contracted power unit price for determining the charge according to the contracted power. A charging management method characterized in that, in the second step, the processor calculates the amount of profit the charger makes from providing power such that the larger the value obtained by multiplying the difference between the usage-based unit price and the charging unit price by the estimated amount of charge, the greater the profit, and the larger the contracted power unit price, the smaller the profit.

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