Power management system and power management method

Abstract

To harmonize power supply and demand of a nanogrid with a vehicle equipped with a rechargeable battery.SOLUTION: A power management system that manages power supply and demand in a plurality of nanogrids includes an arithmetic device that executes a predetermined process, and a calculator having a storage device connected to the arithmetic device. The plurality of nanogrids include a power generation device. At least one vehicle is running between the plurality of nanogrids. The power management system includes an input unit that inputs a power supply and demand forecast of each of the plurality of nanogrids and a transportation plan by the vehicle, an optimization calculation unit that creates an operation plan in which at least two values of a power supply value, which is a value related to the power supply and demand in the plurality of nanogrids, and a transportation provision value, which is a value of the service provided by the vehicle, are optimized on the basis of the power supply and demand forecast and the transportation plan, and an output unit that outputs the created operation plan.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a power management system.

Background Art

[0002] Due to the increase in natural energy power generation for suppressing global warming, the increase in energy supply resistant to disasters, the limitation of power grid capacity, etc., the markets for microgrids and nanogrids are growing. On the other hand, since the power generation amount of natural energy varies greatly, a power management technology for maintaining the supply-demand balance in the grid is required.

[0003] In addition, due to the vulnerability of local transportation networks due to population decline, the increase in the number of people who have difficulty in moving and transporting themselves due to aging, the increase in the home stay rate due to the spread of infectious diseases, etc., the demand for more flexible and inexpensive mobility services is increasing.

[0004] As the background art in this technical field, there is the following prior art. In Patent Document 1 (Japanese Patent Application Laid-Open No. 2006-50887), the sensible heat of the exhaust gas of power generation equipment, combustion equipment, or transportation equipment in a virtual area (hereinafter referred to as an energy supply-demand grid) provided with a plurality of energy-consuming devices is recovered as H2 or CO + H2 by reforming DME (dimethyl ether) or CH3OH (methanol), and this H2 or CO + H2 is supplied as fuel for the plurality of energy-consuming devices or as a chemical raw material within the energy supply-demand grid or within another energy supply-demand grid (see Claim 1).

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] In the energy supply method described in the aforementioned Patent Document 1, fuels such as DME and methanol that can be mutually converted with electricity are used as energy circulation media within and between grids. Compared with electricity and sensible heat, energy storage and supply-demand adjustment are made at lower cost, and electricity costs and the amount of carbon dioxide generated are reduced. However, multi-purpose optimization in power utilization including the transportation of people and goods by electric vehicles is not considered. Also, it is considered that electric vehicles will become mainstream in the provision of mobility services, and harmony between the power consumed by electric vehicles and power supply and demand (for example, formulation of an EV operation plan based on power supply prediction) is required. However, the power generation amount of natural energy and the operation plan of mobility include many factors of variation, and it is difficult to provide a service that optimizes power supply and demand and transportation simultaneously. Furthermore, the storage battery mounted on an electric vehicle is expected to assume the power supply function within a microgrid and the power supply-demand adjustment function between microgrids. Furthermore, correction of the EV operation plan when the power supply prediction is off is not considered.

[0007] Therefore, an object of the present invention is to provide a power management system that harmonizes the power supply and demand of a nanogrid by a vehicle equipped with a rechargeable battery.

Means for Solving the Problems

[0008] A typical example of the invention disclosed in the present application is as follows. That is, a power management system that manages power supply and demand in a plurality of nanogrids, which is configured by a computer having an arithmetic unit that executes predetermined processing and a storage device connected to the arithmetic unit. The plurality of nanogrids include power generation devices, at least one vehicle is running between the plurality of nanogrids, and the power management system includes an input unit to which the power supply and demand prediction of each of the plurality of nanogrids and the transportation plan by the vehicle are input, and based on the power supply and demand prediction and the transportation plan, an optimization calculation unit that creates an operation plan that optimizes at least two values, namely, the power supply value that is the value related to the power supply and demand within the plurality of nanogrids and the transportation service value that is the value of the service by the vehicle, and an output unit that outputs the created operation plan. , the optimization calculation unit includes a first optimization calculation unit that creates a tentative operation plan optimized based on the power supply and demand prediction and the transportation plan, and calculates an evaluation index in the created tentative operation plan, and a second optimization calculation unit that creates an operation plan optimized based on the created tentative operation plan, the transportation request, and the correction value of the power supply and demand prediction. It is characterized by the following.

Advantages of the Invention

[0009] According to one aspect of the present invention, the value provided to users can be improved by power utilization and transportation services. Problems, configurations, and effects other than those described above will be clarified by the description of the following embodiments.

Brief Description of the Drawings

[0010]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Modes for Carrying Out the Invention

[0011] FIG. 1 is a diagram showing facilities installed in an area including a nanogrid 10 controlled by a control system 100 according to an embodiment of the present invention. A solid line indicates a moving route of an electric vehicle 30, and a dotted line indicates a communication line for transmitting information.

[0012] A control system 100, which is a power management system, is communicably connected to a plurality of nanogrids 10.

[0013] The nanogrid 10 includes a power source 11 that generates power, a load 12 that consumes power, and a power control device (not shown) that controls the power generation amount and power consumption. The nanogrid 10 may have a storage battery that stores power in order to fill the difference between power supply and demand. The power source 11 is mainly a device that generates power by natural energy such as solar power generation, wind power generation, and geothermal power generation. The load 12 is mechanical equipment that consumes power within the nanogrid 10, public institutions such as hospitals, agricultural machinery, etc. Also, an electric vehicle 30 traveling within the area also consumes power.

[0014] The control system 100 is communicably connected to a plurality of nanogrids 10 and loads 19. The power control devices of the nanogrids 10 and loads 19 send their power supply and demand states and requests for transporting goods and people to the control system 100. The control system 100 sends an instruction to secure surplus power for charging the electric vehicle 30 and sends a transport completion report obtained from the electric vehicle 30 to the nanogrid 10. Also, the control system 100 outputs the calculation result to the administrator and receives inputs such as the selection of the EV operation plan from the administrator.

[0015] In the area including the nanogrid 10, an electric vehicle 30, which is at least one vehicle that runs on electricity, moves between the nanogrids 10 using the charged power. The electric vehicle 30 is a delivery truck, an on-demand bus, a taxi, etc. that transports goods and people within the area. The electric vehicle 30 is equipped with a rechargeable driving battery. In addition, the electric vehicle 30 is equipped with a rechargeable power transmission battery, charges at a nanogrid 10 with a surplus in power supply and demand, discharges at a nanogrid 10 with a tight power supply and demand, and adjusts the power supply and demand between the nanogrids 10. The power transmission battery and the driving battery may be the same battery or different batteries. It is preferable that the electric vehicle 30 is equipped with a battery that can be rapidly charged, but it may also be equipped with a battery that can only be normally charged or a battery whose battery can be easily replaced in a short time.

[0016] The electric vehicle 30 is preferably an electric vehicle that runs on charged electricity, but may also be a vehicle that runs on energy from an internal combustion engine or a fuel cell. In this case, the nanogrid 10 provides the power transported between the nanogrids 10 without providing driving power to the electric vehicle 30. Also, the electric vehicle 30 may not be equipped with a power transmission battery. In this case, the nanogrid 10 does not provide the power transported between the nanogrids 10 to the electric vehicle 30, and adjusts the power supply and demand according to the location where the driving power is provided.

[0017] FIG. 2 is a diagram showing the flow of power and information in the nanogrid 10 controlled by the control system 100 of an embodiment of the present invention. The solid line represents the power transmission and distribution line, the dotted line represents the information flow, and the broken line represents the transportation of power, goods, and people by the electric vehicle 30.

[0018] The nanogrid 10 is generally balanced in power supply and demand within the nanogrid 10 and is self-sufficient in power, but is connected to the power grid 40 so that power can be supplied from the power grid 40 of the power transmission and distribution utility. A switch 15 is provided between the power grid 40 and the nanogrid 10, and when the switch 15 is closed, power can be supplied from the power grid 40 to the nanogrid 10. Note that the nanogrid 10 includes a DC nanogrid that supplies a DC power source and an AC nanogrid that supplies an AC power source. In the DC nanogrid, an inverter 16 that converts the AC power supplied from the power grid 40 into DC power is provided between the power grid 40.

[0019] As described above, the electric vehicle 30 travels between the nanogrids 10 to transport goods and people, and transports power from a nanogrid 10 with a surplus in power supply and demand to a nanogrid 10 with a tight power supply and demand. The electric vehicle 30 is communicably connected to the control system 100, receives instructions such as movement, charging and discharging, and sends reports such as transport start, transport completion, charging start, discharging start, and battery charge level. Examples of instructions to the electric vehicle 30 are as follows. ·stay: Remain stationary at the current location. The power storage of the electric vehicle 30 is not consumed, and during this period, the electric vehicle 30 can function as a battery for the nanogrid 10. ·pickup: Load the people or goods to be transported onto the electric vehicle 30. The power storage of the electric vehicle 30 is not consumed. ·move: Travel towards the destination (e.g., the nanogrid 10 or other destinations). The power storage of the electric vehicle 30 at the next time step decreases by Δmove. ·charge_from_grid: Charge the electric vehicle 30 by Δcharge in the nanogrid 10. Multiple electric vehicles 30 can be charged simultaneously from the same nanogrid 10. The power storage of the electric vehicle 30 after charging increases by Δcharge. ·charge_to_grid: Discharge the electric vehicle 30 by Δcharge to the nanogrid 10. Multiple electric vehicles 30 can discharge to the same nanogrid 10 simultaneously. However, the power storage of the electric vehicle 30 after discharging decreases by Δcharge.

[0020] The load 19 is a facility (e.g., a factory, a household) that consumes power and does not have a power source 11. The load 19 may be equipped with a power control device similar to the nanogrid 10.

[0021] Figure 3 is a diagram showing the physical configuration of the control system 100 of this embodiment.

[0022] The control system 100 of this embodiment is composed of a computer having a processor (CPU) 101, a memory 102, an auxiliary storage device 103, and a communication interface 104.

[0023] The processor 101 executes the program stored in the memory 102. Note that a part of the processing performed by the processor 101 when executing the program may be executed by other arithmetic units (e.g., arithmetic units based on hardware such as FPGA or ASIC).

[0024] Memory 102 includes a ROM which is a non-volatile memory element and a RAM which is a volatile memory element. The ROM stores unchanging programs (such as BIOS). The RAM is a high-speed and volatile memory element such as a DRAM (Dynamic Random Access Memory), and temporarily stores programs executed by the processor 101 and data used during program execution.

[0025] The auxiliary storage device 103 is a large-capacity and non-volatile storage device such as a magnetic storage device (HDD) or a flash memory (SSD), and stores programs executed by the processor 101 and data used during program execution. That is, the program is read from the auxiliary storage device 103, loaded into the memory 102, and executed by the processor 101.

[0026] The communication interface 104 is a network interface device that controls communication with other devices (such as a power control device in the nanogrid 10) according to a predetermined protocol.

[0027] The control system 100 may have an input interface 105 and an output interface 108. The input interface 105 is an interface to which a keyboard 106, a mouse 107, etc. are connected and which receives input from an operator. The output interface 108 is an interface to which a display device 109, a printer, etc. are connected and which outputs the execution result of a program in a form visible to the operator. Note that a terminal connected to the control system 100 via a network may provide the input interface 105 and the output interface 108.

[0028] The program executed by the processor 101 is provided to the control system 100 via a removable medium (such as a CD-ROM or a flash memory) or a network, and is stored in the non-volatile auxiliary storage device 103 which is a non-transitory storage medium. Therefore, the control system 100 preferably has an interface for reading data from the removable medium.

[0029] The control system 100 is a computer system configured physically on one computer or on a plurality of computers configured logically or physically. It may operate with one or more threads on the same computer, or may operate on a virtual computer built on a plurality of physical computer resources. Each part of the control system 100 may operate on a different computer.

[0030] FIG. 4 is a diagram showing the logical configuration of the control system 100 of this embodiment.

[0031] The control system 100 includes a batch-type optimization calculation unit 110 that performs multi-objective optimization for a relatively long time, an online-type optimization calculation unit 120 that performs dynamic optimization, an input unit 130 into which data used for processing is input, and an output unit 140 that outputs a processing result.

[0032] The batch-type optimization calculation unit 110 is started once a day, for example, and uses a multi-objective optimization method such as Pareto optimization based on predicted values and past data of power generation amount, power demand, transportation, and weather to optimize value indicators (especially power supply value and transportation service value) described later, and creates a one-day EV tentative operation plan. The EV tentative operation plan created by the batch-type optimization calculation unit 110 includes tentative instructions for loading, moving goods or people, and charging and discharging in the nanogrid 10 to the electric vehicle 30. The calculation result by the batch-type optimization calculation unit 110 is output to the administrator via the output unit 140, and is output to the online-type optimization calculation unit 120 together with the selection by the administrator.

[0033] The online optimization calculation unit 120 optimizes value indicators (particularly power supply value and transportation service value) described later and corrects the EV operation plan at short time intervals (for example, every 10 minutes) using a multi-objective optimization method such as Pareto optimization based on the measured values from the power control device of the nanogrid 10 and the electric vehicle 30. That is, the online optimization calculation unit 120 creates a new operation plan every predetermined time (for example, 10 minutes) when there is a deviation between the tentative operation plan and the operation results, a deviation between the tentative operation plan and the operation prediction based on the transportation request, a deviation between the power supply and demand prediction and the power supply and demand results, or a deviation between the power supply and demand prediction and the power supply and demand predicted value based on the power supply and demand results. By correcting the EV operation plan, the power consumption and power transportation volume of the electric vehicle 30 change, and the power supply and demand at each nanogrid 10 can be controlled.

[0034] The input unit 130 receives inputs (selection of tentative operation plan and selection policy) from the administrator to the control system 100 and sends them to the batch optimization calculation unit 110 or the online optimization calculation unit 120. The output unit 140 outputs the calculation results by the batch optimization calculation unit 110 and the online optimization calculation unit 120.

[0035] The outputs of the control system 100 are different in that the batch optimization calculation unit 110 outputs predicted values and plans, and the online optimization calculation unit 120 outputs measured values and actual values, but the following items are output. (1) EV tentative operation plan or electric vehicle operation results · Movement of the electric vehicle 30 · Transportation by the electric vehicle 30 (departure place, arrival place, transportation volume, type of transportation (person, cargo)) · Charging and discharging of the electric vehicle 30 (charging place, charging amount, discharging place, discharging amount) · Number of transportation times of the electric vehicle 30 · Power consumption of the electric vehicle 30 · It may output a plurality of EV tentative operation plans as selection candidates for the administrator, or may rank them according to the policy specified by the administrator and output the recommended EV tentative operation plan. (2) Temporal change of the surplus power value allocated to transportation (3) Charge amount from the nanogrid 10, discharge amount to the nanogrid 10 (4) Value indicators generated by power supply and transportation (4-1) Power supply value · Reduction in the amount of electricity purchased from the power system 40, cost reduction of electricity due to an increase in the proportion of natural energy power generation · Increase in business profit due to reduction in opportunity loss caused by stable power supply · Stabilization of power supply by ensuring the power storage amount of the nanogrid 10 (4-2) Transportation service value · Reduction in transportation waiting time (time from transportation request to start of transportation) by optimizing the EV tentative operation plan and the placement of electric vehicles · Reduction in transportation cost by cheaply using the surplus power of the nanogrid 10 · Reduction in power consumption by optimizing the operation route (4-3) Other values · Reduction of environmental load by reducing the amount of carbon dioxide generated · Activation of economic activities by improving store sales when people's mobility becomes active and their mobility increases

[0036] Figure 5 is a diagram showing the configuration of the batch-type optimization calculation unit 110, and Figure 6 is a flowchart of the processing executed by the batch-type optimization calculation unit 110.

[0037] The batch-type optimization calculation unit 110 includes an operation schedule initialization unit 111, an operation schedule update unit 112, an EV / transportation / power simulation unit 113, a score calculation unit 114, and an annealing temperature scheduling unit 115.

[0038] The operation schedule initialization unit 111 creates an initial value of the EV operation plan based on the input power generation plan, power demand prediction, and transportation plan. The operation schedule update unit 112 updates the EV operation plan using the annealing method. The EV / transportation / power simulation unit 113 executes a simulation based on the updated EV operation plan, and estimates the log of the movement, charging, and discharging of the electric vehicle 30 and the log of the power supply and demand of the nanogrid 10. The score calculation unit 114 calculates various value indicators based on the results of the simulation. The annealing temperature scheduling unit 115 updates the annealing temperature T used in the annealing method, controls the iterative calculation, and outputs the final electric vehicle operation instruction.

[0039] In the batch-type optimization calculation unit 110, as shown in FIG. 6, the operation schedule initialization unit 111 receives the inputs of the power generation plan, power demand prediction, and transportation plan (S101). The power generation plan and the power demand prediction are input from the power control device of the nanogrid 10. The transportation plan includes data such as the type of transportation (person, cargo), the place of generation (departure place, arrival place), and the generation probability, and can be obtained from the shipper who ships the cargo, the delivery company that transports the cargo by the electric vehicle 30, and the transportation company that transports people by the electric vehicle 30 (EV bus, EV taxi). The operation schedule initialization unit 111 may receive the input of the policy in the nanogrid 10 such as the target value of the balance between power and transportation as necessary.

[0040] Thereafter, the operation schedule initialization unit 111 initializes the temperature T used in the annealing method to a large temperature (S102) and creates an initial value of the EV operation plan (S103).

[0041] Next, the operation schedule update unit 112 updates the EV operation plan by transitioning the EV operation plan (initial value) created by the operation schedule initialization unit 111 to the neighborhood in the annealing method (S104). The neighborhood refers to a nearby solution, for example, an operation plan in which the operation of the electric vehicle 30 is slightly changed.

[0042] Next, based on the EV operation plan updated by the operation schedule update unit 112, the EV / transportation / power simulation unit 113 operates the electric vehicle 30 in the simulator to simulate the real world, such as the operation of the nanogrid 10 and the transportation by the electric vehicle 30. (S105).

[0043] Next, the score calculation unit 114 calculates power, transportation value, and cost from the transportation log, charge / discharge log of the electric vehicle 30, and power supply / demand log (such as changes in the stored power) of the nanogrid 10 in the simulation results by the EV / transportation / power simulation unit 113.

[0044] The tempering temperature scheduling unit 115 lowers the tempering temperature T (S107) and determines whether the tempering temperature T is lower than the minimum temperature Tmin (S108). If the tempering temperature T is equal to or higher than the minimum temperature Tmin, the process returns to step S104 and continues the process at the updated tempering temperature T. On the other hand, if the tempering temperature T is lower than the minimum temperature Tmin, the iterative calculation is terminated and the result is output to the user (S109). Also, the calculation result by the batch-type optimization calculation unit 110 is input to the online-type optimization calculation unit 120 together with the selection by the user.

[0045] Although an example of using the tempering method in the batch-type optimization calculation unit 110 has been described, other methods for obtaining the optimal solution may be used.

[0046] The batch-type optimization calculation unit 110 may rank a plurality of tentative operation plans according to the policy input by the administrator. Also, the output unit 140 may output the tentative operation plans according to the ranking.

[0047] Next, the online-type optimization calculation unit 120 will be described. The online-type optimization calculation unit 120 can use the tempering method and can be configured in the same way as the batch-type optimization calculation unit 110 that uses the tempering method described in FIG. 5, so the description of the configuration is omitted.

[0048] FIG. 7 is a flowchart of the processing executed by the online optimization calculation unit 120.

[0049] First, the online optimization calculation unit 120 receives an input of the selection of the EV tentative operation plan by the administrator, together with the calculation results (EV tentative operation plan, predicted value of the time transition of the surplus power value, predicted value of the discharge amount to the nanogrid 10, predicted value of the value, etc.) by the batch optimization calculation unit 110 (S111).

[0050] Next, the online optimization calculation unit 120 initializes the time t to 0 (S112) and receives the input of the data at the time t (S113). The data input to the online optimization calculation unit 120 includes the transportation record at the time t, the measured values of the power generation amount and the power consumption, the transportation plan after the time t, the correction values of the predicted power generation amount and the power consumption, and the like.

[0051] Next, the online optimization calculation unit 120 updates the EV operation plan (transportation, charging / discharging) based on the input data at the time t (S114).

[0052] Next, the online optimization calculation unit 120 instructs the updated EV operation plan to the electric vehicle 30 (S115).

[0053] Next, the online optimization calculation unit 120 receives the transportation result (departure place, arrival place, transportation amount, type of transportation (person or cargo), charging / discharging place, charging / discharging amount, etc. included in the transportation log) and the status log (position, power storage amount, etc.) from the electric vehicle 30 (S116).

[0054] Next, the online optimization calculation unit 120 increments the time t by one step and advances to the next time (S117), and determines whether the time t is the final time t last as described above (S118). If the time t is less than the final time t last it returns to step S113 and continues the calculation.

[0055] On the other hand, if the time t is the final time t lastIf the above conditions are met, the calculation result (log) is output (S119). The output log includes the transportation result (transportation log including the departure location, arrival location, transportation volume, type of transportation (person or cargo), charge / discharge location, and charge / discharge amount) and the status log (position, charge amount). Note that not only the final result but also the log at time t may be output.

[0056] Next, the online optimization calculation unit 120 calculates various value indicators from the final result based on the transportation performance and measured values, and outputs the calculation result of the value indicators (S120).

[0057] FIG. 8 is a diagram for explaining the effects of the present invention.

[0058] As shown in FIG. 8, in the EV operation plan created by the control system 100 of the present embodiment, when the transportation service value improves, the power supply value decreases, and when the power supply value improves, the transportation service value decreases. This is because, for example, when the number of operations is increased to reduce the waiting time or the transportation speed is increased to improve the transportation service value, the energy consumption increases.

[0059] As described with reference to FIG. 6, the batch optimization calculation unit 110 creates and outputs a plurality of EV operation plans in which the power supply value and the transportation service value are optimized. For example, a diagram showing the degree of value as shown in FIG. 8 may be displayed on the screen to prompt the administrator to select from the plurality of EV operation plans. On this screen, when the display location of the EV operation plan is selected and operated, the details of the selected EV operation plan may be displayed.

[0060] In addition, when an unexpected event such as a sudden change in weather occurs and the power generation amount decreases, the operation of the planned electric vehicle and the operation of the device will stop, and the power supply value and the transportation service value will decrease. However, the online optimization calculation unit 120 can suppress the degree of decrease in the power supply value and the transportation service value by optimizing the operation plan according to the current situation.

[0061] The EV operation plan created by the control system 100 described above can be provided for, for example, the movement of farmers' crops. That is, when a farmer operates a regular service of electric trucks for shipping crops or transporting them to a processing plant, the power consumed by farm work and the power generation amount change depending on the weather. Therefore, according to the cause of the change, the frequency of the regular service is adjusted, or the number of electric vehicles 30 (EV trucks) assigned to the power storage use of the nanogrid 10 is optimized. As a result, it is possible to realize the improvement of the value of the local community by the multi-objective optimization of energy and transportation services in areas where the transportation network is vulnerable.

[0062] As described above, the power management system (control system 100) according to the embodiment of the present invention includes an input unit 130 to which power supply and demand forecasts for each of a plurality of nanogrids 10 and a transportation plan by vehicles (electric vehicles 30) are input, and based on the power supply and demand forecasts and the transportation plan, at least two values including a power supply value which is a value related to power supply and demand within the plurality of nanogrids 10 and a transportation service value which is a value of the service by the electric vehicle 30, an optimization calculation unit (batch type optimization calculation unit 110, online type optimization calculation unit 120) that creates an operation plan in which the values are optimized, and an output unit 140 that outputs the created operation plan. Therefore, the value provided to the user by power utilization and transportation services can be improved.

[0063] In addition, since the control system 100 creates an operation plan including a charge and discharge plan of the battery mounted on the electric vehicle 30, both the power supply value and the transportation service value are optimized, and the value provided to the user by power utilization and transportation services can be improved.

[0064] In addition, the created operation plan includes a charging plan for charging the battery with driving power, a charging plan for charging the battery with power for discharging to the nanogrid 10, and a discharging plan for discharging the power charged in the battery to the nanogrid 10. Therefore, the power supply and demand can be adjusted without passing through the grid power line between the nanogrids 10.

[0065] In addition, the control system 100 includes a batch optimization calculation unit 110 that creates a provisional operation plan optimized based on power supply and demand prediction and transportation plan, and calculates evaluation indicators in the created provisional operation plan, and an online optimization calculation unit 120 that creates an operation plan optimized based on the created provisional operation plan, transportation requests, and correction values of power supply and demand prediction. Therefore, the operation plan can be corrected in real time in response to the variable factors specific to natural energy, and the power supply and demand can be appropriately adjusted.

[0066] In addition, when at least one of the divergence between the provisional operation plan and the actual operation results, the divergence between the provisional operation plan and the operation prediction based on transportation requests, the divergence between the power supply and demand prediction and the power supply and demand actual results, and the divergence between the power supply and demand prediction and the power supply and demand prediction value based on the power supply and demand actual results occurs, the online optimization calculation unit 120 creates a new operation plan. Therefore, the operation plan can be corrected promptly in response to changes in power supply and demand due to variable factors, and the power supply and demand can be appropriately adjusted.

[0067] In addition, the batch optimization calculation unit 110 creates a plurality of provisional operation plans, the output unit 140 outputs the plurality of provisional operation plans to prompt selection by the administrator, and the online optimization calculation unit 120 creates an optimized operation plan using the calculation results by the batch optimization calculation unit 110 and the selection results of the provisional operation plan. Therefore, a power utilization and transportation service plan that optimizes both the power supply value and the transportation service value can be provided according to the policy specified by the administrator.

[0068] In addition, the batch optimization calculation unit 110 ranks a plurality of provisional operation plans based on the set policy, and the output unit 140 outputs the plurality of provisional operation plans with rankings. Therefore, an appropriate operation plan according to the policy can be easily selected.

[0069] Note that the present invention is not limited to the above-described embodiments, and includes various modifications and equivalent configurations within the scope of the appended claims. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and the present invention is not necessarily limited to those having all the configurations described. Also, a part of the configuration of one embodiment may be replaced with the configuration of another embodiment. Further, the configuration of another embodiment may be added to the configuration of one embodiment. Also, for a part of the configuration of each embodiment, addition, deletion, or replacement with other configurations may be made.

[0070] Also, each of the above-described configurations, functions, processing units, processing means, etc. may be realized in hardware by designing a part or all of them, for example, by means of an integrated circuit, or may be realized in software by a processor interpreting and executing a program for realizing each function.

[0071] Information such as programs, tables, files, etc. for realizing each function can be stored in a storage device such as a memory, a hard disk, an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, a DVD.

[0072] Also, control lines and information lines show those considered necessary for explanation, and do not necessarily show all the control lines and information lines required for implementation. In reality, it may be considered that almost all configurations are interconnected.

Explanation of Reference Numerals

[0073] 10 Nanogrid 11 Power Supply 12 Load 15 Switch 16 Inverter 19 Load 30 Electric Vehicle 40 Power Grid 100 Control System 101 Processor 102 Memory 103 Auxiliary Storage Device 104 Communication Interface 105 Input Interface 106 Keyboard 107 Mouse 108 Output Interface 109 Display Device 110 Batch-Type Optimization Calculation Unit 111 Operation Schedule Initialization Unit 112 Operation Schedule Update Unit 113 Power Simulation Unit 114 Score Calculation Unit 115 Temperature Scheduling Unit 120 Online-Type Optimization Calculation Unit 130 Input Unit 140 Output Unit

Claims

1. A power management system for managing power supply and demand in a plurality of nanogrids, composed of a computer having an arithmetic unit that executes predetermined processing and a storage device connected to the arithmetic unit, wherein the plurality of nanogrids include power generation devices, at least one vehicle is running among the plurality of nanogrids, and the power management system includes an input unit to which power supply and demand prediction for each of the plurality of nanogrids and a transportation plan by the vehicle are input, an optimization calculation unit that creates an operation plan optimizing at least two values, namely, a power supply value that is a value related to power supply and demand in the plurality of nanogrids and a transportation service value that is a value of the service by the vehicle, based on the power supply and demand prediction and the transportation plan, and an output unit that outputs the created operation plan, wherein the optimization calculation unit includes a first optimization calculation unit that creates a provisional operation plan optimized based on the power supply and demand prediction and the transportation plan, and calculates an evaluation index in the created provisional operation plan, and a second optimization calculation unit that creates an operation plan optimized based on the created provisional operation plan, a transportation request, and a correction value of the power supply and demand prediction. A power management system characterized by having these.

2. The power management system according to claim 1, wherein the power management system creates an operation plan including a charge and discharge plan of a battery mounted on the vehicle. A power management system characterized by this.

3. The power management system according to claim 2, wherein the operation plan includes a charging plan for charging the battery with driving power, a charging plan for charging the battery with power for discharging to the nanogrid, and a discharging plan for discharging the power charged in the battery to the nanogrid. A power management system characterized by including these.

4. The power management system according to claim 1, wherein when at least one of the divergence between the provisional operation plan and the operation result, the divergence between the provisional operation plan and the operation prediction based on the transportation request, the divergence between the power supply and demand prediction and the power supply and demand result, and the divergence between the power supply and demand prediction and the power supply and demand predicted value based on the power supply and demand result occurs, the second optimization calculation unit creates a new operation plan. A power management system characterized by this.

5. The power management system according to claim 1, wherein the first optimization calculation unit creates a plurality of the provisional operation plans, The output unit outputs the plurality of tentative operation plans to prompt selection by an administrator. The second optimization calculation unit creates an optimized operation plan using the calculation result by the first optimization calculation unit and the selection result of the tentative operation plan. A power management system characterized by this.

6. The power management system according to claim 5, wherein The first optimization calculation unit ranks the plurality of tentative operation plans based on a set policy. The output unit outputs the plurality of tentative operation plans with rankings. A power management system characterized by this.

7. A power management method executed by a power management system that manages power supply and demand in a plurality of nanogrids, The power management system is configured by a computer having an arithmetic device that executes predetermined processing and a storage device connected to the arithmetic device. The plurality of nanogrids include power generation devices. At least one vehicle is running among the plurality of nanogrids. The power management method is as follows. An input procedure in which the arithmetic device receives a power supply and demand prediction for each of the plurality of nanogrids and an input of a transportation plan by the vehicle. An optimization calculation procedure in which the arithmetic device creates an operation plan that optimizes at least two values, a power supply value that is a value related to power supply and demand in the plurality of nanogrids and a transportation service value that is a value of the service by the vehicle, based on the power supply and demand prediction and the transportation plan. An output procedure in which the arithmetic device outputs the created operation plan. The optimization calculation procedure is as follows. A procedure in which the arithmetic device creates a tentative operation plan optimized based on the power supply and demand prediction and the transportation plan, and calculates an evaluation index in the created tentative operation plan. A power management method characterized by including a procedure in which the arithmetic device creates an operation plan optimized based on the created tentative operation plan, a transportation request, and a correction value of the power supply and demand prediction.

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