Charge / discharge plan optimization apparatus and charge / discharge plan optimization method

Abstract

To enable support of reduction of accurate power cost based on discharge loss and a regulation of an electricity rate system.SOLUTION: A charge / discharge plan optimization apparatus 1Z01 optimizing a charge / discharge plan with respect to a facility with a storage battery includes: a target peak power determination part 1Z04 referring to information of peak power per unit period when a predetermined charge / discharge plan is adopted based on an actual value of power consumption or a power demand prediction value with respect to the facility in a predetermined period, and determining a target peak power on the basis of an aggregate of the peak power in the period; and a charge / discharge plan optimization part 1Z03 setting an electricity rate in the facility as an objective function, setting a constraint condition based on the determined target peak power, and generating a charge / discharge plan which minimizes the electricity rate in a planning period.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention generally relates to a charge / discharge plan optimization device and a charge / discharge plan optimization method, and more specifically to a technology that can support accurate reduction of electricity costs in consideration of charge / discharge losses and provisions of an electricity rate system. [Background technology]

[0002] Facilities such as commercial facilities, factories, and medical facilities, where power outages have a significant impact on their operations, often install in-house power generation equipment and energy storage equipment to prepare for power outages. In particular, recently, there has been a noticeable trend toward in-house power generation using renewable energy such as solar power generation systems. In such cases, not only is it necessary to ensure business continuity, allowing operations to continue even during a power outage, but it is also necessary to manage charging and discharging by using electricity from renewable energy sources during times when the electricity unit price is high, storing the surplus, and using the stored electricity at night.

[0003] By accurately managing the above-mentioned charge and discharge, it is possible to avoid undesirable situations such as power outages and effectively reduce electricity costs. Therefore, technologies related to such charge and discharge management have been proposed. For example, one such prior art is a technology proposed in Patent Document 1 that reduces contracted power by leveling grid-received power, thereby lowering the basic charge.

[0004] This technology relates to a supply and demand plan creation device that generates an operation schedule for a generator and a storage battery for a predetermined future period with respect to a power system that includes a generator, a storage battery, and load equipment, and that includes: load power prediction means that predicts load power, which is power consumption by the load equipment for the predetermined period; and operation schedule generation means that uses a first objective function related to the cost of power generation by the generator, the cost of purchasing power received from the system, and a cost according to the maximum / minimum value of power received from the system for the predetermined period, to generate an operation schedule for the generator and the storage battery that minimizes the first objective function, based on various constraints related to the generator and the storage battery and the load power prediction value obtained by the load power prediction means. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-28869 Summary of the Invention [Problem to be solved by the invention]

[0006] The technology in Patent Document 1 above proposes a method for optimizing the charging and discharging of storage batteries using mathematical optimization as a means of reducing electricity bills, and uses objective function A and objective functions B-1, B-2, and B-3 for data from the past year. Objective function A minimizes the cost of purchasing grid-received power and the cost of generating power. Objective function B-1 minimizes the cost of generating power, the cost of purchasing grid-received power, the maximum grid-received power, and the maximum and minimum values ​​of grid-received power. B-2 and B-3 are objective functions that include only a portion of B-1, and Patent Document 1 describes B-1 as being the most effective. By applying objective function B-1 to the period before and after the day when power demand was highest in the past year, and objective function A to the other periods, it is attempted to prevent excessive charging and discharging.

[0007] On the other hand, considering that energy loss occurs when a storage battery is charged and discharged, and that electricity rates are determined based on the maximum and total amount of power received from the grid over a certain period, repeated charging and discharging may actually increase electricity rates.With regard to the above-mentioned conventional technology, if there are days when the objective function B-1 should not be applied in the period before and after the day when power demand is at its maximum, excessive charging and discharging may increase charging and discharging losses, leading to an increase in electricity rates.

[0008] Therefore, the present invention has been made in consideration of the above problems, and aims to provide technology that can support accurate reduction of electricity costs, taking into account charging / discharging losses and electricity rate system regulations. [Means for solving the problem]

[0009] The present application includes multiple means for solving the above-mentioned problems, examples of which are as follows: To solve the above-mentioned problems, a charge and discharge plan optimization device according to one aspect of the present invention is an information processing device that optimizes a charge and discharge plan for a facility equipped with a storage battery, and is characterized by comprising: a target peak power determination unit that references information on peak power for each unit period when a predetermined charge and discharge plan is adopted based on actual values ​​of power consumption or forecasted values ​​of power demand for the facility for a predetermined period, and determines a target peak power based on a set of the peak powers for the period, and a charge and discharge plan optimization unit that sets an electricity rate for the facility as an objective function, sets constraints based on the determined target peak power, and generates a charge and discharge plan that minimizes the electricity rate for a planning period.

[0010] In addition, in order to solve the above-mentioned problem, a charge / discharge plan optimization method according to one aspect of the present invention is characterized in that an information processing device that optimizes a charge / discharge plan for a facility equipped with a storage battery performs the following processes: referencing information on peak power for each unit period when a predetermined charge / discharge plan is adopted, based on actual power consumption values ​​or predicted power demand values ​​for the facility for a predetermined period, and determining a target peak power based on the set of peak powers for the period; and setting the electricity rate for the facility as an objective function, setting constraint conditions based on the determined target peak power, and generating a charge / discharge plan that minimizes the electricity rate for the planning period. [Effects of the Invention]

[0011] According to the present invention, it is possible to support appropriate reduction of electricity costs in consideration of the charge / discharge loss and the provisions of the electricity rate system. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a diagram illustrating an example of the configuration of a charge / discharge plan optimization system according to an embodiment of the present invention. [Figure 2] FIG. 1 is a diagram illustrating an example of a hardware configuration of a charge and discharge plan optimization device according to an embodiment of the present invention. [Figure 3] FIG. 3 is a diagram showing a specific example of weather data in the present embodiment. [Figure 4] FIG. 4 is a diagram showing a specific example of an electricity rate table in the present embodiment. [Figure 5] FIG. 2 is a diagram illustrating an example of a correspondence table between peak power sets and electricity rates in this embodiment. [Figure 6] FIG. 4 is a diagram illustrating an example of a table of power demand and power generation amount in the present embodiment. [Figure 7] FIG. 4 is a diagram showing a specific example of a charge / discharge plan table in the present embodiment. [Figure 8] FIG. 4 is a diagram showing a specific example of a storage battery remaining capacity table in the present embodiment. [Figure 9] 5 is a flowchart showing an operation for determining a target peak power in the present embodiment. [Figure 10] 3 is a flowchart showing the operation of the charge and discharge plan optimization device in the present embodiment. [Figure 11] 10 is a flowchart showing the operation of creating a power consumption and renewable energy prediction model in this embodiment. [Figure 12] FIG. 10 is a diagram showing an example of a screen in this embodiment. [Figure 13] FIG. 10 is a diagram showing an example of a screen in this embodiment. [Figure 14] FIG. 2 is a diagram illustrating an example of definition of variables and the like in the present embodiment. [Figure 15] FIG. 2 is a diagram illustrating an example of definition of variables and the like in the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0013] In the following description, a communication device may be one or more communication interface devices, which may be one or more homogeneous communication interface devices (e.g., one or more NICs (Network Interface Cards)) or two or more heterogeneous communication interface devices (e.g., a NIC and an HBA (Host Bus Adapter)).

[0014] In the following description, a "memory" refers to one or more memory devices, which are an example of one or more storage devices. At least one of the memory devices may be a volatile memory device or a non-volatile memory device.

[0015] In the following description, an "auxiliary storage device" may be one or more persistent storage devices, which are an example of one or more storage devices. The persistent storage device may typically be a non-volatile storage device, specifically, for example, a hard disk drive (HDD), a solid state drive (SSD), or a non-volatile memory express (NVMe) drive.

[0016] Furthermore, in the following description, a "processor" may refer to one or more processor devices. The at least one processor device may typically be a microprocessor device such as a CPU (Central Processing Unit), but may also be another type of processor device such as a GPU (Graphics Processing Unit). The at least one processor device may be a single-core or multi-core. The at least one processor device may also be a processor core. The at least one processor device may also be a processor device in a broader sense, such as a hardware circuit that performs part or all of the processing (e.g., an FPGA (Field-Programmable Gate Array), a CPLD (Complex Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit)).

[0017] In the following description, information that provides an output in response to an input may be described using expressions such as "XXX table" or "XXX database." However, this information may be data of any structure (for example, structured data or unstructured data), or may be a learning model such as a neural network, genetic algorithm, or random forest that generates an output in response to an input. Therefore, "XXX table" or "XXX database" may be referred to as "XXX information." In the following description, the structure of each database or table is an example, and one database or table may be divided into two or more databases or tables, or all or part of two or more databases or tables may be one database or table.

[0018] In the following description, processing may be described using a "program" as the subject. However, because a program is executed by a processor to perform a predetermined process using a storage device and / or an interface device, etc., as appropriate, the subject of the process may also be the processor (or a device such as a controller having the processor). A program may be installed in a device such as a computer from a program source. The program source may be, for example, a program distribution server or a computer-readable (e.g., non-transitory) recording medium. In the following description, two or more programs may be realized as one program, or one program may be realized as two or more programs.

[0019] In addition, in the following description, when describing elements of the same type without distinguishing between them, common parts of the reference symbols may be used, and when describing elements of the same type with distinction between them, reference symbols or element identifiers may be used.

[0020] <Network configuration including charge / discharge plan optimization device> The present embodiment will be described below. Fig. 1 is a diagram showing an example of a network configuration of a charge / discharge plan optimization system 1 of the present embodiment. The charge / discharge plan optimization system 1 is composed of a charge / discharge plan optimization device 1Z01 as its minimum configuration. However, as in the network configuration shown in the figure, in addition to the charge / discharge plan optimization device 1Z01, the system may also include at least one of a weather data server 1Z00, a system for managing a commercial facility 1Z09, and an operation panel 1Z20 for a user 1Z21.

[0021] The charge / discharge plan optimization system 1 configured in this way can reduce grid power purchase costs while avoiding excessive charging / discharging based on the predicted power demand value and the predicted renewable energy power generation amount, taking into account the reduction effect of charge / discharge losses and contracted power. It can also display the electricity rate for a certain period based on peak power and the estimated load curve of the power received amount based on the charge / discharge plan for the planning period.

[0022] 1, the charge and discharge plan optimization device 1Z01 in this embodiment is connected to a weather data server 1Z00 and at least one commercial facility 1Z09 (e.g., a management system for a commercial facility) so as to be able to communicate data with each other via a network 1Z19. Therefore, the charge and discharge plan optimization device 1Z01 can receive weather data (described later with reference to FIG. 3) via the network 1Z19.

[0023] Furthermore, the charge / discharge plan optimization device 1Z01 can receive instructions from a user 1Z21 from an operation panel 1Z20 via a network 1Z19 and can also send notifications and the like to the user 1Z21. Specific examples of the operation panel 1Z20 include a personal computer (PC) or tablet terminal used by the user 1Z21, but other devices such as a smartphone or a mobile phone terminal may also be used. Of course, implementation examples of the operation panel 1Z20 are not limited to these.

[0024] [Commercial facility composition] Meanwhile, in the above-mentioned commercial facility 1Z09, grid-in power from the commercial power grid 1Z22 is supplied to load equipment 1Z17 and storage battery 1Z15 via distribution board 1Z16. Similarly, power generated by solar power generation equipment 1Z18 is also supplied to load equipment 1Z17 and storage battery 1Z15 via distribution board 1Z16. In the commercial facility 1Z09, the power demand of load equipment 1Z17 is sometimes met by power discharged from storage battery 1Z15 or power generated by solar power generation equipment 1Z18, and sometimes met by power purchased from the above-mentioned commercial power grid 1Z22.

[0025] When commercial facility 1Z09 purchases electricity from commercial power grid 1Z22, it enters into a power usage contract with the power company in advance. Commercial facility 1Z09 pays the power company a "basic fee" determined by the size of the contracted power. Commercial facility 1Z09 also pays a "metered fee" based on the amount of grid-received power purchased from the power company, i.e., the amount of power. In the present invention, for example, by reducing the maximum peak power demand of commercial facility 1Z09 and reducing the grid-received power, it is possible to reduce the total electricity bill, taking into account the basic fee and the metered fee.

[0026] The commercial facility 1Z09 is equipped with an EMS (Energy Management System) 1Z10, which is responsible for information processing. The EMS 1Z10 is connected to a distribution board 1Z16, a storage battery 1Z15, a solar power generation facility 1Z18, and a load facility 1Z17. The EMS 1Z10 includes at least a data output unit 1Z14, a data management unit 1Z13, an equipment control unit 1Z12, and a data collection unit 1Z11.

[0027] Of these, the data collection unit 1Z11 has a function of collecting information such as the power demand of the load equipment 1Z17 and the remaining battery capacity of the storage battery 1Z15 using sensors such as a power meter or a predetermined management application. The data management unit 1Z13 has a function of storing the information obtained by the data collection unit 1Z11 and the output of the charge / discharge plan optimization device 1Z01. The data output unit 1Z14 has a function of sending information on the storage battery 1Z15 and the load equipment 1Z17 to the charge / discharge plan optimization device 1Z01 via the network 1Z19. The equipment control unit 1Z12 has a function of sending control commands to the load equipment 1Z17, the storage battery 1Z15, etc. based on preset control setting values ​​or the charge / discharge plan values ​​of the charge / discharge plan optimization device 1Z01.

[0028] [Configuration of the charge / discharge plan optimization device] The charge / discharge plan optimization device 1Z01 includes an input / output unit 1Z08, a data acquisition unit 1Z07, a power demand forecasting unit 1Z06, a renewable energy power generation forecasting unit 1Z05, a target peak power determination unit 1Z04, a charge / discharge plan optimization unit 1Z03, and a data management unit 1Z02. This charge / discharge plan optimization device 1Z01 is typically realized on a PC (Personal Computer) or a general-purpose server personal computer device.

[0029] The hardware configuration of the charge / discharge plan optimization device 1Z01 corresponds to the configuration of a typical information processing device, for example, as shown in Fig. 2. In this case, it includes a processor 2Z01 that performs various calculations, a memory 2Z03 that is a main storage device, an auxiliary storage device 2Z04 such as a hard disk drive, an input device 2Z05 such as a keyboard or a mouse, a display unit 2Z02 such as a display, a communication unit 2Z07 such as a network interface, and an output unit 2Z06 that sends calculation results and data to the outside. However, it may further include other components.

[0030] [Data acquisition and management units of the charge / discharge plan optimization device] The data acquisition unit 1Z07 of the charge / discharge plan optimization device 1Z01 has a function of collecting information such as weather data and actual power demand in load equipment 1Z17 of the commercial facility 1Z09. Therefore, the data acquisition unit 1Z07 periodically acquires, for example, the latest actual weather data values ​​and forecast values ​​from the weather data server 1Z00 via the network 1Z19 and stores the information in the data management unit 1Z02.

[0031] FIG. 3 shows an example of the weather data 3000. The weather data 3000 records weather elements such as temperature, humidity, and solar radiation for a specific date and time period. The weather data 3000 is stored for each time period, and in this example, records are stored every 30 minutes. Note that the way the weather data 3000 is divided into time periods may differ depending on the 1Z00 weather data server from which it is obtained.

[0032] In addition to the weather data 3000, the data acquisition unit 1Z07 periodically acquires information from the EMS 1Z10 of the commercial facility 1Z09 via the network 1Z19. This information includes information such as the actual power demand of the load equipment 1Z17 and the remaining battery charge of the storage battery 1Z15. Information obtainable from the EMS 1Z10 also includes the total power demand of each load equipment 1Z17. Figure 6 shows an example of an actual power demand table 6000, which lists power demand and power generation, and Figure 8 shows a specific example of a remaining battery charge table 8000. The user 1Z21 can also set the desired time interval (unit time) for each piece of information and configure the electricity rate table 4000 (Figure 4) according to their contract details. The information thus configured is stored in the data management unit 1Z02. The electricity rate table 4000 shown in Figure 4 stores the unit price of power usage for each of two conceptual categories: basic charge and energy charge. The electricity rate column stores the unit price of electricity usage for each of the following periods: peak hours (e.g., morning hours before work or evening hours when housework is done), daytime hours (summer and other seasons), and nighttime hours.

[0033] [Power demand and renewable energy power generation forecasting section of the charge / discharge plan optimization device] The power demand forecasting unit 1Z06 and renewable energy power generation forecasting unit 1Z05 of the charge / discharge plan optimization device 1Z01 forecast the power demand and renewable energy power generation per unit time during the forecast period using the weather data 3000 stored in the data management unit 1Z02, the actual power demand and actual renewable energy power generation of the commercial facility 1Z09 (Figure 6), and the weather data 3000 for the forecast period. The forecast unit time here uses the same time interval as the actual power demand and weather data 3000.

[0034] Various existing methods can be used to forecast electricity demand and renewable energy power generation. For example, a method that performs regression analysis on the correspondence between similar past weather conditions (e.g., weather, temperature) and actual electricity demand values ​​or actual renewable energy power generation values ​​under those conditions, or a method that uses a neural network that has been trained in advance to predict the relationship between feature values ​​such as temperature, humidity, and solar radiation and electricity demand or power generation, is used. The same method can be applied to electricity demand forecasting and renewable energy power generation forecasting, but different methods can also be used.

[0035] [Input / output section] The input / output unit 1Z08 of the charge / discharge plan optimization device 1Z01 has a function of accepting inputs, settings, etc. for charge / discharge plan optimization from the user 1Z21 via a keyboard, etc., and displaying the calculation results to the user 1Z21 on a display, etc. However, the user 1Z21 does not need to perform the above inputs or settings every time the device is run, and a configuration may be adopted in which the input / output unit 1Z08 acquires preset values ​​as the targets for the inputs and settings, and automatically executes subsequent processing in accordance with these values.

[0036] [Target peak power determination section] The target peak power determination unit 1Z04 of the charge / discharge plan optimization device 1Z01 determines the target peak power, which is an important constraint for optimizing the charge / discharge plan. To make this determination, the target peak power determination unit 1Z04 calculates a set of maximum peak powers (a set of peak powers for each unit period, such as one day, during the period) and a set of minimized electricity charges (minimum charges) when optimizing the charge / discharge plan for a predetermined period. The target peak power determination unit 1Z04 also sets the target peak power using at least two methods based on the set of maximum peak powers and the set of minimum charges thus calculated. One method sets the target peak power to the minimum value of the maximum peak powers during the predetermined period, and the other method sets the maximum peak power that minimizes the electricity charge during the predetermined period to the target peak power. Note that the user 1Z21 may select the target peak power from either of the values ​​obtained by these two methods.

[0037] As a specific example, consider a case where daily charge / discharge plan optimization is performed for the past year. The goal of optimizing the charge / discharge plan is to minimize the metered charge. As a result, the maximum peak power in the annual charge / discharge plan optimization is used as the contracted power to calculate the basic charge. The annual electricity charge is calculated by the total of the daily metered charge and the annual basic charge. When calculating the charge, the basic charge may be divided by day, and the total of the daily metered charge and the basic charge may be reflected in the annual electricity charge.

[0038] When adopting the minimum value of the maximum peak power demand in a specified period, the aim is to maximize the use of the 1Z15 storage battery and minimize the contracted power demand. However, considering that the charge / discharge loss in the 1Z15 storage battery increases the metered charge, the overall electricity charge may not be minimized. This option is beneficial when aiming to minimize the contracted power demand and reduce the environmental impact during peak hours. On the other hand, when selecting the peak power demand that minimizes the electricity charge, it is beneficial to reduce the overall electricity charge by considering not only the basic charge but also the increase in the metered charge due to the charge / discharge loss in the 1Z15 storage battery.

[0039] These target peak power determination methods do not refer to past actual power values, but calculate the target peak power based on the peak power set obtained when optimizing the charge and discharge plan. For example, when introducing a new storage battery 1Z15 or changing the specifications of the storage battery 1Z15, situations may arise where past actual values ​​cannot be used as a reference, so applying this method is beneficial.

[0040] [Charge / Discharge Plan Optimization Department] Next, the operation of the charge / discharge plan optimization unit 1Z03 will be described. The charge / discharge plan optimization unit 1Z03 solves an optimization problem written by combining the formulas 1 to 18, based on the definitions (variables and symbols) of Figures 14 and 15.

[0041] Here, the key points in formulating the optimal charging and discharging of the storage battery for each unit time t (t∈T) in the optimization problem to be solved are as follows: 1. The objective function is to minimize the pay-as-you-go fee based on the charge / discharge loss, the amount of power received and charged, and the amount of natural discharge. This prevents unnecessary charging and discharging of the 1Z15 storage battery, optimizes the timing of charging in consideration of the loss due to natural discharge, and reduces the amount of power received and charged. 2. By taking into account the forecast error and introducing a target peak power margin and a reverse power flow margin, the risk due to the forecast error and the reverse power flow risk are reduced. 3. A formulation based on linear programming can be used to efficiently and precisely create plans using existing optimization solvers, making it possible to instantly create charging and discharging plans that reflect real-time weather data3000.

[0042] Each formula is explained below. Formula (1) below is a formula corresponding to the objective function of the charge / discharge optimization problem. This formula minimizes the metered charge, and achieves efficient charge / discharge control by taking into account the amount of power received and charged from the grid, surplus power, and the amount of natural discharge. By incorporating charge / discharge losses into the objective function, unnecessary charging / discharging of the storage battery 1Z15 is suppressed. This makes it possible to consider not only the increase in the metered charge, but also the shortened lifespan of the storage battery 1Z15 due to the increase in the number of cycles associated with charging / discharging.

[0043] In order to avoid exceeding the target peak power, the amount of power received and charged is used as a means to satisfy the constraints on the target peak power. For example, if the weather is cloudy or rainy and solar power generation is low, the power demand of commercial facility 1Z09 during the day may exceed the target peak power. In such a case, a charge / discharge plan that satisfies the constraints can be created by charging storage battery 1Z15 from grid power in advance and discharging that power during peak times. minimizeΣt(C t +E t +B nt )U t ···(1)

[0044] The following formula (2) defines the energy balance constraint. The received power amount Rt[t] is expressed as the difference between the power consumption Pt[t], the received power charge amount Ct[t], and the surplus power Et, and the solar power generation amount St[t], the solar charge amount Sct[t], and the battery discharge amount Bdt[t]. R t =P t +C t -(S t -S ct )-B dt +(E t ) ···(2)

[0045] The following formula (3) shows the battery charge / discharge matching constraint: This formula indicates that the battery charge amount Bct is equal to the sum of the received power charge amount Ct and the solar photovoltaic charge amount Sct. B ct =C t +S ct ···(3)

[0046] The following formula (4) is a mathematical formula showing a constraint on the natural discharge amount: This constraint indicates that the natural discharge amount Bnt of the storage battery 1Z15 reduces the storage battery charge amount Bst (remaining charge amount). B nt =B st-1 *B nt ···(4)

[0047] The following equation (5) is a state update equation for the storage battery 1Z15. This constraint indicates that the state of the storage battery charge amount Bst in the storage battery 1Z15 is updated over time by the storage battery charge amount Bct, the storage battery discharge amount Bdt, and the natural discharge amount Bnt. B st+1 =B st +η*B ct -B dt -B nt ···(5)

[0048] Furthermore, the following formula (6) is a mathematical expression showing the target peak power constraint. This constraint indicates that the amount of received power Rt is smaller than the value obtained by subtracting the target peak power margin Mtarget_power from the target contract power Ptarget (target peak power). The target peak power margin is set taking into consideration the prediction error. The larger the error, the larger the margin is generally set. A simple setting method may be to set it uniformly at, for example, 10% of the target peak power. On the other hand, a complex setting method may be to set it dynamically depending on the prediction error. Of course, such a target peak power margin may also be set by the user 1Z21. R t <P target -M target_power ···(6)

[0049] Furthermore, the following equation (7) is a mathematical expression showing the constraint for preventing reverse power flow. This equation constrains that the value obtained by subtracting the solar charge amount Sct and surplus power Et from the sum of the battery discharge amount Bdt and solar power generation amount St must be smaller than the value obtained by subtracting the reverse power flow margin Mreverse_flow from the power consumption Pt. If the sum of the battery discharge amount and solar power generation amount exceeds the power usage, reverse power flow will occur. If reverse power flow occurs, power generation will stop and it will take time to restart. The reverse power flow margin is a constraint that takes into account prediction errors in solar power generation. The setting method can be the same as equation (6). B dt +S t -S ct -E t <P t -M reverse_flow ···(7)

[0050] The following formula (8) is a formula showing the storage capacity constraint. This formula constrains the storage amount Bst of the storage battery 1Z15 to be greater than the minimum storage capacity Bmin_cap and less than the maximum storage capacity Bmax_cap. Note that the maximum storage capacity and the maximum storage capacity may be set by the user 1Z21. B min_cap st max_cap ···(8) ​​

[0051] The following formula (9) is a formula showing the unit time maximum charge amount constraint. This formula is a constraint that specifies that the battery charge amount Bct is smaller than the maximum charge amount per unit time Bmax_charge_rate. The battery unit time maximum charge amount can be set by the user 1Z21. The unit time is assumed to be the same as the unit time t of the charge / discharge plan optimization. B ct max_charge_rate ···(9)

[0052] Furthermore, the following formula (10) is a formula showing the unit time maximum discharge amount constraint. In this formula, the storage battery discharge amount Bdt shows a constraint that is smaller than the maximum discharge amount per unit time Bmax_discharge_rate. Note that the storage battery unit time maximum discharge amount can be set by the user 1Z21. The unit time is assumed to be the same as the unit time t of the charge / discharge plan optimization. B dt max_discharge_rate ···(10)

[0053] The following equation (11) represents a non-negative constraint on the battery charge amount: In this equation, the battery charge amount Bct is constrained to be equal to or greater than 0. B ct ≧0 (11)

[0054] Furthermore, the following formula (12) is a formula showing a non-negative constraint on the battery discharge amount: In this formula, the battery discharge amount Bdt is constrained to be 0 or more. B dt ≧0 (12)

[0055] ​​The following formulas (13) and (14) are formulas that represent the constraints on the unidirectional charging and discharging of the battery. These formulas constrain the battery from charging and discharging simultaneously by specifying that the battery charge amount Bct is equal to or less than the value obtained by applying the maximum charge amount per unit time Bmax_charge_rate to the charge / discharge direction CIt (formula (13)), and that the battery discharge amount Bdt is equal to or less than the value obtained by applying the maximum discharge amount per unit time Bmax_discharge_rate minus 1 in the charge / discharge direction CIt (formula (14)). B ct ≦B max_charge_rate *CI t ···(13) B dt ≦B max_discharge_rate (1-CI t ) ···(14)

[0056] Furthermore, the following equations (15), (16), (17), and (18) are mathematical expressions that indicate surplus power constraints. These equations indicate that surplus power Et occurs when the battery storage capacity Bst is the maximum storage capacity Bmax_cap multiplied by the full charge index EIt and the received power Rt is 0 (received power 0 index RIt = 1). These constraints restrict the prioritization of the solar power generation amount St as grid received power and the charging of the storage battery 1Z15. Furthermore, if there is surplus power, surplus power Et will occur. Note that with an eye to the future, constraints on selling power may also be considered. R t ≦Inf*(1-RI t ) ···(15) E t ≦S t *RI t ···(16) E t ≦S t *EI t ···(17) B st ≧B max_cap *EI t ···(18)

[0057] [Electricity Rate Table] 4 is a diagram showing an example of an electricity rate table 4000. This electricity rate table 4000 shows an example of electricity rate regulations based on season and time period. Since electricity rates vary depending on the contract between the commercial facility 1Z09 and the electric power company, the following shows one specific example.

[0058] In Japan, electricity rates are divided into a basic rate and a metered rate. The metered rate is synonymous with the energy rate. In this example, the metered rate has different electricity unit prices during the daytime depending on the season, but the same unit price during peak hours and nighttime hours regardless of the season. Furthermore, the basic rate is a fixed unit price regardless of the season.

[0059] This section explains how basic charges and metered charges are determined. The charges that commercial facilities 1Z09 and consumers pay to purchase electricity from the power company each month are divided into basic charges and metered charges. The contracted power is determined based on the amount of power that does not exceed the maximum demand of commercial facilities 1Z09 and consumers throughout the year, so the basic charge is determined based on that contracted power. If the maximum demand for the current month exceeds the contracted power, the basic charge will increase from the following month. On the other hand, metered charges are calculated based on the unit price of electricity for each time period and the amount of power received from the grid during that time period.

[0060] [Flowchart for determining target peak power] 9 is a flowchart showing the operation of the charge and discharge plan optimization system 1 in this embodiment. This operation is executed before optimizing the charge and discharge plan for the planning period. First, the charge and discharge plan optimization device 1Z01 constituting the charge and discharge plan optimization system 1 executes S10 (setting the calculation period) to set the calculation period for the maximum peak power and the electricity rate when optimizing the charge and discharge plan. This setting may be performed by reading out a predetermined setting value from the auxiliary storage device 2Z04 or the like, or may be performed by accepting a setting operation from the user 1Z21.

[0061] Furthermore, the charge / discharge plan optimization device 1Z01 executes S11 (peak power calculation range setting) to set the peak power range, which is a constraint condition for optimizing the charge / discharge plan. For example, based on information on the power demand of the commercial facility 1Z09 (e.g., FIG. 6), the charge / discharge plan optimization device 1Z01 extracts and sets the fluctuation of the maximum value of power demand for each day of the calculation period as the peak power range. On the other hand, if information on power demand is not available, an operation may be adopted in which a predefined wide range (e.g., 1 kW to 200 kW) is set. Note that the above settings may be replaced by a process of accepting a setting operation by the user 1Z21.

[0062] Furthermore, the charge / discharge plan optimization device 1Z01 executes S12 (determine whether data on power demand and renewable energy power generation amount for the calculation period exists) to check whether data on power demand and renewable energy power generation amount for the calculation period exists. This check corresponds to, for example, checking whether data exists for the relevant period in table 6000 of FIG. 6. If the check confirms that the data exists (S12: Yes), the charge / discharge plan optimization device 1Z01 proceeds to S13. On the other hand, if the data does not exist (S12: No), the charge / discharge plan optimization device 1Z01 proceeds to S14.

[0063] Furthermore, the charge / discharge plan optimization device 1Z01 uses the power demand prediction unit 1Z06 and the renewable energy power generation prediction unit 1Z05 to predict the power demand and renewable energy power generation amount for the calculation period as S14 (power demand / renewable energy power generation amount prediction for the calculation period). The prediction method is as already described. Note that if actual values ​​for the power demand and renewable energy power generation amount for the calculation period do not exist, predicted values ​​can be used instead.

[0064] Furthermore, the charge and discharge plan optimization device 1Z01 sets the peak power, which is a constraint condition for optimizing the charge and discharge plan for the calculation period, to the minimum peak power within the range of peak power set in S11 above, i.e., the peak power minimum value, in S13 (setting the peak power to the minimum value). Then, the process proceeds to S15. Furthermore, the charge and discharge plan optimization device 1Z01 executes the charge and discharge plan optimization for the calculation period in S15 (charging and discharge plan optimization). The detailed process of the charging and discharge plan optimization will be described later with reference to FIG. 10. Then, the process proceeds to S16.

[0065] Furthermore, the charge / discharge plan optimization device 1Z01 determines in S16 (determine whether a solution is found for all days and the maximum value of the peak power calculation range is reached) whether a solution is found for all days in the calculation period and the maximum value of the peak power calculation range is reached in the results of optimizing the charge / discharge plan for the calculation period. If the result of this determination is that a solution is found for all days in the calculation period and the maximum value of the peak power calculation range is reached (S16: Yes), the charge / discharge plan optimization device 1Z01 proceeds to S18. On the other hand, if not (S16: No), the charge / discharge plan optimization device 1Z01 proceeds to S17.

[0066] Furthermore, in S17 (incrementing the peak power by 1 kW), if the condition of S16 is not satisfied, the charge and discharge plan optimizing device 1Z01 increments the peak power, which is a constraint condition, by 1 kW and proceeds to S15. Then, a loop occurs until the condition of S16 is satisfied.

[0067] Furthermore, in S18 (determining the target peak power), the charge / discharge plan optimization device 1Z01 sets the maximum value of the minimum peak power during the calculation period or the peak power that minimizes the electricity rate based on the set of maximum peak powers and electricity rates identified in S15 (the set of maximum peak powers and electricity rates when the charge / discharge plan is optimized within the peak power range during the calculation period), and then proceeds to S19.

[0068] Furthermore, the charge and discharge plan optimization device 1Z01 registers the target peak power calculated in S18 in the data management unit 1Z02 of the charge and discharge plan optimization device 1Z01 in S19 (registering the target peak power in the data management unit of the charge and discharge plan optimization device).

[0069] The flowchart in Figure 9 makes it possible to determine the target peak power, which is a constraint for optimizing the charge / discharge plan within the planning period. The calculation period can be set by the user 1Z21 based on the power contract. For example, if it is known in advance that power demand is highest in the summer, the calculation period can be limited to the summer. The user 1Z21 can set the peak power calculation range, which calculates electricity rates for different peak powers depending on this setting. The user 1Z21 can analyze the results. For example, if the user is willing to accept a slightly higher peak power rate in consideration of the risk of exceeding the contracted power, the user can set the target peak power higher. Furthermore, even if there is a lack of actual data on power demand or renewable energy power generation, calculations to determine the target peak power can be performed by making a prediction.

[0070] [Charge and discharge plan planning flowchart] FIG. 10 is a flowchart showing the operation (S15 in FIG. 9) of optimizing a charge and discharge plan for a planning period by the charge and discharge plan optimization device 1Z01 in this embodiment. This operation is executed after determining the target peak power. First, the charge and discharge plan optimization device 1Z01 determines whether it is time to update the charge and discharge plan in S21 (determine whether it is time to update the charge and discharge plan). If the result of this determination is that it is time to update (S21: Yes), the charge and discharge plan optimization device 1Z01 proceeds to the process in S22. On the other hand, if it is not (S21: No), the charge and discharge plan optimization device 1Z01 returns the process to S21.

[0071] Furthermore, the charge / discharge plan optimization device 1Z01 acquires weather data 3000 for the planning period from the data management unit 1Z02 as S22 (acquires weather data from the data management unit). Then, proceeds to S23. Furthermore, the charge / discharge plan optimization device 1Z01 uses the weather data 3000 acquired in S22 above to perform predictions of power demand and renewable energy power generation amount by the power demand prediction unit 1Z06 and the renewable energy power generation amount prediction unit 1Z05 as S23 (prediction of power demand and renewable energy power generation amount for the planning period). Then, proceeds to S24.

[0072] Furthermore, the charge and discharge plan optimization device 1Z01 acquires information about the storage battery 1Z15 from the EMS 1Z10 of the commercial facility 1Z09 in S24 (acquires information about the storage battery from the EMS of the commercial facility, consumer, etc.). Then, proceeds to S25. Furthermore, the charge and discharge plan optimization device 1Z01 acquires the target peak power from the data management unit 1Z02 in S25 (acquires target peak power from the data management unit). Then, proceeds to S26.

[0073] The charge and discharge plan optimization device 1Z01 also optimizes the charge and discharge plan for the planning period in S26 (optimizing the charge and discharge plan for the planning period). Then, the process proceeds to S27. The charge and discharge plan optimization device 1Z01 also registers the charge and discharge plan values ​​for the planning period obtained by S26 in the EMS 1Z10 of the commercial facility 1Z09 in S27 (registering the calculation results in the EMS).

[0074] In optimizing the charge / discharge plan for the planning period, optimization is performed using the remaining battery capacity data obtained from EMS1Z10, with the target peak power calculated in advance for a specified period as a constraint. This effectively reduces peak power while suppressing unnecessary charging and discharging of the storage battery 1Z15. As a specific example, the planning period is set to the next day, and the specified period is set to the past year. The target peak power for the planning period is calculated based on actual or predicted values ​​for the past year. Therefore, a target peak power that does not exceed the peak power set for the past year can be obtained. Not exceeding this target peak power avoids the risk of future increases in basic charges. Furthermore, since this target peak power is based on calculation results for one year, consideration is given to appropriately setting the target peak power to prevent excessive charging and discharging losses.

[0075] [Prediction model creation flowchart] 11 is a flowchart showing the operation of creating a model for the power demand prediction unit 1Z06 and the renewable energy power generation amount prediction unit 1Z05 of the charge and discharge plan optimization device 1Z01 in this embodiment. Here, an example is shown in which the charge and discharge plan optimization device 1Z01 creates a prediction model. However, the charge and discharge plan optimization device 1Z01 may be configured to acquire a model generation result from an external machine learning engine. Furthermore, when the charge and discharge plan optimization device 1Z01 generates a prediction model, for example, a known machine learning engine is provided so that it can be used, and training data (e.g., a set of information on various events such as weather data 3000 and actual values ​​of power demand and renewable energy power generation amount during the period in which the event occurs) is provided to the machine learning engine to proceed with model learning and obtain a prediction model.

[0076] First, the charge / discharge plan optimization device 1Z01 accepts the setting of the learning period and test period for the power demand forecasting model and the renewable energy power generation forecasting model by the user 1Z21 in S31 (setting the learning period and test period). Then, the process proceeds to S32. The charge / discharge plan optimization device 1Z01 acquires weather data 3000 relating to the learning period and test period set in S31 from the data management unit 1Z02 in S32 (acquiring weather data from the data management unit). Then, the process proceeds to S33.

[0077] In addition, the charge / discharge plan optimization device 1Z01 acquires power demand and renewable energy power generation data for the period specified by the user in S31 from the EMS 1Z10 of the commercial facility 1Z09 as S33 (acquires power demand / renewable energy power generation data from EMS).

[0078] Furthermore, the charge and discharge plan optimization device 1Z01 proceeds with learning the power demand / renewable energy power generation prediction model using the weather data 3000 and the power demand / renewable energy power generation data acquired in S32 and S33 above as S34 (learning the power demand / renewable energy power generation prediction model). Then, it proceeds to S35. Furthermore, the charge and discharge plan optimization device 1Z01 saves the model learned in S34 and its test results in the data management unit 1Z02 as S35 (save the learned model and test results in the data management unit).

[0079] [Screen output example] FIG. 12 is a diagram showing an example of a screen output from the input / output unit 1Z08 of the charge / discharge plan optimization device 1Z01 in this embodiment. The screen 1G1 is a screen on which a user 1Z21 inputs information related to charge / discharge plan optimization to determine a target peak power, and the results are displayed. The interface 1G101 is an interface through which the user 1Z21 inputs information related to a calculation period 1G101a and a peak power calculation range 1G101b, and executes processing according to the results of the input in response to a click of the execute button 1G101c. When the user 1Z21 presses the execute button 1G101c, a maximum peak power set and an electricity rate set based on the charge / discharge plan optimization during the calculation period are calculated.

[0080] An interface 1G102 displays the results of the calculation, displaying a maximum value 1G102a of the minimum peak power based on the charge / discharge plan optimization during the calculation period and a set 1G102b of the minimum peak power. The set 1G102b of the minimum peak power displays the minimum peak power by day.

[0081] When determining one of the target peak powers, the maximum value of the minimum peak power during the calculation period is displayed by a horizontal line 1G102c. Also, the peak power 1G102d at which the electricity bill will be minimized and the minimum electricity bill 1G102e are displayed on the respective interfaces. Graph G102f displays the set of maximum values ​​of the minimum peak power during the calculation period and the electricity bill. The range of the maximum value of the minimum peak power 1G102g is from the minimum value of the maximum peak power for which a solution exists for all days to the maximum value of the peak power calculation range set by the user 1Z21. Also displayed is the peak power 1G102h at which the electricity bill will be minimized during the calculation period.

[0082] In Figure 12, user 1Z21 can analyze the peak power set and electricity rate set by setting and examining the charge and discharge plan for the calculation period. As a specific example, for a commercial facility 1Z09 that does not have a storage battery 1Z15, the past year is specified as the calculation period for the target peak power. Then, if a storage battery 1Z15 is installed during the calculation period, how the electricity rate and peak power will change is examined. From these results, user 1Z21 can obtain useful information regarding investment in a new storage battery 1Z15 or solar power generation equipment 1Z18.

[0083] There are also at least two methods for determining the target peak power, each of which provides different value to the user 1Z21. Furthermore, the user 1Z21 can set the target peak power from other perspectives in addition to these methods. For example, it is possible to minimize the electricity bill while also considering the risk of exceeding the contracted power, and instead of the minimum peak power, it is also possible to aim for a range in which the peak power is minimized and the electricity bill is minimized. By showing these options in Figure 12, the user 1Z21 can set the target peak power in a flexible and important way.

[0084] 13 shows an example of an output screen 1G2 of the input / output unit 1Z08 of the charge / discharge plan optimization device 1Z01 in this embodiment. This screen 1G2 is composed of an input interface 1G201 for inputting information related to charge / discharge plan optimization for a planning period, and an interface 1G202 for displaying the results of optimizing the charge / discharge plan for that planning period. In this case, a user 1G21 inputs a planning period 21G201a and a target peak power 1G201b in the input interface 1G201 and presses an execute button 1G201c. The graph 1G202a in the interface 1G202 displays the estimated photovoltaic power generation amount, the estimated power demand amount, and the load curve of the received power amount for the planning period 21G201a. The table 1G202b displays the estimated grid received power amount and the charge / discharge plan value for the planning period in a tabular format.

[0085] The user 1Z21 can easily check the results of the optimization of the charge / discharge plan for the planning period in the form of a load curve of the estimated amount of received power on the screen 1G2 shown in Fig. 13. In addition, the user 1Z21 can adjust the target peak power for the planning period and check the results, so that the user 1Z21 can check the setting results from other perspectives in addition to the two methods of determining the target peak power shown in Fig. 12. This provides the user 1Z21 with a wider range of options, enabling more diverse decision-making.

[0086] Although one embodiment of the present invention has been described above, this is merely an example for explaining the present invention, and the scope of the present invention is not limited to this embodiment. The present invention can be implemented in various other forms.

[0087] The above description can be summarized as follows: The following summary may include supplementary explanations and explanations of variations of the above description.

[0088] In the charge / discharge plan optimization device of this embodiment, the charge / discharge plan optimization unit may calculate peak power for each unit period when a predetermined charge / discharge plan is adopted, based on the actual value of power consumption or the predicted value of power demand for the facility in the predetermined period.

[0089] According to this, by calculating the peak power for each unit period (e.g., one day) in the charge / discharge plan optimization device, it becomes possible to improve the overall processing efficiency, and ultimately to support more accurate reduction of electricity costs, taking into account discharge losses and the provisions of the electricity rate system.

[0090] Moreover, the charge / discharge plan optimization device of this embodiment may further include a power demand prediction unit that predicts power demand for the facility during the specified period, and a renewable energy power generation prediction unit that predicts the amount of power generated from renewable energy.

[0091] This allows for efficient estimation of the power supply-demand balance and efficient optimization of charging and discharging plans, which in turn supports accurate reduction of power costs in accordance with the provisions of the electricity rate system and discharge losses.

[0092] In the charge and discharge plan optimizing device of this embodiment, the target peak power determining unit may select one value from the set of peak powers to be the target peak power.

[0093] This allows the target peak power to be determined efficiently and accurately, which in turn supports more accurate reduction of power costs in accordance with the provisions of the discharge loss and electricity rate system.

[0094] In the charge and discharge plan optimizing device of the present embodiment, the renewable energy power generation amount predicting unit may calculate a predicted value of power consumption using weather data for a predetermined period.

[0095] This allows for highly accurate prediction of power consumption, which in turn supports more accurate reduction of power costs in accordance with the provisions of the electricity rate system and discharge loss.

[0096] Furthermore, in the charge and discharge plan optimization device of this embodiment, the target peak power determination unit may select a value from the set of peak powers that minimizes the electricity fee based on the reduction effect of contracted power in the facility and charge and discharge loss of a storage battery.

[0097] This allows for the optimization of charging and discharging plans that take into account the positive and negative impacts of charging and discharging losses and contracted power, which in turn supports the accurate reduction of electricity costs in accordance with the provisions of the electricity rate system and discharge losses.

[0098] In the charge / discharge plan optimization device of this embodiment, the charge / discharge plan optimization unit may formulate the charge / discharge loss and set it as the constraint condition.

[0099] This makes it possible to perform the process of optimizing the charge / discharge plan taking into account the charge / discharge loss with high accuracy and excellent computational efficiency, thereby supporting the accurate reduction of electricity costs in consideration of the discharge loss and the provisions of the electricity rate system.

[0100] Furthermore, the charge and discharge plan optimization device of this embodiment may further include an input / output unit that displays a graph showing the electricity charges and the power reception load curve in the facility when the generated charge and discharge plan is applied.

[0101] This allows various information related to the creation of a charge / discharge plan to be visually presented, helping users to confirm and consider the plan. This in turn helps users to accurately reduce electricity costs, taking into account discharge losses and electricity rate system regulations.

[0102] In the charge and discharge plan optimizing device of this embodiment, the target peak power determining unit may select a peak power that minimizes the contracted power when selecting from the set of peak powers.

[0103] This allows for accurate and efficient selection of peak power when generating a charge / discharge plan, which in turn supports accurate reduction of power costs in accordance with discharge losses and electricity rate system regulations.

[0104] Furthermore, in the charge / discharge plan optimization device of this embodiment, the charge / discharge plan optimization unit may set a constraint based on the sum of the target peak power and the safety margin, which is set by a user, and generate the charge / discharge plan.

[0105] This allows for the optimization of charging and discharging plans to accurately avoid situations where the power demand for each time period cannot be met, and ultimately supports accurate reduction of power costs in accordance with the provisions of the electricity rate system and discharge loss.

[0106] In addition, in the charge / discharge plan optimization device of this embodiment, the charge / discharge plan optimization unit may formulate the objective function and the constraint conditions by linear programming and solve an optimization problem using an optimization solver, thereby generating the charge / discharge plan.

[0107] This makes it possible to efficiently generate accurate charge and discharge plans by solving optimization problems, which in turn helps to accurately reduce electricity costs in accordance with the discharge loss and electricity rate system regulations.

[0108] In the charge and discharge plan optimization device of the present embodiment, the charge and discharge plan optimization unit may also formulate a charge and discharge plan based on information relating to the capacity of the storage battery.

[0109] This allows for the optimization of charging and discharging plans based on the characteristics and current status of each storage battery, which in turn supports the accurate reduction of electricity costs based on discharge losses and electricity rate system regulations. [Explanation of symbols]

[0110] 1Z00 Weather Data Server 1Z01 Charge and discharge plan optimization device 1Z02 Data Management Department 1Z03 Charging and discharging plan optimization unit 1Z04 Target peak power determination unit 1Z05 Renewable Energy Power Generation Forecasting Department 1Z06 Electricity Demand Forecasting Department 1Z07 Data Acquisition Unit 1Z08 Input / output section 1Z09 Commercial facilities 1Z10 EMS 1Z11 Data Collection Unit 1Z12 Equipment control unit 1Z13 Data Management Department 1Z14 Data output section 1Z15 storage battery 1Z16 Distribution board 1Z17 Load equipment 1Z18 Solar power generation equipment 1Z19 Network 1Z20 Operation Panel 1Z21 User 1Z22 Commercial power system 2Z00 Information processing equipment 2Z01 processor 2Z02 Display section 2Z03 Memory 2Z04 Auxiliary storage device 2Z05 Input device 2Z06 Output section 2Z07 Communication Department 3000 weather data 4000 Electricity Rate Table 5000 Peak power and electricity price correspondence table 6000 Electricity Demand and Generation Table 7000 Charging and discharging planning table 8000 Battery Remaining Capacity Table

Claims

1. An information processing device that optimizes a charge / discharge plan for a facility equipped with a storage battery, a target peak power determination unit that refers to information on peak power for each unit period when a predetermined charge / discharge plan is adopted, based on an actual value of power consumption or a predicted value of power demand for the facility for a predetermined period, and determines a target peak power based on a set of the peak power for the period; a charge / discharge plan optimization unit that sets an electricity rate in the facility as an objective function, sets constraint conditions based on the determined target peak power, and generates a charge / discharge plan that minimizes the electricity rate during a planning period; A charge and discharge plan optimization device comprising:

2. the charge / discharge plan optimization unit calculates peak power for each unit period when a predetermined charge / discharge plan is adopted, based on an actual value of power consumption or a predicted value of power demand for the facility during the predetermined period; 2. The charge / discharge plan optimization device according to claim 1.

3. an electricity demand forecasting unit that forecasts electricity demand for the facility during the predetermined period; a renewable energy power generation amount prediction unit that predicts the amount of power generation derived from renewable energy; The charge / discharge plan optimization device according to claim 2, further comprising:

4. the target peak power determination unit selects one value from the set of peak powers as the target peak power; 4. The charge / discharge plan optimization device according to claim 3.

5. The renewable energy power generation amount prediction unit calculates a predicted value of power consumption using weather data for a predetermined period.

5. The charge / discharge plan optimization device according to claim 4.

6. the target peak power determination unit selects a value from the set of peak powers that minimizes the electricity fee based on a reduction effect of contracted power in the facility and charge / discharge loss of a storage battery.

5. The charge / discharge plan optimization device according to claim 4.

7. The charge / discharge plan optimization unit formulates the charge / discharge loss and sets it as the constraint condition.

7. The charge / discharge plan optimization device according to claim 6.

8. An input / output unit that displays a graph showing an electricity rate and a load curve of received electricity in the facility when the generated charge / discharge plan is applied.

8. The charge / discharge plan optimization device according to claim 7.

9. the target peak power determination unit selects a peak power that minimizes the contracted power when selecting from the set of peak powers; 5. The charge / discharge plan optimization device according to claim 4.

10. the charge / discharge plan optimization unit sets a constraint based on a sum of the target peak power and the safety margin based on a safety margin of the target peak power set by a user, and generates the charge / discharge plan; 3. The charge / discharge plan optimization device according to claim 2.

11. The charge / discharge plan optimization unit formulates a charge / discharge plan based on information related to the capacity of the storage battery.

3. The charge / discharge plan optimization device according to claim 2.

12. The charge / discharge plan optimization unit formulates the objective function and the constraint conditions by linear programming and solves an optimization problem by an optimization solver to generate the charge / discharge plan.

3. The charge / discharge plan optimization device according to claim 2.

13. An information processing device that optimizes a charge and discharge plan for a facility equipped with a storage battery, a process of referring to information on peak power for each unit period when a predetermined charge / discharge plan is adopted, based on actual values ​​of power consumption or predicted values ​​of power demand for the facility for a predetermined period, and determining a target peak power based on a set of the peak power for the period; a process of setting an electricity rate in the facility as an objective function, setting constraints based on the determined target peak power, and generating a charge / discharge plan that minimizes the electricity rate during a planning period; A charge and discharge plan optimization method, characterized by executing the above.

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