Management System

Abstract

Generates power plans that are appropriately guaranteed to be feasible. [Solution] A management system uses a mathematical model to generate a power plan for charging and discharging a power storage device, the power plan including a plan for variable power that fluctuates within a specific fluctuation range. The mathematical model includes constraint equations for calculating a surplus scenario that is a change in the charge amount of the power storage device over time when the variable power is biased to the charging side to the maximum, constraint equations for calculating a shortage scenario that is a change in the charge amount of the power storage device over time when the variable power is biased to the discharging side to the maximum, constraint equations that limit the upper limit of the surplus scenario, constraint equations that limit the lower limit of the shortage scenario, constraint equations that add virtual additional discharging power in the discharging direction to the surplus scenario based on the charge amount in the surplus scenario, and constraint equations that add virtual additional charging power in the charging direction to the shortage scenario based on the charge amount in the shortage scenario.

Description

[Technical Field]

[0001] TECHNICAL FIELD This disclosure relates to managing power in an electric power system. [Background technology]

[0002] Various technologies have been proposed for managing power in a power system to which power storage devices such as storage batteries are connected. For example, Patent Document 1 discloses a configuration for calculating the amount of power that a storage battery can supply to the power trading market. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 7486653 Summary of the Invention [Problem to be solved by the invention]

[0004] However, with conventional power management technologies, it is practically difficult to ensure appropriate adjustment of the charge amount by the power storage device, and it is desirable to generate a power plan that is realistically feasible. In consideration of the above circumstances, one aspect of the present disclosure aims to generate a power plan that appropriately ensures feasibility. [Means for solving the problem]

[0005] A management system according to one aspect of the present disclosure is a management system that uses a mathematical model to generate a power plan for charging and discharging a power storage device, the power plan including a plan for variable power that fluctuates within a specific fluctuation range, and the mathematical model includes a constraint equation for calculating a surplus scenario that is the change over time in the charge amount of the power storage device when the variable power is maximally biased toward the charging side, a constraint equation that limits the upper limit of the surplus scenario, and a constraint equation that adds virtual additional discharge power in the discharge direction to the surplus scenario based on the charge amount in the surplus scenario.

[0006] A management system according to another aspect of the present disclosure is a management system that uses a mathematical model to generate a power plan for charging and discharging a power storage device, the power plan including a plan for variable power that fluctuates within a specific fluctuation range, and the mathematical model includes a constraint equation for calculating a shortage scenario that is the change in the charge amount of the power storage device over time when the variable power is maximally biased toward the discharge side, a constraint equation that limits the lower limit of the shortage scenario, and a constraint equation that adds virtual additional charging power in the charging direction to the shortage scenario based on the charge amount in the shortage scenario.

[0007] Another aspect of the present disclosure is a management system that generates a power plan for charging and discharging a power storage device, the power plan including a plan for variable power that fluctuates within a specific fluctuation range, using a mathematical model, and the mathematical model includes a constraint equation for calculating a surplus scenario that is the change over time in the charge amount of the power storage device when the variable power is maximally biased toward the charging side, a constraint equation for calculating a shortage scenario that is the change over time in the charge amount of the power storage device when the variable power is maximally biased toward the discharging side, a constraint equation that limits the upper limit of the surplus scenario, a constraint equation that limits the lower limit of the shortage scenario, a constraint equation that adds virtual additional discharge power in the discharging direction to the surplus scenario based on the charge amount in the surplus scenario, and a constraint equation that adds virtual additional charge power in the charging direction to the shortage scenario based on the charge amount in the shortage scenario. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram illustrating a configuration of a power system according to an embodiment. [Figure 2] FIG. [Figure 3] FIG. 1 is a block diagram illustrating the configuration of a mathematical model. [Figure 4] FIG. 10 is an explanatory diagram regarding a surplus scenario. [Figure 5] FIG. 10 is an explanatory diagram regarding surplus sub-scenario. [Figure 6] FIG. 10 is an explanatory diagram illustrating an example of the relationship between a specific time point and a time point at which electricity trading is actually performed. [Figure 7] FIG. 10 is an explanatory diagram regarding a shortage scenario. [Figure 8] FIG. 10 is an explanatory diagram regarding a shortage sub-scenario. DETAILED DESCRIPTION OF THE INVENTION

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] The following description of an embodiment of the present disclosure will be given with reference to the accompanying drawings. Note that the embodiment described below is an exemplary embodiment that may be envisioned when implementing the present disclosure. Therefore, the scope of the present disclosure is not limited to the embodiment exemplified below.

[0010] A: Embodiment Fig. 1 is a block diagram illustrating the configuration of a power system 100 according to an embodiment of the present disclosure. As illustrated in Fig. 1, the power system 100 includes a power grid 10, a power storage system 20, a control system 30, and a management system 40. The power grid 10 is, for example, a distribution system or a transmission system for supplying power generated by a power generation facility (not shown) such as a thermal power plant or a nuclear power plant to consumers such as business facilities or ordinary households.

[0011] The power storage system 20 is a power facility capable of charging and discharging power, and is connected to the power grid 10 at an interconnection point 11. As illustrated in FIG. 1 , the power storage system 20 includes a storage battery 21, a control device 22, and a transformer 23. The storage battery 21 is a system storage battery that charges and discharges DC power. Any type of storage battery 21 may be used, but examples of the storage battery 21 include secondary batteries such as lithium-ion batteries or sodium-sulfur batteries. Note that the power storage system 20 may include multiple storage batteries 21.

[0012] The control device 22 is a PCS (Power Conditioning System) that controls discharging and charging of the storage battery 21. Specifically, the control device 22 is a power conversion device that converts between DC power discharged or charged by the storage battery 21 and AC power transformed by the transformer 23. The transformer 23 converts the voltage of the AC power.

[0013] The control system 30 is a computer system that controls the operation of the power storage system 20. The control system 30 is capable of communicating with the power storage system 20 via a communication network (not shown) such as a dedicated line. Specifically, the control system 30 transmits a power command to the power storage system 20. The power command is a command for the power that the power storage system 20 should charge or discharge. The control system 30 generates the power command in accordance with, for example, an adjustment capability command B and a power plan P. The adjustment capability command B is a command value for adjustment capability that should be dynamically provided in accordance with the relationship between supply and demand in the supply and demand balancing market. For example, the adjustment capability command B is notified to the control system 30 from a central load dispatching center system (intermediate supply system).

[0014] The power plan P is a plan regarding charging and discharging of the power storage system 20. Specifically, the power plan P defines the operation of the power storage system 20 for each of a plurality of periods (hereinafter referred to as "frames") on a time axis. Each of the plurality of frames has a predetermined length (for example, 30 minutes). Therefore, one day is made up of a total of 48 frames.

[0015] The power plan P includes, for example, a power storage operation plan, a power adjustment capability plan, and a power trading plan. The power storage operation plan is a plan for operation to charge or discharge the power storage system 20. The power adjustment capability plan is a plan that specifies, for example, the fluctuation range of the power adjustment capability for each frame (hereinafter referred to as "power adjustment capability fluctuation range"). The above-mentioned power adjustment capability command B commands the power adjustment capability within the range of the power adjustment capability fluctuation range (ΔkW). The power trading plan is a plan that specifies, for example, the power to be sold or purchased. As described above, the power plan P includes a plan for power adjustment capability (variable power) that fluctuates depending on the power adjustment capability fluctuation range.

[0016] In this embodiment, as illustrated in FIG. 2 , the adjustment capability in the power storage system 20 is treated as the magnitude of the fluctuation range (power value) that can be obtained within a range up to the rated output on the discharge side, with the output of the storage battery 21 based on the power trading plan set as a reference value (=0). For example, for a section that requires the rated output on the charge side in the power trading plan, the power storage system 20 can provide adjustment capability in the range from the rated output on the charge side to the rated output on the discharge side. Therefore, the range of the upward adjustment capability that can be provided to increase the power at the interconnection point 11 in the power system 10 (hereinafter referred to as "interconnection point power") corresponds to twice the rated output of the storage battery 21. The upward adjustment capability is an adjustment capability that resolves power shortages in the power system 10.

[0017] 1 is a computer system (EMS: Energy Management System) that generates an electric power plan P. The management system 40 manages, for example, electric power transactions between the wholesale electric power market (spot market and hourly market) and the supply and demand balancing market, and the generation of the electric power plan P.

[0018] 1, the management system 40 includes a control device 41, a storage device 42, and a communication device 43. The management system 40 may be realized by a single device, or may be realized by multiple devices configured separately from each other.

[0019] The control device 41 is composed of one or more processors that control each element of the management system 40. Specifically, the control device 41 is composed of one or more types of processors, such as a programmable logic device (PLD), a central processing unit (CPU), a digital signal processor (DSP), a field programmable gate array (FPGA), or an application specific integrated circuit (ASIC).

[0020] The communication device 43 communicates with external devices. Specifically, the communication device 43 communicates with the control system 30 via a communication network (not shown) such as a dedicated line. For example, the communication device 43 transmits a power plan P to the control system 30.

[0021] The storage device 42 is one or more memories that store programs executed by the control device 41 and data used by the control device 41. The storage device 42 is configured with a known recording medium such as a magnetic recording medium or a semiconductor recording medium. The storage device 42 may also be configured with a combination of multiple types of recording media.

[0022] The storage device 42 of this embodiment stores a mathematical model M. The control device 41 generates a power plan P using the mathematical model M. The mathematical model M is a model for optimizing the power plan P (charging and discharging by the power storage system 20). Specifically, the mathematical model M is a model for generating a power plan P that can accommodate power supply with an adjustment capability fluctuation range (ΔkW) that is twice the rated output while preventing the storage battery 21 from becoming fully charged or empty.

[0023] [Mathematical Model M] Fig. 3 is a block diagram illustrating an example of the configuration of the mathematical model M. As illustrated in Fig. 3, the mathematical model M includes an expected value model Ma, a surplus model Mb, and a shortage model Mc. The expected value model Ma, the surplus model Mb, and the shortage model Mc are models corresponding to different activation rates of the adjustment capacity command B.

[0024] The activation rate is the ratio of the supply power instructed by the regulation capability command B to the regulation capability fluctuation range. As described above, in this embodiment, the output of the storage battery 21 based on the power trading plan is set as a reference value (=0), and the regulation capability fluctuation range (ΔkW) is set. Therefore, an activation rate of 0% corresponds to a situation in which the supply power instructed by the regulation capability command B is biased to the maximum extent toward the charging side (i.e., a situation in which the regulation capability command B requests charging and discharging of the reference value). When the activation rate is 0%, the amount of charge in the power storage system 20 is likely to exceed the plan, resulting in an excess amount of charge in the power storage system 20. On the other hand, an activation rate of 100% corresponds to a situation in which the supply power instructed by the regulation capability command B is biased to the maximum extent toward the discharging side (i.e., a situation in which the regulation capability command B requests charging and discharging of a power value obtained by adding the regulation capability fluctuation range (ΔkW) to the reference value). If the activation rate is 100%, the amount of charge in the power storage system 20 will fall below the plan, and as a result, the amount of charge in the power storage system 20 is likely to be insufficient.

[0025] The expected value model Ma is a model that describes the behavior of each element of the power system 100 when the activation rate is a standard predicted value (expected value). In other words, the expected value model Ma corresponds to a case where the charge amount of the power storage system 20 is neither surplus nor shortage. On the other hand, the surplus model Mb is a model that describes the behavior of each element of the power system 100 when the adjustment capability is biased to the charging side to the maximum (hereinafter referred to as the "case of the maximum command on the charging side"). In other words, the surplus model Mb corresponds to a case where the charge amount of the storage battery 21 is surplus. The case of the maximum command on the charging side corresponds to a case where the activation rate is 0%. The shortage model Mc is a model that describes the behavior of each element of the power system 100 when the adjustment capability is biased to the discharging side to the maximum (hereinafter referred to as the "case of the maximum command on the discharging side"). In other words, the shortage model Mc corresponds to a case where the charge amount of the power storage system 20 is shortage. The case of the maximum command on the discharging side corresponds to a case where the activation rate is 100%.

[0026] The expected value model Ma includes a wholesale electricity market submodel Ma1, a balancing market submodel Ma2, a revenue calculation submodel Ma3, a storage battery submodel Ma4, and an interconnection point submodel Ma5. The wholesale electricity market submodel Ma1 is a model that represents electricity trading in the wholesale electricity market (spot market and hourly market). The balancing market submodel Ma2 is a model that represents electricity trading in the balancing market. The revenue calculation submodel Ma3 is a model for calculating daily revenue according to the results of electricity trading in the wholesale electricity market and the balancing market.

[0027] The storage battery sub-model Ma4 is a model that simulates charging and discharging by the power storage system 20. Specifically, the storage battery sub-model Ma4 is a model for calculating the change over time in the charge amount of the power storage system 20 when the activation rate is maintained at an expected value over all frames (hereinafter referred to as "expected value scenario Sa"). In other words, the expected value scenario Sa is the transition of the charge amount of the power storage system 20 when the adjustment capability instructed by the adjustment capability command B is as predicted or planned. The charge amount of the power storage system 20 is expressed, for example, by SOC (State Of Charge).

[0028] The interconnection point submodel Ma5 is a model that links the interconnection point power based on market transactions (wholesale power market, supply and demand balancing market) of the wholesale electricity market submodel Ma1 and the supply and demand balancing market submodel Ma2 with the interconnection point power based on the charge and discharge power of the storage battery submodel Ma4. Specifically, the interconnection point submodel Ma5 describes how the power calculated based on the results of electricity buying and selling in the wholesale electricity market and the supply and demand balancing market and the expected value of the activation rate matches the power (charge or discharge) supplied by the storage battery 21 under the expected value scenario Sa at the interconnection point.

[0029] The surplus model Mb includes a storage battery submodel Mb1, a virtual trading market submodel Mb2, a grid connection point submodel Mb3, and a virtual trading management submodel Mb4.

[0030] The storage battery sub-model Mb1 is a model that describes the behavior of the storage battery 21 in the case of a maximum command on the charging side (activation rate 0%). Specifically, the storage battery sub-model Mb1 is a model for calculating the time change in the charge amount of the power storage system 20 in the case of a maximum command on the charging side (hereinafter referred to as "surplus scenario Sb").

[0031] In the case of a maximum command on the charging side, the amount of charge in the storage battery 21 may become surplus. The virtual trading market submodel Mb2 is a model that describes the virtual additional sale of the surplus amount of charge in the storage battery 21 (hereinafter referred to as "virtual power sale"). In other words, the virtual trading market submodel Mb2 is a model that represents the sale of power in a virtual power selling market (virtual power selling market). Furthermore, the virtual trading management submodel Mb4 is a model that describes the behavior of a virtual energy management system (EMS) that manages the virtual power sale in the case of a maximum command on the charging side.

[0032] The interconnection point submodel Mb3 is a model that links the interconnection point power based on market transactions (wholesale power market, supply and demand balancing market) of the wholesale power market submodel Ma1, the supply and demand balancing market submodel Ma2, and the virtual trading market submodel Mb2 in the case of a maximum command on the charging side with the interconnection point power based on the charging and discharging power of the storage battery submodel Mb1. Specifically, the interconnection point submodel Mb3 describes how the power calculated based on the results of power trading in the wholesale power market and the supply and demand balancing market and a 0% activation rate matches the power supplied by the storage battery 21 under the surplus scenario Sb at the interconnection point.

[0033] The shortage model Mc includes a storage battery submodel Mc1, a virtual trading market submodel Mc2, a grid connection point submodel Mc3, and a virtual trading management submodel Mc4.

[0034] The storage battery sub-model Mc1 is a model that describes the behavior of the storage battery 21 in the case of a maximum command on the discharge side (activation rate 100%). Specifically, the storage battery sub-model Mc1 is a model for calculating the change over time in the charge amount of the power storage system 20 in the case of a maximum command on the discharge side (hereinafter referred to as "shortage scenario Sc").

[0035] In the case of a maximum command on the discharge side, the charge amount of the storage battery 21 may be insufficient. The virtual trading market sub-model Mc2 is a model that describes the virtual additional purchase of electricity to make up for the insufficient charge amount of the storage battery 21 (hereinafter referred to as "virtual electricity purchase"). In other words, the virtual trading market sub-model Mc2 is a model that represents electricity purchases in a virtual electricity purchasing market (virtual electricity purchasing market). Furthermore, the virtual trading management sub-model Mc4 is a model that describes the behavior of a virtual energy management system (EMS) that manages virtual electricity purchases in the case of a maximum command on the discharge side.

[0036] The interconnection point sub-model Mc3 is a model that links the interconnection point power based on market transactions (wholesale power market, supply and demand balancing market) of the wholesale power market sub-model Ma1, the supply and demand balancing market sub-model Ma2, and the virtual trading market sub-model Mc2 in the case of a maximum command on the discharge side with the interconnection point power based on the charging and discharging power of the storage battery sub-model Mc1. Specifically, the interconnection point sub-model Mc3 describes how the power calculated based on the results of power trading in the wholesale power market and the supply and demand balancing market and a 100% activation rate matches the power supplied by the storage battery 21 under the shortage scenario Sc (the calculation result by the storage battery sub-model Mc1) at the interconnection point.

[0037] As described above, in the mathematical model M of this embodiment, in addition to the standard expected value scenario Sa, the surplus scenario Sb corresponding to the maximum command on the charging side and the shortage scenario Sc corresponding to the maximum command on the discharging side are managed in parallel with each other.

[0038] The following describes the specific content of the mathematical model M exemplified above. In the following description, the symbol I refers to the number of any one of the 48 frames on the time axis.

[0039] In the following description, decision variables in optimization using the mathematical model M are marked with "d" and constants in optimization are marked with "c." The control device 41 generates a power plan P including decision variables set by optimization using the mathematical model M and transmits it to the control system 30. Note that the power plan P may also include the results of calculations performed on the results of optimization using the mathematical model M.

[0040] [Expectation model Ma] The wholesale electricity market sub-model Ma1 of the expected value model Ma is expressed by the following constraint equation Qa1. PRFESMW d [I]=(ESMW d [I] - EBMW d [I]) * DLTT c *UDMCSTMW c [I] (Qa1) PRFESMW d [I]: Profit from buying and selling electricity in the wholesale electricity market [yen] ESMW d [I]: Total electricity sold in the wholesale electricity market [kW] EBMW d [I]: Total electricity purchased in the wholesale electricity market [kW] DLTT c : The time length of one frame (DLTT c =0.5[h]) UDMCSTMW c [I]: Electricity unit price [yen / kWh]

[0041] The supply and demand adjustment market sub-model Ma2 is expressed by the following constraint equation Qa2. PRFESMB d [I] = ESMB d [I] * UKWCSTMB c [I] + ESMB_EXP d [I] * DLTT c *UDMCSTMB c [I] (Qa2) PRFESMB d [I]: Profit from selling electricity in the supply and demand adjustment market [yen] ESMBd [I]: Total amount of regulation power fluctuation range [kW] UKWCSTMB c [I]: Unit price of fluctuation range of adjustment capacity [yen / kW] ESMB_EXP d [I]: Power output [kW] when the reference value in the expected value scenario Sa is set to 0 UDMCSTMB c [I]: Unit price of electricity [yen / kW] The first term on the right side of the constraint equation Qa2 corresponds to the contracted charge when the adjustment capacity fluctuation range (ΔkW) is contracted in the supply and demand adjustment market. The second term on the right side of the constraint equation Qa2 corresponds to the supplied power (ESMB_EXP d [I]) corresponds to the charge for the amount of electricity generated. Also, the variable ESMB_EXP d [I] is the power supply when the reference value in the expected value scenario Sa is set to 0, and the total amount of fluctuation in the regulation capacity ESMB d This is the power obtained by multiplying [I] by the expected value of the activation rate.

[0042] The revenue calculation sub-model Ma3 is expressed by the following constraint equation Qa3. maximize Value: sum (PRFESMW d [I] + PRFESMB d [I]) (Qa3) That is, the profit calculation submodel Ma3 calculates the profit of buying and selling electricity in the wholesale electricity market. d [I] and the profit from selling electricity in the supply and demand adjustment market (PRFESMB) d This is a process of maximizing the sum of [I] and [I]. For example, the power plan P is optimized using the constraint equation Qa3 as the objective function.

[0043] The battery sub-model Ma4 is expressed by the following constraint equation Qa4. CAPASB c * (SOCSB d [I] - (if I=1 then SOCINISB c else SOCSB d [I-1])) / 100 / DLTT c = - ESBSHU d [I] (Qa4) SOCINISB c : Initial value of the charge amount of the storage battery 21 [kWh] CAPASB c : Capacity of storage battery 21 [kWh] SOCSB d [I]: State of charge (SOC) of the storage battery 21 at the end of the first frame [%] ESBSHU d [I]: Charging and discharging power of the storage battery 21 [kW]

[0044] That is, the charge amount at the end of the first frame SOCSB d [I] and the charge amount SOCSB at the end of the previous (I-1) frame d Difference from [I-1] (SOCSB d [I] - SOCSB d [I-1]) with the capacity of the storage battery 21 CAPASB c By multiplying this, the charge and discharge power of the storage battery 21, ESBSHU d [I] is calculated. Charging amount SOCSB d The time series of [I] corresponds to the expected value scenario Sa. That is, the constraint equation Qa4 is an arithmetic equation for calculating the expected value scenario Sa, which is the time change in the charge amount of the storage battery 21 when the fluctuating power is an expected value within the adjustment capability fluctuation band.

[0045] The interconnection point sub-model Ma5 is expressed by the following constraint equation Qa5. ESBSHU d [I] = ESMW d [I] - EBMW d [I] + ESMB_EXP d [I] (Qa5)

[0046] [Surplus Model Mb] Fig. 4 is an explanatory diagram of the surplus scenario Sb. The surplus scenario Sb illustrated in Fig. 4 is a time change in the charge amount of the storage battery 21 when the regulation capability commanded by the regulation capability command B is biased to the maximum extent toward the charging side. Specifically, the surplus scenario Sb corresponds to a case where the activation rate is maintained at 0% (maximum command on the charging side) for all 48 frames in total.

[0047] In this embodiment, it is assumed that at the end of the Jth frame (J=0-48) in the process of the surplus scenario Sb, the adjustment capability commanded by the adjustment capability command B changes to the maximum command on the discharge side (activation rate 100%) (hereinafter referred to as "command reversal"). In the following explanation, the change over time in the charge amount of the storage battery 21 when the command reversal from the maximum command on the charge side to the maximum command on the discharge side occurs in the Jth frame is referred to as the "Jth surplus sub-scenario Ssb[J]."

[0048] Figure 5 illustrates a total of 49 surplus subscenario Ssb[J] (J = 0-48). The Jth surplus subscenario Ssb[J] corresponds to a case where a command reversal occurs from the maximum charge command to the maximum discharge command at the end of the Jth frame out of a total of 49 frames from the 0th frame (the frame immediately before the planning period) to the 48th frame. Of the 49 surplus subscenario Ssb[J], there is one surplus subscenario Ssb

[48] in which the adjustment capability does not change to the maximum discharge command until the final 48th frame, which corresponds to one surplus scenario Sb in which the maximum charge command is maintained throughout the entire 48 frames. Note that the 0th (J = 0) surplus subscenario Ssb[J] corresponds to a case where a command reversal occurs at the start of the 1st frame, resulting in the maximum discharge command being maintained throughout the entire 48 frames.

[0049] Considering the above relationship, the storage battery sub-model Mb1 of the surplus model Mb is expressed by the following constraint equation Qb1. CAPASB c * (SOCSB_MAX d [I,J] - (if I=1 then SOCINISB_MAX c else SOCSB_MAXd [I-1,J])) / 100 / DLTT c = - (if I>J then ESBSHU_MAX_MIN d [I] else ESBSHU_MAX_MAX d [I]) (Qb1) SOCSB_MAX d [I, J]: State of charge (SOC) [%] of the storage battery 21 in the surplus scenario Sb SOCINISB_MAX c : Maximum initial value of the state of charge (SOC) of the storage battery 21 [%] ESBSHU_MAX_MIN d [I]: Charging and discharging power of the storage battery 21 at the maximum command on the discharging side [kW] ESBSHU_MAX_MAX d [I]: Charging / discharging power of the storage battery 21 at the maximum command on the charging side [kW]

[0050] As shown in the constraint Qb1, in the Jth surplus sub-scenario Ssb[J], in each frame before the Jth frame (I≦J), the charge amount SOCSB_MAX at the end of the frame is d [I,J] and the charge amount SOCSB_MAX at the end of the previous (I-1) frame d Difference from [I-1,J](SOCSB_MAX d [I,J]-SOCSB_MAX d The charge / discharge power (left side of constraint equation Qb1) corresponding to [I-1,J]) is the charge / discharge power ESBSHU_MAX_MAX corresponding to the maximum command on the charge side in the surplus model. d On the other hand, in the Jth surplus sub-scenario Ssb[J], in each frame after the Jth frame (I>J), the charge amount at the end of that frame is set to SOCSB_MAX d [I,J] and the charge amount SOCSB_MAX at the end of the previous (I-1) frame d Difference from [I-1,J](SOCSB_MAX d [I,J]-SOCSB_MAX dThe charge / discharge power (left side of constraint equation Qb1) corresponding to [I-1,J] is the charge / discharge power ESBSHU_MAX_MIN corresponding to the maximum command on the discharge side in the surplus model. d It is set to [I].

[0051] As can be understood from the above explanation, of the 49 surplus subscenarios Ssb[J] from 0th to 48th, the 48 surplus subscenarios Ssb[J] (J=0-47) from 0th to 47th correspond to the case where the regulation power changes from the maximum command on the charge side to the maximum command on the discharge side in the Jth frame. On the other hand, of the 49 surplus subscenarios Ssb[J] from 0th to 48th, the final 48th surplus subscenario Ssb

[48] is the surplus scenario Sb in which the regulation power is maintained at the maximum command on the charge side throughout all 48 frames.

[0052] As described above, the constraint equation Qb1 of the battery sub-model Mb1 in the surplus model Mb is (1) A constraint equation (J=48) for calculating the surplus scenario Sb (=Ssb

[48] ), which is the time change in the charge amount of the storage battery 21 when the adjustment capability is maximally biased toward the charge side; (2) A constraint equation (J = 0-47) for calculating the surplus sub-scenario Ssb[J], which is the time change in the charge amount of the storage battery 21 when the power fluctuations during the target period in the surplus scenario Sb are maximally biased toward the discharge side. Including the total charge amount SOCSB_MAX d The time series of [I,48] corresponds to the surplus scenario Sb, and the charge amount SOCSB_MAX over all frames d The time series [I,J] (J=0-47) corresponds to the surplus sub-scenario Ssb[J].

[0053] The interconnection point sub-model Mb3 of the surplus model Mb is expressed by the following constraint equations Qb31 and Qb32. ESBSHU_MAX_MIN d [I] = ESMW d [I] - EBMW d [I] + ESMB_MAXd [I] + ESMW_TEMP d [I] (Qb31) ESBSHU_MAX_MAX d [I] = ESMW d [I] - EBMW d [I] + ESMB_MIN d [I] + ESMW_TEMP d [I] (Qb32) ESMW_TEMP d [I]: Virtually sold power (virtual additional discharge power) [kW] ESMB_MAX d [I]: Output power [kW] when the reference value corresponding to the maximum command on the discharge side is set to 0 ESMB_MIN d [I]: Output power [kW] when the reference value corresponding to the maximum command on the charging side is set to 0 Virtual additional discharge power ESMW_TEMP in constraint equation Qb31 and constraint equation Qb32 d [I] is the power virtually sold to the virtual trading market sub-model Mb2, and is the power in the discharging direction that is added in common to the surplus scenario Sb and the surplus sub-scenario Ssb[J].

[0054] The virtual trade management sub-model Mb4 of the surplus model Mb includes the following constraint equation Qb41: SOCSB_MAX d [I,48] <= SOCUPPERSB c (Qb41) That is, the charge amount SOCSB_MAX at the end of any frame in the 48th surplus sub-scenario Ssb[J] (i.e., surplus scenario Sb) d [I,48] is the predetermined upper limit SOCUPPERSB c It is limited to the following numerical value: As described above, the constraint Qb41 is a constraint that limits the upper limit of the surplus scenario Sb.

[0055] In the surplus scenario Sb where the maximum command on the charging side is maintained over all frames, the charge amount SOCSB_MAX is determined by the above constraint equation Qb41. d[I,48] is the upper limit SOCUPPERSB c On the other hand, in the surplus sub-scenario Ssb[J] (J=0-47) where the command reversal occurs at the end of the Jth frame from the maximum command on the charge side to the maximum command on the discharge side, the charge amount SOCSB_MAX d There is a possibility that [I,J] may decrease excessively. Therefore, the virtual trade management sub-model Mb4 further includes the following constraint Qb42: SOCSB_MAX d [I,J] >= SOCLOWERSB c (Qb42)

[0056] As per constraint Qb42, in the surplus sub-scenario Ssb[J] (J=1-47) when the command reversal from the maximum command on the charge side to the maximum command on the discharge side occurs at the end of the Jth frame, the charge amount SOCSB_MAX at the end of any frame is d [I,J] is the given lower bound SOCLOWERSB c As described above, the constraint Qb42 is a constraint that limits the lower limit of the surplus sub-scenario Ssb[J].

[0057] However, the constraint by constraint equation Qb42 is limited to a specific period (hereinafter referred to as the "target period") in the surplus sub-scenario Ssb[J]. The start point of the target period is the point at which the command reversal from the maximum command on the charge side to the maximum command on the discharge side occurs (the end point of the Jth frame). The end point of the target period is a point a predetermined length (for example, a time length corresponding to a predetermined number of frames) after the start point of the target period. The constraint by constraint equation Qb42 is invalid for the period of the surplus sub-scenario Ssb[J] after the target period has elapsed.

[0058] There is a certain amount of deviation between the time of replanning (hereinafter referred to as the "specific time point") and the time when the traded power based on this replanning is charged or discharged to the storage battery 21 (hereinafter referred to as the "power trading time point"). In order to associate the specific time point with the actual power trading time point, the surplus model Mb includes the following constraint equation Qb43: ESMW_TEMP_DATA d[I,REPLAN_TIMING d [I]]=ESMW_TEMP d [I] (Qb43) REPLAN_TIMING d [I]: The frame starting from the most recent specific point in time at which replanning for buying and selling in frame I is possible. As can be seen from constraint Qb43, the variable ESMW_TEMP_DATA d [I,REPLAN_TIMING d [I]] is the variable REPLAN_TIMING d This is the power sold (virtual additional discharge power) that is planned at the start point of the frame indicated by [I] and in which the power trading frame is the Ith frame.

[0059] The virtual trade management sub-model Mb4 of the surplus model Mb further includes the following constraint equation Qb44 and constraint equation Qb45. sum ESMW_TEMP_DATA d [I,K] = ESMW_TEMP_DATA2 d [J] (Qb44) ESMW_TEMP_DATA2 d [J] * DLTT c <= CAPASB c * (SOCSB_MAX d [J-1,48] - SOCSB d [J-1]) / 100 (Qb45) In the sum of constraint equation Qb44, the variable ESMW_TEMP_DATA d The range in which the elements of [I,K] are added is limited. Specifically, for any piece J (J=0-47), the variable ESMW_TEMP_DATA d The addition is limited to the range of [I,K] where I>=J and K<=J. Variable ESMW_TEMP_DATA d In the range of I>=J in [I,K], the Jth frame and onwards are the virtual additional discharge power ESMW_TEMP that will be used for power trading. d [I] is saved. Also, the variable ESMW_TEMP_DATA dIn the range of K<=J in [I,K], the virtual additional discharge power ESMW_TEMP is a specific point in time before the start of the Jth frame. d [I] is saved. Therefore, the variable ESMW_TEMP_DATA2 d [J] is the virtual additional discharge power ESMW_TEMP for which replanning has been completed at the start of the Jth frame but actual trading has not been completed. d It corresponds to the sum of [I].

[0060] Figure 6 shows the variable ESMW_TEMP_DATA2 d The virtual additional discharge power ESMW_TEMP is added up when calculating [J] d This is an explanatory diagram illustrating the relationship of [I] with respect to the range of I (hereinafter referred to as the "specific period") with respect to J. When the start point of the command reversal frame in FIG. 6 is set as a specific time point, the range of possible frames for power trading traded through rescheduling at that specific time point is set as the trading frame. When J=8, at the start point of the 8th frame, power trading traded through rescheduling at least from the start point of the 5th frame onward has not been completed. Therefore, the start point of the specific period is before the start point of the 5th frame. Also, the frame for power trading traded through rescheduling at the start point of the 8th frame is at least from the 11th frame onward. Therefore, the end point of the specific period is after the end point of the 11th frame. Therefore, when J=8, for example, the specific period in FIG. 6 includes the range from the 5th frame to the 11th frame.

[0061] The left side of constraint equation Qb45 is the virtual additional discharge power ESMW_TEMP during a specific period when the start point of the Jth frame is set as a specific time point. d The right side of the constraint Qb45 is the charge amount SOCSB_MAX at the start of the Jth frame in the surplus scenario Sb. d [J-1,48] and the charge amount SOCSB at the start of the Jth frame in the expected value scenario Sa d Difference from [J-1] (SOCSB_MAX d [J-1,48]-SOCSB d [J-1]).

[0062] As described above, the constraint equation Qb45 is set to the virtual additional discharge power ESMW_TEMP according to the surplus difference. d Constraint [I]. Specifically, constraint Qb45 is the difference (ESMW_TEMP_DATA2 d [J]*DLTT c ) does not exceed the surplus difference, d [I] is limited. That is, the virtual additional discharge power ESMW_TEMP scheduled in the rescheduling up to a specific point in time is limited. d The total amount of [I] (i.e., the power for which replanning has been completed but the trading has not been completed) is limited to be equal to or less than the surplus difference at a specific time point. As explained above, the surplus model Mb in this embodiment is the charge amount SOCSB_MAX in the surplus scenario Sb. d Based on [I,48], the hypothetical additional discharge power ESMW_TEMP in the discharge direction for the excess scenario Sb d Add [I].

[0063] In the actual operation of the power system 100, replanning is performed based on the results of measuring the actual value of the charge amount of the storage battery 21. The specific time point corresponding to the surplus difference of the constraint equation Qb45 is the time point at which the actual value of the charge amount of the storage battery 21 used for replanning is measured. In addition, the end point of the target period mentioned above is the end point of the specific period when the start point of the target period (the time point at which the command reversal occurs) is set as the specific time point.

[0064] [Missing Model Mc] Fig. 7 is an explanatory diagram of the shortage scenario Sc. The shortage scenario Sc illustrated in Fig. 7 is a time change in the charge amount of the storage battery 21 when the adjustment capability commanded by the adjustment capability command B is biased to the maximum extent toward the discharge side. Specifically, the shortage scenario Sc corresponds to a case where the activation rate is maintained at 100% (maximum command on the discharge side) over all 48 frames.

[0065] In this embodiment, it is assumed that at the end of the Jth frame (J=0-48) in the process of the shortage scenario Sc, the adjustment capability commanded by the adjustment capability command B changes to the maximum command on the charge side (activation rate 0%) (command reversal). In the following explanation, the change over time in the charge amount of the storage battery 21 when the command reversal from the maximum command on the discharge side to the maximum command on the charge side occurs in the Jth frame is referred to as the "Jth shortage sub-scenario Ssc[J]."

[0066] FIG. 8 illustrates a total of 49 shortage subscenario Ssc[J] (J = 0-48). The Jth shortage subscenario Ssc[J] corresponds to a case where a command reversal occurs from the maximum command on the discharge side to the maximum command on the charge side at the end of the Jth frame out of a total of 49 frames from the 0th frame (the frame immediately before the planning period) to the 48th frame. Of the 49 shortage subscenario Ssc[J], one shortage subscenario Ssc

[48] , in which the adjustment capability does not change to the maximum command on the charge side until the final 48th frame, corresponds to one shortage scenario Sc in which the maximum command on the discharge side is maintained throughout the entire 48 frames. Note that the 0th (J = 0) shortage subscenario Ssc[J] corresponds to a case where a command reversal occurs at the start of the 1st frame, resulting in the maximum command on the charge side being maintained throughout the entire 48 frames.

[0067] Considering the above relationship, the battery sub-model Mc1 of the shortage model Mc is expressed by the following constraint equation Qc1. CAPASB c * (SOCSB_MIN d [I,J] - (if I=1 then SOCINISB_MIN d else SOCSB_MIN d [I-1,J])) / 100 / DLTT c = - (if I>J then ESBSHU_MIN_MAX d [I] else ESBSHU_MIN_MIN d [I]) (Qc1) SOCSB_MIN d[I, J]: State of charge (SOC) of the storage battery 21 in the shortage scenario Sc [%] SOCINISB_MIN c : Minimum initial value of the state of charge (SOC) of the storage battery 21 [%] ESBSHU_MIN_MAX d [I]: Charging / discharging power of the storage battery 21 at the maximum command on the charging side [kW] ESBSHU_MIN_MIN d [I]: Charging and discharging power of the storage battery 21 at the maximum command on the discharging side [kW]

[0068] As per the constraint Qc1, in the Jth shortage sub-scenario Ssc[J], in each frame before the Jth frame (I≦J), the charge amount SOCSB_MIN at the end of the frame is d [I,J] and the charge amount SOCSB_MIN at the end of the previous (I-1) frame d Difference from [I-1,J] (SOCSB_MIN d [I,J]-SOCSB_MIN d The charge / discharge power (left side of constraint Qc1) corresponding to [I-1,J] is the charge / discharge power ESBSHU_MIN_MIN corresponding to the maximum command on the discharge side in the shortage model. d On the other hand, in the Jth shortage sub-scenario Ssc[J], in each frame after the Jth frame (I>J), the charge amount SOCSB_MIN at the end of that frame is set. d [I,J] and the charge amount SOCSB_MIN at the end of the previous (I-1) frame d Difference from [I-1,J] (SOCSB_MIN d [I,J]-SOCSB_MIN d The charge / discharge power (left side of constraint equation Qc1) corresponding to [I-1,J]) is the charge / discharge power equivalent to the maximum command on the charge side in the shortage model. d It is set to [I].

[0069] As can be understood from the above explanation, of the 49 shortage subscenarios Ssc[J] from 0th to 48th, the 48 shortage subscenarios Ssc[J] (J=0-47) from 0th to 47th correspond to the case where the regulation power changes from the maximum command on the discharge side to the maximum command on the charge side in the Jth frame. On the other hand, of the 49 shortage subscenarios Ssc[J] from 0th to 48th, the final 48th shortage subscenario Ssc

[48] is the shortage scenario Sc in which the regulation power is maintained at the maximum command on the discharge side throughout all 48 frames.

[0070] As described above, the constraint equation Qc1 of the battery sub-model Mc1 in the shortage model Mc is (1) A constraint equation (J=48) for calculating the shortage scenario Sc, which is the time change in the charge amount of the storage battery 21 when the adjustment capability is biased to the maximum extent on the discharge side; (2) A constraint equation (J = 0-47) for calculating the shortage sub-scenario Ssc[J], which is the time change in the charge amount of the storage battery 21 when the power fluctuations during the target period in the shortage scenario Sc are maximally biased toward the charge side. Including the total charge amount SOCSB_MIN d The time series [I,48] corresponds to the shortage scenario Sc, and the charge amount SOCSB_MIN over all frames d The time series [I,J] (J=0-47) corresponds to the shortage sub-scenario Ssc[J].

[0071] The interconnection point sub-model Mc3 of the shortage model Mc is expressed by the following constraint equations Qc31 and Qc32. ESBSHU_MIN_MIN d [I] = ESMW d [I] - EBMW d [I] + ESMB_MAX d [I] - EBMW_TEMP d [I] (Qc31) ESBSHU_MIN_MAX d [I] = ESMW d [I] - EBMW d[I] + ESMB_MIN d [I] - EBMW_TEMP d [I] (Qc32) EBMW_TEMP d [I]: Virtually purchased power (virtual additional charging power) [kW] ESMB_MAX d [I]: Output power [kW] when the reference value corresponding to the maximum command on the charging side is set to 0 ESMB_MIN d [I]: Output power [kW] when the reference value corresponding to the maximum command on the discharge side is set to 0 Virtual additional charging power EBMW_TEMP in constraint equation Qc31 and constraint equation Qc32 d [I] is the power virtually purchased from the virtual buying and selling market sub-model Mc2, and is the power in the charging direction that is added in common to the shortage scenario Sc and the shortage sub-scenario Ssc[J].

[0072] The virtual trade management sub-model Mc4 of the shortage model Mc includes the following constraint equation Qc41: SOCSB_MIN d [I,48] >= SOCLOWERSB c (Qc41) That is, the charge amount SOCSB_MIN at the end of any frame in the 48th shortage sub-scenario Ssc[J] (i.e., shortage scenario Sc) d [I,48] is the given lower bound SOCLOWERSB c As described above, the constraint equation Qc41 is a constraint equation that limits the lower limit of the shortage scenario Sc.

[0073] In the shortage scenario Sc, where the maximum command on the discharge side is maintained over the entire frame, the charge amount SOCSB_MIN is determined by the above constraint Qc41. d [I,48] is the lower limit SOCLOWERSB c On the other hand, in the shortage sub-scenario Ssc[J] (J=1-47) where the command reversal occurs at the end of the Jth frame from the maximum command on the discharge side to the maximum command on the charge side, the charge amount SOCSB_MIN dThere is a possibility that [I,J] may increase excessively. Therefore, the virtual trade management sub-model Mc4 further includes the following constraint equation Qc42: SOCSB_MIN d [I,J] <= SOCUPPERSB c (Qc42)

[0074] As per constraint Qc42, in the shortage sub-scenario Ssc[J] (J=1-47) when the command reversal from the maximum command on the discharge side to the maximum command on the charge side occurs at the end of the Jth frame, the charge amount SOCSB_MIN at the end of any frame is d [I,J] is the predetermined upper bound SOCUPPERSB c It is limited to the following numerical value. As described above, constraint equation Qc42 is a constraint equation that limits the upper limit of the shortage subscenario Ssc[J]. However, the constraints imposed by constraint equation Qc42 are limited to the target period of the shortage subscenario Ssc[J]. In other words, the constraints imposed by constraint equation Qc42 are invalidated for the period after the target period of the shortage subscenario Ssc[J].

[0075] As described above with reference to Figure 6, there is a certain amount of deviation between the specific time point (the time point of replanning) and the actual power trading frame. In order to associate the specific time point with the actual power trading frame, the shortage model Mc includes the following constraint equation Qc43. EBMW_TEMP_DATA d [I,REPLAN_TIMING d [I]]=EBMW_TEMP d [I] (Qc43) REPLAN_TIMING d [I]: The frame starting from the most recent specific point in time at which replanning for buying and selling in frame I is possible. As can be seen from constraint Qc43, the variable EBMW_TEMP_DATA d [I,REPLAN_TIMING d [I]] is the variable REPLAN_TIMING d This is the purchased power (virtual additional charging power) that is planned at the start point of the frame indicated by [I] and in which the frame for power trading is the Ith frame.

[0076] The virtual trade management sub-model Mc4 of the shortage model Mc further includes the following constraint equations Qc44 and Qc45. sum EBMW_TEMP_DATA d [I,K] = EBMW_TEMP_DATA2 d [J] (Qc44) EBMW_TEMP_DATA2 d [J] * DLTT c <= CAPASB c * (SOCSB d [J-1] - SOCSB_MIN d [J-1,48]) / 100 (Qc45) In the sum of constraint equation Qc44, the variable EBMW_TEMP_DATA d The range in which the elements of [I,K] are added is limited. Specifically, for any piece J (J=0-47), the variable EBMW_TEMP_DATA d The addition is limited to the range of [I,K] where I>=J and K<=J. Variable EBMW_TEMP_DATA d In the range of I>=J in [I,K], the virtual additional charging power EBMW_TEMP is the power trading piece from the Jth piece onwards. d [I] is saved. Also, the variable EBMW_TEMP_DATA d In the range of K<=J in [I,K], the virtual additional charging power EBMW_TEMP is a specific point in time before the start of the Jth frame. d [I] is saved. Therefore, the variable EBMW_TEMP_DATA2 d [J] is the virtual additional charging power EBMW_TEMP for which replanning has been completed at the start of the Jth frame but actual trading has not been completed. d It corresponds to the sum of [I].

[0077] The left side of the constraint equation Qc45 is the virtual additional charging power EBMW_TEMP during a specific period when the start point of the Jth frame is set as a specific time point. dThe right side of the constraint equation Qc45 is the charge amount SOCSB at the start of the Jth frame in the expected value scenario Sa. d [J-1] and the charge amount SOCSB_MIN at the start of the Jth frame in the shortage scenario Sc d Difference from [J-1,48] (SOCSB d [J-1]-SOCSB_MIN d [J-1,48]).

[0078] As described above, the constraint equation Qc45 determines the virtual additional charging power EBMW_TEMP according to the difference. d Constraint [I]. Specifically, constraint Qc45 is the difference (EBMW_TEMP_DATA2 d [J]*DLTT c ) does not exceed the shortage difference, d [I] is limited, i.e., the virtual additional charging power EBMW_TEMP scheduled at a specific time. d The total amount of [I] (i.e., electricity for which replanning has been completed but trading has not yet been completed) is limited to be less than the shortfall at a specific point in time. As described above, the shortage model Mc in this embodiment is a charging amount SOCSB_MIN in the shortage scenario Sc. d Based on [I,48], the hypothetical additional charging power EBMW_TEMP in the charging direction for the shortage scenario Sc d Add [I].

[0079] As described above, in the first embodiment, the mathematical model M used to generate the power plan P includes (1) constraint equations (Qb31, Qb32) that add hypothetical additional discharging power in the discharging direction to the surplus scenario Sb based on the charge amount in the surplus scenario Sb, and (2) constraint equations (Qc31, Qc32) that add hypothetical additional charging power in the charging direction to the shortage scenario Sc based on the charge amount in the shortage scenario Sc. Therefore, it is possible to generate a power plan P that appropriately ensures the feasibility of adjusting the charge amount, taking into account the power sale when the charge amount of the storage battery 21 is in surplus and the power purchase when the charge amount is insufficient.

[0080] For example, the power system 100 can be operated in three ways: posiwatt operation, which generates power in accordance with the adjustment capability command B; negawatt operation, which suppresses demand in accordance with the adjustment capability command B; and negative-positive operation, which includes both. When only posiwatt operation is assumed, the storage battery 21 continues to discharge while adjustment capability is being provided, which poses a risk of insufficient charge. Therefore, by estimating the activation rate to 100%, the possibility of insufficient charge can be sufficiently reduced. On the other hand, when only negawatt operation is assumed, the storage battery 21 continues to charge while adjustment capability is being provided, which poses a risk of surplus charge. Therefore, by estimating the activation rate to 0%, the possibility of surplus charge can be sufficiently reduced. However, in negative-positive operation, both the risk of insufficient charge and the risk of surplus charge are assumed, so a measure of fixing the activation rate to a specific value is not effective. In this embodiment, the power plan P is generated taking into account both the surplus scenario Sb and the shortage scenario Sc, so that both the risk of a shortage of charge amount and the risk of an excess of charge amount can be reduced in negative-positive operation.

[0081] Furthermore, in this embodiment, the virtual additional discharge power is limited according to the surplus difference, which is the difference between the charge amount in the surplus scenario Sb and the charge amount in the expectation scenario Sa, and the virtual additional charge power is limited according to the shortage difference, which is the difference between the charge amount in the expectation scenario Sa and the charge amount in the shortage scenario Sc. That is, power sales in excess of the surplus for the expectation scenario Sa and power purchases in excess of the shortage for the expectation scenario Sa are avoided. Therefore, the possibility of generating an infeasible power plan P can be reduced. In particular, in this embodiment, the additional amount of virtual additional discharge power in a specific period is limited so as not to exceed the surplus difference, and the additional amount of virtual additional charge power in a specific period is limited so as not to exceed the shortage difference. Therefore, a power plan P with even higher feasibility can be generated.

[0082] In this embodiment, the charge amount SOCSB_MAX of the surplus sub-scenario Ssb[J] when the adjustment capability is biased to the discharge side to the maximum extent during the target period of the surplus scenario Sb isd Lower bound SOCLOWERSB on [I,J] c The charging amount SOCSB_MIN of the shortage sub-scenario Ssc[J] when the adjustment power is maximally biased toward the charging side during the target period of the shortage scenario Sc is d Upper bound SOCUPPERSB on [I,J] c Therefore, it is possible to generate a power plan P that ensures the feasibility of adjusting the charge amount.

[0083] B: Modified example Specific modified embodiments that can be added to each of the embodiments exemplified above are exemplified below. Two or more embodiments arbitrarily selected from the following examples may be appropriately combined within the scope of not being mutually contradictory.

[0084] (1) In the above-described embodiment, attention has been focused on the storage battery 21, but the target of optimization using the mathematical model M is not limited to the storage battery 21. For example, the present disclosure may be applied to the management of a hydrogen system using a water electrolysis device or a fuel cell, or a hydrogen system combining a water electrolysis device and a fuel cell. In other words, the target of optimization using the mathematical model M includes a storage device for an energy medium that can be converted into electricity bidirectionally or unidirectionally, and is comprehensively expressed as a power storage device that can store electricity.

[0085] (2) The target of the power plan P optimized using the mathematical model M is not limited to the adjustment capacity (ΔkW) of the supply and demand adjustment market. For example, a plan for adjustment capacity provided based on a contract for utilizing surplus capacity is also optimized using the same mathematical model M as in the above-mentioned embodiment. A contract for utilizing surplus capacity is a contract that requests the provision of adjustment capacity when there is room for the provision of adjustment capacity, regardless of whether or not there is a contract for adjustment capacity. By adding a reward according to the amount of adjustment capacity provided to the objective function (e.g., constraint equation Qa3) to be optimized in the mathematical model M, the amount of adjustment capacity provided and the time period can be planned.

[0086] (3) In the above embodiment, the mathematical model M includes both the surplus model Mb and the deficient model Mc. However, one of the surplus model Mb and the deficient model Mc may be omitted from the mathematical model M.

[0087] (4) In the above-described embodiment, attention was focused on the upward adjustment capability that increases the interconnection point power, but the above-described embodiment can also be applied to the planning of the downward adjustment capability that decreases the interconnection point power. The downward adjustment capability is the adjustment capability in the direction of eliminating surplus power in the power grid 10.

[0088] (5) In a configuration in which the energy storage system 20 is installed next to a power supply facility (e.g., a renewable energy power generation facility such as a solar power generation facility) where fluctuations in power generation or power demand are likely to occur, it is also possible to replace the expected fluctuation range of the power supply facility with the adjustment power fluctuation range.

[0089] (6) In the above-described embodiment, the charge / discharge efficiency of the storage battery 21 is not taken into consideration. d [I], ESBSHU_MIN_MIN d [I], ESBSHU_MIN_MAX d [I], ESBSHU_MAX_MIN d [I], ESBSHU_MAX_MAX d The above-described embodiment is also applicable to a model in which [I]) is corrected by charge / discharge efficiency or charge / discharge loss. The above-described embodiment is also applicable to a model in which the excess difference or the shortage difference is corrected by charge / discharge efficiency or charge / discharge loss.

[0090] (7) In the above-described embodiment, the electricity traded in the wholesale electricity market and the balancing market and the charging / discharging power of the storage battery 21 are linked at the interconnection point 11. However, the above-described embodiment is also applicable when other elements are added. Specifically, the right-hand side of the interconnection point sub-model (Qa5, Qb31, Qb32, Qc31, Qc32) may be added with electricity based on bilateral transactions with a retail electricity supplier or a specified wholesale supplier or load-following supply, or may be replaced with the wholesale electricity market (including a virtual buying and selling market). Furthermore, the left-hand side of the interconnection point sub-model may be added with the electricity of other storage batteries, on-site loads, water electrolysis equipment, fuel cells, or other devices that supply or consume electricity.

[0091] (8) In the above-described embodiment, the objective function is to maximize the profits of the wholesale electricity market and the supply-demand balancing market, but the content or conditions of the objective function may be changed arbitrarily. The above-described embodiment is applicable to any configuration in which any objective function is applied.

[0092] (9) All constraints containing inequalities in the above-described embodiment are applicable to models written based on the penalty method. For example, in the constraint (Qb41), the SOCSB_MAX d [I,48] is the right-hand side of SOCUPPERSB c However, it may be written in such a way that a decision variable that can relax the constraint is added to the right-hand side and a penalty according to the size of this decision variable is subtracted from the objective function.

[0093] (10) Even if any constraint equations not included in the above-mentioned embodiments are included in the mathematical model, the above-mentioned embodiments are deemed to be applied as long as the constraint equations described in the above-mentioned embodiments (including equivalent or similar constraint equations) are included.

[0094] (11) As described above, the functions of the management system 40 according to the above-described embodiment are realized through cooperation between one or more processors constituting the control device 41 and a program stored in the storage device 42. The programs exemplified above can be provided in a form stored on a computer-readable recording medium and installed on a computer. The recording medium is, for example, a non-transitory recording medium, such as an optical recording medium (optical disk) such as a CD-ROM, but also includes any known form of recording medium, such as a semiconductor recording medium or a magnetic recording medium. Note that a non-transitory recording medium includes any recording medium other than a transitory, propagating signal, and does not exclude volatile recording media. Furthermore, in a configuration in which a distribution device distributes a program via a communication network, the recording medium storing the program in the distribution device corresponds to the non-transitory recording medium described above.

[0095] (12) The term "nth" (n is a natural number) in this application is used only as a formal and convenient label to distinguish each element in the description and does not have any substantive meaning. Therefore, there is no room for restrictive interpretation of the position or order of each element based on the term "nth."

[0096] C: Notes From the above-described exemplary embodiments, the following configurations can be understood, for example: Note that, to facilitate understanding of each embodiment, reference numerals in the specification or drawings are conveniently written in parentheses below, but this is not intended to limit the present disclosure.

[0097] A management system 40 (40) according to one aspect (aspect 1) of the present disclosure is a management system 40 (40) that generates, by using a mathematical model (M), a power plan (P) related to charging and discharging of a power storage device (21), the power plan (P) including a plan of variable power that fluctuates within a specific fluctuation range, and the mathematical model (M) includes a constraint equation (Qb1) for calculating a surplus scenario (Sb) that is a time change in the charge amount of the power storage device (21) when the variable power is biased to the charging side to the maximum, a constraint equation (Qc1) for calculating a shortage scenario (Sc) that is a time change in the charge amount of the power storage device (21) when the variable power is biased to the discharging side to the maximum, a constraint equation (Qb41) that limits an upper limit of the surplus scenario (Sb), a constraint equation (Qc41) that limits a lower limit of the shortage scenario (Sc), and a hypothetical additional discharge power (ESMW_TEMP) in a discharging direction with respect to the surplus scenario (Sb) based on the charge amount in the surplus scenario (Sb). d [I]) in the shortage scenario (Sc), and the virtual additional charging power (EBMW_TEMP d According to the above configuration, the mathematical model (M) used to set the power plan (P) includes the constraint equations (Qc31, Qc32) that add the virtual additional discharge power (ESMW_TEMP [I]) in the discharge direction for the surplus scenario (Sb) based on the charge amount in the surplus scenario (Sb). d (2) the virtual additional charging power (EBMW_TEMP d Therefore, it is possible to generate a power plan (P) that ensures the feasibility of adjusting the charge amount, taking into consideration the sale of power when the charge amount of the power storage device (21) is in excess and the purchase of power when the charge amount is insufficient.

[0098] In a specific example (aspect 2) of aspect 1, the mathematical model (M) further includes a constraint equation (Qa4) for calculating an expected value scenario (Sa) that is a time change in the charge amount of the power storage device (21) when the fluctuating power is an expected value within the fluctuation range, and the virtual additional discharge power (ESMW_TEMP) is calculated according to a surplus difference that corresponds to a difference between the charge amount in the surplus scenario (Sb) and the charge amount in the expected value scenario (Sa). d [I]) (Qb44, Qb45), and the virtual additional charging power (EBMW_TEMP d In the above configuration, the virtual additional discharge power (ESMW_TEMP [I]) is limited according to the surplus difference, which is the difference between the charge amount in the surplus scenario (Sb) and the charge amount in the expected value scenario (Sa) (Qc44, Qc45). d [I]) is limited, and the virtual additional charging power (EBMW_TEMP d [I]) is limited. That is, power sales that exceed the surplus amount for the expected value scenario (Sa) and power purchases that exceed the shortage amount for the expected value scenario (Sa) are avoided. Therefore, it is possible to reduce the possibility of generating an infeasible power plan (P).

[0099] In a specific example (aspect 3) of aspect 2, the mathematical model (M) calculates the virtual additional discharge power (ESMW_TEMP) for a specific period. d [I]) integrated value (ESMW_TEMP_DATA2 d [J] * DLTT c ) so as not to exceed the surplus difference at a specific time point within the specific period; and d [I]) integrated value (EBMW_TEMP_DATA2 d [J] * DLTT cIn the above configuration, the virtual additional discharge power (ESMW_TEMP) in the specific period is further limited to the constraint equations (Qc44, Qc45) that limit the virtual additional discharge power (ESMW_TEMP) in the specific period so that it does not exceed the shortage difference at the specific time point. d [I]) is limited so that it does not exceed the surplus difference, and the virtual additional charging power (EBMW_TEMP d The additional amount of [I] is limited so that it does not exceed the shortfall. Therefore, a more feasible power plan (P) can be generated.

[0100] In a specific example (aspect 4) of aspect 3, the specific point in time is a point in time at which an actual value of the charge amount of the power storage device (21) used for replanning is measured, and the specific period is a period that begins at a point in time before the specific point in time at which the actual value is measured and during which a period in which the charge amount of the power storage device (21) can be changed by replanning based on the actual value begins after the specific point in time, and ends at a point in time after the start of a period in which the charge amount of the power storage device (21) can be changed by replanning based on the actual value measured at the specific point in time.

[0101] In a specific example (aspect 5) of aspect 4, the mathematical model (M) further includes a constraint equation (Qb1) for calculating a surplus sub-scenario (Ssb[J]) representing a time change in the charge amount of the power storage device (21) when the fluctuating power during the target period in the surplus scenario (Sb) is biased to the maximum toward discharge, a constraint equation (Qc1) for calculating a shortage sub-scenario (Ssc[J]) representing a time change in the charge amount of the power storage device (21) when the fluctuating power during the target period in the shortage scenario (Sc) is biased to the maximum toward charge, a constraint equation (Qb42) for limiting a lower limit of the charge amount of the surplus sub-scenario (Ssb[J]) during the target period, and a constraint equation (Qc42) for limiting an upper limit of the charge amount of the shortage sub-scenario (Ssc[J]) during the target period. For example, if additional power sale is planned when there is a surplus of charge, but fluctuating power is biased to the maximum toward discharge before the actual power sale, a shortage of charge may occur. Similarly, for example, if additional power purchase is planned when the charge amount is insufficient, but variable power is biased toward charging until the actual power purchase, a surplus of charge may occur. In aspect 5, a lower limit is imposed on the charge amount in the surplus sub-scenario (Ssb[J]) when variable power is biased to the maximum toward discharging during the target period of the surplus scenario (Sb), and an upper limit is imposed on the charge amount in the shortage sub-scenario (Ssc[J]) when variable power is biased to the maximum toward charging during the target period of the shortage scenario (Sc). Therefore, it is possible to generate a power plan (P) that ensures the feasibility of adjusting the charge amount.

[0102] In a specific example (Aspect 6) of Aspect 5, the target period is a period from the specific time point to the end point of the specific period. [Explanation of symbols]

[0103] 100...power system, 10...power system, 11...interconnection point, 20...energy storage system, 21...storage battery, 22...control device, 23...transformer, 30...control system, 40...management system, 41...control device, 42...storage device, 43...communication device

Claims

1. A management system that generates a power plan for charging and discharging a power storage device, the power plan including a plan for fluctuating power that fluctuates within a specific fluctuation range, using a mathematical model, The mathematical model is A constraint equation for calculating a surplus scenario that is a time change in the amount of charge of the power storage device when the fluctuating power is maximally biased toward the charging side; a constraint equation that limits the upper limit of the surplus scenario; and a constraint equation for adding a virtual additional discharge power in a discharge direction to the surplus scenario based on the charge amount in the surplus scenario. Management system.

2. The mathematical model is The power supply voltage Vcc further includes a constraint equation for calculating an expected value scenario that is a time change in the amount of charge of the power storage device when the fluctuating power is an expected value within the fluctuation range, The virtual additional discharge power is limited according to a surplus difference corresponding to a difference between the charge amount in the surplus scenario and the charge amount in the expected value scenario. The management system of claim 1.

3. The mathematical model is The integrated value of the virtual additional discharge power in a specific period of time is further limited to a constraint equation that limits the integrated value of the virtual additional discharge power in a specific period of time so as not to exceed a surplus difference at a specific point in time within the specific period of time. The management system of claim 2.

4. The specific time point is a time point at which an actual value of the charge amount of the power storage device to be used for replanning is measured, The specific period is: a time point at which the actual value was measured before the specific time point, and a time point at which a period in which the charge amount of the power storage device can be changed by replanning based on the actual value begins after the specific time point; The period is a period whose end point is after the start point of a period in which the amount of charge of the power storage device can be changed by replanning based on the actual value measured at the specific time point. The management system of claim 3.

5. The mathematical model is a constraint equation for calculating a surplus sub-scenario that is a time change in the amount of charge of the power storage device when the fluctuating power during the target period in the surplus scenario is maximally biased toward the discharge side; and and a constraint equation that limits a lower limit of the charge amount of the surplus sub-scenario during the target period. The management system of claim 4.

6. A management system that generates a power plan for charging and discharging a power storage device, the power plan including a plan for fluctuating power that fluctuates within a specific fluctuation range, using a mathematical model, The mathematical model is A constraint equation for calculating a shortage scenario that is a time change in the charge amount of the power storage device when the fluctuating power is maximally biased toward the discharge side; a constraint that limits the lower bound of the shortage scenario; and a constraint equation for adding virtual additional charging power in the charging direction for the shortage scenario based on the charging amount in the shortage scenario. Management system.

7. The mathematical model is The power supply voltage Vcc further includes a constraint equation for calculating an expected value scenario that is a time change in the amount of charge of the power storage device when the fluctuating power is an expected value within the fluctuation range, The virtual additional charging power is limited according to a shortage difference corresponding to a difference between the charging amount in the expected value scenario and the charging amount in the shortage scenario. The management system of claim 6.

8. The mathematical model is a constraint equation that limits the integrated value of the virtual additional charging power in a specific period so as not to exceed a shortage difference at a specific time point within the specific period; Also includes The management system of claim 7.

9. The specific time point is a time point at which an actual value of the charge amount of the power storage device to be used for replanning is measured, The specific period is: a time point at which the actual value was measured before the specific time point, and a time point at which a period in which the charge amount of the power storage device can be changed by replanning based on the actual value begins after the specific time point; The period is a period whose end point is after the start point of a period in which the amount of charge of the power storage device can be changed by replanning based on the actual value measured at the specific time point. The management system of claim 8.

10. The mathematical model is A constraint equation for calculating a shortage sub-scenario that is a time change in the amount of charge of the power storage device when the variable power during the target period in the shortage scenario is maximally biased toward the charging side; and a constraint expression that limits an upper limit of the charging amount of the shortage sub-scenario during the target period. The management system of claim 9.

11. The target period is the period from the specific point in time to the end point of the specific period. The management system according to claim 5 or claim 10.

12. A management system that generates a power plan for charging and discharging a power storage device, the power plan including a plan for fluctuating power that fluctuates within a specific fluctuation range, using a mathematical model, The mathematical model is A constraint equation for calculating a surplus scenario that is a time change in the amount of charge of the power storage device when the fluctuating power is maximally biased toward the charging side; A constraint equation for calculating a shortage scenario that is a time change in the charge amount of the power storage device when the fluctuating power is maximally biased toward the discharge side; a constraint equation that limits the upper limit of the surplus scenario; a constraint that limits the lower bound of the shortage scenario; A constraint equation that adds a virtual additional discharge power in a discharge direction to the surplus scenario based on the charge amount in the surplus scenario; and a constraint equation for adding virtual additional charging power in the charging direction for the shortage scenario based on the charging amount in the shortage scenario. Management system.

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