Power inference device, power control system, system stabilization system, model generation device, and power inference method

Abstract

The purpose of the present invention is to provide a technique with which it is possible to utilize an existing power storage device for normal time control for emergency control. This power inference device is provided with: a generation unit that generates an inference model on the basis of charge / discharge power in a main control, and system information; a charge / discharge power inference unit that infers charge / discharge power in the main control on the basis of the inference model and the system information; and a control surplus power inference unit that infers control surplus power, which is the charge / discharge power that can be used in the sub-control, on the basis of the inferred charge / discharge power in the main control.

Description

Power inference device, power control system, power system stabilization system, model generation device, and power inference method

[0001] The present disclosure relates to a power inference device, a power control system, a power grid stabilization system, a model generation device, and a power inference method.

[0002] Various technologies have been proposed for power systems. For example, Patent Literature 1 describes a technology in which the gain of Δf feedback control of a storage battery is changed and a system simulation is performed to estimate the future charge / discharge amount or remaining capacity and adjust the gain so that the remaining capacity of the storage battery that performs frequency control does not approach the upper or lower limit.

[0003] Japanese Patent Application Laid-Open No. 2017-99131

[0004] There is a growing need for emergency control using fast-response storage batteries to charge and discharge during grid disturbances, etc. However, because emergency control is only performed when grid disturbances occur and the facility utilization rate is low, installing energy storage devices solely for emergency control is difficult from a cost-effectiveness perspective.

[0005] Therefore, it is conceivable to utilize existing power storage devices that are installed for normal control such as frequency control and load leveling control for emergency control as well. However, in conventional technologies, charging and discharging of power storage devices by multiple controls such as normal control and emergency control is not assumed, and therefore there is a problem that existing power storage devices that are installed for normal control cannot be utilized for emergency control.

[0006] Therefore, the present disclosure has been made in consideration of the above-mentioned problems, and aims to provide a technology that enables existing power storage devices for normal control to be utilized for emergency control.

[0007] The power inference device of the present disclosure includes an acquisition unit that acquires the charge / discharge power during main control of a power storage device that charges and discharges power to and from a power grid through a combination of main control and secondary control that is performed with a lower priority than the main control, and acquires system information, which is information about the power grid; a generation unit that generates an inference model that can infer the charge / discharge power during the main control from the system information based on the charge / discharge power during the main control and the system information; a charge / discharge power inference unit that infers the charge / discharge power during the main control based on the inference model and the system information; and a control reserve inference unit that infers the control reserve, which is the charge / discharge power that can be used in the secondary control, based on the inferred charge / discharge power during the main control.

[0008] According to the present disclosure, an inference model is generated based on the charge / discharge power in the primary control and grid information, the charge / discharge power in the primary control is inferred based on the inference model and the grid information, and the control margin available for the secondary control is inferred based on the inferred charge / discharge power in the primary control. With this configuration, an existing power storage device for normal control can be used for emergency control.

[0009] The objects, features, aspects and advantages of the present disclosure will become more apparent from the following detailed description and the accompanying drawings.

[0010] 1 is a diagram showing the configuration of a power system according to embodiment 1. FIG. 2 is a diagram showing the configuration of a power inference device according to embodiment 1. FIG. 3 is a diagram showing an overview of the operation of the power inference device according to embodiment 1. FIG. 4 is a flowchart showing the processing of a learning phase of the power inference device according to embodiment 1. FIG. 5 is a flowchart showing the processing of an inference phase of the power inference device according to embodiment 1. FIG. 6 is a diagram showing the configuration of a power system according to embodiment 2. FIG. 7 is a diagram showing the configuration of a power system stabilizing device according to embodiment 2. FIG. 8 is a flowchart showing the processing of the power system stabilizing device according to embodiment 2. FIG. 9 is a flowchart showing the processing of the power system stabilizing device according to embodiment 3. FIG. 10 is a diagram showing the configuration of a power system according to a modification. FIG. 11 is a block diagram showing the hardware configuration of a power inference device according to another modification. FIG. 12 is a block diagram showing the hardware configuration of a power inference device according to another modification.

[0011] <First Embodiment> In this specification, for example, at least one of A, B, C, ..., and Z means any one of all combinations of one or more types extracted from the group of A, B, C, ..., and Z. Furthermore, in this specification, acquisition includes acquisition as a result of input.

[0012] FIG. 1 is a diagram showing the configuration of a power inference device according to the first embodiment and other components. The configuration of FIG. 1 includes a load 1, a power source 2, an inverter power source 3, a measuring device 4, a control device 5, a power storage device 6, a power control device 7, and a power inference device 8.

[0013] The load 1, power source 2, inverter power source 3, and power storage device 6 are connected to a power grid 9. The load 1 includes, for example, a consumer device that uses power from the power grid 9. The power source 2 includes at least one generator, such as a nuclear generator, a thermal generator, or a hydroelectric generator. The inverter power source 3 includes at least one device with an inverter, such as a solar generator or a wind generator.

[0014] The measurement device 4 sequentially measures the load amount, power generation amount, node voltage, branch current, etc. as measurement information for the load 1, power source 2, inverter power source 3, and power system 9. The measurement device 4 sequentially transmits the measurement information of the measurement device 4 to the control device 5 and the power inference device 8 via the communication network 10. The measurement device 4 may or may not store the measurement information.

[0015] The control device 5 controls the power of the load 1, the power source 2, and the inverter power source 3 based on the measurement information of the measurement device 4 acquired via the communication network 10. If the control device 5 can acquire control information of another control device 5 and measurement information of the power control device 7 via the communication network 10, the control device 5 may control the power of the load 1, the power source 2, and the inverter power source 3 taking this information into consideration.

[0016] The power storage device 6 includes, for example, at least one of a storage battery, a flywheel battery, an electric double layer capacitor, and a FACTS (Flexible AC Transmission System) device, and performs charging and discharging between the power storage device 6 and the power grid 9. Charging and discharging include at least one of charging from the power grid 9 to the power storage device 6 and discharging from the power storage device 6 to the power grid 9, and charging and discharging power includes at least one of charging power and discharging power. The unit of charging and discharging power (kW) is different from the unit of charging and discharging power and capacity (kWh).

[0017] The power control device 7 sequentially measures and stores the charging / discharging power of the power storage device 6 as measurement information, and sequentially transmits the measurement information of the power control device 7 to the power inference device 8 via the communication network 10. The power control device 7 controls the charging / discharging performed by the power storage device 6 between the power grid 9 based on the measurement information of the power control device 7. Note that, if the power control device 7 can acquire the measurement information of the measurement device 4 and the control information of the control device 5 via the communication network 10, it may also take this information into consideration when controlling the charging / discharging performed by the power storage device 6 between the power grid 9.

[0018] The power control device 7 controls the charging and discharging of the power storage device 6 by issuing commands for charging and discharging to and from the power grid 9 through a combination of a primary control and a secondary control that is executed with a lower priority than the primary control.

[0019] In the following description, the primary control is normal control for continuously charging and discharging the power storage device 6, and the secondary control is emergency control for charging and discharging the power storage device 6 for only a certain period of time. However, the primary control and secondary control are not limited to normal control and emergency control, respectively. The normal control may include frequency control for charging and discharging the power storage device 6 so that the grid frequency becomes a reference value (e.g., 50 or 60 Hz), and load leveling control for charging the power storage device 6 during time periods when the load is low and discharging the power storage device 6 during time periods when the load is high. The emergency control may include stabilization control for charging and discharging the power storage device 6 to improve transient stability and frequency stability when a grid disturbance occurs due to a ground fault / short circuit accident, a power supply drop, a load drop, or the like.

[0020] The power inference device 8 infers the control reserve, which is the charge / discharge power of the power storage device 6 that can be used for emergency control, based on the measurement information from the measurement device 4 and the power control device 7. The configuration of the power inference device 8 will be described in detail below. The power control device 7 and the power inference device 8 are provided in a power control system 450.

[0021] Fig. 2 is a block diagram showing the configuration of the power inference device 8 according to the present embodiment 1. The power inference device 8 in Fig. 2 includes an acquisition unit 21, a recording unit 22, a learning unit 23 which is a generation unit, a charge / discharge power inference unit 24, a control margin inference unit 25, and an output unit 26.

[0022] <Acquisition unit 21> The acquisition unit 21 acquires measurement information from the measurement device 4 and the power control device 7, and thereby acquires the charge / discharge power during normal control of the power storage device 6 and system information, which is information about the power system 9. The charge / discharge power during normal control of the power storage device 6 is included in, for example, the measurement information from the power control device 7. Hereinafter, the charge / discharge power during normal control of the power storage device 6 may be abbreviated as "normal charge / discharge power."

[0023] The grid information includes at least one of facility information, measurement information, power dispatching system information, supply and demand control system (EMS) information, and supervisory control and analysis (SCADA) information. The facility information includes, for example, at least one of the generator rated capacity (kVA), inverter power output (kW), power storage device rated capacity (kWh), and power storage device output (kW). The rated capacity corresponds to the amount of power, the output corresponds to the amount of electric power, and the power storage device output includes, for example, the battery output and the PCS output. The measurement information is, for example, information included in the measurement information of the measurement device 4 and the power control device 7, and includes at least one of the generator / inverter power output active / reactive power (kW, kVar), node frequency (Hz), remaining capacity (kWh or %) of the power storage device, load, and power supply information obtainable via the ITM or CDT of the substation.

[0024] The information of the power supply control system includes, for example, at least one of the system frequency (Hz), the local demand (kW), the generator EDC command value (kW), and the generator LFC command value (kW). The local demand represents the load change in the power system 9 and is expressed, for example, as "system constant × system capacity × frequency change + interconnection line power flow change." The system constant is the change in generator output with respect to a frequency change, the system capacity is the sum of the rated capacities of the power sources in operation, and the interconnection line power flow change is the change in power flowing through the transmission lines connecting the inside and outside of the jurisdiction. Economic load dispatch control (EDC) is a control that determines the output allocation of each generator taking into account economic efficiency with respect to the required power generation amount, and the generator EDC command value is the output command value for the generator determined by EDC. Load frequency control (LFC) is a control that increases or decreases generator output using the local demand as an index to balance supply and demand in the power system, and the generator LFC command value is the output command value for the generator determined by LFC.

[0025] In addition, the system information may include information other than the above as long as it is information about the power system 9, or may include information that can be derived from the above information (for example, residual demand obtained by subtracting inverter power supply output from load amount).

[0026] The acquisition unit 21 stores the acquired normal charging / discharging power and grid information in the recording unit 22 .

[0027] <Learning unit 23> The learning unit 23 generates an inference model that models the relationship between the system information and the normal charging / discharging power based on the normal charging / discharging power and the system information, and that can infer the normal charging / discharging power from the system information. The normal charging / discharging power and system information used to generate the inference model are the normal charging / discharging power and system information at multiple points in time that have been previously acquired by the acquisition unit 21 and stored in the recording unit 22. The system information used to generate the inference model may include, for example, a local demand amount, a frequency deviation, a grid line power flow, a generator output (kW), a generator EDC command value, and a generator LFC command value, or may be information other than these.

[0028] The learning unit 23 may generate an inference model using, for example, a statistical method that generates a statistical model, or may generate an inference model using machine learning (training) that generates a trained model. Machine learning may be, for example, supervised machine learning, unsupervised machine learning, or reinforcement learning. The learning unit 23 may also use a statistical method, an optimization method, or the like. Supervised machine learning may be, for example, a decision tree, a regression tree, a random forest, a random forest regression, a support vector machine, a support vector regression, a neural network, deep learning, or the like, or other methods. The machine learning may be learning using a classification method or learning using a regression method.

[0029] The learning unit 23 may use all of the grid information acquired by the acquisition unit 21 to generate the inference model, or may use a portion of the grid information selected from all of the grid information to generate the inference model. Methods for selecting a portion of the grid information from all of the grid information include, but are not limited to, a selection method based on a method for determining a normal control command value of the power storage device 6, a selection method based on qualitative characteristics of the inference accuracy of the inference model, and a selection method specified by a user.

[0030] The inference of the normal charging / discharging power may include predicting future normal charging / discharging power, or may include estimating past or present normal charging / discharging power. When the learning unit 23 generates the inference model using normal charging / discharging power acquired after the grid information, the inference model can predict future normal charging / discharging power from the current grid information.

[0031] The learning unit 23 stores the generated inference model in the recording unit 22.

[0032] <Charge / Discharge Power Inference Unit 24> The charge / discharge power inference unit 24 infers the normal charge / discharge power based on the inference model generated by the learning unit 23 and stored in the recording unit 22 and on the system information. For example, the charge / discharge power inference unit 24 infers the normal charge / discharge power by inputting the same type of system information as the system information used by the learning unit 23 into the inference model and acquiring the normal charge / discharge power output from the inference model. Note that the system information used to infer the normal charge / discharge power may be the system information stored in the recording unit 22 or may be the system information acquired by the acquisition unit 21 at the time of inference.

[0033] The charge / discharge power inference unit 24 stores the inferred normal charge / discharge power in the recording unit 22 .

[0034] <Control margin inference unit 25> The control margin inference unit 25 infers a control margin, which is the charge / discharge power (kW) of the power storage device 6 that can be used for emergency control, based on the normal charge / discharge power inferred by the charge / discharge power inference unit 24 and stored in the recording unit 22, and the power storage device output. The power storage device output used to infer the control margin may be the power storage device output included in the system information, or may be a default power storage device output set in advance in the control margin inference unit 25. When the default power storage device output set in advance in the control margin inference unit 25 is used to infer the control margin, the control margin inference unit 25 will essentially infer the control margin based on the normal charge / discharge power inferred by the charge / discharge power inference unit 24.

[0035] The control margin inference unit 25 may infer the control margin by subtracting the normal charging / discharging power inferred by the charging / discharging power inference unit 24 from the power storage device output. In this inference, for example, if the power storage device output is −300 kW to 300 kW, positive and negative values ​​represent charging and discharging, respectively, and the inferred normal charging / discharging power is 100 kW, 200 kW and 400 kW are inferred as the control margins for charging and discharging, respectively.

[0036] Note that the inference of the control margin is not limited to the above. For example, in order to strictly evaluate the control margin, the control margin inference unit 25 may infer the control margin by subtracting a value obtained by adding a margin, which is a fixed amount specified by a user or the like, to the normal charging / discharging power and the obtained value from the power storage device output. Conversely, in order to loosely evaluate the control margin, the control margin inference unit 25 may infer the control margin by subtracting a value obtained by subtracting a margin from the normal charging / discharging power and the obtained value from the power storage device output. Furthermore, the inference of the control margin may include predicting the future control margin or estimating the past or present control margin.

[0037] The control margin inference unit 25 stores the inferred control margin in the recording unit 22 .

[0038] <Output unit 26> The output unit 26 transmits the control margin inferred by the control margin inference unit 25 to the power control device 7 via the communication network 10, and the power control device 7 controls the charging and discharging of the power storage device 6 taking into account the transmitted control margin.

[0039] The output unit 26 is not limited to transmitting the control margin to the power control device 7, but may display the control margin on a display device (not shown) or transmit the control margin to other devices and systems via the communication network 10. Furthermore, the output unit 26 may display or transmit not only the control margin, but also an inference model, normal charging / discharging power, and measurement information used for the inference.

[0040] <Operation> Fig. 3 is a diagram showing an outline of the operation of the power inference device 8 according to the present embodiment 1. As shown in Fig. 3, the power inference device 8 performs a process in a learning phase and a process in an inference phase.

[0041] 4 is a flowchart showing the learning phase processing of the power inference device 8. The learning phase processing is performed before the inference phase processing, but does not have to be performed for each inference phase processing. The learning phase processing may be performed when the power inference device 8 is installed, or may be performed periodically, such as once every few days.

[0042] In step S1, the acquisition unit 21 acquires past system information and past normal charging / discharging power, and stores them in the recording unit 22. In step S2, the learning unit 23 acquires normal charging / discharging power and system information at multiple points in time required for learning from the recording unit 22. In step S3, the learning unit 23 generates an inference model based on the acquired normal charging / discharging power and system information. In step S4, the learning unit 23 stores the generated inference model in the recording unit 22. Thereafter, the processing of FIG. 4 ends.

[0043] FIG. 5 is a flowchart showing the processing of the inference phase of the power inference device 8. In step S11, the charge / discharge power inference unit 24 acquires system information used to infer the normal charge / discharge power. In step S12, the charge / discharge power inference unit 24 inputs the acquired system information into an inference model and acquires the normal charge / discharge power output from the inference model, thereby inferring the normal charge / discharge power. In step S13, the control margin inference unit 25 infers the control margin of the power storage device 6 based on the normal charge / discharge power inferred by the charge / discharge power inference unit 24 and the power storage device output. In step S14, the output unit 26 outputs the inferred control margin. The processing of FIG. 5 then ends.

[0044] Summary of First Embodiment According to the power estimation device 8 of the first embodiment, an estimation model is generated based on the charge / discharge power under normal control and grid information, the charge / discharge power under normal control is estimated based on the estimation model and the grid information, and the control margin available for emergency control is estimated based on the estimated charge / discharge power under normal control. This allows the power storage device 6 to be charged / discharged by multiple controls such as normal control and emergency control, so that an existing power storage device for normal control can be used for emergency control.

[0045] Furthermore, when the learning unit 23 generates an inference model using machine learning, it can appropriately generate the inference model and infer the control margin.

[0046] 6 is a diagram showing the configuration of a power inference device and other components according to the second embodiment. In the following, among the components according to the second embodiment, components that are the same as or similar to the components described above are given the same or similar reference numerals, and different components will be mainly described.

[0047] The power inference device and other components in Fig. 6 are similar to those in Fig. 1 with a power grid stabilization device 13 added, and the power inference device 8 according to the second embodiment is similar to the power inference device 8 according to the first embodiment. The power grid stabilization device 13 is capable of communicating with the measurement device 4, the control device 5, the power control device 7, and the power inference device 8 via a communication network 10, and determines power supply limitations and load limitations of the power grid 9 based on grid information and control margin, as will be described below. The power inference device 8 and the power grid stabilization device 13 are provided in a power grid stabilization system.

[0048] Power source limitation, also called power control, is a control that limits or stops generator output with the aim of stabilizing the power grid 9, and affects power costs. Load limitation, also called load control, is a control that cuts off loads on consumers and the like to limit power consumption with the aim of stabilizing the power grid 9, and affects power quality.

[0049] Fig. 7 is a block diagram showing the configuration of a power system stabilizing device 13 according to Embodiment 2. The power system stabilizing device 13 in Fig. 7 includes an acquisition unit 41, a recording unit 42, a power system stabilization calculation unit 43, and an output unit 44.

[0050] <Acquisition unit 41> The acquisition unit 41 acquires information such as measurement information from the measurement device 4 and the power control device 7, thereby acquiring system configuration information, equipment information, measurement information, control conditions, and control margin inferred by the power inference device 8.

[0051] The system configuration information includes, for example, at least one of the system topology and the on / off state of the switches of the power system 9. The equipment information includes, for example, at least one of the rated capacity of the generator, the inverter power output, the power storage device rated capacity, the power storage device output, the transformer capacity, and the line type of the transmission line. The line type of the transmission line includes, for example, at least one of the thickness and material of the transmission line. The measurement information is, for example, information included in the measurement information of the measurement device 4 and the power control device 7, and includes at least one of the node voltage / phase, the branch current, the generator output, the inverter power output, and the load amount. The control conditions include, for example, at least one of the conditions for shearing / negative control and information on equipment subject to shearing / negative control that indicates whether the equipment is subject to shearing / negative control.

[0052] The information acquired by the acquisition unit 41 is not limited to the above, as long as it includes measurement information and control margin. The acquisition unit 41 stores the acquired information in the recording unit 42.

[0053] <Grid stabilization calculation unit 43> The grid stabilization calculation unit 43 determines power supply limits and load limits for the power grid 9 based on information including measurement information and control margin. The information used to determine the power supply limits and load limits may be information stored in the recording unit 42, or may be information acquired by the acquisition unit 41 when the power supply limits and load limits are determined.

[0054] As an example of determining the power supply limit and the load limit, first, a model is defined in which a model simulating a power storage device system is added to a simulation system model used for detailed stability calculation. The system stabilization calculation unit 43 determines the power supply limit and the load limit by repeatedly performing a simulation (detailed stability calculation) by inputting measurement information and control margin into the defined model. Note that the method for determining the power supply limit and the load limit is not limited to this, and may be a method of determining the power supply limit and the load limit by optimization calculation such as combinatorial optimization, or a method of determining the limit by simulating all candidates.

[0055] The system stabilization calculation unit 43 stores the system simulation model and the determination results of the power supply limit and the load limit in the recording unit 42.

[0056] <Output unit 44> The output unit 44 transmits the determination results of the power supply limit and the load limit determined by the system stabilization calculation unit 43 to the equipment that controls the restriction target via the communication network 10. The equipment that controls the restriction target is connected to the power system 9, and appropriately performs power supply limit and load limit based on the transmitted determination results.

[0057] <Operation> Fig. 8 is a flowchart showing the processing of the power grid stabilization device 13 according to the second embodiment. In step S21, the acquisition unit 41 acquires information including measurement information and control margin, and stores the information in the recording unit 42. In step S22, the power grid stabilization calculation unit 43 determines power supply restrictions and load restrictions for the power grid 9 based on the information including the measurement information and control margin, and stores the determined results in the recording unit 42. In step S23, the output unit 44 transmits the power supply restrictions and load restrictions determined by the power grid stabilization calculation unit 43 to the equipment that is the target of the restrictions via the communication network 10. Thereafter, the processing in Fig. 8 ends.

[0058] Summary of Second Embodiment According to the system stabilization device 13 according to the second embodiment described above, power supply restriction and load restriction of the power system 9 are determined based on system information and control margin. As a result, when the power storage device 6 uses the control margin in emergency control, appropriate power supply restriction and load restriction can be performed on the power system 9.

[0059] <Embodiment 3> The power inference device according to this embodiment 3 and other configurations are the same as the power inference device according to embodiment 2 and other configurations (i.e., the configuration in FIG. 6 ). Of the components according to this embodiment 3, components that are the same as or similar to the components described above are given the same or similar reference numerals, and different components will be mainly described.

[0060] The power inference device 8 according to the third embodiment is similar to the power inference device 8 according to the first embodiment. The power system stabilization device 13 according to the third embodiment is similar to the power system stabilization device 13 according to the second embodiment, except that the power system stabilization device 13 according to the third embodiment determines the stabilization control amount of the power storage device 6 based on measurement information and information including control margin. Below, components of the power system stabilization device 13 according to the third embodiment that are different from the power system stabilization device 13 according to the second embodiment, specifically, the power system stabilization calculation unit 43 and the output unit 44 in FIG. 6 will be described.

[0061] The system stabilization calculation unit 43 determines a power supply limit and a load limit for the power system 9 based on information including the measurement information and the control margin, and also determines a stabilization control amount for the power storage device 6. The stabilization control amount for the power storage device 6 is a control amount for controlling the power storage device 6 within the range of the control margin, and is determined so that the power supply limit and the load limit are appropriately performed. Note that the system stabilization calculation unit 43 may determine the stabilization control amount for the power storage device 6 by performing a simulation similar to that used when determining the power supply limit and the load limit. The system stabilization calculation unit 43 stores the system simulation model, the determined power supply limit and load limit, and the stabilization control amount for the power storage device 6 in the recording unit 42.

[0062] The output unit 44 transmits the results of the power supply restriction and load restriction determined by the system stabilization calculation unit 43 to the equipment that controls the restriction target via the communication network 10. The output unit 44 also transmits the stabilization control amount of the power storage device 6 to the power control device 7 via the communication network 10. The power control device 7 controls the charging and discharging of the power storage device 6 taking into consideration the transmitted stabilization control amount.

[0063] <Operation> Fig. 9 is a flowchart showing the processing of the grid stabilization device 13 according to the third embodiment. In step S31, the acquisition unit 41 acquires information including measurement information and control margin, and stores the information in the recording unit 42. In step S32, the grid stabilization calculation unit 43 determines a power supply limit and a load limit for the power grid 9 based on the information including the measurement information and control margin, and determines a stabilization control amount for the power storage device 6, and stores the results in the recording unit 42. In step S33, the output unit 44 transmits the determination results of the power supply limit and the load limit determined by the grid stabilization calculation unit 43 to the equipment that is subject to the restrictions via the communication network 10. The output unit 44 also transmits the stabilization control amount for the power storage device 6 determined by the grid stabilization calculation unit 43 to the power control device 7 via the communication network 10. Thereafter, the processing of Fig. 9 ends.

[0064] Summary of Third Embodiment According to the system stabilization device 13 according to the third embodiment as described above, the stabilization control amount of the power storage device 6 is determined based on the system information and the control margin. As a result, when the power storage device 6 uses the control margin in emergency control, it is possible to appropriately charge and discharge the power storage device 6 while performing appropriate power supply restrictions and load restrictions on the power system 9.

[0065] <Modification> Fig. 10 is a diagram showing the configuration of a power inference device and other components according to this modification. As shown in Fig. 10, the power inference device 8 may include, in addition to the components in Fig. 2, a power grid stabilization unit 28 having the same function as the power grid stabilization device 13. For example, the power grid stabilization unit 28 may determine the power supply limit and load limit of the power grid 9 based on the power grid information and the control margin. In this case, the same effect as in the second embodiment can be obtained. Furthermore, for example, the power grid stabilization unit 28 may determine the stabilization control amount of the power storage device 6 based on the power grid information and the control margin. In this case, the same effect as in the third embodiment can be obtained.

[0066] Furthermore, some of the components of the power inference device 8 described above may be configured as separate devices. For example, the acquisition unit 21 and the learning unit 23 may configure a model generation device that generates an inference model. Alternatively, the power inference device may be configured by an acquisition unit that acquires the inference model generated by the model generation device, and a charge / discharge power inference unit 24 that infers charge / discharge power in main control based on the inference model and grid information.

[0067] <Other Modifications> The acquisition unit 21, learning unit 23, charge / discharge power inference unit 24, and control reserve inference unit 25 shown in FIG. 2 are hereinafter referred to as the "acquisition unit 21, etc." The acquisition unit 21, etc. are realized by a processing circuit 81 shown in FIG. 11. That is, the processing circuit 81 includes: an acquisition unit 21 that acquires charge / discharge power during main control of a power storage device that charges and discharges power to and from a power grid through a combination of main control and secondary control that is performed with a lower priority than the main control, and acquires grid information that is information about the power grid; a learning unit 23 that generates an inference model that can infer charge / discharge power during main control from the grid information based on the charge / discharge power during main control and the grid information; a charge / discharge power inference unit 24 that infers charge / discharge power during main control based on the inference model and the grid information; and a control reserve inference unit 25 that infers control reserve, which is charge / discharge power that can be used in secondary control, based on the inferred charge / discharge power during main control. The processing circuit 81 may be implemented by dedicated hardware or a processor that executes a program stored in memory. Examples of processors include central processing units, processing units, arithmetic units, microprocessors, microcomputers, and DSPs (Digital Signal Processors).

[0068] When the processing circuitry 81 is dedicated hardware, the processing circuitry 81 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination thereof. The functions of each unit such as the acquisition unit 21 may be realized by a circuit in which processing circuits are distributed, or the functions of each unit may be realized by a single processing circuit.

[0069] When the processing circuit 81 is a processor, the functions of the acquisition unit 21 and the like are realized in combination with software and the like. The software and the like may include, for example, software, firmware, or both software and firmware. The software and the like is written as a program and stored in a memory. As shown in FIG. 12 , the processor 82 applied to the processing circuit 81 realizes the functions of each unit by reading and executing a program stored in a memory 83. That is, the power inference device 8 includes a memory 83 for storing a program that, when executed by the processing circuit 81, results in the following steps: acquiring charge / discharge power under main control of a power storage device that charges / discharges to / from a power grid through a combination of main control and secondary control that is performed with a lower priority than the main control, and acquiring grid information that is information about the power grid; generating an inference model that can infer the charge / discharge power under main control from the grid information based on the charge / discharge power under main control and the grid information; inferring the charge / discharge power under main control based on the inference model and the grid information; and inferring a control margin, which is the charge / discharge power available for secondary control, based on the inferred charge / discharge power under main control. In other words, this program can be said to cause a computer to execute the procedures and methods of the acquisition unit 21, etc. Here, the memory 83 may be, for example, a non-volatile or volatile semiconductor memory such as a random access memory (RAM), a read-only memory (ROM), a flash memory, an erasable programmable read-only memory (EPROM), or an electrically erasable programmable read-only memory (EEPROM), a hard disk drive (HDD), a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, a digital versatile disk (DVD), a drive device for any of these, or any storage medium that will be used in the future.

[0070] The above describes a configuration in which each function of the acquisition unit 21, etc. is realized either by hardware or software, etc. However, this is not limited to this, and a configuration in which part of the acquisition unit 21, etc. is realized by dedicated hardware and another part is realized by software, etc. For example, the function of the acquisition unit 21 can be realized by a processing circuit 81 as dedicated hardware, and the other functions can be realized by the processing circuit 81 as a processor 82 reading and executing a program stored in a memory 83.

[0071] As described above, the processing circuit 81 can realize the above-mentioned functions by hardware, software, or a combination of these. Note that the components of the power system stabilization device 13 in Fig. 7 and the power system stabilization unit 28 in Fig. 10 are similar to those described above.

[0072] It should be noted that the embodiments and modifications may be freely combined, and the embodiments and modifications may be modified or omitted as appropriate.

[0073] The above description is illustrative in all respects and is not restrictive. It is understood that countless variations not illustrated can be envisioned.

[0074] 6 Power storage device, 7 Power control device, 8 Power inference device, 9 Power system, 13 System stabilization device, 21 Acquisition unit, 23 Learning unit, 24 Charge / discharge power inference unit, 25 Control margin inference unit, 28 System stabilization unit, 450 Power control system.

Claims

1. An acquisition unit that acquires the charge / discharge power in the main control of a power storage device that performs charging and discharging with a power system by a combination of main control and sub-control which is performed with a lower priority than the main control, and acquires system information which is information of the power system, A generation unit generates an inference model capable of inferring the charge / discharge power in the main control from the system information based on the charge / discharge power in the main control and the system information, A charge / discharge power inference unit that infers the charge / discharge power in the main control based on the inference model and the system information, A control reserve inference unit infers the control reserve, which is the charge / discharge power available for use in the sub-control, based on the charge / discharge power inferred in the main control. A power inference device equipped with the following features.

2. A power inference device according to claim 1, A power inference device in which the main control is for normal operation and the sub-control is for emergency operation.

3. A power inference device according to claim 1 or claim 2, The generation unit is a power inference device that generates the inference model using machine learning.

4. A power inference device according to claim 1 or claim 2, A power inference device further comprising a system stabilization unit that determines power supply limits and load limits for the power system based on the system information and the control margin.

5. A power inference device according to claim 4, The aforementioned system stabilization unit is A power inference device that further determines the amount of stabilization control for the power storage device based on the system information and the control margin.

6. A power inference device according to claim 1 or claim 2, A power control device that controls the charging and discharging of the power storage device based on the control margin, A power control system equipped with the following features.

7. A power inference device according to claim 1 or claim 2, A power system stabilization device that determines the power supply limit and load limit of the power system based on the aforementioned system information and the control margin. A power grid stabilization system equipped with the following features.

8. A system stabilization system according to claim 7, The aforementioned system stabilization device is A grid stabilization system that further determines the amount of stabilization control for the power storage device based on the grid information and the control margin.

9. An acquisition unit that acquires the charge / discharge power in the main control of a power storage device that performs charging and discharging with a power system by a combination of main control and sub-control which is performed with a lower priority than the main control, and acquires system information which is information of the power system, A generation unit generates an inference model capable of inferring the charge / discharge power in the main control from the system information, based on the charge / discharge power in the main control and the system information. A model generation device equipped with the following features.

10. An acquisition unit that acquires an inference model capable of inferring the charge / discharge power in the main control of a power storage device that performs charging and discharging with a power system by a combination of main control and sub-control performed with a lower priority than the main control, and system information which is information of the power system, based on the system information, A charge / discharge power inference unit that infers the charge / discharge power in the main control based on the inference model and the system information. A power inference device equipped with the following features.

11. A power storage device that performs charging and discharging with a power system by a combination of a main control and a sub-control that is performed with a lower priority than the main control acquires the charging and discharging power in the main control, and acquires system information which is information of the power system, Based on the charge / discharge power in the main control and the system information, an inference model is generated that can infer the charge / discharge power in the main control from the system information. Based on the inference model and the system information, the charge / discharge power in the main control is inferred. A power inference method for inferring control margin, which is the charge / discharge power available in the sub-control, based on the inferred charge / discharge power in the main control.