Power management system, power management server, and power management method

Abstract

To appropriately absorb or compensate an excess portion or a shortage portion of generated power in a power network with which a photovoltaic power generation device is connected.SOLUTION: A CEMS server executes processing comprising steps of: if a prediction start condition is established (YES in S100), acquiring a predicted value and reliability of solar radiation (S102); calculating a predicted value of generated power (S104); if the predicted value of the generated power is larger than required power (YES in S106), and if the reliability of the predicted value is high (YES in S108), setting a first target range (S110); if the reliability of the predicted value is low (NO in S108), setting a second target range (S112); if the predicted value of the generated power is equal to or less than the required power (NO in S106), and if the reliability of the predicted value is high (YES in S114), setting a third target range (S116); and if the reliability of the predicted value is low (NO in S114), setting a fourth target range (S118).SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present disclosure relates to management of power generated using a solar power generation device. [Background technology]

[0002] Examples of power adjustment resources for power grids such as microgrids include generators, naturally variable power sources, power storage systems, charging equipment, and vehicles equipped with power storage devices. Among these, an example of naturally variable power sources is a photovoltaic power generation device such as a solar panel. When a photovoltaic power generation device is installed in an area covered by a microgrid, it is necessary to accurately predict the power generated by the photovoltaic power generation device in order to perform power adjustment with high accuracy.

[0003] For example, Japanese Patent Laid-Open Publication No. 2011-124287 (Patent Document 1) discloses a technique for predicting the amount of solar radiation and calculating the power generation of a solar power generation device from information on the predicted amount of solar radiation. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2011-124287 A Summary of the Invention [Problem to be solved by the invention]

[0005] The above-mentioned solar radiation forecast information is provided by various organizations such as the Japan Meteorological Agency, but the reliability is not necessarily high, and the forecasted solar radiation value may be significantly different from the actual solar radiation. This may result in a deterioration in the forecast accuracy of the power generation of the photovoltaic power generation device, and the actual power generation may be higher or lower than the predicted power generation. As a result, it is necessary to appropriately absorb or compensate for the surplus or shortage of power generation.

[0006] The present disclosure has been made to solve the above-mentioned problems, and its purpose is to provide a power management system, a power management server, and a power management method that appropriately absorb or compensate for surplus or shortage of generated power in a power grid to which a solar power generation device is connected. [Means for solving the problem]

[0007] A power management system according to an aspect of the present disclosure is a power management system that manages power in a power grid installed in a predetermined area. The power management system includes a photovoltaic power generation device installed in the predetermined area and connected to the power grid, a power storage device connectable to the power grid, an acquisition device that acquires a predicted value of solar radiation at a target time of prediction at a location where the photovoltaic power generation device is installed, and a control device that calculates a predicted value of power generation by the photovoltaic power generation device at the target time of prediction using the predicted value of solar radiation, sets a target range of SOC of the power storage device using the predicted value, and controls the SOC so that it falls within the target range by the time of the target time of prediction. When the reliability of the predicted value is low, the control device sets the target range wider than when the reliability is high.

[0008] In this way, when the reliability of the predicted value is low, the generated power may be excessive or insufficient relative to the predicted value. Therefore, by setting the target range of the SOC of the power storage device to a wide range in preparation for the generated power being excessive or insufficient relative to the predicted value, it is possible to appropriately absorb the excessive generated power or compensate for the insufficient generated power.

[0009] In one embodiment, when the control device charges the storage device using part of the generated power at the predicted time, the control device sets the lower limit of the target range lower when the reliability of the predicted value is low than when the reliability is high.

[0010] In this way, for example, when a storage device is charged using surplus power generated by a solar power generation system, by setting the lower limit of the target range low, the surplus generated power can be absorbed in the storage device even if the generated power becomes excessive compared to the predicted value due to low reliability of the predicted value.

[0011] Furthermore, in one embodiment, when the control device supplies the power of the storage device to outside the power grid together with the generated power at the predicted time, the control device sets the upper limit value of the target range higher when the reliability of the predicted value is low than when the reliability is high.

[0012] In this way, for example, when power is supplied from a power storage device to make up for a shortfall in the power generated by a solar power generation device, by setting the upper limit value of the target range high, the shortfall can be made up using power from the power storage device even if the generated power is less than the predicted value due to low reliability of the predicted value.

[0013] Furthermore, in one embodiment, the control device calculates the reliability using an error rate calculated from the actual measured value and the predicted value of the amount of solar radiation at the same time.

[0014] In this way, the reliability can be calculated with high accuracy using the error rate calculated from the actual measured value and the predicted value of the amount of solar radiation.

[0015] A power management server according to another aspect of the present disclosure is a power management server that manages power of a power grid installed in a predetermined area. A photovoltaic power generation device and a power storage device installed in the predetermined area are connected to the power grid. The power management server acquires a predicted value of solar radiation at a target prediction time at a location where the photovoltaic power generation device is installed. The power management server calculates a predicted value of power generation of the photovoltaic power generation device at the target prediction time using the predicted value of solar radiation. The power management server sets a target range of SOC of the power storage device using the predicted value. The power management server controls the SOC so that it falls within the target range by the time the target prediction time arrives. When the reliability of the predicted value is low, the power management server sets the target range wider than when the reliability is high.

[0016] A power management method according to still another aspect of the present disclosure is a power management method for managing power in a power grid installed in a predetermined area. A photovoltaic power generation device and a power storage device installed in the predetermined area are connected to the power grid. The power management method includes the steps of: acquiring a predicted value of solar radiation at a point where the photovoltaic power generation device is installed at a prediction target time; calculating a predicted value of power generated by the photovoltaic power generation device at the prediction target time using the predicted value of solar radiation; setting a target range of SOC of the power storage device using the predicted value; controlling the SOC so that it falls within the target range by the time of the prediction target time; and setting a wider target range when the reliability of the predicted value is low than when the reliability is high. Effect of the Invention

[0017] According to the present disclosure, it is possible to provide a power management system, a power management server, and a power management method that appropriately absorb or compensate for surplus or shortage of generated power in a power grid to which a photovoltaic power generation device is connected. [Brief description of the drawings]

[0018] [Figure 1] 1 is a diagram showing a schematic configuration of a power management system according to an embodiment of the present invention; [Diagram 2]FIG. 2 is a diagram for explaining an example of a configuration for predicting power generation in a solar power generation device. [Diagram 3] 10 is a flowchart illustrating an example of a process executed by a CEMS server. [Figure 4] 10 is a diagram for explaining the flow of power between a solar power generation device, a power grid, and a battery when a predicted value of generated power is greater than required power. FIG. [Diagram 5] FIG. 4 is a diagram for explaining a first target range and a second target range. [Figure 6] 10 is a diagram for explaining the flow of power between a solar power generation device, a power grid, and a battery when a predicted value of generated power is smaller than required power. FIG. [Figure 7] FIG. 11 is a diagram for explaining a third target range and a fourth target range. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0019] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are designated by the same reference characters and their description will not be repeated.

[0020] 1 is a diagram showing a schematic configuration of a power management system according to the present embodiment. The power management system 100 includes, for example, a CEMS 1, a CEMS server 2, a power receiving and transforming facility 3, a power system 4, and a power transmission and distribution company server 5. CEMS stands for Community Energy Management System or City Energy Management System.

[0021] The CEMS 1 includes a Factory Energy Management System (FEMS) 11, a Building Energy Management System (BEMS) 12, a Home Energy Management System (HEMS) 13, a generator 14, a naturally variable power source 15, an Energy Storage System (ESS) 16, Electric Vehicle Supply Equipment (EVSE) 17, and a vehicle 18. In the CEMS 1, a microgrid MG is constructed by these components. The microgrid MG corresponds to an example of the "power grid" according to the present disclosure.

[0022] The FEMS 11 is a system that manages the supply and demand of electricity used in a factory. The FEMS 11 includes a factory building (including lighting fixtures, air conditioning equipment, etc.) and industrial equipment (production lines, etc.) that operate with electricity supplied from the microgrid MG. Although not shown, the FEMS 11 may also include power generation equipment (generators, etc.) installed in the factory. Electricity generated by these power generation equipment may be supplied to the microgrid MG. The FEMS 11 further includes a FEMS server 110 that is capable of bidirectional communication with the CEMS server 2.

[0023] The BEMS 12 is a system that manages the supply and demand of electricity used in buildings such as offices or commercial facilities. The BEMS 12 includes lighting fixtures and air conditioning equipment installed in the building. The BEMS 12 may include power generation equipment or a cold heat source system (such as a waste heat recovery system or a heat storage system). The BEMS 12 further includes a BEMS server 120 that is capable of bidirectional communication with the CEMS server 2.

[0024] The HEMS 13 is a system that manages the supply and demand of electricity used in the home. The HEMS 13 includes household appliances (such as lighting equipment, air conditioners, and other electrical appliances) that operate using power supplied from the microgrid MG. The HEMS 13 may also include a household heat pump system, a household cogeneration system, a household storage battery, and the like. The HEMS 11 further includes a HEMS server 130 that is capable of bidirectional communication with the CEMS server 2.

[0025] The generator 14 is a power generation facility that is not dependent on weather conditions, and outputs the generated power to the microgrid MG. The generator 14 may include a steam turbine generator, a gas turbine generator, a diesel engine generator, a gas engine generator, a biomass generator, a stationary fuel cell, etc. The generator 14 may include a cogeneration system that utilizes heat generated during power generation.

[0026] The naturally variable power source 15 is a power generation facility whose power output varies depending on weather conditions, and outputs the generated power to the microgrid MG. Although Fig. 1 illustrates a photovoltaic power generation device 15A (Fig. 2) such as a solar panel, the naturally variable power source 15 may include a wind power generation device in addition to the photovoltaic power generation device 15A.

[0027] The power storage system 16 is a stationary power source that stores power generated by the naturally variable power source 15 or the like. The power storage system 16 is a secondary battery, for example a lithium-ion battery or a nickel-metal hydride battery that is a battery (recycled product) used in a vehicle. However, the power storage system 16 is not limited to a secondary battery, and may be a power-to-gas device that produces gaseous fuel (hydrogen, methane, etc.) using surplus power.

[0028] The charging facility 17 is electrically connected to the microgrid MG and configured to be capable of charging and discharging (power supply) between the charging facility 17 and the microgrid MG.

[0029] Specifically, the vehicle 18 is a plug-in hybrid vehicle (PHV), an electric vehicle (EV), or the like. The vehicle 18 is configured to be capable of one or both of external charging and external power feeding. That is, the vehicle 18 is configured to be capable of supplying power from the microgrid MG to the vehicle 18 when a charging cable is connected to an inlet (not shown) of the vehicle 18 (external charging). The vehicle 18 may also be configured to be capable of supplying power from the vehicle 18 to the microgrid MG when a charging cable is connected to an outlet (not shown) of the vehicle 18 (external power feeding).

[0030] In the example shown in Fig. 1, the CEMS 1 includes one each of the FEMS 11, BEMS 12, HEMS 13, generator 14, naturally variable power source 15, and power storage system 16, but the number of these systems or facilities included is arbitrary. The CEMS 1 may include a plurality of these systems or facilities, or there may be systems or facilities not included in the CEMS 1. Each of the FEMS 11 (factory buildings, industrial facilities, etc.), BEMS 12 (lighting fixtures, air conditioning facilities, etc.), HEM 13 (household appliances, etc.), generator 14, naturally variable power source 15, power storage system 16, charging facilities 17, and vehicles 18 included in the CEMS 1 corresponds to a "power adjustment resource" according to the present disclosure, and therefore, hereinafter, when there is no particular distinction between these systems or facilities, they will also be referred to as "power adjustment resources."

[0031] The CEMS server 2 is a computer that manages power adjustment resources within the CEMS 1. The CEMS server 2 includes a control device 21, a storage device 22, and a communication device 23. The control device 21 includes a processor, and is configured to execute predetermined arithmetic processing. The storage device 22 includes a memory that stores programs executed by the control device 21, and stores various information used by the programs (maps, relational expressions, parameters, etc.). The communication device 23 includes a communication interface, and is configured to communicate with the outside (other servers, etc.).

[0032] The CEMS server 2 may be an aggregator server. An aggregator is an electric utility that provides an energy management service by bundling multiple power adjustment resources. The CEMS server 2 corresponds to the “power management server” according to the present disclosure.

[0033] The power receiving and transforming equipment 3 is provided at an interconnection point (power receiving point) of the microgrid MG, and is configured to be able to switch between parallel (connection) and parallel-off (disconnection) between the microgrid MG and the power system 4. The power receiving and transforming equipment 3 includes a high-voltage side (primary side) switchgear, a transformer, a protective relay, measuring instruments, and a control device, all of which are not shown. When the microgrid MG is interconnected with the power system 4, the power receiving and transforming equipment 3 receives, for example, extra-high voltage AC power (a voltage exceeding 7000 V) from the power system 4, and steps down the received power to supply it to the microgrid MG.

[0034] The power system 4 is a power network constructed by power plants and power transmission and distribution facilities. In this embodiment, an electric power company serves as both a power generation business operator and a power transmission and distribution business operator. The electric power company corresponds to a general power transmission and distribution business operator, and also corresponds to a manager of the power system 4, and maintains and manages the power system 4.

[0035] The electricity transmission and distribution company server 5 is a computer that belongs to an electric power company and manages the supply and demand of electricity in the electric power system 4. The electricity transmission and distribution company server 5 is also configured to be capable of bidirectional communication with the CEMS server 2.

[0036] In the power management system 100 having the above configuration, as described above, the naturally variable power source 15 used as a power adjustment resource of the microgrid MG is exemplified by a photovoltaic power generation device 15A such as a solar panel. When the photovoltaic power generation device 15A is installed in a predetermined area targeted by the microgrid MG, in order to perform power adjustment with high accuracy, it is required to predict the power generated by the photovoltaic power generation device 15A with high accuracy. Therefore, for example, it is considered to predict the amount of solar radiation and calculate the power generation or amount of power generation of the photovoltaic power generation device 15A from the information of the predicted amount of solar radiation.

[0037] Fig. 2 is a diagram for explaining an example of a configuration for predicting power generation in a solar power generation device 15A. As shown in Fig. 2, the CEMS server 2 acquires, for example, information indicating an actual measured value of the amount of solar radiation at a point where the solar power generation device 15A is installed and information indicating a predicted value of the amount of solar radiation at a time point after the current time from an external server 200. The external server 200 includes, for example, a server of the Japan Meteorological Agency and a server of an organization that provides information regarding the amount of solar radiation to the outside. The vehicle 18 includes an ECU (Electronic Control Unit) 18A and a battery 18B. The CEMS server 2 is configured to be able to communicate with the ECU 18A of the vehicle 18 by wired communication or wireless communication.

[0038] A pyranometer 118 is installed at the site where the solar power generation device 15A is installed. The pyranometer 118 detects the amount of solar radiation and transmits information indicating the detection result to the external server 200. The external server 200 calculates a predicted value of the amount of solar radiation at a time later than the current time, for example, by using a history of actual measured values ​​of the amount of solar radiation acquired from the pyranometer 118 installed at the site where the solar power generation device 15A is installed. The external server 200 may calculate a predicted value, for example, an average value of actual measured values ​​of the amount of solar radiation at the same time on the same day for the past few years, or may calculate a predicted value by using an arrangement of atmospheric pressure, machine learning, or the like. Note that the external server 200 is not limited to the above-mentioned method as long as it can calculate a predicted value of the amount of solar radiation using a known technology. The external server 200 stores the actual measured value of the amount of solar radiation at the same time at the site where the solar power generation device 15A is installed in a storage device (not shown) in association with the predicted value. When the external server 200 receives a request from the CEMS server 2 for information regarding the amount of solar radiation at the point where the photovoltaic power generation device 15A is installed, the external server 200 transmits to the CEMS server 2 information regarding the actual measured value and predicted value of the amount of solar radiation at that point.

[0039] The CEMS server 2 can calculate the power generation at the point where the photovoltaic power generation device 15A is installed at the prediction target time by using the predicted value of the amount of solar radiation. The prediction target time may be, for example, a time after a predetermined time (e.g., 30 minutes or 1 hour) has elapsed from the current time, or may be a time when power adjustment is performed in the macrogrid MG or between the microgrid MG and the power system 4. The CEMS server 2 can then calculate the predicted value of the power generation of the photovoltaic power generation device 15A at the prediction target time by using the predicted value of the amount of solar radiation at the point where the photovoltaic power generation device 15A is installed.

[0040] For example, when the CEMS server 2 supplies power from the microgrid MG to the power system 4 in response to a DR (Demand Response) request or the like, if the power generation during the daytime or the like is greater than the power requested from the power system 4 (hereinafter, may be referred to as requested power), surplus power is generated in the microgrid MG, and the CEMS server 2 is required to absorb the generated surplus power in the microgrid MG. For example, a battery 18B mounted on the vehicle 18 is given as an example of a means for absorbing such surplus power. When surplus power is absorbed using the battery 18B, it is required to control the SOC (State Of Charge) of the battery 18B to a value that allows the surplus power to be absorbed by the time when the surplus power is generated (the prediction target time). For this reason, the CEMS server 2 sets a target range for the SOC of the battery 18B using the predicted value of the generated power at the prediction target time and the current value of the SOC of the battery 18B, and controls the SOC so that it falls within the set target range by the time the prediction target time is reached.

[0041] At this time, for example, a value that does not exceed a predetermined upper limit value of the SOC even when charging with the predicted surplus power is set as the upper limit value of the target range, and a value lower than the upper limit value by a certain margin α is set as the lower limit value of the target range. The ECU 18A of the vehicle 18 sets the lowest possible value within the target range as the target value. The ECU 18A sets the target value using, for example, the current SOC of the battery 18B, the upper limit value of the charging power of the battery 18B, the upper limit value of the power supply of the battery 18B, the time until the predicted target time, etc.

[0042] The CEMS server 2 receives information (SOC information) regarding the SOC of the battery 18B from the ECU 18A of the vehicle 18, and transmits a control command (SOC control command) to the vehicle 18 to control the SOC so that it falls within a set target range.

[0043] On the other hand, when the CEMS server 2 supplies power from the microgrid MG to the power system 4, if the generated power is smaller than the required power, the power supplied from the photovoltaic power generation device 15A to the power system 4 is insufficient. Therefore, it is required to make up for the insufficient power within the microgrid MG. For example, a battery 18B mounted on the vehicle 18 is one example of a means for making up for such a power shortage. When making up for the power shortage using the battery 18B, it is required to control the SOC of the battery 18B to a value that can make up for the power shortage by the time when the power shortage occurs (the prediction target time). Therefore, the CEMS server 2 sets a target range for the SOC of the battery 18B using a predicted value of the generated power at the prediction target time, and controls the SOC so that it falls within the set target range by the time the prediction target time is reached.

[0044] At this time, for example, a value that does not exceed a predetermined lower limit value of the SOC even if the predicted power shortage is supplied is set as the lower limit value of the target range, and a value higher than the lower limit value by a certain margin α is set as the upper limit value of the target range. The ECU 18A of the vehicle 18 sets the highest possible value within the target range as the target value. The ECU 18A sets the target value using, for example, the current SOC of the battery 18B, the upper limit value of the charging power of the battery 18B, the upper limit value of the power supply of the battery 18B, the time until the predicted target time, etc.

[0045] The above-mentioned solar radiation forecast information is provided by various organizations such as the Japan Meteorological Agency, but the reliability is not necessarily high. If the reliability of the forecast value is low, the forecast value of the solar radiation is likely to deviate significantly from the actual solar radiation. Therefore, depending on the reliability of the forecast value, the forecast accuracy of the power generation of the solar power generation device 15A may deteriorate, and the actual power generation may be too high or too low compared to the predicted power generation. As a result, it is required to appropriately absorb or compensate for the surplus or shortage of the power generation.

[0046] Therefore, in this embodiment, when the reliability of the predicted value of the amount of solar radiation in the solar power generation device 15A is low, the CEMS server 2 sets the target range of the SOC of the above-mentioned battery 18B wider than when the reliability is high.

[0047] In this way, when the reliability of the predicted value of the amount of solar radiation is low, the generated power may be excessive or insufficient relative to the predicted value. Therefore, by setting the target range of the SOC of the battery 18B wide in preparation for the generated power being excessive or insufficient relative to the predicted value, it is possible to appropriately absorb the excessive amount or compensate for the insufficient amount.

[0048] An example of processing executed by the CEMS server 2 will be described below with reference to Fig. 3. Fig. 3 is a flowchart showing an example of processing executed by the CEMS server 2. A series of processing shown in this flowchart is repeatedly executed at every predetermined control period.

[0049] In step (hereinafter, step will be abbreviated as S) 100, the CEMS server 2 determines whether or not a prediction start condition is satisfied. The prediction start condition includes, for example, a condition that a prediction of power generation at a prediction target time is requested of the photovoltaic power generation device 15A. The CEMS server 2 determines, for example, that a condition that a prediction of power generation at a prediction target time is requested when the power transmission and distribution company server 5 requests that the photovoltaic power generation device 15A supply power generated at the prediction target time to the power system 4 is satisfied. If it is determined that the prediction start condition is satisfied (YES in S100), the process proceeds to S102.

[0050] In S102, the CEMS server 2 acquires the predicted value of the amount of solar radiation at the point where the solar power generation device 15A is installed at the prediction target time and information on the reliability of the predicted value. As described above, the CEMS server 2 acquires the predicted value of the amount of solar radiation at the point where the solar power generation device 15A is installed at the prediction target time from the external server 200. Furthermore, the CEMS server 2 acquires the actual measured value and predicted value of the amount of solar radiation at the point where the solar power generation device 15A is installed at the current time, and acquires information on the reliability using the acquired actual measured value and predicted value of the amount of solar radiation at the current time. More specifically, the CEMS server 2 calculates an error rate from the actual measured value and predicted value of the amount of solar radiation at the current time. For example, the CEMS server 2 calculates a value calculated by a predetermined evaluation function (for example, Mean Absolute Percentage Error (MAPE)) as the error rate. For example, the CEMS server 2 calculates the absolute value of a value obtained by dividing the difference between the predicted value and the actual measured value at the current time by the actual measured value as the error rate. The CEMS server 2 may obtain actual values ​​and predicted values ​​at multiple times before the current time, calculate the error rate for each of the multiple times, and calculate the average of the error rates as the final error rate. Alternatively, when the error rate as described above is calculated in the external server 200, the CEMS server 2 may obtain the error rate obtained from the external server 200 as the reliability of the predicted value of the amount of solar radiation at the prediction target time.

[0051] In S104, the CEMS server 2 calculates a predicted value of the generated power at the target prediction time from the obtained predicted value of the amount of solar radiation. The CEMS server 2 may calculate the predicted value of the generated power from the predicted value of the amount of solar radiation, for example, by using the conversion efficiency from the amount of solar radiation to the generated power, or may calculate the predicted value of the generated power from the predicted value of the amount of solar radiation by using a predetermined map, table, formula, or the like that indicates the relationship between the amount of solar radiation and the generated power.

[0052] In S106, the CEMS server 2 determines whether the predicted value of the generated power is greater than the requested power. The CEMS server 2 determines whether the predicted value of the generated power is greater than the power requested for the photovoltaic power generation device 15A or the power requested from the power grid 4. For example, the CEMS server 2 may set the power requested for multiple power supply sources in the microgrid MG using the power requested from the power grid 4, and set the power requested for the photovoltaic power generation device 15A as the requested power, or may set the power requested from the power grid 4 as the requested power. If it is determined that the predicted value of the generated power is greater than the requested power (YES in S106), the process proceeds to S108.

[0053] In S108, the CEMS server 2 determines whether the reliability of the predicted value of the amount of solar radiation is high. For example, if the error rate calculated as described above is equal to or less than a threshold value, the CEMS server 2 determines that the reliability of the predicted value of the amount of solar radiation is high. Alternatively, for example, if the error rate calculated as described above is greater than the threshold value, the CEMS server 2 determines that the reliability of the predicted value of the amount of solar radiation is low. If the reliability of the predicted value of the amount of solar radiation is determined to be high (YES in S108), the process proceeds to S110.

[0054] In S110, the CEMS server 2 sets a first target range for the SOC of the battery 18B. At this time, for example, a value that does not exceed a predetermined upper limit value of the SOC even when charging with the predicted surplus power is set as the upper limit value of the first target range, and a value lower than the upper limit value by a predetermined margin α is set as the first lower limit value of the first target range. If it is determined that the reliability of the predicted value of the amount of solar radiation is not high (low) (NO in S108), the process proceeds to S112.

[0055] In S112, the CEMS server 2 sets a second target range for the SOC of the battery 18B. At this time, the same value as the upper limit value of the first target range is set as the upper limit value of the second target range, and a value lower than the upper limit value by a predetermined margin β is set as the second lower limit value of the second target range. The magnitude of the margin β is greater than the margin α. In other words, the second target range is wider than the first target range. If it is determined that the predicted value of the generated power is equal to or less than the required power (NO in S106), the process proceeds to S114.

[0056] In S114, the CEMS server 2 determines whether the reliability of the predicted value of the amount of solar radiation is high. The method of determining the reliability is similar to the process of S108 described above, and therefore detailed description thereof will not be repeated. If it is determined that the reliability of the predicted value of the amount of solar radiation is high (YES in S114), the process proceeds to S116.

[0057] In S116, the CEMS server 2 sets a third target range for the SOC of the battery 18B. At this time, for example, a value that does not exceed a predetermined lower limit value of the SOC even if the predicted power shortage is supplied is set as the lower limit value of the third target range, and a value higher than the lower limit value by a margin α is set as the first upper limit value of the third target range. If it is determined that the reliability of the predicted value of the amount of solar radiation is not high (NO in S114), the process proceeds to S118.

[0058] In S118, the CEMS server 2 sets a fourth target range for the SOC of the battery 18B. At this time, the same value as the lower limit value of the third target range is set as the lower limit value of the fourth target range, and a value higher than the lower limit value by a margin β is set as the upper limit value of the fourth target range.

[0059] In S120, the CEMS server 2 outputs a control command for the SOC to the vehicle 18 so that the SOC falls within the set target range. The ECU 18A of the vehicle 18 controls the SOC so that the SOC falls within the target range received as the SOC control command. When charging the battery 18B at the prediction target time, the ECU 18A controls the SOC of the battery 18B so that the SOC becomes as close as possible to the lower limit value (first lower limit value or second lower limit value) of the set target range. On the other hand, when power is supplied from the battery 18B at the prediction target time, the ECU 18A controls the SOC of the battery 18B so that the SOC becomes as close as possible to the upper limit value (first upper limit value or second upper limit value) of the set target range. The ECU 18A sets a target value within the target range using, for example, the current SOC and the time from the current time to the prediction start time, and controls the SOC so that the SOC becomes the target value by the prediction target time. ECU 18A may, for example, lower the SOC of battery 18B by supplying power to any consumer equipment of the microgrid MG or to charging equipment other than EVSE 17, or by operating electrical equipment in vehicle 18, or may increase the SOC of battery 18B by receiving power from any power supply equipment of the microgrid MG via EVSE 17.

[0060] An example of the operation of the CEMS server 2 in the present embodiment based on the above-mentioned structure and flowchart will be described with reference to Figs. 4 to 7. Fig. 4 is a diagram for explaining the flow of power between the photovoltaic power generation device 15A, the power system 4, and the battery 18B when the predicted value of the generated power is larger than the required power. Fig. 5 is a diagram for explaining the first target range and the second target range. Fig. 5 shows the SOC of the battery 18B as a bar graph, and the upper limit value and the lower limit value set as the target range are shown in the bar area. Fig. 6 is a diagram for explaining the flow of power between the photovoltaic power generation device 15A, the power system 4, and the battery 18B when the predicted value of the generated power is smaller than the required power. Fig. 7 is a diagram for explaining the third target range and the fourth target range. Fig. 7 shows the SOC of the battery 18B as a bar graph, and the upper limit value and the lower limit value set as the target range are shown in the bar area.

[0061] For example, it is assumed that the supply of power generated by the photovoltaic power generation device 15A to the power grid 4 is requested at a prediction target time after a predetermined time has elapsed from the current time. When a prediction of the power generation is requested and a prediction start condition is satisfied (YES in S100), information on the predicted value of the amount of solar radiation at the prediction target time and its reliability (for example, history information on the actual measured value and the predicted value before the current time) is acquired from the external server 200 (S102). Then, a predicted value of the power generation in the photovoltaic power generation device 15A is calculated using the predicted value of the amount of solar radiation at the prediction target time (S104). When it is determined that the calculated predicted value of the power generation is greater than the required power required for the photovoltaic power generation device 15A (YES in S106) and that the reliability of the predicted value is high (YES in S108), a first target range is set (S110), and a control command for the SOC is output to the vehicle 18 (S120).

[0062] 4, when it is determined that the predicted value of the generated power is greater than the required power, a part of the generated power corresponding to the required power is supplied from the photovoltaic power generation device 15A to the power grid 4 at the prediction target time, and the remaining surplus part is supplied to the battery 18B. Therefore, the surplus part is charged in the battery 18B at the prediction target time.

[0063] When the reliability of the predicted value of the amount of solar radiation is high, the predicted value of the generated power is unlikely to fluctuate significantly, and the surplus portion is unlikely to fluctuate significantly. Therefore, as shown in Fig. 5, when the SOC is controlled within the first target range, even when the battery 18B is charged using the surplus portion of the generated power, the generated surplus portion can be absorbed by the battery 18B.

[0064] On the other hand, if the calculated predicted power generation value is greater than the required power (YES in S106) and the reliability of the predicted solar radiation value is low (NO in S108), a second target range is set (S112), and a control command for the SOC is output to the vehicle 18 (S120).

[0065] When the reliability of the predicted value of the amount of solar radiation is low, the predicted value of the generated power is likely to fluctuate greatly. In this case, if the surplus portion is too small, it can be absorbed by the battery 18B, but if the surplus portion is too large, the SOC of the battery 18B may exceed a predetermined upper limit value when the battery 18B is charged using the surplus portion of the generated power. Therefore, by setting the second target range, if the SOC of the battery 18B is controlled to a value close to the lower limit value (second lower limit value) of the second target range, the state of the SOC of the battery 18B can be made lower than the first lower limit value of the first target range at the prediction target time. Therefore, even if the surplus portion is too large, the generated surplus portion can be absorbed by the battery 18B.

[0066] Next, if the calculated predicted power generation value is equal to or less than the required power (NO in S106) and the predicted solar radiation value is highly reliable (YES in S114), a third target range is set (S116), and a control command for the SOC is output to vehicle 18 (S120).

[0067] 6, when it is determined that the predicted value of the generated power is smaller than the required power, at the prediction target time, all of the generated power is supplied to the power grid 4, and the shortfall is supplied from the battery 18B, and power is supplied from the battery 18B. Therefore, the shortfall is supplied from the battery 18B at the prediction target time.

[0068] When the reliability of the predicted value of the amount of solar radiation is high, the predicted value of the generated power is unlikely to fluctuate significantly, and the power shortage is unlikely to fluctuate significantly. Therefore, as shown in Fig. 7, when the SOC is controlled within the third target range, even if the shortage of generated power is supplied from the battery 18B, the shortage of power can be compensated for without the SOC falling below a predetermined lower limit.

[0069] On the other hand, if the calculated predicted power generation value is equal to or less than the required power (NO in S106) and the predicted solar radiation amount has low reliability (NO in S114), a fourth target range is set (S118), and a control command for the SOC is output to the vehicle 18 (S120).

[0070] When the reliability of the predicted value of the amount of solar radiation is low, the predicted value of the generated power is likely to fluctuate greatly. In this case, when the generated power becomes excessive and the power shortage becomes small, the shortage can be made up by power supply from the battery 18B, but when the generated power becomes insufficient and the power shortage becomes large, if the generated power is too small and the power shortage becomes large, the SOC of the battery 18B may exceed a predetermined lower limit value when the SOC of the battery 18B is supplied to a value close to the upper limit value (second upper limit value) of the fourth target value by setting the fourth target range, the state of the SOC of the battery 18B can be made higher than the first upper limit value of the third target range at the prediction target time. Therefore, even if the power shortage becomes large, it is possible to make up for the power shortage from the battery 18B.

[0071] As described above, according to the power management system 100 of the present embodiment, when the reliability of the predicted value of the amount of solar radiation is low, the generated power may be excessive or insufficient relative to the predicted value. Therefore, by setting the target range of the SOC of the battery 18B to a wide range in preparation for the generated power being excessive or insufficient relative to the predicted value, it is possible to appropriately absorb the excessive amount of generated power or compensate for the insufficient amount of generated power. Therefore, it is possible to provide a power management system, a power management server, and a power management method that appropriately absorb or compensate for the surplus or shortage of generated power in the power grid to which the photovoltaic power generation device is connected.

[0072] In particular, when battery 18B is charged using a portion of the generated power at the predicted time, the lower limit of the target range is set lower when the reliability of the predicted value is low than when the reliability is high, so that even if the generated power becomes excessive relative to the predicted value, the surplus generated power can be absorbed by battery 18B.

[0073] Furthermore, when the power of battery 18B is supplied to power system 4 together with the generated power at the predicted time, the upper limit value of the target range is set higher when the reliability of the predicted value is low than when the reliability is high. Therefore, even if the generated power is less than the predicted value and the power shortage becomes large, the shortage can be made up using the power of battery 18B.

[0074] Furthermore, by calculating an error rate using the actual measured value and the predicted value of the amount of solar radiation at the same time, the reliability can be calculated with high accuracy.

[0075] Modifications will be described below. In the above embodiment, the CEMS server 2 has been described as acquiring information regarding the amount of solar radiation at the point where the solar power generation device 15A is installed from the external server 200. However, the CEMS server 2 may directly acquire information regarding the amount of solar radiation at the point where the solar power generation device 15A is installed by using an actinometer 118 or the like installed at that point.

[0076] Furthermore, in the above embodiment, the CEMS server 2 has been described as predicting the power generation at the prediction target time, but, for example, the amount of power generation during a planned power adjustment period may be predicted. The CEMS server 2 may, for example, predict the amount of power generation during the planned power adjustment period by multiplying the predicted power generation by the control period and integrating it for the planned power adjustment period (or a predetermined period).

[0077] Furthermore, in the above-described embodiment, the CEMS server 2 has been described as obtaining a predicted value of the amount of solar radiation at the point where the solar power generation device 15A is installed from the external server 200. However, the CEMS server 2 may calculate a predicted value of the amount of solar radiation at the point using a history of actual measured values ​​of the amount of solar radiation at the point.

[0078] Furthermore, in the above embodiment, a case where one photovoltaic power generation device 15A is installed in the microgrid MG has been described as an example, but a plurality of photovoltaic power generation devices 15A may be installed in the microgrid MG.

[0079] Furthermore, in the above-described embodiment, an example has been described in which surplus power generated by the solar power generation device 15A is charged or a shortage of generated power is absorbed or compensated for by one vehicle 18, but there may be multiple vehicles 18, or at least one of the multiple vehicles may be selected that is capable of controlling the SOC within the target range set by the predicted target time.

[0080] Furthermore, in the above-described embodiment, an example has been described in which solar power generation device 15A and battery 18B are used to operate to satisfy the power requirement of power system 4, but other power sources, consumption facilities, etc. may also be combined.

[0081] Furthermore, in the above embodiment, the error rate is calculated as the mean absolute percentage error using the predicted value and the actual measured value of the amount of solar radiation at the same time, and the error rate is used to determine whether the reliability is high or not, but the method of calculating the error rate is not particularly limited to this, and for example, the ratio of the actual measured value to the predicted value (=actual measured value / actual measured value) may be calculated as the error rate. Alternatively, the method of determining whether the reliability is high or not is not limited to the method using the error rate, and for example, multiple ratios of the actual measured value to the predicted value may be calculated from the history of predicted values ​​and the history of actual measured values, and whether the reliability is high or not may be determined based on whether the ratios are within a predetermined confidence interval.

[0082] Furthermore, in the above embodiment, the case where the SOC of the battery 18B is controlled by the ECU 18A of the vehicle 18 has been described as an example. However, for example, the SOC of the battery 18B may be controlled using the EVSE 17.

[0083] Furthermore, in the above-described embodiment, the battery 18B mounted on the vehicle 18 is used as an example of a power storage device that absorbs the surplus of generated power and compensates for the power shortage, but a fixed power storage device may also be used, and the present invention is not limited to a power storage device mounted on a vehicle.

[0084] Furthermore, in the above-described embodiment, an example has been described in which the same value α is used as the margin for setting the first target range and the third target range, but different values ​​of margin may be set for setting the first target range and the third target range.

[0085] Furthermore, in the above-described embodiment, an example was described in which the same value β is used as the margin for setting the second target range and the fourth target range, but different values ​​of margin may be set for setting the second target range and the fourth target range.

[0086] Furthermore, in the above-described embodiment, the margins α and β are both predetermined values, but the margins α and β may be values ​​that are set according to, for example, the predicted value of the power generation, the size of the surplus, or the size of the power shortage.

[0087] The above-described modified examples may be implemented in whole or in part in appropriate combination. The embodiments disclosed herein should be considered to be illustrative and not restrictive in all respects. The scope of the present invention is defined by the claims, not the above description, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0088] 1 CEMS, 2 CEMS server, 3 substation equipment, 4 power system, 5 power transmission and distribution company server, 11 FEMS, 12 BEMS, 13 HEMS, 14 generator, 15 naturally variable power source, 15A solar power generation device, 16 power storage system, 17 charging equipment, 18 vehicle, 18A ECU, 18B battery, 21 control device, 22 storage device, 23 communication device, 100 power management system, 110 FEMS server, 120 BEMS server, 130 HEMS server, 118 pyranometer, 200 external server.

Claims

1. A power management system that manages power in a power grid installed in a predetermined area, A solar power generation device installed in the predetermined area and connected to the power grid; A power storage device connectable to the power grid; an acquisition device that acquires a predicted value of the amount of solar radiation at a prediction target time at a location where the solar power generation device is installed; a control device that calculates a predicted value of power generated by the photovoltaic power generation device at the prediction target time using the predicted value of the amount of solar radiation, sets a target range of an SOC of the power storage device using the predicted value of the power generation, and controls the SOC so that the SOC falls within the target range by the time the prediction target time arrives, The control device, when the reliability of the predicted value of the amount of solar radiation is low, sets the target range wider than when the reliability is high.

2. 2. The power management system according to claim 1, wherein, when the control device charges the storage device using a portion of the generated power at the predicted time, when the reliability of the predicted value of the amount of solar radiation is low, the control device sets the lower limit of the target range lower than when the reliability is high.

3. 2. The power management system according to claim 1, wherein when the control device supplies the power of the power storage device to outside the power grid together with the generated power at the predicted time, when the reliability of the predicted value of the amount of solar radiation is low, the control device sets an upper limit value of the target range higher than when the reliability is high.

4. The power management system according to claim 1 , wherein the control device calculates the reliability using an error rate calculated from an actual measurement value and a predicted value of the amount of solar radiation at the same time.

5. A power management server that manages power of a power grid installed in a predetermined area, the power grid being connected to a photovoltaic power generation device and a power storage device installed in the predetermined area; The power management server includes: Obtaining a predicted value of solar radiation at a prediction target time at a location where the solar power generation device is installed; calculating a predicted value of power generation of the photovoltaic power generation device at the prediction target time using the predicted value of the amount of solar radiation; setting a target range for an SOC of the power storage device using the predicted value of the generated power; controlling the SOC so that the SOC is within the target range by the time the prediction target time arrives; When the reliability of the predicted value of the amount of solar radiation is low, the power management server sets the target range wider than when the reliability is high.

6. A power management method for managing power of a power grid installed in a predetermined area, the power grid being connected to a photovoltaic power generation device and a power storage device installed in the predetermined area; The power management method includes: Obtaining a predicted value of solar radiation at a prediction target time at a location where the solar power generation device is installed; calculating a predicted value of power generation of the photovoltaic power generation device at the prediction target time using the predicted value of the amount of solar radiation; setting a target range for an SOC of the power storage device using the predicted value of the generated power; controlling the SOC so that the SOC is within the target range by the time the prediction target time arrives; and setting the target range wider when the reliability of the predicted value of the amount of solar radiation is low than when the reliability is high.

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