Planning method, planning device, and electric power system

Abstract

A planning method according to the present disclosure is implemented in an electric power system (200) provided with a fuel cell device (40), the planning method comprising a step for switching between: a first method for planning the output of the fuel cell device so as to compensate for the difference between a demand electric power of an electric power consumer and the output of a photovoltaic electric power generation device (30); and a second method for planning the output of the fuel cell device so as to be more restricted than the output of the fuel cell device as planned according to the first method, on the basis of the amount of hydrogen that can be used in a prescribed period.

Description

Planning method, planning device and power system

[0001] The present disclosure relates to a planning method, a planning device, and a power system.

[0002] Patent Document 1 describes a household distributed power supply system equipped with a solar cell, a fuel cell, and a power storage device. In the household distributed power supply system described in Patent Document 1, a control signal for the output required by the fuel cell is calculated as the difference between the load current and the output current of the solar cell. The power storage device supplies the power shortage caused by a delay in the increase in the fuel cell output.

[0003] Japanese Patent Application Laid-Open No. 2004-208436

[0004] In the prior art, no consideration has been given to how to deal with the case where there is a limit to the amount of hydrogen that can be used in a fuel cell.

[0005] The present disclosure provides techniques for dealing with situations where the amount of available hydrogen becomes limited.

[0006] The present disclosure provides a planning method for a power system equipped with a fuel cell device, the planning method comprising a step of switching between a first method for planning the output of the fuel cell device so as to compensate for the difference between the power demand of a power consumer and the output of a solar power generation device, and a second method for planning the output of the fuel cell device that is more limited than the output of the fuel cell device planned by the first method based on the amount of hydrogen available for use in a specified period of time.

[0007] The technology disclosed herein can appropriately deal with situations where there are restrictions on the amount of hydrogen available.

[0008] FIG. 1 is a configuration diagram of a power system according to an embodiment of the present disclosure. FIG. 2 is a functional block diagram of the control device and database shown in FIG. 1. FIG. 3 is a flowchart showing a process of switching between a learning mode and a prediction mode. FIG. 4A is a graph showing fluctuations in various powers and a charge storage rate in the power system when operated in the prediction mode. FIG. 4B is a graph showing fluctuations in various powers and a charge storage rate in the power system when operated in the learning mode. FIG. 5 is a flowchart showing an example of a process of switching from a first method to a second method. FIG. 6 is a flowchart showing another example of a process of switching from the first method to the second method. FIG. 7 is a flowchart showing yet another example of a process of switching from the first method to the second method. FIG. 8 is a flowchart showing yet another example of a process of switching from the first method to the second method.

[0009] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. The present disclosure is not limited to the following embodiments.

[0010] 1 is a configuration diagram of a power system according to an embodiment of the present disclosure. The power system 200 includes a control device 10, a database 20, a solar power generation system 30, a fuel cell system 40, and a power storage system 50. The solar power generation system 30, the fuel cell system 40, and the power storage system 50 are connected to a load 300 via a power line 102. Electric power generated by the solar power generation system 30 and the fuel cell system 40 is supplied to the load 300 via the power line 102. As needed, the electric power generated by the solar power generation system 30 and the fuel cell system 40 is stored in the power storage system 50, and the electric power is supplied from the power storage system 50 to the load 300.

[0011] A commercial power source 100 is connected to the power line 102. The power system 200 may be interconnected with the commercial power source 100. Power may be purchased from the commercial power source 100, or surplus power may be sold to the commercial power source 100 (reverse power flow). However, according to the power system 200 of this embodiment, power shortages are unlikely to occur, and surplus power is also unlikely to occur.

[0012] The solar power generation apparatus 30 includes a solar cell module 31, a first PCS (Power Conditioning Subsystem) 32, a first power meter 33, and a first control device 34. The solar power generation apparatus 30 may include a plurality of solar cell modules 31. The solar cell module 31 may be configured with a plurality of solar cell panels. The first PCS 32 converts the power generated by the solar cell module 31 from DC power to AC power and outputs the AC power to the power line 102. The first power meter 33 detects the power output from the first PCS 32, i.e., the power generated by the solar power generation apparatus 30. The first control device 34 is communicatively connected to the control device 10. The first control device 34 controls the solar cell module 31 or the first PCS 32 in accordance with instructions received from the control device 10. The first control device 34 may be a computer including a storage device in which a program required for controlling the solar power generation apparatus 30 is stored and a processor that reads and executes the program from the storage device.

[0013] The fuel cell system 40 includes a fuel cell unit 41, a second PCS 42, a second power meter 43, and a second control device 44. The fuel cell system 40 may include multiple fuel cell units 41 that can operate independently of each other. The power generated by the fuel cell system 40 can be changed by adjusting the number of operating fuel cell units 41 and / or their output. The second PCS 42 converts the power generated by the fuel cell unit 41 from DC power to AC power and outputs it to the power line 102. The second power meter 43 detects the power output from the second PCS 42, i.e., the power generated by the fuel cell system 40. The second control device 44 is communicatively connected to the control device 10. The second control device 44 controls the fuel cell unit 41 or the second PCS 42 in accordance with instructions received from the control device 10. The second control device 44 may be a computer including a storage device that stores a program required for controlling the fuel cell system 40 and a processor that reads and executes the program from the storage device.

[0014] A hydrogen storage device 45 is connected to the fuel cell device 40. The hydrogen storage device 45 stores liquefied hydrogen. An example of the hydrogen storage device 45 is a hydrogen storage tank. Hydrogen gas is produced from the liquefied hydrogen and supplied to the fuel cell unit 41. The hydrogen storage device 45 is provided with a level sensor that detects the remaining amount of hydrogen. The detected value of the level sensor is acquired via the receiver 60 at a predetermined sampling period and input to the control device 10. The detected value indicating the remaining amount of hydrogen may be stored in chronological order in the database 20.

[0015] The remaining amount of hydrogen may be measured by a method other than a level sensor. For example, when high-pressure hydrogen gas is stored in the hydrogen storage device 45, the remaining amount of hydrogen is detected by a pressure sensor. The remaining amount of hydrogen may be calculated, for example, from the difference between the amount of hydrogen refilled into the hydrogen storage device 45 and the amount of hydrogen released from the hydrogen storage device 45. The manager of the power system 200 may be responsible for determining the remaining amount of hydrogen using the level sensor. For example, if the measurement result of the remaining amount of hydrogen by the level sensor is displayed on a display unit provided in the hydrogen storage device 45, the manager can determine the remaining amount of hydrogen and decide, for example, when to refill the hydrogen storage device 45 with hydrogen. The manager may be a user of the power system 200.

[0016] The hydrogen storage device 45 may be a facility independent of the power system 200. In this case, the line connecting the hydrogen storage device 45 and the fuel cell device 40 may be a hydrogen gas pipeline.

[0017] The fuel cell in the fuel cell device 40 may be a polymer electrolyte fuel cell, a solid oxide fuel cell, a phosphoric acid fuel cell, a molten carbonate fuel cell, or the like.

[0018] The power storage device 50 includes a storage battery 51, a third PCS 52, a third wattmeter 53, and a third control device 54. The storage battery 51 may be a secondary battery. The power storage device 50 may include a capacitor instead of the storage battery 51. The third PCS 52 is a bidirectional PCS. When power is stored in the storage battery 51, the third PCS 52 converts AC power to DC power. When power is discharged from the storage battery 51, the third PCS 52 converts DC power to AC power. The third wattmeter 53 detects the power output from the third PCS 52 and the power input to the third PCS 52. In other words, the third wattmeter 53 detects the charging power and discharging power of the power storage device 50. The third control device 54 is communicatively connected to the control device 10. The third control device 54 controls the storage battery 51 or the third PCS 52 according to instructions received from the control device 10. The third control device 54 may be a computer including a storage device that stores a program required for controlling the power storage device 50, and a processor that reads and executes the program from the storage device.

[0019] The third control device 54 sequentially transmits the state of charge (SOC) of the power storage device 50 to the control device 10. The state of charge (SOC) of the power storage device 50 is stored in the database 20 in chronological order.

[0020] The load 300 represents a power consumer such as a factory. The fourth power meter 302 detects, for example, the power consumption of the factory. The fourth power meter 302 may be part of the power system 200.

[0021] The control device 10 issues control instructions to each of the first control device 34, the second control device 44, and the third control device 54 to control the operation of the photovoltaic power generation device 30, the fuel cell device 40, and the power storage device 50. Specifically, the control device 10 transmits information necessary for the respective control operations to each of the first control device 34, the second control device 44, and the third control device 54. The control device 10 is a computer equipped with a storage device that stores programs necessary for controlling these devices and a processor that reads and executes the programs from the storage device. The control device 10 acquires detection values ​​from the first wattmeter 33, the second wattmeter 43, the third wattmeter 53, and the fourth wattmeter 302 at a predetermined sampling period (e.g., every 30 seconds) and transmits them to the database 20. From these detection values, the power generated by the photovoltaic power generation device 30, the power generated by the fuel cell device 40, the charging power of the power storage device 50, the discharging power of the power storage device 50, and the power consumption of the load 300 can be determined.

[0022] The database 20 is configured by a server computer and is communicably connected to the control device 10. The database 20 stores data in chronological order, such as the power generated by the solar power generation device 30, the power generated by the fuel cell device 40, the charging power of the power storage device 50, the discharging power of the power storage device 50, the power consumption of the load 300, and the power storage rate of the power storage device 50. The amount of power (kWh) can be calculated from the time-series data.

[0023] The control device 10 may be a cloud computer or an edge computer. The database 20 may be a database in a cloud server or an edge server. The cloud computer and the cloud server may be located at a location away from the locations where the photovoltaic power generation device 30, the fuel cell device 40, and the power storage device 50 are installed. The cloud computer as the control device 10 is communicatively connected to the first control device 34, the second control device 44, and the third control device 54 via a communication network such as the Internet. The edge computer and the edge server may be located near the locations where the photovoltaic power generation device 30, the fuel cell device 40, and the power storage device 50 are installed.

[0024] 2 is a functional block diagram of the control device 10 and database 20 shown in FIG. 1. The database 20 stores factory operation data, weather data, power data, and power storage data. The control device 10 creates a prediction model through machine learning using the various data stored in the database 20, and uses the prediction model to create operation instructions for the fuel cell device 40. The prediction model includes a prediction model for predicting the power demand of the factory and a prediction model for predicting the power generated by the solar power generation device 30.

[0025] In the database 20, the factory operation data is data entered by the administrator from the terminal 21. The factory operation data is a combination of data indicating whether the factory is operating or not and date data. The data indicating whether the factory is operating or not is data indicating a non-business day or an operating day. The factory operation data makes it possible to identify whether a specific day in the past was a non-business day or an operating day. There is a correlation between the power consumption of a factory and whether the factory is operating or not. The power consumption of a factory is high on operating days, but low on non-business days. Therefore, the factory operation data can be used as learning data when creating a prediction model for predicting the power demand of a factory.

[0026] Even when the load 300 (FIG. 1) is a facility other than a factory, there is a correlation between power consumption and whether or not it is operating. Examples of facilities other than factories include commercial facilities, hospitals, schools, and office buildings. For example, when the load 300 is a commercial facility such as a department store, the operation data can be a combination of date data and data indicating one of "holiday," "business day and weekday," and "business day and holiday." A commercial facility consumes more power on business days, but less power on holiday days. Even on the same business day, there is a difference between power consumption on weekdays and power consumption on holidays.

[0027] In the database 20, weather data is input from a weather information service 22 via a communication network such as the Internet. The weather data may be input by an administrator from the terminal 21. The weather data is a combination of data indicating the nature of the weather and date data. The data indicating the nature of the weather is, for example, data combining a time period and the intensity of sunlight. The weather data allows the intensity of sunlight for each time period in the past to be determined. The intensity of sunlight is expressed in multiple intensities, for example, from an intensity corresponding to clear skies to an intensity corresponding to rain. There is a correlation between the intensity of sunlight and the power generated by the solar power generation device 30. When there is sunlight, the power generation power (kW) is high, and when there is no sunlight, the power generation power is low. Therefore, the weather data indicating the intensity of sunlight can be used as learning data when creating a prediction model for predicting the power generation power of the solar power generation device 30. Instead of or in addition to the intensity of sunlight, the weather data may include the duration of sunlight for each time period. There is a correlation between the duration of sunlight and the power generation amount (kWh) of the solar power generation device 30.

[0028] Data indicating weather conditions may include data on a combination of time period and temperature. For example, when the temperature is high, the power consumption of air conditioners increases, and so does the power consumption of factories. Even when the temperature is low, the power consumption of air conditioners increases, and so does the power consumption of factories. Therefore, weather data indicating temperatures can be used as learning data when creating a prediction model for predicting the power demand of factories.

[0029] The data indicating the weather conditions is not limited to the above, and may include other data that is correlated with the power generated by the solar power generation device 30, or other data that is correlated with the power demand.

[0030] In the database 20, the power data is data input from the power meters 33, 43, 53, and 302 via the control device 10. The power data may be time-series data for the power generated by the photovoltaic power generation system 30, the power generated by the fuel cell system 40, the charging power of the power storage system 50, the discharging power of the power storage system 50, and the power consumption of the load 300. The power data makes it possible to identify the power generated by the photovoltaic power generation system 30, the power generated by the fuel cell system 40, the charging power of the power storage system 50, the discharging power of the power storage system 50, and the power consumption of the load 300 at a specific time in the past. The power data indicating the power consumption of the load 300 can be used as learning data when creating a prediction model for predicting the power demand of the factory. The data on the power generated by the photovoltaic power generation system 30 can be used as learning data when creating a prediction model for predicting the power generation of the photovoltaic power generation system 30.

[0031] In the database 20, the power storage data is data input from the power storage device 50 via the control device 10. The power storage data is data indicating the power storage rate of the power storage device 50.

[0032] The control device 10 includes a prediction unit 12 , a planning unit 14 , and a control unit 16 .

[0033] The prediction unit 12 has a power demand prediction unit 12a and a photovoltaic power generation prediction unit 12b. In the power demand prediction unit 12a, the predicted value of power demand is predicted based on the correlation between actual weather conditions and actual values ​​of power demand, and on the weather forecast. In the power demand prediction unit 12a, the predicted value of power demand is predicted based on the correlation between actual weather conditions and actual values ​​of power demand of the factory, the weather forecast, and the factory operation plan. In the photovoltaic power generation prediction unit 12b, the predicted value of output of the photovoltaic power generation device 30 is predicted based on the correlation between actual weather conditions and actual values ​​of output of the photovoltaic power generation device 30, and on the weather forecast.

[0034] The power demand prediction unit 12a may be a program module including a prediction model for predicting the power demand of the load 300. The prediction model in the power demand prediction unit 12a is created using actual power demand records, weather records, and factory operation records. Power data indicating the power consumption of the load 300 is used as the actual power demand records. Weather data is used as the weather records. The weather records are weather records for areas where power consumers such as factories are located. Factory operation data is used as the factory operation records. The prediction model is, for example, a regression model. The power data, weather data, and factory operation data are supervised data in machine learning.

[0035] A predicted value of the power demand (power consumption) of the factory can be obtained by inputting a weather forecast and a factory operation plan into the prediction model in the power demand prediction unit 12a. That is, a predicted value of the power demand of the factory, which is a dependent variable, is obtained using the weather forecast and the factory operation plan as explanatory variables. For example, data on the temperature at the time or time period when the predicted value of the power demand should be obtained is used as the weather forecast. The weather forecast may include data indicating the intensity of sunlight or the duration of sunlight. The weather forecast is a weather forecast for an area where power consumers such as factories are located. Data indicating whether the factory will be operating on the date and time when the predicted value of the power demand should be obtained is used as the factory operation plan.

[0036] The solar power generation prediction unit 12b may be a program module including a prediction model for predicting the power generation of the solar power generation device 30. The prediction model in the solar power generation prediction unit 12b is created using the power generation record and weather record of the solar power generation device 30. Power data indicating the power generation of the solar power generation device 30 is used as the power generation record of the solar power generation device 30. Weather data is used as the weather record. The prediction model is, for example, a regression model. The power data and weather data are supervised data in machine learning.

[0037] By inputting the weather forecast into the prediction model in the solar power generation prediction unit 12b, a predicted value of the output (power generation) of the solar power generation device 30 can be obtained. That is, the predicted value of the output of the solar power generation device 30, which is the objective variable, is obtained using the weather forecast as an explanatory variable. As the weather forecast, for example, data indicating the intensity or duration of sunlight at the time or time zone when the predicted value of the output of the solar power generation device 30 should be obtained is used.

[0038] To create each of the above-described prediction models in the prediction unit 12, various data from a predetermined period (e.g., three months to one year) is used. The prediction models may be updated daily, which is expected to improve prediction accuracy. The prediction models may be stored in the database 20.

[0039] The process of obtaining predicted values ​​by the prediction unit 12 is executed at a predetermined cycle. For example, a plurality of predicted values ​​from the present to 24 hours later are obtained at a cycle of once every hour. The plurality of predicted values ​​are, for example, 24 predicted values ​​at hourly intervals.

[0040] A process of correcting the predicted value may be performed. For example, the predicted value of the power demand may be corrected in the following manner. That is, the predicted value obtained from the prediction model may be corrected based on the actual value of the power demand for the most recent first period and the predicted value of the power demand for the second period corresponding to the first period. The most recent first period is a period from the current time back a predetermined time (30 minutes to 1 hour). For example, if the current time is 10:00, the most recent first period is the period from 9:00 to 10:00. The actual value of the power demand for this period is stored in chronological order in the database 20 as the power consumption of the load 300. The actual value of the power demand for the first period may be an average value for the first period. Next, the second period corresponding to the first period is a period corresponding to the first period in the 24-hour period for which the 24 predicted values ​​were obtained. For example, when the first period is from 9:00 to 10:00, the corresponding second period is from 9:00 to 10:00.

[0041] For example, assume that the actual power demand value for the first period from 9:00 to 10:00 is 100 kW. Meanwhile, assume that the predicted power demand value for the second period from 9:00 to 10:00 is 90 kW. In this case, the actual value exceeds the predicted value by 10 kW. Therefore, a correction is performed by adding 10 kW to the predicted power demand value for 10:00 to 11:00. This improves the prediction accuracy. The difference between the actual value and the predicted value may be used directly for the correction, or a predetermined percentage (e.g., 80%) of the difference between the actual value and the predicted value may be used for the correction. The degree of correction is arbitrary. Furthermore, of the predicted values ​​for 24 future points, only the most recently used predicted value may be corrected, or multiple predicted values ​​including the most recently used predicted value may be corrected.

[0042] The predicted value of the power generation power of the photovoltaic power generation device 30 may be corrected using the same method. That is, the predicted value obtained from the prediction model may be corrected based on the actual value of the output of the photovoltaic power generation device 30 for the most recent third period and the predicted value of the output of the photovoltaic power generation device 30 for a fourth period corresponding to the third period. This can improve the prediction accuracy. The third period may be the same period as the first period or may be a different period. The fourth period may be the same period as the second period or may be a different period.

[0043] The predicted values ​​calculated by the prediction unit 12 are stored in the database 20. With this configuration, it is possible to execute the prediction process for calculating the predicted values ​​and the planning process for calculating the planned values ​​asynchronously. The server that serves as the database 20 is an example of a storage device that stores the predicted values ​​of power demand and the predicted values ​​of the output of the photovoltaic power generation device 30.

[0044] The planner 14 includes a fuel cell output planner 14a. The fuel cell output planner 14a may be a program module for calculating a planned value of the output (power generation) of the fuel cell device 40. The fuel cell output planner 14a acquires a predicted value Pd of power demand and a predicted value Ppv of the output of the photovoltaic power generation device 30 from the predictor 12, and calculates a planned value of the output of the fuel cell device 40 using these predicted values. For example, when the current time is 8:50, a predicted value of power demand and a predicted value of the output of the photovoltaic power generation device 30 for the time period from 9:00 to 10:00 are created in the predictor 12, and a planned value of the output of the fuel cell device 40 is calculated from these predicted values. The predicted value and the planned value may be expressed in terms of instantaneous power (kW) or the amount of power per unit time (kWh).

[0045] In this embodiment, the planner 14 plans the output of the fuel cell device 40 so as to compensate for the difference between the predicted value Pd of power demand and the predicted value Ppv of the output of the photovoltaic power generation device 30. By planning the output of the fuel cell device 40 using the predicted value, fluctuations in the output of the fuel cell device 40 can be suppressed compared to when the output of the fuel cell device 40 is planned based only on the most recent actual values. Since there is a correlation between the lifespan of the stack of the fuel cell device 40 and the frequency of fluctuations in the output of the fuel cell device 40, suppressing fluctuations in the output of the fuel cell device 40 extends the lifespan of the fuel cell device 40.

[0046] The planned value Pfc of the output of the fuel cell device 40 is calculated, for example, as the difference (Pd-Ppv) between the predicted value Pd of power demand and the predicted value Ppv of the output of the photovoltaic power generation device 30. Therefore, when the current time is 8:50, the planned value Pfc of the output of the fuel cell device 40 for the time slot from 9:00 to 10:00 can be (Pd-Ppv). If the difference is zero or less, that is, if (Pd-Ppv)≦0, the planned value Pfc of the output of the fuel cell device 40 is zero.

[0047] According to the method of this embodiment, a predicted value Pd of power demand and a predicted value Ppv of the output of the photovoltaic power generation device 30 are calculated. Therefore, even if a method of determining the output of the fuel cell device 40 based on the most recent data would cause the output of the fuel cell device 40 to be varied, the method of this embodiment may determine that it is better not to vary the output of the fuel cell device 40. This difference is due to the poor tracking ability of the output of the fuel cell device 40.

[0048] The process of calculating the planned values ​​by the planning unit 14 is executed at a predetermined interval. For example, the planned values ​​required for operation in the immediate time period are calculated once every hour.

[0049] The planner 14 is an example of a planner that executes a planning method for planning the output of the fuel cell device 40 so as to compensate for the difference between the predicted value Pd of power demand and the predicted value Ppv of the output of the photovoltaic power generation device 30 .

[0050] In this specification, "compensating for the difference" means both compensating for the entire difference and compensating for only a portion of the difference. In the above example, the difference between the predicted value Pd of power demand and the predicted value Ppv of the output of the photovoltaic power generation device 30 is regarded as the planned value Pfc of the output of the fuel cell device 40, and therefore the entire difference is compensated for by the output of the fuel cell device 40.

[0051] The control unit 16 includes a fuel cell correction control unit 16a, a power storage control unit 16b, and a solar cell output suppression unit 16c.

[0052] In the control unit 16, the fuel cell correction control unit 16a may be a program module that determines whether or not the planned value Pfc of the output of the fuel cell device 40 needs to be corrected, and corrects the planned value Pfc as necessary. The fuel cell correction control unit 16a acquires the planned value Pfc of the output of the fuel cell device 40 from the planner 14, and also acquires the actual value Rd of the power demand, the actual value Rpv of the output of the photovoltaic power generation device 30, and the state of charge (SOC) of the power storage device 50 from the database 20. The actual value Rd of the power demand is the power consumption of the load 300. Specifically, the average value of the power consumption over a predetermined period can be used as the actual value Rd of the power demand. The average value of the power generated by the photovoltaic power generation device 30 over the predetermined period can be used as the actual value Rpv of the output of the photovoltaic power generation device 30. The average value is, for example, a moving average value. The predetermined period is, for example, the period from 30 minutes ago to the time when the most recent data was acquired (approximately the current time). The charge rate of the power storage device 50 is the charge rate of the power storage device 50 at the time when the most recent data was acquired (approximately the current time).

[0053] It is desirable for the power system 200 to avoid purchasing power from the commercial power source 100 and selling power to the commercial power source 100 (reverse power flow) as much as possible, and it is also desirable for the power storage device 50 to be able to charge and discharge at all times. If the power storage device 50 is in a fully charged state or a fully discharged state, it becomes difficult for the power storage device 50 to balance supply and demand in the power system 200. In this embodiment, the fuel cell correction control unit 16a corrects the planned value of the output of the fuel cell device 40, taking into account the power storage rate of the power storage device 50, so as to prevent the power storage rate of the power storage device 50 from becoming a fully charged state or a fully discharged state.

[0054] The fuel cell correction control unit 16a corrects the planned value Pfc of the output of the fuel cell device 40 based on the storage rate (SOC) of the power storage device 50 predicted from the difference between the actual value Rd of power demand and the sum of the actual value Rpv of the output of the photovoltaic power generation device 30 and the planned value Pfc of the output of the fuel cell device 40. This makes it possible to create a command value for the output of the fuel cell device 40 while taking into account the storage rate of the power storage device 50, and ultimately to maintain the power storage device 50 in a state where it can be charged and discharged.

[0055] Specifically, the value (Rd-Rpv-Pfc) is calculated by subtracting the sum of the actual value Rpv of the output of the photovoltaic power generation device 30 and the planned value Pfc of the output of the fuel cell device 40 from the actual value Rd of the power demand. This value may be zero, a negative value, or a positive value.

[0056] When the above value (Rd - Rpv - Pfc) is a negative value, prediction based on the most recent actual value indicates a high possibility of excess power in the future. Therefore, the storage rate after a predetermined time (e.g., one hour) when the power storage device 50 is charged with power corresponding to the absolute value of the value (Rd - Rpv - Pfc) is predicted from the most recent storage rate. The storage rate after the predetermined time is calculated from the most recent storage rate of the power storage device 50, the capacity of the power storage device 50, and the charging power of the power storage device 50. If the storage rate after the predetermined time exceeds a predetermined upper limit value that is lower than the fully charged state (100%), the planned output value Pfc of the fuel cell device 40 is corrected so that the storage rate after the predetermined time is equal to or lower than the upper limit value. For example, the planned output value Pfc of the fuel cell device 40 is corrected by subtracting a correction value from the planned output value Pfc of the fuel cell device 40 or multiplying it by a correction value less than 1. As a result, the fuel cell device 40 is operated at an output lower than the planned value Pfc. The upper limit of the charge rate is set to, for example, 80% of the capacity of the power storage device 50 .

[0057] If the above value (Rd - Rpv - Pfc) is a positive value, it can be said that, based on the most recent actual value, there is a high possibility of a power shortage in the future. Therefore, the storage rate after a predetermined time (e.g., one hour) when power equivalent to the value (Rd - Rpv - Pfc) is discharged from the power storage device 50 is predicted from the most recent storage rate. If the storage rate after the predetermined time falls below a predetermined lower limit value that is higher than a fully discharged state (0%), the planned output value Pfc of the fuel cell device 40 is corrected so that the storage rate after the predetermined time is equal to or higher than the lower limit value. For example, the planned output value Pfc of the fuel cell device 40 is corrected by adding a correction value to the planned output value Pfc of the fuel cell device 40 or multiplying it by a correction value greater than 1. As a result, the fuel cell device 40 will operate at an output greater than the planned value Pfc. The lower limit of the storage rate is set to, for example, 20% of the capacity of the power storage device 50.

[0058] If the above value (Rd - Rpv - Pfc) is zero, the planned value Pfc is not corrected. Also, if the charge rate after a predetermined time is equal to or greater than the lower limit and equal to or less than the upper limit, the planned value Pfc is not corrected.

[0059] The fuel cell correction control unit 16a uses the planned value Pfc or the corrected planned value Pfc' to create a command value for the output of the fuel cell device 40. The command value is sent to the second control device 44 of the fuel cell device 40. The second control device 44 controls the operation of the fuel cell unit 41 so that power is generated in accordance with the command value.

[0060] The process of correcting the planned value Pfc of the output of the fuel cell device 40 may be executed in synchronization with the process of creating the planned value Pfc, or may be executed in a control cycle shorter than that of the process of creating the planned value Pfc. The planned value Pfc may be corrected when it is determined that the power storage rate of the power storage device 50 will exceed the upper limit value or fall below the lower limit value.

[0061] In the control unit 16, the power storage control unit 16b may be a program module for controlling the power storage device 50 to adjust the charging and discharging power of the power storage device 50. The power storage control unit 16b acquires the actual value Rd of power demand, the actual value Rpv of the output of the photovoltaic power generation device 30, and the actual value Rfc of the output of the fuel cell device 40 from the database 20. Since the output of the fuel cell device 40 follows the command value, the command value for the output of the fuel cell device 40 may be considered to be the actual value Rfc of the output of the fuel cell device 40.

[0062] The power storage control unit 16b controls the power storage device 50 so as to compensate for the difference between the actual value Rd of power demand and the sum of the actual value Rpv of the output of the photovoltaic power generation device 30 and the actual value Rfc of the output of the fuel cell device 40 by charging or discharging the power storage device 50. With this configuration, it is possible to achieve a balance between supply and demand in the power system 200, and therefore it is possible to avoid purchasing power from or selling power to the commercial power source 100 as much as possible. This is advantageous from the perspective of avoiding the use of power from the commercial power source 100 and increasing the renewable energy utilization rate.

[0063] Specifically, the actual value Rd of the power demand is subtracted by the actual value Rpv of the output of the photovoltaic power generation device 30 and the actual value Rfc of the output of the fuel cell device 40 to calculate a value (Rd - Rpv - Rfc). This value is zero, a negative value, or a positive value. When the value (Rd - Rpv - Rfc) is negative, there is surplus power, and a command value for charging power of the power storage device 50 is created so that the power storage device 50 is charged with the surplus power. When the value (Rd - Rpv - Rfc) is positive, there is a power shortage, and a command value for discharging power of the power storage device 50 is created so that the power shortage is compensated for by discharging the power storage device 50. When the value (Rd - Rpv - Rfc) is zero, a command value for charging and discharging power of the power storage device 50 is created so that the charging and discharging power is zero. The actual value Rd of the power demand is the power consumption of the load 300. The most recent power consumption can be used as the actual value Rd of the power demand. The most recent output can be used as the actual value Rpv of the output of the photovoltaic power generation device 30 and the actual value Rfc of the output of the fuel cell device 40. The most recent power consumption and the most recent output are values ​​included in the power data stored in the database 20.

[0064] A command value for the charge / discharge power of the power storage device 50 is sent from the power storage control unit 16b to the third control device 54 of the power storage device 50. The third control device 54 controls the operation of the power storage device 50 so that the power storage device 50 is charged with power according to the command value or discharged with power according to the command value. The charge / discharge power of the power storage device 50 is adjusted to a desired value by controlling the third PCS 52.

[0065] In the control unit 16, the solar cell output suppression unit 16c may be a program module for suppressing the output of the solar power generation device 30. When the power storage rate of the power storage device 50 exceeds a first threshold, the solar cell output suppression unit 16c generates a command value for the solar power generation device 30 to suppress the output of the solar power generation device 30. When the power storage rate of the power storage device 50 falls below a second threshold, the suppression of the output of the solar power generation device 30 is released. The first threshold for the power storage rate is, for example, 90% of the capacity of the power storage device 50. The second threshold for the power storage rate is, for example, 85% of the capacity of the power storage device 50. With this configuration, it is possible to prevent the power storage device 50 from reaching a fully charged state, and therefore it is possible to avoid selling power to the commercial power source 100 (reverse power flow) as much as possible.

[0066] The process of suppressing the output of the solar power generation device 30 is as follows: The solar cell output suppression unit 16c sets a value equal to or less than the difference between the sum of the actual value Rd of power demand and the chargeable power Sc of the power storage device 50 and the actual value Rfc of the output of the fuel cell device 40 as the upper limit of the output of the solar power generation device 30. With this configuration, it becomes possible to use the power generated by the solar power generation device 30 without any waste.

[0067] Specifically, a value (Rd+Sc-Rfc) is calculated by subtracting the actual output value Rfc (kW) of the fuel cell device 40 from the sum of the actual power demand value Rd (kW) and the chargeable power Sc (kW) of the power storage device 50. The value (Rd+Sc-Rfc) or a value less than this is set as the upper limit of the output of the solar power generation device 30. The actual power demand value Rd is, for example, power consumption at an arbitrary point in time in the past, and may be the average value of power demand in the most recent time period (e.g., the most recent hour), or the minimum value of power demand in the most recent time period. The chargeable power Sc of the power storage device 50 is any power equal to or less than the maximum charging power of the power storage device 50. The maximum charging power of the power storage device 50 is a design value for the power storage device 50 determined depending on the type of storage battery 51, etc. In other words, the power storage device 50 is not charged with power exceeding the maximum charging power. The actual output value Rfc of the fuel cell device 40 is, for example, the most recent output value of the fuel cell device 40 .

[0068] When the output of the solar power generation device 30 is not suppressed, the first PCS 32 performs MPPT (Maximum Power Point Tracking) control so that the maximum output is supplied from the solar power generation device 30 to the power line 102. On the other hand, when an upper limit value for the output of the solar power generation device 30 is set, the first PCS 32 operates the solar power generation device 30 at an operating point that is different from the optimal operating point on the IV curve so that the output of the solar power generation device 30 does not exceed the upper limit value. In other words, the first PCS 32 does not perform MPPT control. In this embodiment, the first PCS 32 has such a function.

[0069] As described above, in this embodiment, a prediction model for predicting the power demand of a factory and a prediction model for predicting the power generated by the photovoltaic power generation device 30 are used. Creating a prediction model requires a sufficient number of days of various data. Until a prediction model with sufficient accuracy is created, a planned value for the output of the fuel cell device 40 can be calculated using the most recent data on power demand and the most recent data on the output of the photovoltaic power generation device 30. Specifically, the difference between the most recent power demand and the most recent output of the photovoltaic power generation device 30 is calculated as the planned value for the output of the fuel cell device 40. The most recent power demand is, for example, the average value of the power demand over the most recent hour. The most recent output of the photovoltaic power generation device 30 is, for example, the average value of the output of the photovoltaic power generation device 30 over the most recent hour. The average value is, for example, a moving average value. The most recent power demand may be the minimum value of the power demand in the most recent time period (e.g., the most recent hour).

[0070] In this specification, an operating mode in which a planned value for the output of the fuel cell device 40 is calculated using a prediction model is defined as a prediction mode. An operating mode in which a planned value for the output of the fuel cell device 40 is calculated using only the most recent data is defined as a learning mode. However, calculation of the planned value using a prediction model is not essential. In this case, since there is no need to create a prediction model, the power system 200 can be operated in a normal mode in which a planned value for the output of the fuel cell device 40 is calculated using only the most recent data, similar to the learning mode.

[0071] FIG. 3 is a flowchart showing a process for switching between the learning mode and the prediction mode. Each process shown in FIG. 3 is executed by the control device 10. In step S1, the power system 200 is operated in the learning mode. In step S2, it is determined whether a predetermined period has elapsed. After the predetermined period has elapsed, in step S3, the power system 200 is switched from the learning mode to the prediction mode. In step S4, the power system 200 is operated in the prediction mode. That is, after operation in the learning mode is performed for a predetermined period, the power system 200 is switched between the learning mode and the prediction mode. The predetermined period is, for example, three months to one year.

[0072] Prior to the prediction mode, a learning mode is executed in which the output of the fuel cell system 40 is planned to compensate for the difference between the actual value Rd of the factory's power demand and the actual value Rpv of the output of the photovoltaic power generation system 30, thereby collecting the learning data necessary for creating a prediction model. This improves the accuracy of predictions when the prediction mode is executed. After the learning mode is executed for a predetermined period of time, the method for planning the output of the fuel cell system 40 switches from the learning mode to the prediction mode. In the prediction mode, the predicted value Pd of the factory's power demand is predicted based on the actual value Rd of the factory's power demand. In the prediction mode, the predicted value Ppv of the output of the photovoltaic power generation system 30 is predicted based on the actual value Rpv of the output of the photovoltaic power generation system 30.

[0073] According to the flowchart of Fig. 3, the switching from the learning mode to the prediction mode is performed automatically after a predetermined period of time has elapsed. However, the switching from the learning mode to the prediction mode may also be performed in response to an input from an administrator.

[0074] FIG. 4A is a graph showing fluctuations in various powers and energy storage rates in the power system of this embodiment when the prediction mode is executed. FIG. 4B is a graph showing fluctuations in various powers and energy storage rates in the power system of this embodiment when the learning mode is executed. The horizontal axis of the graph represents the passage of time. The vertical axis on the left side of the upper graph represents power (kW). The vertical axis on the right side of the upper graph represents energy storage rate (%). The vertical axis of the lower graph represents purchased power from a commercial power source or reverse flow power (kW) to the commercial power source. The power consumption W1 of the load 300 and the output of the photovoltaic power generation device 30 are data obtained from an actual facility. The output W3 of the fuel cell device 40, the charge / discharge power W4 of the energy storage device 50, the energy storage rate W5, and the reverse flow power W6 are data obtained by computer simulation.

[0075] The power consumption W1 of the load 300 is consistent between Figures 4A and 4B. In the examples of Figures 4A and 4B, no upper limit is set for the output W2 of the solar power generation device 30, so the output W2 of the solar power generation device 30 is also consistent between Figures 4A and 4B.

[0076] As shown in Figure 4B, when the output of the fuel cell device 40 was planned based on the most recent data without prediction using a prediction model, the output W3 of the fuel cell device 40 fluctuated significantly over time. The storage rate W5 of the power storage device 50 was between 80% and 100% for most of the time period. Therefore, during the period when the output W2 of the photovoltaic power generation device 30 exceeded the power consumption W1 (particularly from June 13 to June 14), the charging power W4 of the power storage device 50 could not be increased. In the example of Figure 4B, reverse flow power W6 occurred.

[0077] In contrast, as shown in FIG. 4A , when predictions were made using the prediction model, fluctuations in the output W3 of the fuel cell device 40 over time were small. For example, from June 11 to June 12, the output W3 was maintained at approximately 100 kW. Because the fluctuations in the output of the fuel cell device 40 were small, damage to the stack was suppressed. This leads to a longer lifespan of the fuel cell device 40. The energy storage rate W5 of the power storage device 50 was maintained between 20% and 80% throughout the entire period. Therefore, during the period when the output W2 of the solar power generation device 30 exceeded the power consumption W1 (particularly from June 13 to June 14), the charging power W4 of the power storage device 50 was increased, and the power storage device 50 absorbed the surplus power. In the example of FIG. 4A , no reverse power flow occurred.

[0078] Next, switching between methods for planning the output of the fuel cell device 40 will be described. Hereinafter, a first method is defined as a method for planning the output of the fuel cell device 40 so as to compensate for the difference between the power demand and the output of the photovoltaic power generation device 30. A second method is defined as a method for planning an output of the fuel cell device 40 that is more limited than the output planned by the first method based on the amount of hydrogen available for use in a predetermined period. By switching between the first and second methods, it is possible to appropriately deal with situations in which the amount of available hydrogen is limited. Examples of such situations include situations in which it is desirable to intentionally reduce hydrogen consumption and situations in which there is a problem with refilling hydrogen into the hydrogen storage device 45. In this embodiment, the "amount of available hydrogen" refers to the amount of hydrogen stored in the hydrogen storage device 45. The "predetermined period" refers to a period determined by the expected time when the hydrogen storage device 45 is to be refilled with hydrogen or when the hydrogen storage device 45 is to be replaced. An example of the "predetermined period" is the period from the present time until the hydrogen storage device 45 is expected to be refilled with hydrogen or replaced.

[0079] In the prediction mode, learning mode, and normal mode described above, the output of the fuel cell system 40 is planned according to the first method. In this case, the difference between the power demand and the output of the photovoltaic power generation system 30 is either the difference between predicted values ​​calculated using a prediction model or the difference between actual values ​​stored in chronological order in the database 20. On the other hand, the second method is a method for planning the output of the fuel cell system 40 based on the amount of hydrogen available for use over a predetermined period, without using predicted values ​​or actual data (actual values) of the power demand and the output of the photovoltaic power generation system 30. In the second method, the fuel cell system 40 is operated according to a schedule predetermined by an administrator. The schedule predetermined by the administrator is typically created based on the amount of hydrogen stored in the hydrogen storage tank 45 so that hydrogen consumption is suppressed compared to normal (when the first method is executed). For example, according to the first method, if the average output of the fuel cell system 40 on a factory operating day is 100 kW, a schedule is created so that the fuel cell system 40 is operated at a lower output (e.g., 50 kW). In other words, according to the second method, the fuel cell system 40 can be operated while conserving hydrogen. The schedule is input in advance into the control device 10. The schedule is a plan for the output of the fuel cell device 40 for each time period of the day, set by an administrator through input operations. Each time period has a length of 30 minutes to 1 hour.

[0080] In the second method, as in the first method, the administrator may plan the output of the fuel cell device 40 to compensate for the difference between the power demand and the output of the solar power generation device 30. In this case, however, a planned value is created in which the output of the fuel cell device 40 is suppressed (limited) to, for example, about 50% compared to the first method.

[0081] The schedule may be created so that the amount of hydrogen consumed L2 when the output of the fuel cell device 40 is planned using the second method is less than the amount of hydrogen consumed L1 when the output of the fuel cell device 40 is planned using the first method. The amounts of hydrogen consumed L1 and L2 are, for example, amounts consumed per day. Because the amount of hydrogen consumed L1 when the output of the fuel cell device 40 is planned using the first method varies from day to day, for example, an average value over several days can be used.

[0082] 5 is a flowchart showing an example of a process for switching from the first method to the second method. When a switching instruction is input by the manager of the power system 200 in step S11, the control device 10 switches the method for planning the output of the fuel cell device 40 from the first method to the second method in step S12. The switching instruction by the manager is input to the control device 10, for example, using an input terminal (not shown) provided in the control device 10. In the example shown in FIG. 5, the switching from the first method to the second method is performed manually. For example, it is conceivable that the manager determines whether the remaining amount of hydrogen has fallen below a threshold remaining amount and then issues a switching instruction.

[0083] FIG. 6 is a flowchart showing another example of a process for switching from the first method to the second method. In step S21, the control device 10 receives information indicating the remaining amount of hydrogen via the receiver 60. The information indicating the remaining amount of hydrogen may be a value detected by a level sensor in the hydrogen storage device 45. In step S22, it is determined whether the remaining amount of hydrogen is less than a predetermined threshold. If the remaining amount of hydrogen is less than the predetermined threshold, in step S23, the control device 10 switches the method for planning the output of the fuel cell device 40 from the first method to the second method. In this example shown in FIG. 6, the method switches from the first method to the second method when the remaining amount of hydrogen in the hydrogen storage device 45 decreases. By switching to the second method in response to the remaining amount of hydrogen, it is possible to continue operating the fuel cell device 40 in a planned manner for a predetermined period of time, specifically, until the next time the hydrogen storage device 45 is replenished with hydrogen or the hydrogen storage device 45 is replaced. In other words, the occurrence of a situation in which the operation of the fuel cell device 40 stops completely because the next hydrogen storage device 45 cannot be replenished with hydrogen or the hydrogen storage device 45 cannot be replaced in time is reduced.

[0084] FIG. 7 is a flowchart showing yet another example of a process for switching from the first method to the second method. In step S31, the control device 10 receives weather forecast information via the receiver 60. The weather forecast information may be information provided by the weather information service 22 ( FIG. 2 ). In step S32, it is determined whether bad weather is predicted in the area where the power system 200 is located. If bad weather is predicted in the area where the power system 200 is located, in step S33, the control device 10 switches the method for planning the output of the fuel cell device 40 from the first method to the second method. Thus, in the example shown in FIG. 7 , if the weather forecast predicts bad weather in the area where the power system 200 is located, the method switches from the first method to the second method. If bad weather is predicted in the area where the power system 200 is located, it is predicted that the output of the solar power generation device 30 will decrease and the output of the fuel cell device 40 will increase. In this case, the rate at which the amount of hydrogen decreases will increase, and hydrogen replenishment may not be completed in time, resulting in a complete shutdown of the fuel cell device 40. When bad weather is predicted in the area where the power system 200 is located, such a situation can be avoided by switching to the second method. Examples of information indicating bad weather include typhoons and prolonged rain.

[0085] As long as the period when the output of the fuel cell device 40 is planned according to the second method overlaps with the period when bad weather is predicted in the area where the power system 200 is located, the timing of the switching by the process shown in Fig. 7 is not particularly limited. In other words, the timing of the switching by the process shown in Fig. 7 may be before the bad weather begins in the area where the power system 200 is located, or may be after the bad weather begins in the area where the power system 200 is located. Either timing is included in the present embodiment.

[0086] Note that steps S31 and S32 may be replaced with steps in which an administrator provides input to the control device 10 indicating that bad weather is predicted in the area where the power system 200 is located. In other words, the administrator may determine that bad weather is approaching in the area where the power system 200 is located, and instruct the control device 10 to switch.

[0087] FIG. 8 is a flowchart showing another example of the process for switching from the first method to the second method. In step S41, the control device 10 receives disaster information via the receiver 60. The disaster information may be information provided by the weather information service 22 ( FIG. 2 ) or information provided by a national or local government via a communication network such as the Internet. In step S42, the control device 10 determines whether the received disaster information will cause a delay in refilling the hydrogen storage device 45 that stores hydrogen to be supplied to the fuel cell device 40 with hydrogen or in replacing the hydrogen storage device 45. If the received disaster information will cause a delay in refilling the hydrogen storage device 45 that stores hydrogen to be supplied to the fuel cell device 40 with hydrogen or in replacing the hydrogen storage device 45 (Yes in step S42), in step S43, the control device 10 switches the method for planning the output of the fuel cell device 40 from the first method to the second method. 8 , if a disaster occurs that causes a delay in refilling the hydrogen storage device 45, which stores hydrogen supplied to the fuel cell device 40, with hydrogen or in replacing the hydrogen storage device 45, the system switches from the first method to the second method. A disaster could delay the delivery of hydrogen storage devices to the power system 200, potentially delaying the refilling of the hydrogen storage device 45 with hydrogen or the replacement of the hydrogen storage device 45. By managing the output of the fuel cell device 40 according to a schedule, hydrogen can be conserved, making it possible to continue operating the fuel cell device 40 in a planned manner for a predetermined period of time, specifically, until the next time the hydrogen storage device 45 is to be refilled with hydrogen or the hydrogen storage device 45 is to be replaced. In other words, the occurrence of a situation in which the operation of the fuel cell device 40 is completely stopped because the next hydrogen storage device 45 cannot be refilled with hydrogen or the hydrogen storage device 45 cannot be replaced in time is reduced. Examples of disaster information that may cause a delay in refilling hydrogen into the hydrogen storage device 45 that stores hydrogen to be supplied to the fuel cell device 40 or in replacing the hydrogen storage device 45 include information indicating that a disaster has occurred in an area or facility related to refilling hydrogen into the hydrogen storage device 45 that stores hydrogen to be supplied to the fuel cell device 40 or replacing the hydrogen storage device 45. Specifically, for example, this information is information indicating that a disaster has occurred in the area where the power system 200 is located.Another example is information indicating that a disaster has occurred at a facility that delivers hydrogen storage devices to the power system 200 or in an area where the facility is located. Examples of disasters include earthquakes and fires. A disaster that causes a delay in refilling hydrogen into the hydrogen storage device 45 that stores hydrogen to be supplied to the fuel cell device 40 or in replacing the hydrogen storage device 45 is an example of a situation that causes a delay in refilling hydrogen into the hydrogen storage device that stores hydrogen to be supplied to the fuel cell device of the present disclosure or in replacing the hydrogen storage device.

[0088] Steps S41 and S42 may be replaced by steps in which an administrator inputs to the control device 10 that a disaster has occurred that will cause a delay in refilling the hydrogen storage device 45 with hydrogen or replacing the hydrogen storage device 45. In other words, the administrator may determine that a disaster has occurred that will cause a delay in refilling the hydrogen storage device 45 with hydrogen or replacing the hydrogen storage device 45, and instruct the control device 10 to switch.

[0089] As described with reference to Figures 5 to 8, the trigger for switching may be a switch instruction input to the control device 10 by an administrator, or information such as the remaining amount of hydrogen, weather information, or disaster information input to the control device 10 from an external source. In the example shown in Figure 5, the switching is performed manually. In the examples shown in Figures 6 to 8, the switching is performed automatically.

[0090] The processes shown in Figures 5 to 8 are executed by the control device 10. The control device 10 is an example of a planning device that includes a storage device that stores a first method and a second method, and a controller that switches between the first method and the second method. Specifically, a program that executes the first method and the second method is stored in the memory of the control device 10. The power system 200 includes a fuel cell device 40 and the control device 10 as a planning device. With this configuration, it is possible to supply power to the load 300 while switching between operation using actual data and operation according to a schedule.

[0091] (Other Embodiments) (Additional Notes) The above description of the embodiments discloses the following techniques.

[0092] (Technology 1) A planning method for a power system equipped with a fuel cell device, comprising a step of switching between a first method for planning the output of the fuel cell device so as to compensate for the difference between the power demand of a power consumer and the output of a photovoltaic power generation device, and a second method for planning the output of the fuel cell device that is more limited than the output of the fuel cell device planned by the first method based on the amount of hydrogen available for use in a predetermined period. The technology disclosed herein can appropriately deal with a situation in which the amount of available hydrogen is restricted.

[0093] (Technology 2) The planning method according to Technology 1, in which when the amount of hydrogen remaining in a hydrogen storage tank that stores hydrogen to be supplied to the fuel cell device decreases, the method switches from the first method to the second method. By using the amount of hydrogen remaining as a trigger for switching, it becomes possible to continue operating the fuel cell device in a planned manner for a predetermined period of time.

[0094] (Technology 3) The planning method according to Technology 1, which switches from the first method to the second method when a weather forecast predicts bad weather in the area where the power system is located. When bad weather is predicted, it is predicted that the output of the solar power generation device will decrease and the output of the fuel cell device will increase. In this case, the rate at which the amount of hydrogen decreases will increase, and hydrogen replenishment may not be possible in time, causing the fuel cell device to stop operating completely. By switching to the second method when bad weather is predicted, it is possible to avoid such a situation.

[0095] (Technology 4) The planning method according to Technology 1 switches from the first method to the second method when an event occurs that causes a delay in refilling the hydrogen storage vessel that stores hydrogen to be supplied to the fuel cell device or in replacing the hydrogen storage vessel. A disaster may cause delays in the delivery and refilling of hydrogen. By managing the output of the fuel cell device according to a schedule, hydrogen can be saved, making it possible to continue operating the fuel cell device in a planned manner for a predetermined period of time.

[0096] (Technology 5) A planning device including: a memory that stores a first method for planning the output of a fuel cell device so as to compensate for the difference between the power demand of an electric power consumer and the output of a photovoltaic power generation device; and a second method for planning the output of the fuel cell device that is more limited than the output of the fuel cell device planned by the first method based on the amount of hydrogen available for use in a predetermined period; and a controller that switches between the first method and the second method. With this configuration, it becomes possible to supply power to a load while switching between operation using actual data and operation according to a schedule.

[0097] (Technology 6) A power system including a fuel cell device and the planning device according to Technology 5. With this configuration, it is possible to supply power to a load while switching between operation using actual data and operation according to a schedule.

[0098] The technology of the present disclosure is useful for power systems including photovoltaic power generation devices and fuel cell devices, and is particularly useful for power systems that are distributed power sources.

[0099] REFERENCE SIGNS LIST 10 Control device 12 Prediction unit 14 Planning unit 16 Control unit 20 Database 21 Terminal 22 Weather information service 30 Photovoltaic power generation device 31 Solar cell module 32 First PCS 33 First wattmeter 34 First control device 40 Fuel cell device 41 Fuel cell unit 42 Second PCS 43 Second wattmeter 44 Second control device 45 Hydrogen storage device 50 Power storage device 51 Storage battery 52 Third PCS 53 Third wattmeter 54 Third control device 60 Receiver 100 Commercial power supply 102 Power line 200 Power system 300 Load 302 Fourth wattmeter

Claims

1. A planning method in a power system equipped with a fuel cell device, comprising a step of switching between a first method of planning the output of the fuel cell device so as to compensate for the difference between the demand for power of a power consumer and the output of a solar power generation device, and a second method of planning an output of the fuel cell device that is more limited than the output of the fuel cell device planned by the first method based on the amount of hydrogen available in a specified period of time.

2. The planning method according to claim 1, wherein the method is switched from the first method to the second method when the amount of hydrogen remaining in a hydrogen storage vessel that stores hydrogen to be supplied to the fuel cell device decreases.

3. The planning method according to claim 1, further comprising switching from the first method to the second method when a weather forecast predicts bad weather in an area in which the power system is located.

4. The planning method of claim 1, which switches from the first method to the second method when an event occurs that causes a delay in refilling a hydrogen storage tank that stores hydrogen to be supplied to the fuel cell device or in replacing the hydrogen storage tank.

5. A planning device comprising: a memory that stores a first method for planning the output of a fuel cell device so as to compensate for the difference between the demand for power of an electric power consumer and the output of a solar power generation device; and a second method for planning the output of the fuel cell device that is more limited than the output of the fuel cell device planned by the first method based on the amount of hydrogen available in a specified period of time; and a controller that switches between the first method and the second method.

6. A power system comprising: a fuel cell device; and the planning device according to claim 5.

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