Store power management device
The store power management device improves solar power prediction accuracy by frequent measurement updates and controls, ensuring efficient use of solar power for load equipment through advanced forecasting and battery management.
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- FUJI ELECTRIC CO LTD
- Filing Date
- 2024-11-29
- Publication Date
- 2026-06-10
AI Technical Summary
Existing store power management devices predict solar power generation once a day, leading to low accuracy and inefficient utilization of solar power for load equipment due to errors between measured and predicted power generation values.
A store power management device that acquires solar power generation measurements multiple times a day, updates predictions at each interval, and controls load equipment based on these measurements to improve prediction accuracy, including short-term and long-term forecasting and battery management.
Enhances the accuracy of solar power generation predictions, enabling efficient utilization of solar power for load equipment by reducing errors and effectively managing power supply and demand.
Smart Images
Figure 2026094698000001_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to a store power management device, and particularly to a store power management device including a store control unit that predicts a predicted power generation amount of solar power generation by a solar power generation unit and controls connected load devices.
Background Art
[0002] Conventionally, a store power management device including a control unit that predicts a predicted power generation amount of solar power generation by a solar power generation unit and controls connected load devices is known (see, for example, Patent Document 1).
[0003] Patent Document 1 discloses a power management device (store power management device) including a control unit that predicts a predicted power generation amount of solar power generation by a solar power generation unit and controls connected load devices. This power management device predicts the power generation amount of solar power generation based on weather information and solar radiation amount transmitted from a public institution. Further, the power management device in Patent Document 1 corrects the predicted power generation amount using a correction coefficient in order to improve the accuracy of the predicted power generation amount. Specifically, the correction coefficient is a factor that affects power generation prediction other than the above weather information and solar radiation amount, such as deterioration of the solar power generation unit. Further, the power management device in Patent Document 1 collects the predicted power generation amount and the actual measured power generation amount for one month, and updates the correction coefficient based on the collected data.
Prior Art Documents
Patent Documents
[0004]
Patent Document 1
Summary of the Invention
Problems to be Solved by the Invention
[0005] The power management device described in Patent Document 1 above corrects the predicted power generation value using a correction coefficient to improve the accuracy of the predicted power generation value. However, in the power management device of Patent Document 1, the predicted power generation value is predicted only once per day, and even if an error occurs between the measured power generation value and the predicted power generation value within a day, the predicted power generation value cannot be corrected. As a result, the prediction accuracy of the predicted power generation value is low, and there is a problem that solar power generation electricity cannot be efficiently utilized for load equipment. Therefore, there is a need for a store power management device that can improve the prediction accuracy of solar power generation value and efficiently utilize solar power generation electricity for load equipment in the store based on the predicted power generation value.
[0006] This invention was made to solve the above-mentioned problems, and one of its objectives is to provide a store power management device that can improve the accuracy of predicting the amount of solar power generated and efficiently utilize solar power for load equipment within the store based on the predicted amount of solar power generated. [Means for solving the problem]
[0007] To achieve the above objective, a store power management device according to one aspect of this invention includes a store control unit that is installed in a store and acquires measured values of solar power generation from a solar power generation unit installed in or around the store (hereinafter referred to as "installed in the store"), predicts future power generation based on the acquired measured values, and controls load equipment installed in the store based on the power generation prediction values. The store control unit acquires the measured values multiple times at predetermined intervals within a day, and updates and predicts the power generation prediction values at each predetermined interval in which the measured values are acquired.
[0008] In a store power management device according to one aspect of this invention, as described above, the store control unit acquires actual measured values of solar power generation from a solar power generation unit installed in the store, predicts future power generation based on the acquired measured values, and controls load equipment installed in the store based on the predicted power generation. The store control unit acquires the measured values multiple times at predetermined intervals within a day, and updates and predicts the predicted power generation value at each predetermined interval during which the measured values are acquired. As a result, future power generation predictions can be made based on actual measured values of solar power generation acquired multiple times at predetermined intervals within a day, so that errors between the actual power generation value and the predicted power generation value are less likely to occur compared to the case where the predicted power generation value is only predicted once a day, and the prediction accuracy of the predicted power generation value can be improved. As a result, the prediction accuracy of the predicted power generation value of solar power generation can be improved, and solar power can be efficiently used for load equipment in the store based on the predicted power generation value.
[0009] In the store power management device according to the first aspect described above, preferably, the store control unit is configured to calculate the change in measured values over time and to predict the power generation amount based on the measured values and the change in values. With this configuration, it is possible to predict the future trend of solar power generation based on the change in measured values (the slope of solar power generation over time), so the accuracy of predicting the solar power generation amount can be improved compared to when prediction is based only on measured values.
[0010] In this case, preferably, the store control unit is configured to predict the power generation amount assuming that the calculated change amount continues. With this configuration, the change amount (slope) of the measured value can be used directly as the future power generation amount prediction, making it easy to predict the power generation amount.
[0011] In the store power management device according to the first aspect described above, preferably, the store control unit is configured to calculate the amount of change based on the previous measured value and the current measured value, and to update and predict the power generation amount. With this configuration, the power generation amount prediction can be updated each time at a predetermined period in which measured values are acquired, so that errors occurring between the measured power generation amount and the power generation amount prediction can be effectively suppressed. As a result, the power generation amount prediction can be predicted with greater accuracy so as to track the measured power generation amount.
[0012] In the store power management device according to the first aspect described above, preferably, the store control unit is configured to predict a short-term power generation forecast value, which is a short-term power generation forecast value, based on the measured values and changes acquired at a predetermined period. With this configuration, short-term power generation forecast values based on changes in measured values acquired at a predetermined period can be used to accurately predict short-term changes in solar power generation (for example, changes up to a few minutes to about 30 minutes ahead), so that a short-term operation plan for the store's load equipment can be created.
[0013] In the store power management device according to the first aspect described above, preferably, the store control unit is configured to predict medium- to long-term power generation forecast values, which are predicted power generation values for at least one day, based on past measured values of solar power generation from the solar power generation unit. With this configuration, it is possible to predict medium- to long-term changes in solar power generation (for example, changes between a selected time and sunset) and short-term power generation forecast values based on the medium- to long-term power generation forecast values based on past measured values, so that a rough daily operation plan for the store's load equipment can be created.
[0014] In this case, preferably, the store control unit is configured to compare the acquired measured value with multiple past measured values, select a past measured value that matches or approximates the measured value at a time corresponding to the measurement time of the measured value, and predict the medium- to long-term power generation forecast value. With this configuration, the prediction accuracy of the medium- to long-term power generation forecast value can be improved by selecting a past measured value from among multiple past measured values that matches or approximates the measured value at a time corresponding to the measurement time of the measured value. Furthermore, if the selected past measured value deviates from the medium- to long-term power generation forecast value, the medium- to long-term power generation forecast value can be corrected by selecting another past measured value from among multiple past measured values.
[0015] In this case, preferably, the store control unit is configured to predict medium- to long-term power generation forecasts by selecting past measured values that match or approximate the measured values and change amounts, respectively, at a time corresponding to the measurement time of the measured values, based on the acquired measured values and the change amounts of the measured values. With this configuration, from among multiple past measured values, past measured values can be selected not only based on the acquired measured values but also on the change amounts of the measured values at a time corresponding to the measurement time of the measured values. For example, when selecting past measured values based only on the acquired measured values, even if the measured values at the corresponding time match or approximate, if the change amounts of the measured values at the corresponding time are different, it may not be possible to accurately predict future power generation forecasts. Therefore, by using both the acquired measured values and the change amounts of the measured values at the corresponding time to predict medium- to long-term power generation forecasts, the prediction accuracy can be further improved.
[0016] In the store power management device according to the first aspect described above, preferably, the store control unit controls the storage and discharge of electricity generated by the solar power generation unit to the battery based on at least one of the predicted power consumption and actual power consumption of the load equipment and the predicted power generation amount. With this configuration, the balance between the power demand based on the predicted power consumption or actual power consumption of the load equipment and the power supply based on the predicted power generation amount of the solar power generation unit can be controlled with high precision by using the battery. As a result, future power supply shortages or surpluses can be effectively suppressed.
[0017] In this case, preferably, the store control unit predicts the timing at which surplus power will be generated by the solar power generation unit relative to the power consumption of the load equipment, based on at least one of the predicted power consumption and actual power consumption of the load equipment and the predicted power generation amount. At the timing at which surplus power is generated, the store control unit controls the storage and discharge of power generated by the solar power generation unit to the storage battery so that the power generated by the solar power generation unit can be stored in the storage battery. With this configuration, when it is predicted that the power consumption of the load equipment will be less than the amount of solar power generated and surplus power will be generated, the storage battery can be discharged or storage suppressed in advance to make it ready for storage. As a result, surplus power can be stored in the storage battery at the timing at which surplus power is predicted to be generated, so that the surplus power can be used effectively without waste.
[0018] In the store power management device according to the first aspect described above, preferably, the store control unit predicts the timing at which a power shortage will occur in the power generated by the solar power generation unit relative to the power consumption of the load equipment, based on at least one of the predicted power consumption value and the measured power consumption value of the load equipment and the predicted power generation value. At the timing at which a power shortage occurs, the store control unit controls the storage and discharge of power generated by the solar power generation unit to the storage battery so that the power stored in the storage battery can be discharged. With this configuration, when it is predicted that the power consumption of the load equipment will exceed the amount of solar power generation and a power shortage will occur, the amount of power stored in the storage battery can be increased in advance by storing power in the storage battery or suppressing discharge. As a result, at the timing at which a power shortage is predicted to occur, the power stored in the storage battery can be discharged and used, thereby preventing excessive procurement of power from the grid (power company). [Effects of the Invention]
[0019] According to the present invention, as described above, it is possible to provide a store power management device that can improve the accuracy of predicting the amount of solar power generated and efficiently utilize solar power for load equipment within the store based on the predicted amount of solar power generated. [Brief explanation of the drawing]
[0020] [Figure 1] This is a block diagram showing the overall configuration of a store, including the store management device, according to the first embodiment of the present invention. [Figure 2] This is a schematic diagram illustrating the control of a store management device in the first embodiment of the present invention. [Figure 3] This figure illustrates the prediction of power generation amount using slope calculation in the first embodiment of the present invention. [Figure 4] This figure illustrates the operational control for storing and discharging solar power in a battery based on the predicted power consumption, measured power consumption, and predicted power generation value in the first embodiment of the present invention. [Figure 5]This is a flowchart for explaining the power generation amount prediction process in the first embodiment of the present invention. [Figure 6] This is a flowchart for explaining the correction process of the predicted power generation amount by slope calculation in the first embodiment of the present invention. [Figure 7] This is a block diagram showing the configuration of an entire store including a store management device in the second embodiment of the present invention. [Figure 8] This is a diagram for explaining the prediction of the predicted power generation amount by selecting past measured values in the second embodiment of the present invention. [Figure 9] This is a flowchart for explaining the correction process of the predicted power generation amount by selecting past measured values in the second embodiment of the present invention. [Figure 10] This is a diagram for explaining the prediction of the predicted power generation amount by slope calculation and selection of past measured values in a modified example of the present invention. <As shown in Figure 1, the store power management device 10 is located inside the store 100 and includes a store control unit 12. In a store power management device 10, for example, in a convenience store or supermarket, the control unit 12 controls the device so that it can be driven when power is supplied from the grid power 200 to multiple load devices 11, and controls these devices to enable efficient operation. The store power management device 10 controls the device so that it can be driven when power is supplied from the grid power 200, power generated by a solar power generation system 20 installed on the roof of the store 100, and power discharged from a storage battery 30, and controls these devices to enable efficient operation. In addition, a cloud server 300 located outside the store 100 acquires publicly available weather information and predicts power generation amount and power consumption of load devices 11 based on past performance data stored in the cloud server 300, and transmits these predictions to the store power management device 10.
[0026] The solar power generation system 20 is configured to generate electricity and supply power using solar energy. The solar power generation system 20 comprises a solar power generation unit 21 and a solar power generation control unit 22. The solar power generation unit 21 includes a solar power generation panel 21a that converts solar energy into electricity, and a group of sensors 21b for measuring the temperature of the solar power generation panel 21a, as well as the temperature, humidity, and CO2 concentration of the outside air. Examples of sensors used in the group of sensors 21b include a thermometer, a pyranometer, a thermometer / hygrometer, a current transformer such as a CT, and a CO2 concentration meter.
[0027] The multiple load devices 11 are powered by grid power 200, power generated by the solar power generation system 20, and power discharged from the storage battery 30. The multiple load devices 11 include a showcase 11a, an air conditioner 11b, an electric heating device 11c, and lighting 11d.
[0028] Showcase 11a includes a refrigeration cycle. The refrigeration cycle includes a compressor, a condenser, an expansion section, and an evaporator.
[0029] The compressor is configured to compress the refrigerant and change it to a high pressure. The condenser is configured to cool and liquefy the refrigerant compressed in the compressor. The expansion unit expands the refrigerant supplied from the condenser, changing it into a low-pressure, low-temperature refrigerant. The evaporator is configured to cool the inside of the display case. The evaporator also performs heat exchange between the refrigerant supplied from the expansion unit and the object to be cooled, and cools the object to be cooled through the air cooled by the evaporation of the refrigerant. The object to be cooled is, for example, articles arranged inside the display case, and the object to be cooled is cooled through the air cooled by the evaporator.
[0030] The air conditioner 11b includes a refrigeration cycle similar to that of the showcase 11a. The configuration of the refrigeration cycle is the same as that of the showcase 11a, so a detailed explanation is omitted. The air conditioner 11b has multiple operating modes, including cooling and heating. In cooling mode, the air in the store is cooled by heat exchange with the refrigerant in the evaporator (heat is transferred to the refrigerant). In heating mode, the air in the store is heated by heat exchange with the refrigerant in the condenser (heat is received from the refrigerant).
[0031] The electric heating device 11c includes a heated display case (warmer) and a fryer. The heated display case is configured to heat and keep warm items. The heated display case includes, for example, a heater. The fryer is used for deep-frying. The fryer includes a heater.
[0032] The store control unit 12 includes a processing unit, a storage unit, and a communication unit. The processing unit has a CPU (Central Processing Unit) and memory such as ROM (Read Only Memory) and RAM (Random Access Memory), and is configured to perform control processing. The storage unit includes ROM and RAM, etc. The store control unit 12 is connected to a cloud server 300, and the control performed by the store control unit 12 is processed by either the processing unit or the cloud server 300. The cloud server 300 predicts the amount of solar power generation for one day based on publicly available weather information. The cloud server 300 also predicts the amount of power consumed by multiple load devices for one day.
[0033] The store control unit 12 is configured to control the rotation speed of the compressor to cool the items in the showcase 11a to a set temperature and maintain the cooled state. The store control unit 12 is configured to control the rotation speed of the compressor to cool or heat the inside of the store to a set temperature and maintain the set temperature. The store control unit 12 is configured to control the amount of power supplied to the heater in order to heat the electric heating device 11c to a set temperature. The store control unit 12 is configured to control the on state and the off state of the lighting 11d.
[0034] The store control unit 12 is configured to obtain a daily power generation forecast and a forecast of the power consumption of multiple load devices from the cloud server 300, and to perform operational control of the multiple load devices based on these. For example, if the power generation forecast exceeds the power consumption forecast at a certain time, and it is determined that the power consumption of multiple load devices can be covered by solar power alone, the store control unit will operate the multiple load devices using solar power without using grid power.
[0035] In this embodiment, the store control unit 12 acquires measured values of the amount of solar power generated by the solar power generation unit 21 installed in the store 100 from the solar power generation control unit 22, and predicts future power generation based on the acquired measured values. The store control unit 12 also controls the load equipment 11 installed in the store 100 based on the predicted power generation. Furthermore, the store control unit 12 acquires measured values of the amount of power generated by the solar power generation unit 21 from the solar power generation control unit 22 multiple times at predetermined intervals within a day, and performs control to update and predict (correct) the predicted power generation value at predetermined intervals in which measured values are acquired.
[0036] Specifically, the store control unit 12 acquires measured values of the amount of power generated by the solar power generation unit 21 from the solar power generation control unit 22 at predetermined intervals (for example, every minute) within a day, calculates a predicted value of the amount of power generated every minute, and uses this as a new predicted value of the amount of power generated. The measured values of the amount of power generated are acquired by the solar power generation control unit 22, which monitors environmental conditions and the state of the solar power generation panels 21a using a group of sensors 21b provided in the solar power generation system 20, and grasps the amount of power generated in the solar power generation unit 21, and is transmitted to the store control unit 12.
[0037] As shown in Figure 2, the store control unit 12 is configured to communicate with the cloud server 300. The cloud server 300 predicts power generation forecast values from publicly available weather information and predicts power consumption forecast values for the load equipment 11 from past performance data stored in the cloud server 300. The store control unit 12 obtains the power generation forecast values and power consumption forecast values from the cloud server 300, plans the operation schedule for the load equipment 11, and controls it. The store control unit 12 obtains actual power generation values at predetermined intervals, performs correction processing on the power generation forecast values, and modifies the operation schedule accordingly. The store control unit 12 also transmits the actual power generation values obtained within a one-day period to the cloud server 300. The cloud server 300 receives the actual power generation values and saves them as past measured values.
[0038] Furthermore, the store control unit 12 calculates the rate of change (slope) of the measured value with respect to time and performs control to predict the power generation amount based on the measured value and the rate of change. For example, the store control unit 12 acquires measured values every minute, calculates the rate of change (slope) of the measured value with respect to time (1 minute) every minute, and predicts the power generation amount by predicting the trend of subsequent solar power generation. This makes it possible to predict a power generation amount that is closer to the most recent measured value, which takes into account the influence of external environmental factors such as weather. Each time the store control unit 12 predicts the power generation amount, it reflects the prediction result in the operation plan of multiple load devices 11 and performs operation control that enables efficient use of solar power generation.
[0039] Furthermore, the store control unit 12 performs control to predict the power generation amount assuming that the calculated slope continues. Specifically, as shown in Figure 3, if a measured value is obtained at the time of 1 minute, after calculating the slope, it predicts the power generation amount up to 30 minutes later, assuming that the same slope continues from 1 minute later to n minutes later (for example, 30 minutes later). The store control unit 12 performs the same control every minute, predicting the power generation amount up to 30 minutes later each time and updating the predicted value.
[0040] Furthermore, the store control unit 12 calculates the slope based on the previous measured value and the current measured value, and performs control to predict the power generation amount. For example, as shown in Figure 3, if a measured value is obtained at 2 minutes past the hour, and the previous measured value was obtained at 1 minute past the hour, a straight line is drawn passing through both the measured value at 1 minute past the hour and the measured value at 2 minutes past the hour, the slope of that line is calculated, and the power generation amount is predicted from 2 minutes past the hour to 30 minutes later. Subsequently, if a measured value is obtained at 3 minutes past the hour, a straight line is drawn passing through both the measured value at 2 minutes past the hour and the measured value at 3 minutes past the hour, the slope of that line is calculated, and the power generation amount is predicted from 3 minutes past the hour to 30 minutes later. As a result, the slope of the measured value at 2 minutes past the hour changes at 3 minutes past the hour, and the power generation amount is updated. The store control unit 12 performs the same control every minute, predicting the power generation amount up to 30 minutes later each time, and updating the predicted value.
[0041] Furthermore, the store control unit 12 is configured to predict short-term power generation forecasts, which are short-term power generation forecasts, based on measured values and changes acquired at predetermined intervals. Specifically, it can predict short-term changes in solar power generation (for example, changes up to a few minutes to about 30 minutes ahead) based on changes in measured values acquired at predetermined intervals, and create a short-term operation plan for the store's load equipment.
[0042] Furthermore, the store control unit 12 controls the storage and discharge of electricity generated by the solar power generation unit 21 to the battery 30 based on at least one of the predicted power consumption values and actual power consumption values of multiple load devices 11 obtained from the cloud server 300, and the predicted power generation value. Specifically, based on the predicted power consumption values and actual power consumption values of the load devices 11, if it is determined that solar power can be stored, the solar power is stored in the battery 30. If solar power alone is insufficient to cover the power consumption, the store control unit 12 discharges the electricity stored in the battery 30 to supply power to the load devices 11. For example, as shown in Figure 4, if the predicted power generation value A is determined to exceed the predicted power consumption value between time 4 and time 5, the store control unit 12 creates an operation plan to store solar power in the battery 30. Specifically, in order to secure the capacity of the battery 30, the electricity stored in the battery 30 by time 4 is discharged to the load devices 11. Furthermore, if the predicted power generation value A determines that the power generation will fall below the predicted power consumption value after time 5, the store control unit 12 creates an operation plan to discharge the power stored in the battery 30. With this configuration, it is possible to discharge the power stored in the battery 30 during peak power consumption and suppress power consumption. As a result, surplus solar power can be used efficiently without being wasted, thus contributing to energy conservation.
[0043] Furthermore, the store control unit 12 controls the discharge of grid power stored in the battery 30 at night when the predicted value of solar power generation during the day falls below the predicted value of power consumption (i.e., there is a power shortage), thereby supplying power to the load equipment 11.
[0044] Furthermore, the store control unit 12 predicts the timing at which surplus power will be generated relative to the power consumption of the load equipment 11, based on at least one of the predicted power consumption and the measured power consumption of the load equipment 11, and the predicted power generation amount. Specifically, it compares the predicted power consumption obtained from the cloud server 300 and the measured power consumption measured from the load equipment 11 with the predicted power generation amount to predict the timing at which the amount of power generated will exceed the power consumption. At the timing at which surplus power is generated, the store control unit 12 controls the storage and discharge of power generated by the solar power generation unit 21 to the storage battery 30 so that the power generated by the solar power generation unit 21 can be stored in the storage battery 30.
[0045] Furthermore, the store control unit 12 predicts the timing at which a power shortage will occur in the power generated by the solar power generation unit relative to the power consumption of the load equipment 11, based on at least one of the predicted power consumption and the measured power consumption of the load equipment 11, and the predicted power generation amount. Specifically, it compares the predicted power consumption obtained from the cloud server 300 and the measured power consumption measured from the load equipment 11 with the predicted power generation amount and predicts the timing at which the amount of power generated will fall below the power consumption. At the timing when power is generated, the store control unit 12 controls the storage and discharge of power generated by the solar power generation unit 21 to the storage battery 30 so that the power stored in the storage battery 30 can be discharged.
[0046] Furthermore, if an event is scheduled to be held nearby, the store control unit 12 sets event information (for example, estimated power consumption by time of day), predicts power consumption values tailored to the event, and controls the storage and discharge of power generated by the solar power generation unit 21 to the storage battery 30 based on the predicted power generation values.
[0047] (Power generation forecasting process) Referring to Figure 5, the control process of the store control unit when performing power generation prediction processing according to the first embodiment will be described.
[0048] In step S1, the store control unit 12 determines whether or not it is the update time for the publicly available weather information. If it is the update time for the weather information (step S1, Yes), the store control unit 12 proceeds to step S2. If it is not the update time (step S1, No), the process in step S1 is repeated until it is the update time.
[0049] In step S2, the store control unit 12 obtains weather information from the cloud server 300 and proceeds to step S3.
[0050] In step S3, the store control unit 12 determines whether or not it is the predicted power generation time. If it is the predicted power generation time (step S3, Yes), proceed to step S4. If it is not the predicted power generation time (step S3, No), terminate the process.
[0051] In step S4, the store control unit 12 performs power generation forecasting processing on the cloud server 300 and predicts the amount of power generated. Specifically, the cloud server 300 uses past power generation amounts by time of day, weather conditions (temperature, humidity, solar radiation, etc.), and similar past measured values such as the weather conditions for the day to be predicted as the predicted power generation value. In step S5, the store control unit 12 obtains the predicted power generation value from the cloud server 300. In step S6, the store control unit 12 creates an operation control plan for the load equipment 11 based on the predicted power generation value. Then, the process proceeds to step S7. In step S7, the store control unit 12 obtains the measured power generation value. Then, the process proceeds to step S8.
[0052] In step S8, the store control unit 12 determines whether the acquired measured power generation value and the predicted power generation value are approximate or match. If the acquired measured power generation value and the predicted power generation value are approximate or match (step S8, Yes), the process proceeds to step S10. If the acquired measured power generation value and the predicted power generation value do not match (step S8, No), the process proceeds to step S9. Approximation means that the error between the measured power generation value and the predicted power generation value is within a predetermined controllable range.
[0053] In step S9, the store control unit 12 performs correction processing on the predicted power generation value. The correction processing on the predicted power generation value will be explained in detail with reference to Figure 6.
[0054] In step S10, the store control unit 12 executes the operation control plan for the load equipment 11 that was planned in step S11, and then terminates the process.
[0055] (Correction process for predicted power generation values (slope calculation)) Referring to Figure 6, the correction process for the predicted power generation amount based on the slope calculation in step S9 of Figure 5 according to the first embodiment will be explained.
[0056] In step S11, the store control unit 12 determines whether one minute has passed since the acquisition of the previous measured value. If one minute has passed since the acquisition of the previous measured value (step S11, Yes), the process proceeds to step S12. If one minute has not passed since the acquisition of the previous measured value (step S11, No), the process in step S11 is repeated until one minute has passed.
[0057] In step S12, the store control unit 12 sets the prediction calculation time (number of times) to M=0. In step S13, the store control unit 12 obtains the latest measured power generation value. In step S14, it subtracts the previous measured value from the latest measured value to calculate the change amount (slope) with respect to time. In step S15, it sets time = current time (minutes). In step S16, it sets t=t+1 (minutes) and M=M+1.
[0058] In step S17, the store control unit 12 determines whether the slope calculated in step S14 matches the slope calculated previously. If they do not match (step S17, Yes), proceed to step S18. If they match (step S17, No), proceed to step S19.
[0059] In step S18, the store control unit 12 calculates the predicted power generation amount for t minutes using the latest measured value + the latest slope × M.
[0060] In step S19, the store control unit 12 determines whether or not there are unpredicted periods. If there are unpredicted periods (the slope calculated this time matches the slope calculated last time), a new prediction is required (step S19, Yes), and the process proceeds to step S20. If there are no unpredicted periods (data calculated in the past already exists) (step S19, No), the process returns to step S16.
[0061] In step S20, the store control unit 12 calculates the predicted power generation amount for minute t using the latest measured value + the previous slope × M. In other words, it performs an extension process on the predicted power generation amount, assuming that the slope after t minutes will be the same as the previous slope.
[0062] In step S21, the store control unit 12 determines whether the prediction calculation time (number of calculations) is M=30. If the prediction calculation time (number of calculations) is M=30, that is, if the prediction of power generation up to 30 minutes in advance has been completed (step S21, Yes), the process ends. If the prediction calculation time (number of calculations) is not M=30 (step S21, No), the process returns to step S16.
[0063] (Effects of the first embodiment) In the first embodiment, the following effects can be obtained.
[0064] In the first embodiment, as described above, the store control unit 12 is installed in the store 100 and acquires measured values of the amount of solar power generated by the solar power generation unit 21 via the solar power generation control unit 22. Based on the acquired measured values, it predicts future power generation amounts and controls the load equipment 11 installed in the store 100 based on the predicted power generation amounts. The store control unit 12 also acquires the measured values multiple times at predetermined intervals within a day and updates and predicts the predicted power generation amount at each predetermined interval during which the measured values are acquired. As a result, future power generation amounts can be predicted based on measured values of solar power generation acquired multiple times at predetermined intervals within a day. This reduces the likelihood of errors between the measured power generation amount and the predicted power generation amount compared to the case where the predicted power generation amount is predicted only once a day, thereby improving the prediction accuracy of the predicted power generation amount. As a result, the prediction accuracy of the predicted power generation amount for solar power generation is improved, and the use of solar power for the load equipment 11 in the store 100 can be efficiently carried out based on the predicted power generation amount.
[0065] Furthermore, in the first embodiment, as described above, the store control unit 12 is configured to calculate the amount of change in the measured value with respect to time and to predict the amount of power generation based on the measured value and the amount of change. This makes it possible to predict the future trend of solar power generation based on the amount of change in the measured value (the slope of solar power generation with respect to time), thus improving the accuracy of the predicted amount of solar power generation compared to when predictions are made based only on measured values.
[0066] Furthermore, in the first embodiment, as described above, the store control unit 12 is configured to predict the power generation amount based on the assumption that the calculated change amount will continue. This makes it possible to use the change amount (slope) of the measured value directly as the future power generation amount prediction, thus making it easy to predict the power generation amount.
[0067] Furthermore, in the first embodiment, as described above, the store control unit 12 is configured to calculate the amount of change based on the previous measured value and the current measured value, and to update and predict the power generation amount. As a result, the power generation amount prediction can be updated each time at a predetermined period in which measured values are acquired, so that errors occurring between the measured power generation amount and the power generation amount prediction can be effectively suppressed. As a result, the power generation amount prediction can be predicted with greater accuracy so as to track the measured power generation amount.
[0068] Furthermore, in the first embodiment, as described above, the store control unit 12 is configured to predict a short-term power generation forecast value, which is a short-term power generation forecast value, based on the measured values and changes acquired at predetermined intervals. As a result, short-term changes in solar power generation (for example, changes up to a few minutes to about 30 minutes ahead) can be accurately predicted using the short-term power generation forecast value based on the changes in measured values acquired at predetermined intervals, making it possible to create a short-term operation plan for the store's load equipment.
[0069] Furthermore, in the first embodiment, as described above, the store control unit 12 controls the storage and discharge of electricity generated by the solar power generation unit 21 to the battery 30 via the solar power generation control unit 22, based on at least one of the predicted power consumption value and the actual power consumption value of the load equipment 11, and the predicted power generation amount. This allows for accurate control of the balance between the power demand based on the predicted power consumption value or actual power consumption value of the load equipment 11 and the power supply based on the predicted power generation amount of the solar power generation, by using the battery 30. As a result, it is possible to effectively suppress future power supply shortages or power supply surpluses.
[0070] Furthermore, in the first embodiment, as described above, the store control unit 12 predicts the timing at which surplus power will be generated by the solar power generation unit 21 relative to the power consumption of the load equipment 11, based on at least one of the predicted power consumption value and the actual power consumption value of the load equipment 11, and the predicted power generation value. At the timing at which surplus power is generated, the store control unit 12 controls the storage and discharge of power generated by the solar power generation unit 21 to the storage battery 30 via the solar power generation control unit 22 so that the power generated by the solar power generation unit 21 can be stored in the storage battery 30. As a result, when it is predicted that the power consumption of the load equipment 11 will be less than the amount of solar power generated and surplus power will be generated, the storage battery 30 can be discharged or storage suppressed to prepare the storage battery 30 for storage in advance. As a result, when it is predicted that surplus power will be generated, the surplus power can be stored in the storage battery 30, so that the surplus power can be used effectively without waste.
[0071] Furthermore, in the first embodiment, as described above, the store control unit 12 predicts the timing at which a power shortage will occur in the power generated by the solar power generation unit 21 relative to the power consumption of the load equipment 11, based on at least one of the predicted power consumption value and the actual power consumption value of the load equipment 11, and the predicted power generation value. At the timing at which a power shortage occurs, the store control unit 12 controls the storage and discharge of power generated by the solar power generation unit 21 to the storage battery 30 via the solar power generation control unit 22 so that the power stored in the storage battery 30 can be discharged. This makes it possible to increase the amount of power stored in the storage battery 30 in advance by storing power in the storage battery 30 or suppressing discharge when it is predicted that the power consumption of the load equipment 11 will exceed the amount of solar power generation and a power shortage will occur. As a result, when it is predicted that a power shortage will occur, the power stored in the storage battery 30 can be discharged and used, so it is possible to suppress the procurement of excessive power from the grid (power company).
[0072] [Second Embodiment] Next, with reference to Figures 7-9, the configuration of the store power management device 10 according to the second embodiment of the present invention will be described.
[0073] In the second embodiment, the store control unit 12a is configured to select a plurality of past measured values that approximate or match the acquired measured values in the power generation forecast value correction process, and to make predictions of short-term and medium- to long-term power generation values for one day (for example, power generation forecast up to 30 minutes ahead and power generation forecast for several hours until sunset).
[0074] As shown in Figure 7, the store power management device 10 according to the second embodiment is located inside the store 100 and includes a store control unit 12a. In a store power management device 10, for example, in a convenience store or supermarket, the control unit 12a controls the supply of power from the grid power 200 to multiple load devices 11, enabling them to be driven and allowing them to operate efficiently. The store power management device 10 controls the supply of power from the grid power 200, power generated by a solar power generation system 20 installed on the roof of the store 100, and power discharged from a storage battery 30, enabling multiple load devices 11 to be driven and allowing them to operate efficiently. In addition, a cloud server 300 located outside the store 100 acquires publicly available weather information and predicts power generation and power consumption of load devices 11 based on past performance data stored in the cloud server 300, and transmits these predictions to the store power management device 10.
[0075] The store control unit 12a includes a processing unit, a storage unit, and a communication unit. The processing unit has a CPU (Central Processing Unit) and memory such as ROM (Read Only Memory) and RAM (Random Access Memory), and is configured to perform control processing. The storage unit includes ROM and RAM, and stores past power consumption and past measured values of solar power generation. The store control unit 12a is connected to the cloud server 300, and the control performed by the store control unit 12a is processed by either the processing unit or the cloud server 300. The cloud server 300 predicts the daily solar power generation amount based on publicly available weather information. The cloud server 300 also predicts the daily power consumption of multiple load devices.
[0076] The store control unit 12a is configured to predict the medium- to long-term power generation amount for a day by comparing the acquired measured value with multiple past measured values and slopes, and selecting past measured values that match or approximate the measured value at a time corresponding to the measurement time of the measured value. For example, as shown in Figure 8, if a measured value is acquired at time 1 minute, past measured value A is selected from past measured values A, B, and C, which have a measured value and slope that approximates or matches the measured value at the same time, and the power generation amount prediction value from the time of selection onward is assumed to have a similar trend to past measured value A, thereby predicting the power generation amount for up to one day (medium- to long-term power generation amount prediction). Also, if a measured value is acquired at time 10 minutes, the store control unit 12a selects past measured value B from past measured values A, B, and C, which have a measured value and slope that approximates or matches the measured value at the same time, and predicts the medium- to long-term power generation amount. The store control unit 12a performs the same control at predetermined intervals (for example, every minute), predicting the medium- to long-term power generation forecast value each time and updating the forecast value. Approximation means that the measured value and slope are within a predetermined range.
[0077] Furthermore, the store control unit 12a is configured to predict medium- to long-term power generation forecasts, which are predicted power generation values for at least one day, based on past measured values of solar power generation by the solar power generation unit 21. Specifically, it predicts medium- to long-term changes in solar power generation (for example, changes between a selected time and sunset) and short-term power generation forecasts based on past measured values, and creates a rough daily operating plan for the store's load equipment.
[0078] (Correction process for predicted power generation values (selection of past measured values)) Referring to Figure 9, the correction process for power generation prediction values based on past measured values according to the second embodiment will be explained.
[0079] In step S31, the store control unit 12a determines whether one minute has passed since the acquisition of the previous measured value. If one minute has passed since the acquisition of the previous measured value (step S31, Yes), the process proceeds to step S32. If one minute has not passed since the acquisition of the previous measured value (step S31, No), the process in step S31 is repeated until one minute has passed.
[0080] In step S32, the store control unit 12a sets the number of past measured values N to N=0. In step S33, the store control unit 12a acquires the latest measured power generation value, and then in step S34, acquires a past measured value for the same time as the acquired power generation value. In step S35, the store control unit 12a sets the number of past measured values N to N=N+1.
[0081] In step S36, the store control unit 12a subtracts past measured values from the latest measured values to calculate the difference dN between the latest measured values and past measured values. In step S37, the store control unit 12a subtracts the previous measured value from the latest measured value to calculate the latest change (slope) of the measured value with respect to time. In step S38, the store control unit 12a subtracts the previous measured value at the same time in the past from the past measured value at the same time in the past to calculate the change (slope) of the past measured value with respect to time. Then, in step S39, the store control unit 12a subtracts the past slope from the latest slope to calculate the difference DN between the latest slope and the past slope.
[0082] In step S40, the store control unit 12a determines whether the number of past measured values N is 5. If the number of past measured values is 5, that is, if 5 past measured values have been acquired (step S40, Yes), the process proceeds to step S41. If N is not 5 (step S40, Yes), the process returns to step S35.
[0083] In step S41, the store control unit 12a selects a store where the difference dN between the latest measured value and a past measured value is within a predetermined range. The predetermined range is set so that the past measured value approximates or matches the latest measured value. Furthermore, in step S42, the store control unit selects a past measured value where the difference DN between the latest slope and the past slope is the minimum value, and terminates the process.
[0084] The other configurations of the second embodiment are the same as those of the first embodiment described above.
[0085] (Effects of the second embodiment) In the second embodiment, as described above, the store control unit 12a is configured to predict medium- to long-term power generation forecast values, which are predicted power generation values for at least one day, based on past measured values of solar power generation by the solar power generation unit 21. With this configuration, it is possible to predict medium- to long-term changes in solar power generation (for example, changes between a selected time and sunset) and short-term power generation forecast values based on the medium- to long-term power generation forecast values based on past measured values, so that a rough daily operation plan for the store's load equipment can be created.
[0086] Furthermore, in the second embodiment, as described above, the store control unit 12a is configured to compare the acquired measured value with a plurality of past measured values, select a past measured value that matches or approximates the measured value at a time corresponding to the measurement time of the measured value, and predict the medium- to long-term power generation forecast value. This improves the prediction accuracy of the medium- to long-term power generation forecast value by selecting a past measured value from among a plurality of past measured values that matches or approximates the measured value at a time corresponding to the measurement time of the measured value. In addition, if the selected past measured value deviates from the medium- to long-term power generation forecast value, the medium- to long-term power generation forecast value can be corrected by selecting another past measured value from among the plurality of past measured values.
[0087] Furthermore, in the second embodiment, as described above, the store control unit 12a is configured to predict medium- to long-term power generation forecast values by selecting past measured values that match or approximate the measured values and change amounts, respectively, at a time corresponding to the measurement time of the measured values, based on the acquired measured values and the change amounts of the measured values. This makes it possible to select past measured values from among multiple past measured values, not only based on the acquired measured values but also on the change amounts of the measured values, at a time corresponding to the measurement time of the measured values. For example, when selecting past measured values based only on the acquired measured values, even if the measured values at the corresponding time match or approximate, if the change amounts of the measured values at the corresponding time are different, it may not be possible to predict future power generation forecast values with accuracy. Therefore, by using both the acquired measured values and the change amounts of the measured values at the corresponding time to predict medium- to long-term power generation forecast values, the prediction accuracy can be further improved.
[0088] Furthermore, the other effects of the second embodiment are the same as those of the first embodiment.
[0089] [Differentiation] It should be noted that the embodiments disclosed herein are illustrative and not restrictive in all respects. The scope of the present invention is indicated by the claims rather than by the description of the embodiments above, and further includes all modifications (exceptions) within the meaning and scope equivalent to the claims.
[0090] For example, the first and second embodiments described above show examples in which the predicted power generation value is updated and predicted at predetermined intervals for acquiring measured values, but the present invention is not limited thereto. In the present invention, for example, in addition to predetermined intervals, measured values may be acquired at any necessary timing and the predicted power generation value may be updated and predicted based on them.
[0091] Furthermore, while the first and second embodiments described above show an example where the predetermined period for acquiring measured values within a day is set to 1 minute, the present invention is not limited to this. In the present invention, for example, measured values may be acquired multiple times within a day by setting a predetermined period for each time period, or the predetermined period may be set only for the necessary time periods. With this configuration, it is possible to set a longer predetermined period during times when the accuracy of predicting solar power generation is not important, such as at night, and suppress the power consumption when acquiring measured values.
[0092] Furthermore, in the first and second embodiments described above, the prediction period for the short-term power generation forecast was set to 30 minutes, but the present invention is not limited to this. In the present invention, for example, the prediction period for the short-term power generation forecast is not limited to 30 minutes, but may be several minutes to several hours.
[0093] Furthermore, in the first and second embodiments described above, the amount of change over time of the acquired measured values was calculated to predict the amount of power generated, but the present invention is not limited to this. In the present invention, for example, prediction may be made from the acquired measured values instead of from the amount of change, or the calculated amount of change may be further corrected using a correction coefficient to predict the amount of power generated.
[0094] Furthermore, in the first and second embodiments described above, the amount of change over time was calculated based on the latest measured value and the previous measured value, but the present invention is not limited thereto. In the present invention, for example, the amount of change may be calculated based on the latest actual value and the required measured value from before the previous measurement, or the amount of change may be calculated from three or more measured values. When calculating the amount of change from three or more measured values, if a straight line passing through all the measured values cannot be obtained, the slope (amount of change) may be obtained by a statistical method.
[0095] Furthermore, in the first and second embodiments described above, when both correction processing by calculating the amount of change in measured values (slope of solar power generation with respect to time) and correction processing by selecting past measured values are performed, an example is shown where the correction processing by calculating the amount of change in measured values (slope of solar power generation with respect to time) is performed first, followed by the correction processing by selecting past measured values. However, the present invention is not limited to this. The correction processing by selecting past measured values may be performed first, followed by the correction processing by calculating the amount of change in measured values (slope of solar power generation with respect to time).
[0096] Furthermore, in the first and second embodiments described above, examples were shown in which the correction process for the predicted power generation amount based on the selection of past measured values is performed based on the difference dN between the latest measured value and the past measured value and the difference DN between the latest slope and the past slope, but the present invention is not limited thereto. In the present invention, for example, past measured values may be selected based only on the difference dN between the latest measured value and the past measured value, or past measured values may be selected based only on the difference DN between the latest slope and the past slope.
[0097] Furthermore, in the first and second embodiments described above, the correction process for the predicted power generation amount by selecting past measured values was shown as an example in which past measured values are selected by the difference dN between the latest measured value and past measured values, and then past measured values are selected by the difference DN between the latest slope and past slopes. However, the present invention is not limited to this. In the present invention, for example, a plurality of past measured values in which the difference DN between the latest slope and past slopes is within a predetermined range may be selected, and then past measured values may be selected by the difference dN between the latest measured value and past measured values.
[0098] Furthermore, in the first and second embodiments described above, the store control unit (12, 12a) controlled the storage and discharge of the battery 30 based on at least one of the predicted power consumption value and the actual power consumption value of the load equipment 11, and the predicted power generation value, but the present invention is not limited thereto. In the present invention, for example, control may be performed based on the predicted power consumption value and the predicted power generation value of the load equipment, or control may be performed based on the actual power consumption value and the predicted power generation value.
[0099] Furthermore, in the first and second embodiments described above, the store control unit (12, 12a) predicts the timing at which surplus power will be generated by the solar power generation unit 21 relative to the power consumption of the load equipment 11, based on at least one of the predicted power consumption value and the measured power consumption value of the load equipment 11 and the predicted power generation amount, and controls the storage and discharge of power generated by the solar power generation unit 21 to the storage battery 30 via the solar power generation control unit 22 so that the power generated by the solar power generation unit 21 can be stored in the storage battery 30 at the timing at which surplus power is generated. However, the present invention is not limited to this. In the present invention, for example, control may be performed based on the predicted power consumption value of the load equipment and the predicted power generation amount, or control may be performed based on the measured power consumption value and the predicted power generation amount.
[0100] Furthermore, in the first and second embodiments described above, the store control unit (12, 12a) predicts the timing of a power shortage in the power generated by the solar power generation unit 21 relative to the power consumption of the load equipment 11, based on at least one of the predicted power consumption value and the measured power consumption value of the load equipment 11 and the predicted power generation amount, and controls the storage and discharge of power generated by the solar power generation unit 21 to the storage battery 30 via the solar power generation control unit 22 so that the power stored in the storage battery 30 can be discharged at the timing of the power shortage. However, the present invention is not limited to these examples. In the present invention, for example, control may be performed based on the predicted power consumption value of the load equipment and the predicted power generation amount, or control may be performed based on the measured power consumption value and the predicted power generation amount.
[0101] Furthermore, in the first and second embodiments described above, the store control unit (12, 12a) is shown to perform correction processing on the predicted power generation amount by calculating the amount of change of the measured value with respect to time or by selecting past measured values that approximate or match the measured value, but the present invention is not limited thereto. In the present invention, for example, the correction processing of the predicted power generation amount according to the first and second embodiments may be combined. Specifically, the store control unit may be configured to predict a short-term predicted power generation amount, which is a short-term predicted power generation amount, based on measured values and amounts of change acquired at predetermined intervals, and to predict a medium- to long-term predicted power generation amount, which is a predicted power generation amount that is longer than the prediction period of the short-term predicted power generation amount and at least one day in the medium to long term, based on past measured values, which are past measured values of solar power generation by the solar power generation unit. For example, as shown in the modified example in Figure 9, if a measured value is obtained at the time of 1 minute, after calculating the slope, a short-term power generation forecast value (short-term power generation forecast value) is predicted up to 1 minute + n minutes later (for example, 30 minutes later). At the same time, from past measured values A, B, and C, past measured value A that approximates or matches the measured value and slope at the same time is selected, and a medium- to long-term power generation forecast value is predicted. The store control unit performs the same control at predetermined intervals, predicting the short-term power generation forecast value and the medium- to long-term power generation forecast value each time, and updating the predicted values. Note that if a measured value is obtained at predetermined intervals and the measured value and the power generation forecast value match, it is not necessary to perform the prediction process for one or both of the short-term power generation forecast value and the medium- to long-term power generation forecast value. This makes it possible to predict the short-term changes in solar power generation amount using the short-term power generation forecast value and the medium- to long-term changes in solar power generation amount using the medium- to long-term power generation forecast value. As a result, it is possible to create a battery storage and discharge plan for the entire day by prioritizing short-term power generation forecasts for periods of up to 30 minutes, and then prioritizing medium- to long-term power generation forecasts for subsequent operating plans. [Explanation of symbols]
[0102] 10 Store Power Management Devices 11 Load equipment 11a Showcase 11b Air conditioner 11c electric heating device 11d lighting 12 Store Control Unit 12a Store Control Unit 20 Solar power generation systems 21 Solar Power Generation Department 22 Solar power generation control unit 30 Storage batteries 100 stores 300 cloud servers
Claims
1. The store includes a store control unit that is installed in the store and acquires measured values of the amount of solar power generated by a solar power generation unit installed in or around the store, predicts future power generation values based on the acquired measured values, and controls load equipment installed in the store based on the predicted power generation values. The store control unit is a store power management device that acquires the measured values multiple times at predetermined intervals within a one-day period, and updates and predicts the predicted power generation value each time the measured values are acquired at the predetermined interval.
2. The store power management device according to claim 1, wherein the store control unit calculates the amount of change over time of the measured value and predicts the amount of power generated based on the measured value and the amount of change.
3. The store power management device according to claim 2, wherein the store control unit predicts the predicted power generation amount assuming that the calculated change amount continues.
4. The store control unit calculates the amount of change based on the previous measured value and the current measured value, and predicts the predicted amount of power generation, as described in claim 2.
5. The store control unit predicts a short-term power generation forecast value, which is a short-term power generation forecast value, based on the measured value and the amount of change acquired at a predetermined period, as described in claim 2.
6. The store power management device according to claim 2, wherein the store control unit predicts a medium- to long-term power generation forecast value, which is a predicted power generation value for at least one day, based on the past measured values of the amount of solar power generated by the solar power generation unit.
7. The store power management device according to claim 6, wherein the store control unit compares the acquired measured value with a plurality of past measured values, selects the past measured value having a measured value that matches or approximates the measured value at a time corresponding to the measurement time of the measured value, and predicts the medium- to long-term power generation forecast value.
8. The store power management device according to claim 7, wherein the store control unit selects past measured values that match or approximate the measured values and the amount of change of the measured values, respectively, at a time corresponding to the measurement time of the measured values, based on the acquired measured values and the amount of change of the measured values, and predicts the medium- to long-term power generation forecast value.
9. The store power management device according to claim 1, wherein the store control unit controls the storage and discharge of electricity generated by the solar power generation unit to a storage battery based on at least one of the predicted power consumption value and the measured power consumption value of the load equipment and the predicted power generation value.
10. The store control unit predicts the timing at which surplus power will be generated relative to the power consumption of the load equipment based on at least one of the predicted power consumption and the measured power consumption of the load equipment and the predicted power generation amount, and controls the storage and discharge of power generated by the solar power generation unit to the storage battery so that the power generated by the solar power generation unit can be stored in the storage battery at the timing at which surplus power is generated, as described in claim 9.
11. The store control unit predicts the timing at which a power shortage will occur in the power generated by the solar power generation unit relative to the power consumption of the load equipment, based on at least one of the predicted power consumption value and the measured power consumption value of the load equipment and the predicted power generation amount, and controls the storage and discharge of the power generated by the solar power generation unit to the storage battery so that the power stored in the storage battery can be discharged at the timing at which the power shortage occurs, as described in claim 9.