Panel control system, panel control method, and panel control program

Abstract

To minimize electricity costs and maximize crop selling prices.SOLUTION: A panel control system S comprising a solar panel 4 provided at a variable tilt angle α above a farmland 5 includes: solar power generation information acquisition means 110 that acquires predicted information on power to be generated by the solar panel 4 in future on the basis of information indicating the power that has been generated by the solar panel 4 in the past; facility demand power information acquisition means 120 that acquires predicted information on the power that is to be consumed by a facility 7 in future on the basis of information indicating the power that has been consumed by the facility 7 in the past; crop information acquisition means 130 that acquires information on a crop 51 grown in the farmland 5; tilt angle determination means 160 that determines the tilt angle α on the basis of the predicted information on the power generated by the solar panel, the predicted information on the power that is to be consumed by the facility 7, and the information on the crop 51; and control means 140 that adjusts the tilt angle α to the determined angle.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a panel control system, a panel control method, and a panel control program for agricultural solar power generation in which solar panels generate solar power while crops are grown below the solar panels, and for adjustably controlling the tilt angle of the solar panels so that sunlight is appropriately irradiated onto the solar panels and crops. [Background technology]

[0002] Agricultural solar power generation is known, in which supports such as yagura are erected on farmland, solar panels are placed on top of the supports, and solar power is generated while farming continues. For example, Patent Document 1 discloses a system that includes a solar panel and a reflector, and controls the tilt angle of the solar panel to be a predetermined angle smaller than the tilt angle of the reflector. This document describes that by providing a reflector between solar panels, sunlight is reflected by the reflector and effectively irradiates the crops. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2020-184987 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the invention of Patent Document 1 requires the placement of reflectors between solar panels, making it impossible to arrange solar panels without gaps across the entire farmland, resulting in a small amount of solar power generated relative to the area. As a result, various electrical appliances are used in facilities adjacent to farmland, but the power supply is insufficient for these appliances. For this reason, facilities have no choice but to rely on power from the power grid operated by the power company for their electricity, which poses the problem of electricity bills easily exceeding peak values ​​and becoming expensive. To address this issue, solar panels can be installed seamlessly across the entire farmland, which can generate more solar power and reduce the burden on the grid. However, in this case, the solar panels will block sunlight from reaching the crops (receiving light). This results in other problems, such as poor growth and lower selling prices for the crop. These problems are particularly relevant for crops that have no or high light saturation points, but in conventional agricultural solar power generation, there was no technology to automatically adjust the amount of sunlight irradiated on crops or solar panels, leaving room for improvement.

[0005] The present invention has been made in consideration of the above circumstances, and aims to provide a panel control system, a panel control method, and a panel control program for agricultural solar power generation that employ solar panels with adjustable tilt angles and that can automatically adjust the tilt angle to an appropriate angle based on conditions. [Means for solving the problem]

[0006] In order to achieve the above-mentioned object, a panel control system according to one embodiment of the present invention comprises a solar power generation information acquisition means that acquires predicted information about the power that will be generated by the solar panel in the future based on information indicating the power that has been generated by the solar panel in the past; a facility demand power information acquisition means that acquires predicted information about the power that will be consumed by the facility in the future based on information indicating the power that has been consumed by the facility in the past; a crop information acquisition means that acquires information about crops to be grown in the farmland; an inclination angle determination means that determines the inclination angle based on the predicted information about the power to be generated by the solar panel, the predicted information about the power that will be consumed by the facility, and the information about the crops; and a control means that adjusts the inclination angle to the determined angle.

[0007] In addition, a panel control method according to another aspect of the present invention is a control method capable of varying the tilt angle of solar panels installed above agricultural land, and includes the steps of: obtaining predicted information about the amount of solar power that will be generated by the solar panels in the future based on information indicating the amount of solar power that has been generated by the solar panels in the past; obtaining predicted information about the amount of power that will be consumed by the facility in the future based on information indicating the amount of power that has been consumed by the facility in the past; obtaining information about crops to be grown on the agricultural land; determining the tilt angle based on the predicted information about the amount of solar power that will be generated, the predicted information about the amount of power that will be consumed by the facility, and the information about the crops; and adjusting the tilt angle to the determined angle.

[0008] In addition, a panel control program according to another aspect of the present invention causes a computer that variably controls the tilt angle of solar panels installed above farmland to function as: a solar power generation information acquisition means that acquires predicted information about the amount of solar power that will be generated by the solar panels in the future based on information indicating the amount of solar power generated by the solar panels in the past; a facility demand power information acquisition means that acquires predicted information about the amount of power that will be consumed by the facility in the future based on information indicating the amount of power consumed by the facility in the past; a crop information acquisition means that acquires information about crops to be grown on the farmland; a tilt angle determination means that determines the tilt angle based on the predicted information about the amount of solar power generated, the predicted information about the amount of power consumed by the facility, and the information about the crops; and a control means that adjusts the tilt angle to the determined angle. [Effects of the Invention]

[0009] The present invention allows for minimizing power costs and maximizing the selling price of crops. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a schematic diagram of a panel control system according to an embodiment of the present invention; [Figure 2]FIG. 2 is a hardware configuration diagram of a server. [Figure 3] FIG. 1 is a plan view of a solar panel. [Figure 4] 1A and 1B are side views of a solar panel, in which (a) shows a solar panel with an inclination angle of α=30°, (b) shows an example of an inclination angle of 30°<α<120°, and (c) shows a solar panel with an inclination angle of α=120°. [Figure 5] FIG. 2 is a functional block diagram of a panel control system. [Figure 6] FIG. 10(a) is an explanatory diagram regarding the generation of a photovoltaic power generation power prediction model, and FIG. 10(b) is a diagram showing that photovoltaic power generation prediction information is output by inputting predetermined information into the photovoltaic power generation power prediction model. [Figure 7] (a) is an example of a solar power generation power DB that stores solar power generation power (actual results). (b) is an example of a weather information DB that stores weather, temperature, and humidity (actual results). (c) is an example of information including the amount of solar power generation (prediction) output by a solar power generation power prediction model. [Figure 8] FIG. 10(a) is an explanatory diagram regarding the generation of a facility power demand prediction model, and FIG. 10(b) is a diagram showing that prediction information for facility power demand is output by inputting specified information into the facility power demand prediction model. [Figure 9] 1(a) is an example of a facility power demand DB storing actual facility power demand data. FIG. 1(b) is an example of information including predicted facility power demand data output by a facility power demand prediction model. [Figure 10] (a) is a diagram showing how the shipping period is determined based on the growth rate of the crop. (b) is a diagram showing how the price of the crop during the shipping period is predicted based on past crop prices (performance) and how the highest price date is determined as the target shipping date. [Figure 11] (a) is a diagram showing the growth rate of crops and the moisture content of farmland (soil), and (b) is an explanatory diagram regarding the shipping period. [Figure 12] (a) is an example of a crop price DB that stores past crop prices (actual results), and (b) is a chart showing crop prices (forecasts). [Figure 13] 1 is a graph showing trends (forecasts) in crop prices. [Figure 14] 10 is a chart showing determination patterns a to h for determining the tilt angle based on the growth rate, the photovoltaic power generation power (prediction), and the facility power demand (prediction). [Figure 15] FIG. 2 is a main flowchart of the panel control method of the present invention. [Figure 16] 10 is a sub-flowchart showing a procedure for acquiring predicted information on photovoltaic power generation. [Figure 17] 10 is a sub-flowchart showing a procedure for acquiring predicted information on facility power demand. [Figure 18] 10 is a sub-flowchart showing a procedure for acquiring crop information. DETAILED DESCRIPTION OF THE INVENTION

[0011] Preferred embodiments of a panel control system, a panel control method, and a panel control program according to the present invention will be described with reference to the drawings.

[0012] FIG. 1 is a schematic diagram of a panel control system S according to one embodiment of the present invention. As shown in Figure 1, the panel control system S of this embodiment includes a server 1, a weather information providing device 2, a solar power generation system 4S equipped with solar panels 4, farmland 5 planted with crops 51, a drone 6, a facility 7, and a facility management system 7S that manages the facility 7. The components are connected to each other so as to be able to communicate with each other via a communication line such as the Internet 9.

[0013] (Server 1 hardware configuration) FIG. 2 is a diagram showing the hardware configuration of the server 1. As shown in FIG. The server 1 performs control to automatically vary the tilt angle α of the solar panel 4 according to predetermined conditions. The server 1 is an information processing device including a processor 101, a memory 102, a storage 103, and a communication device 104. The processor 101 executes a program to control each unit of the server 1 and perform processing to realize the functions of the server 1. The processor 101 may be, for example, a CPU (Central Processing Unit). The memory 102 is a computer-readable recording medium that stores programs executed by the processor 101. The memory 102 may include, for example, a RAM (Random Access Memory) and a ROM (Read Only Memory). The storage 103 is a computer-readable recording medium that stores various data and programs used by the processor 101. The storage 103 may be, for example, a hard disk drive (HDD) or a solid state drive (SSD). The programs include the panel control program of the present invention. The communication device 104 is connected to the Internet 9 and transmits and receives information to and from each communication means of the weather information providing device 2, the solar power generation system 4S, the drone 6, the facility management system 7S, and the like via the Internet 9, for example.

[0014] (Solar power generation system 4S) This section explains the 4S solar power generation system. FIG. 3 is a plan view of the solar panel 4. FIG. 4 is a side view illustrating various tilt angles of the solar panel 4. In FIG. FIG. 5 is a functional block diagram of the panel control system S. As shown in these figures, the solar power generation system 4S includes a solar panel 4, a tilt angle adjustment unit 410, a control processing unit 420, and a power generation amount management unit 430.

[0015] The solar panel 4 generates solar power when sunlight is irradiated onto the panel surface. The solar-generated electricity can be supplied to drones 6 and various electrical devices 710 managed in the facility 7. Since the panel control system S is a system related to agricultural solar power generation, the solar panels 4 are installed above the farmland 5 (crops 51).

[0016] The tilt angle adjustment unit 410 is a movable part for adjusting the tilt angle of the solar panel 4 to any desired angle. As shown in FIG. 4, the tilt angle adjustable part 410 is configured by a worm gear, which is a combination of a cross-hair gear (worm) 412 and a helical gear (worm wheel) 413 that matches the cross-hair gear. A worm wheel 413 is joined to one end or both ends of a rotation shaft 411 at the center of the solar panel 4, and a worm 412 is rotated by a motor (not shown). As a result, the worm wheel 413 is rotated by the rotation, and the rotation shaft 411 rotates in response to the rotation, so that the solar panel 4 can be rotated around the rotation shaft 411.

[0017] The control processing unit 420 includes a processor, and executes a program to cause the tilt angle adjustment unit 410 to adjust the tilt angle α to a predetermined angle. Specifically, the control processing unit 420 can change the tilt angle α to any angle based on a command received from the server 1 and then fix it. In this embodiment, a plurality of solar panels 4 are provided, and the control means 140 issues commands to all control processing units 420 simultaneously, so that the tilt angle of each solar panel 4 is always adjusted to the same angle (FIG. 3).

[0018] FIG. 4 is a diagram showing a state in which the control processing unit 420 adjusts the tilt angle α to a predetermined angle in response to receiving a command signal including angle information of the tilt angle α from the server 1. Figure 4(a) is a side view of a solar panel 4 with an inclination angle α=30°, Figure 4(b) is a side view showing an example of an inclination angle of 30<α<120° (α=45°), and Figure 4(c) is a side view of a solar panel 4 with α=120°. The tilt angle of the solar panel 4 varies depending on the season, time of day, direction, etc., but for convenience, it is assumed here that sunlight travels perpendicular to the panel surface when the tilt angle α=30°. Therefore, when the tilt angle α is 30°, the amount of sunlight irradiating the solar panel 4 is the greatest, and therefore the amount of electricity generated by solar power generation is the greatest, while the amount of sunlight irradiating the crops 51 is the least (Figure 4(a)). Furthermore, when the tilt angle α is 120°, sunlight travels parallel to the panel surface, so the amount of sunlight irradiating the solar panel 4 is the smallest, and therefore the amount of electricity generated by solar power generation is the smallest. On the other hand, the amount of sunlight irradiating the crops 51 is the largest (Figure 4(c)).

[0019] From the above, it can be seen that the amount of electricity generated by solar power generation is highest when the tilt angle α = 30° and lowest when the tilt angle α = 120°, and the amount of sunlight irradiated onto the crops 51 is lowest when the tilt angle α = 30° and highest when the tilt angle α = 120°. In other words, the amount of power generated by solar power generation and the amount of sunlight irradiated onto the crops 51 vary at an inclination angle α in the range of 30° to 120° (FIG. 4(b)), and there is a trade-off relationship in which as one increases, the other decreases. The power generation amount management unit 430 manages (stores) the amount of power generated by photovoltaic power generation on a daily basis, and transmits the managed information to the server 1.

[0020] (5 farmland, 51 crops) Crops 51 are planted in the farmland 5, and solar panels 4 are installed above them. The crops 51 require sunlight to perform photosynthesis. In particular, in the case of crops 51 that do not have a light saturation point, the rate at which photosynthesis is carried out increases as the amount of sunlight irradiated increases. Therefore, the more sunlight the crop 51 is exposed to (the stronger the light intensity), the faster it grows, and the less sunlight the crop 51 is exposed to, the slower it grows. Even for the crop 51 that has a light saturation point, the growth rate of the crop 51 changes depending on the amount of sunlight irradiation below the light saturation point. The crops 51 also need an appropriate amount of moisture for growth. For example, if the soil contains an appropriate amount of moisture, the crops will grow healthily, but if the soil contains too little moisture, the crops will stunt their growth. From the above, under certain conditions, the crop 51 grows faster the greater the amount of sunlight irradiation or the amount of moisture contained in the soil, and grows slower the less the amount of sunlight irradiation or the amount of moisture contained in the soil. The crop 51 may be one type or two or more types, and is not limited to a specific type.

[0021] (Weather Information Device 2) The weather information providing device 2 is a web server that handles a known weather forecast service, and provides forecast information such as whether the weather will be sunny, cloudy, or rainy in the future via the Internet 9. The weather information providing device 2 also provides future temperature and humidity forecast information via the Internet 9 . The server 1 can receive forecast information on the daily weather and temperature / humidity for a specific period, such as one month or six months, from the next day, from the weather information providing device 2 via the Internet 9 .

[0022] (Facility 7 and Facility Management System 7S) The facility 7 is a structure such as a building where the farmer who grows the crop 51 lives or operates. The facility 7 is equipped with drones 6 (described below) and other electrical equipment 710 (for example, chargers for the drones 6 and electric vehicles, air conditioning equipment, lighting fixtures and other household appliances), and power is supplied to and consumed by each electrical equipment 710 as appropriate. The facility 7 receives grid power 81 supplied from an electric power company and solar-generated power 82 supplied from a solar power generation system 4S. In this embodiment, photovoltaic power generation power 82 is supplied and consumed preferentially, but grid power 81 is supplied and consumed to cover the load that cannot be covered by photovoltaic power generation power 82. Therefore, the more the amount of power generated by photovoltaic power generation 82 is, the more the consumption of grid power 81 can be reduced. The power consumption management unit 711 manages (stores) the amount of power consumption in the facility 7, and transmits the amount of power consumption to the server 1 on a daily basis.

[0023] (Drone 6) Drone 6 is an example of an unmanned aerial vehicle, and is a multi-purpose drone capable of performing multiple tasks. The "plurality of tasks" include, for example, watering the crops 51 from above, spraying fertilizers and pesticides, photographing (inspecting) the crops 51 from above, and the like. In addition to the general flight functions of a normal flying object, the drone 6 also has a communication function, a positioning unit, a power supply unit, a photographing unit, a liquid spraying unit, and a control function. The communication function is a function for transmitting and receiving various data to and from the server 1 via a network such as a mobile phone network such as LTE or a fixed communication network such as the Internet 9. The positioning unit is a positioning means such as a global navigation satellite system (GNSS) including GPS, and measures the position information (latitude and longitude) of the drone 6. Therefore, by specifying the position information of the crops 51 or the farmland 5, the drone can be made to fly (hover) above the crops 51 or the farmland 5. The power supply unit includes a battery, which supplies driving power to the drone 6. The drone 6 is placed at a facility 7 when on standby, and the battery is charged by a charger while the drone 6 is placed at the facility 7. The image capturing unit is a camera that captures moving images or still images. The photographing unit is used to photograph the crops 51 and farmland 5 to be inspected from above. The photographed data is transmitted to the server 1. The liquid spraying unit is a component for spraying liquids such as water, fertilizer, and pesticides from the sky.

[0024] In the control function, the CPU executes the programs stored in the ROM to perform the following controls: For example, the control function can cause the drone 6 to take off from a waiting location in the facility 7 at a fixed time each day, and fly over the target farmland 5 or crops 51 based on specified position information while causing the camera to photograph the farmland 5 or crops 51. The photographed images of the farmland 5 or crops 51 can be transmitted to the server 1. In addition, the control function allows the liquid spraying unit to spray water, fertilizer, and pesticides while flying over the target farmland 5 or crops 51 based on specified location information, based on commands from the server 1.

[0025] (Operations in Server 1 and Panel Control System S) As shown in FIG. 5, the server 1 includes a database 150 inside the storage 103, and also includes a photovoltaic power generation information acquisition means 110, a facility demand power information acquisition means 120, a crop information acquisition means 130, and a control means 140. The database 150 includes, for example, a solar power generation DB 151 that stores past performance information on solar power generation power 82, a weather information DB 152 that stores past performance information on weather, temperature, and humidity, a facility demand power DB 153 that stores past performance information on facility power consumption, and a crop price DB 154 that stores past price information on crops 51.

[0026] The solar power generation power DB 151 is constructed by the server 1 receiving and storing, via the Internet 9, information on past (e.g., the last 10 years) solar power generation power 82 managed by the power generation amount management unit 430 of the solar power generation system 4S. The weather information DB 152 is configured by storing past (for example, the most recent 10 years' worth) weather, temperature, and room temperature performance information. The facility power demand DB 153 is configured by the server 1 receiving and storing, via the Internet 9, information on facility power demand (power consumed by the facility 7) from the past (for example, the last 10 years) managed by the power consumption management unit 711 of the facility management system 7S. The crop price DB 154 is configured by storing price information such as sales prices, wholesale prices, and retail prices of the crops 51 in the past (for example, for the most recent 10 years).

[0027] The photovoltaic power generation information acquisition means 110 acquires prediction information about the power that will be generated by the photovoltaic panel 4 in the future, based on information indicating the power that has been generated by the photovoltaic panel 4 in the past. Specifically, as shown in Figure 6(a), a combination of past dates (including times), solar power generation power 82 (actual results) on those dates, and weather (actual results) on those dates is used as a dataset, and by preparing many sets of such datasets over a long period of time and performing machine learning, a program (solar power generation power prediction model) is generated that can output a predicted amount of solar power generation power 82 on a specific date or for a specific period in the future. The solar power generation power 82 (actual result) may be acquired from the solar power generation power DB 151, and the weather (actual result) may be acquired from the weather information DB 152. For example, if learning performance data for 10 years from May 1, 2010, a data set is prepared that combines, by date, the dates for each day from May 1, 2010 to April 30, 2020, the actual information on the amount of solar power generated 82 for each day (Figure 7(a)), and the actual information on the weather for each day (Figure 7(b)). These data sets are then input into a neural network consisting of an input layer, multiple intermediate layers, and an output layer, allowing it to autonomously learn the correlation between date, weather, and solar power generation power 82. Through this learning, a program (photovoltaic power generation power prediction model) is generated that outputs the corresponding photovoltaic power generation power 82 when the date and weather are input (FIGS. 6(a) and 6(b)).

[0028] For example, when a future date is specified, weather (forecast) information for that date is obtained from the weather information providing device 2, and that date and the extracted weather (forecast) information are input into the photovoltaic power generation power prediction model (Figure 6(b)). The weather (forecast) may be predicted in the server 1, and the prediction result may be input to the photovoltaic power generation power prediction model as "weather (forecast) information." This allows the solar power generation power prediction model to output the solar power generation power 82 (prediction) for that date (FIG. 6(b)). Therefore, by specifying any date between May 1st and May 31st, 2020, it is possible to obtain forecast information on the amount of power generated by photovoltaic power generation 82 in May, 2020 (see FIG. 7(c)). In this embodiment, a data set at 30-minute intervals is prepared and learned, so that the amount of power generated (predicted value) of solar power generation power 82 can be output at 30-minute intervals (see FIGS. 7(a) to (c)). The time interval may be 30 minutes or less (for example, 10 minutes), or may be 30 minutes or more (for example, 1 hour or 1 day). Temperature and humidity can also be added to the learning subjects.

[0029] The facility demand power information acquisition means 120 acquires prediction information of power to be consumed in the facility 7 in the future (facility demand power) based on information indicating power consumed in the facility 7 in the past (facility demand power). Specifically, as shown in Figure 8(a), a combination of a past date (including time), the facility power demand (actual) on that date, the temperature and humidity (actual) on that date, and the day of the week on that date is used as a dataset, and by preparing a large number of such datasets and performing machine learning, a program (facility power demand forecasting model) is generated that can output a forecast of the facility power demand on a specific date or for a specific period in the future. The facility power demand (actual result) may be acquired from the facility power demand DB 153, and the temperature and humidity (actual result) may be acquired from the weather information DB 152. For example, if learning from 10 years of actual data from May 1, 2010, a dataset is prepared that combines the dates of each day from May 1, 2010 to April 30, 2020, the actual information on the daily facility power consumption (Figure 9(a)), the actual information on the daily temperature and humidity (Figure 7(b)), and the day of the week information (Figure 9(a)) for each day. These data sets are then input into a neural network consisting of an input layer, multiple intermediate layers, and an output layer, allowing it to autonomously learn the relationship between date, temperature, humidity, day of the week, and facility power demand. Through this learning, a program (facility power demand forecasting model) is generated that outputs the corresponding facility power demand when the date, temperature, humidity, and day of the week are input (Fig. 8(a) and (b)).

[0030] For example, when a future date is specified, the temperature and humidity (forecast) information for that date is obtained from the weather information providing device 2, and the date, day of the week, and the extracted temperature and humidity (forecast) information are input into the facility demand power forecasting model. This allows the facility power demand (prediction) for that date to be output from the facility power demand prediction model (FIG. 8(b)). Therefore, by specifying each date between May 1st and May 31st, 2020, the facility demand power prediction model can output predicted information on the power consumption of facility 7 for each day in May 2020 (see Figure 9(b)). This allows the facility power demand information acquisition means 120 to acquire forecast information on the power demand at the facility 7 for the specific period (FIG. 8(b)). In this embodiment, a data set at 30-minute intervals is prepared and learned, so that facility demand power consumption (predicted value) can be output at 30-minute intervals (see FIGS. 9(a) to 9(b)). The time interval may be 30 minutes or less (for example, 10 minutes), or may be 30 minutes or more (for example, 1 hour or 1 day). Weather can also be added to the learning topics.

[0031] The crop information acquisition means 130 acquires information about the crops 51 grown in the farmland 5. The crop information acquisition means 130 includes a growth rate specification means 131 , a shipping period specification means 132 , a crop price information acquisition means 133 , a target shipping date determination means 134 , and a growth rate determination means 135 .

[0032] The growth rate specification means 131 specifies the growth rate of the crop 51. Specifically, during the growing period, the drone 6 flies over the farmland 5 and the crops 51 on a regular or irregular basis, and the image of the crops 51 captured by the camera is sent to the server 1. The server 1 then extracts feature points from the received image of the crops 51 using known image recognition technology, determines the growth rate based on the size, shape, color, etc. of the crops 51 identified from the feature points, and stores the growth rate together with the date. For example, corn grows to a height of about 5 cm 8 to 9 days after sowing (start of cultivation) (growth rate of about 10%), grows to a height of about 10 cm 20 to 30 days after starting cultivation (growth rate of about 25%), grows to a height of about 50 cm 40 to 45 days after starting cultivation (growth rate of about 50%), tassels appear 50 days after starting cultivation and grow to a height of about 100 cm (growth rate of about 58%), and after 86 days after starting cultivation, the kernels turn brown with silk threads and are ready for harvest (growth rate of 100%). Therefore, the growth rate can be determined based on the height of the crop 51 identified by image recognition and the condition of the ears and silk threads. For example, Figure 11(a) shows that as of May 4, 2020, the growth rate of crop 51 was 57%, as of May 5, 2020, the growth rate of crop 51 was 58%, and as of May 31, 2020, the growth rate of crop 51 was 79%.

[0033] The shipping period specifying means 132 specifies the shipping period of the crop 51 based on the growth rate. FIG. 11(b) is a diagram showing a method for identifying a shipping period based on a growth rate. As shown in the figure, if the crop 51 grows linearly, a regression equation y=ax+b (y is the growth rate, x is the date) is created, and the date x when y is 100% is set as the standard shipping date. If the width of the shipping period that can be varied depending on the amount of photosynthesis is β days, the shipping period for the crop 51 can be specified as (x−β) days to (x+β) days. In this example, the shipping period for crop 51 as of May 31, 2020 is to be identified. In other words, the shipping period is determined based on the growth rates mentioned above (growth rate of crop 51 as of May 4, 2020: 57%, growth rate of crop 51 as of May 5, 2020: 58%, growth rate of crop 51 as of May 31, 2020: 79%, etc.). As a result, as shown in FIG. 11(b), the shipping period: June 5, 2020 to June 15, 2020 is identified. The shipping period varies not only depending on the amount of photosynthesis but also on the amount of moisture and fertilizer in the farmland 5, so it is possible to set a period taking these factors into consideration.

[0034] The crop price information acquisition means 133 acquires predicted information on the price of the crop 51 during the shipping period based on the past price of the crop 51. Specifically, a combination of past dates, crop 51 prices (actual), and temperature and humidity (actual) is used as a dataset, and by preparing a large number of such datasets and performing machine learning, a program (crop price prediction model) is generated that can output predicted information on crop prices at least for the shipping period. Weather may also be included in the learning subject. Past crop prices (actual results) can be obtained from the crop price DB 154 (FIG. 12(a)), and temperature and humidity (actual results) can be obtained from the weather information DB 152 (FIG. 7(b)). The learning method is the same as the learning method for the solar power generation power prediction model, and therefore a detailed description thereof will be omitted. This allows the crop price prediction model to output crop prices (predictions) for future dates. Therefore, by specifying June 1st to June 20th, 2020, which includes the shipping period, you can obtain forecast information for daily crop prices during that period, as shown in Figure 12(b).

[0035] The target shipping date determination means 134 determines the target shipping date based on the predicted price information of the crop 51 during the shipping period. Specifically, the target shipping date is determined to be the day during the shipping period when the price of the crop 51 is high. In this example, as shown in Figures 12(b) and 13, June 12, 2020 is the highest price (223 yen / kg) during the shipping period, so this date is determined as the target shipping date.

[0036] The growth rate determining means 135 determines the growth rate of the crop 51 relative to the target shipping date. For example, if the growth rate of a crop 51 on a certain day is x%, and the day on which the growth rate of the crop 51 is predicted to reach 100% is earlier than the target shipping date, the growth rate is determined to be "fast." On the other hand, if the day on which the growth rate of the crop 51 is predicted to reach 100% is later than the target shipping date, the growth rate is determined to be "slow." As a specific example, as of May 31, 2020, the growth rate of Crop 51 is 79%, so the standard shipping date is June 10, 2020, but the target shipping date is June 12, 2020, so the growth rate is determined to be "fast" at that time. Thereafter, for example, if the standard shipping date calculated based on the growth rate of crop 51 as of June 5, 2020, is June 14, 2020, the growth rate is determined to be "slow" at that time.

[0037] The tilt angle determination means 160 determines the tilt angle based on predicted information about the amount of electricity generated by the solar panel 4, predicted information about the amount of electricity consumed in the facility 7, and information about the crops 51 (the growth rate of the crops 51). The control means 140 then adjusts the tilt angle to the determined angle.

[0038] The reason why "electricity generated by solar power" and "electricity consumed at the facility" are used is that, depending on the amount of each, the grid power 81 at facility 7 may exceed the peak value, resulting in a high burden, and even in that case, if the amount of solar power generation is large, this high burden can be avoided or reduced, and this can be controlled by adjusting the tilt angle. The reason for using "crop growth rate" is that we aim for a growth rate of 100% on the day when Crop 51 can be shipped at a high price, and the cultivation method differs depending on whether the growth rate is fast or slow, and this can be controlled by adjusting the tilt angle. Specifically, during growth, the tilt angle is determined periodically (for example, daily) or irregularly based on the determination patterns a to h shown in FIG.

[0039] Regarding the "growth rate" in Figure 14, "early" indicates that the standard shipping date determined based on the growth rate of crop 51 on that day is predicted to be earlier than the target shipping date, and "late" indicates that the standard shipping date determined based on the growth rate of crop 51 on that day is predicted to be later than the target shipping date. Regarding "Photovoltaic power generation" in FIG. 14, "high" indicates that the amount of photovoltaic power generation 82 on that day is high, and "low" indicates that the amount of photovoltaic power generation 82 on that day is low. The "high / low" level of the amount of power generated by the photovoltaic power generation 82 may be determined based on a reference amount of power generation, or may be determined relatively in comparison with the amount of power demanded by the facility. Regarding the "facility power demand" in FIG. 14, "high" indicates that the facility power demand amount for that day is high, and "low" indicates that the facility power demand amount for that day is low. The "high / low" determination of facility demand power may be based on a reference power amount (a peak value that is the boundary between whether or not electricity charges will be high), or may be a relative determination in comparison with the power amount of solar power generation power 82.

[0040] Pattern a is a case where the growth rate is "fast", the photovoltaic power generation power is "high", and the facility power demand is "high" on that day, and in this case, the tilt angle of the solar panel 4 on that day is determined and adjusted to 30°. This is because setting the tilt angle to 30° minimizes the amount of sunlight irradiated onto the crops 51, slowing down the growth rate. In other words, by slowing down the growth rate, the growth completion date can be made to coincide with or approach the target shipping date when the crops 51 become expensive. Furthermore, by setting the tilt angle to 30°, it is possible to maximize the amount of sunlight irradiated onto the solar panel 4, thereby increasing the amount of power generated by solar power generation 82. In other words, it is possible to reduce consumption of grid power 81 and reduce power costs. Furthermore, since the facility power demand on that day is "high" and the consumption of grid power 81 is likely to exceed the peak value, setting the tilt angle to 30° makes it possible to prevent grid power 81 from exceeding the peak value. In other words, it is possible to achieve a double reduction in power costs. In this way, by determining and adjusting the tilt angle to 30° in pattern a, it is possible to reduce the price of crop 51 and the electricity cost.

[0041] Pattern b is a case where the growth rate is "fast", the photovoltaic power generation power is "high", and the facility power demand is "low" on that day, and in this case, the tilt angle of the solar panel 4 on that day is determined and adjusted to 30°. This is because setting the tilt angle to 30° minimizes the amount of sunlight irradiated onto the crops 51, slowing down the growth rate. In other words, by slowing down the growth rate, the growth completion date can be made to coincide with or approach the target shipping date when the crops 51 become expensive. Furthermore, by setting the tilt angle to 30°, it is possible to maximize the amount of sunlight irradiated onto the solar panel 4, thereby increasing the amount of power generated by solar power generation 82. In other words, it is possible to reduce power costs by suppressing consumption of grid power 81. The facility power demand on that day is "low," and the possibility that the consumption of grid power 81 will exceed the peak value is low. In this way, by determining and adjusting the tilt angle to 30° in pattern b, it is possible to reduce the price of crop 51 and the electricity cost.

[0042] Pattern c is a case where the growth rate is "fast", the photovoltaic power generation power is "low", and the facility power demand is "high" on that day, and in this case, the tilt angle of the solar panel 4 on that day is determined and adjusted to 30°. This is because setting the tilt angle to 30° minimizes the amount of sunlight irradiated onto the crops 51, slowing down the growth rate. In other words, by slowing down the growth rate, the growth completion date can be made to coincide with or approach the target shipping date when the crops 51 become expensive. The facility power demand on that day is "high" and the photovoltaic power generation power 82 is "low." For this reason, on that day, the consumption of grid power 81 may exceed the peak value, but it is not expected that solar power generation will be able to supply enough power to suppress the peak value. However, even in this case, by setting the tilt angle to 30°, it is possible to maximize the amount of sunlight irradiated onto the solar panel 4, and to minimize the consumption of grid power 81 (power costs). In this way, by determining and adjusting the tilt angle to 30° in pattern c, it is possible to reduce the price of crop 51 and the electricity cost.

[0043] Pattern d is when the growth rate is "slow", the solar power generation power is "high", and the facility power demand is "high" on that day, and in this case, the tilt angle of the solar panel 4 on that day is determined and adjusted to an angle within the range of 30° to 120°. There is a trade-off between the amount of electricity generated by solar power generation 82 and the amount of sunlight irradiated on the crops 51; if too much priority is given to increasing the growth rate, there is a risk that the disadvantage in terms of electricity costs will become significantly greater, while on the other hand, if too much priority is given to reducing electricity costs, there is a risk that crop prices will fall significantly. Therefore, for example, the tilt angle can be determined and adjusted to 75°, which is the intermediate value between 30° and 120°. Furthermore, depending on the management policy, if the growth rate and price of the crop 51 are to be balanced, the angle may be determined and adjusted to between 75° and 120° (for example, 97.5°), or if reducing electricity costs is relatively prioritized, the angle may be determined and adjusted to between 30° and 75° (for example, 52.5°). It is also possible to focus on the total cost calculated based on the sales amount of the crop 51 and the electricity cost, and determine and adjust the tilt angle to the angle at which the total cost is minimized. The configuration for determining and adjusting the tilt angle to minimize the overall cost will be described in detail later in "Modification 4."

[0044] Pattern e is a case where the growth rate is "fast", the photovoltaic power generation power is "low", and the facility power demand is "low" on that day, and in this case, the tilt angle of the solar panel 4 on that day is determined and adjusted to 30°. This is because setting the tilt angle to 30° minimizes the amount of sunlight irradiated onto the crops 51, slowing down the growth rate. In other words, by slowing down the growth rate, the growth completion date can be made to coincide with or approach the target shipping date when the crops 51 become expensive. The solar power generation power 82 on that day is "low" and a large power supply cannot be expected, but the facility power demand is "low" and therefore the consumption of grid power 81 is unlikely to exceed the peak value, so the power cost is unlikely to be high. In this way, by determining and adjusting the tilt angle to 30° in pattern e, it is possible to increase the price of crop 51 without any problems with electricity costs.

[0045] Pattern f is a case where the growth rate is "slow", the photovoltaic power generation power is "high", and the facility power demand is "low" on that day, and in this case, the tilt angle of the solar panel 4 on that day is determined and adjusted to 120°. This is because a tilt angle of 120° can maximize the amount of sunlight irradiated onto the crops 51, thereby accelerating the growth rate. In other words, by accelerating growth, the growth completion date can be made to coincide with or approach the target shipping date when the crops 51 become expensive. Since the facility power demand on that day is "low," there is little possibility that the consumption of grid power 81 will exceed the peak value. In other words, there is little possibility that the power cost will be high. In this way, by determining and adjusting the tilt angle to 120° in pattern f, it is possible to increase the price of crop 51 without any problems with electricity costs. As in pattern d, it is also possible to focus on the total cost calculated based on the sales amount of the crops 51 and the electricity cost, and determine and adjust the tilt angle that minimizes the total cost.

[0046] Pattern g is when the growth rate is "slow", the solar power generation power is "low", and the facility power demand is "high" on that day, and in this case, the tilt angle of the solar panel 4 on that day is determined and adjusted to an angle within the range of 30° to 120°. There is a trade-off between the amount of electricity generated by solar power generation 82 and the amount of sunlight irradiated on the crops 51; if too much priority is given to increasing the growth rate, there is a risk that the disadvantage in terms of electricity costs will become significantly greater, while on the other hand, if too much priority is given to reducing electricity costs, there is a risk that crop prices will fall significantly. Therefore, for example, the tilt angle can be determined and adjusted to 75°, which is the intermediate value between 30° and 120°. Furthermore, depending on the management policy, if the growth rate and price of the crop 51 are to be balanced, the angle may be determined and adjusted to between 75° and 120° (for example, 97.5°), or if reducing electricity costs is relatively prioritized, the angle may be determined and adjusted to between 30° and 75° (for example, 52.5°). As with pattern d, it is also possible to focus on the total cost calculated based on the sales amount of the crops 51 and the electricity cost, and determine and adjust the tilt angle that minimizes the total cost.

[0047] Pattern h is a case where the growth rate is "slow", the photovoltaic power generation power is "low", and the facility power demand is "low" on that day, and in this case, the tilt angle of the solar panel 4 on that day is determined and adjusted to 120°. This is because a tilt angle of 120° can maximize the amount of sunlight irradiated onto the crops 51, thereby accelerating the growth rate. In other words, by accelerating growth, the growth completion date can be made to coincide with or approach the target shipping date when the crops 51 become expensive. The solar power generation power 82 on that day is "low" and a large power supply cannot be expected, but the facility power demand is "low" and therefore the consumption of grid power 81 is unlikely to exceed the peak value, so the power cost is unlikely to be high. In this way, by determining and adjusting the tilt angle to 120° in pattern h, it is possible to increase the price of crop 51 without any problems with electricity costs.

[0048] In this way, the determination means 180 determines to prioritize one of the supply of solar-generated electricity 82 to the facility 7 and the growth rate of the crops 51, based on the forecast information on the electricity generated by solar power, the forecast information on the electricity consumed at the facility 7, and information on the crops 51. If the judgment means 180 determines that the supply of solar power generation electricity 82 is to be prioritized, the inclination angle determination means 160 determines the inclination angle to be an angle that makes it easy for sunlight to irradiate the solar panel 4 (30° or an angle close to 30°), and if the judgment means 180 determines that the growth rate of the crop 51 is to be prioritized, the inclination angle determination means 160 determines the inclination angle to be an angle that makes it difficult for sunlight to irradiate the solar panel 4 (120° or an angle close to 120°).

[0049] (Panel control method) The processing procedure of the panel control method will be described with reference to FIGS. FIG. 15 is a main flowchart showing the processing procedure in the panel control method of the present invention.

[0050] As shown in Figure 15, the panel control method performs the following processes: obtain forecast information for solar power generation power 82 (S101), obtain forecast information for facility demand power (power consumed by facility 7) (S102), and obtain crop information (S103). Note that S101 to S103 are not limited to the above order, and may be in any order.

[0051] FIG. 16 is a sub-flowchart showing the procedure for acquiring predicted information on the photovoltaic power generation power 82. As shown in the figure, in order to obtain forecast information for the photovoltaic power generation power 82, first, the correlation between past dates, weather, and the photovoltaic power generation power 82 is learned (S201). Specifically, a combination of past dates, solar power generation power 82 (actual results), and weather (actual results) (Figures 7(a) and (b)) is used as a dataset, and machine learning is performed by preparing multiple sets of such datasets (Figure 6). As a result of the learning, a photovoltaic power generation prediction model capable of outputting a predicted amount of photovoltaic power generation 82 in the future is generated (S202). Next, predetermined information (each date in a specific future period) is input to the photovoltaic power generation power prediction model, so that predicted information of photovoltaic power generation power 82 in the specific future period is output for each date (S203). As a result, the photovoltaic power generation information acquiring means 110 acquires forecast information of the photovoltaic power generation power 82 for a specific future period (FIG. 7(c)).

[0052] FIG. 17 is a sub-flowchart showing the procedure for acquiring predicted information on facility power demand. As shown in the figure, in order to obtain predicted information on facility power demand, first, correlations between past dates, temperature, humidity, days of the week, and facility power demand are learned (S301). Specifically, a combination of past dates, facility demand power (actual), temperature and room temperature (actual), and day of the week (Fig. 9(a), Fig. 7(b)) is used as a dataset, and machine learning is performed using a large number of such datasets (Fig. 8). As a result of the learning, a facility power demand prediction model capable of outputting a predicted amount of facility power demand in the future is generated (S302). Next, predetermined information (each date in a specific future period) is input to the facility power demand prediction model, thereby outputting prediction information of facility power demand in the specific future period (S303). As a result, the facility power demand information acquisition means 120 acquires forecast information of facility power demand for a specific future period (FIG. 9(b)).

[0053] FIG. 18 is a sub-flowchart showing the procedure for acquiring crop information. As shown in the figure, in order to obtain crop information, first, the growth rate of the crop is identified (S401). Specifically, the growth rate specification means 131 specifies the growth rate of the crop 51. More specifically, the drone 6 flies over the farmland 5 and the crops 51, and the image of the crops 51 captured by the camera is sent to the server 1. The server 1 extracts feature points from the received image of the crops 51 using known image recognition technology, determines the growth rate based on the size, shape, color, etc. of the crops 51 identified from the feature points, and stores the growth rate together with the date (Figure 11(a)).

[0054] Next, the shipping period is identified (S402). Specifically, the shipping period specifying means 132 specifies the shipping period of the crop 51 based on the growth rate of the crop 51. More specifically, the standard shipping date of the crop 51 is determined based on the growth rate of the crop 51, and the period obtained by adding ±β days to the standard shipping date is determined as the shipping period (FIG. 11(b)). In addition, standard shipping dates can also be predicted using machine learning. In this case, a model can be generated that learns the correlation between growth rate and date, and outputs a date when a future growth rate is input. Then, by inputting a growth rate of 100% into the model, the model can output a predicted standard shipping date.

[0055] Next, crop price information is acquired (S403). Specifically, the crop price information acquisition means 133 acquires (FIG. 12(b)) forecast information on the price of the crop 51 during the shipping period based on the past price of the crop 51 (FIG. 12(a)). More specifically, a combination of past dates, crop 51 prices (actual), and temperature and humidity (actual) is used as a dataset, and by preparing a large number of such datasets and performing machine learning, a program (crop price prediction model) is generated that can output predicted information on crop prices during the shipping period. By inputting a future date into this crop price prediction model, the crop price (prediction) for that date can be output.

[0056] Next, the target shipping date is determined (S404). Specifically, the target shipping date determination means 134 determines the target shipping date based on predicted information on the price of the crop 51 during the shipping period. More specifically, the target shipping date is determined to be the day during the shipping period when the price of the crop 51 is high (FIGS. 12(b) and 13).

[0057] Next, the growth rate is determined (S405). Specifically, the growth rate determining means 135 determines the growth rate of the crop 51 relative to the target shipping date. For example, if the growth rate of a crop 51 on a certain day is x%, and the day on which the growth rate of the crop 51 is predicted to reach 100% is earlier than the target shipping date, the growth rate is determined to be "fast." On the other hand, if the day on which the growth rate of the crop 51 is predicted to reach 100% is later than the target shipping date, the growth rate is determined to be "slow."

[0058] Returning to the main flowchart, the tilt angle of the solar panel 4 is determined (S104). Specifically, the tilt angle determination means 160 determines the tilt angle based on predicted information on the amount of electricity generated by solar power, predicted information on the amount of electricity consumed in the facility 7, and information on the crops 51 (growth rate of the crops 51) (Figure 14). More specifically, if the determination means 180 determines that the supply of solar-generated power 82 has a higher priority, it determines the tilt angle to be an angle that makes it easier for sunlight to irradiate the solar panel 4, and if it determines that the growth rate of the crop 51 has a higher priority, it determines the tilt angle to be an angle that makes it harder for sunlight to irradiate the solar panel 4 (Figure 14). Furthermore, as shown in Variant Example 4 described below, the cost of electricity at facility 7 and the sales amount of crop 51 can be calculated based on forecast information on the amount of electricity generated by solar power, forecast information on the amount of electricity consumed at facility 7, and information on crop 51, and the tilt angle can be determined based on the calculation results.

[0059] Then, the solar panel is moved to the determined tilt angle (S105). Specifically, the control means 140 issues a command to the control processing unit 420 of the solar power generation system 4S, and the control processing unit 420 operates the tilt angle movable unit 410 of each solar panel 4, thereby changing the tilt angle to the determined angle.

[0060] (Variation 1) The agricultural land 5 can be photographed with a drone 6 (camera unit) and the amount of moisture contained in the agricultural land 5 (soil) can be determined based on the image, or the amount of moisture contained in the agricultural land 5 can be determined by installing a soil moisture sensor in the agricultural land 5 in advance. The chart in FIG. 11(a) shows the detection results of the amount of moisture contained in the farmland 5. For example, by learning the correlation between past dates, the growth rate (actual) of the crop 51, and the moisture content (actual) of the farmland 5 in the server 1, it is possible to derive the growth rate (prediction) of the crop 51 for future dates, taking into account the moisture content of the farmland 5. In addition to adjusting the tilt angle, the growth rate of the crops 51 can be increased or decreased by controlling the watering of the crops 51 by the drone 6. Furthermore, the growth rate of the crops 51 can be accelerated or slowed down by controlling the spraying of fertilizer by the drones 6.

[0061] (Variation 2) By storing and taking into account the actual tilt angle, it is also possible to derive forecast information for the amount of power generated by solar power generation. In this case, the solar power generation information acquisition means 110 acquires information indicating the power that will be generated by the solar panel 4 in the future and the tilt angle of the solar panel when that power will be generated, based on information indicating the power that was generated by the solar panel 4 in the past and the tilt angle of the solar panel 4 when that power was generated. This allows, for example, when generating a solar power generation power prediction model, to learn the correlation between past dates, weather (actual results), solar power generation power 82 (actual results), and the tilt angle of the solar panel 4 when that power was generated, and to output prediction information on how much solar power will be generated in the future (power generation amount) and at what tilt angle. This makes it possible to predict, for example, the amount of power generated by solar power generation and the corresponding tilt angle for each day during a specific period.

[0062] (Variation 3) In addition to the second modification, it is also possible to store and take into account the actual tilt angle data and derive forecast information for crop prices. In this case, the crop price information acquisition means 133 can acquire predicted information on the price of the crop 51 during the shipping period based on the past price of the crop 51 and information indicating the tilt angle of the solar panel 4. For example, by learning the correlation between the price of crops during the shipping period and the tilt angle of the solar panel 4 in addition to past dates, crop prices (actual), temperature and humidity (actual), a model (crop price prediction model) can be generated that can output predictive information on the price at which crops can be sold in the future at a certain tilt angle. This allows, for example, the price of the crop 51 and the corresponding tilt angle to be predicted on a daily basis for a specific period.

[0063] (Variation 4) By providing the configuration of the third modification, it is also possible to provide a configuration for determining and adjusting the tilt angle that minimizes the overall cost calculated based on the crop price and the electricity cost. That is, the calculation means 170 of the server 1 calculates the cost of electricity at the facility 7 and the sales amount of the crop 51 based on the predicted information on the electricity generated by solar power, the predicted information on the electricity consumed at the facility 7, information on the crop 51 (price information), and the predicted information on the tilt angle, and the tilt angle determination means 160 determines the tilt angle based on the calculation results of the calculation means 170. An example will be described below.

[0064] The "cost A of electricity in facility 7" can be calculated using the following formula 1, which is based on a known formula for calculating electricity charges. A = Basic charge (basic charge unit price × contracted power) + power factor discount / surcharge + energy charge (energy usage amount (power amount of facility demand (forecast) - solar power generation amount (forecast)) × energy charge unit price) + fuel cost adjustment amount (energy usage amount (power amount of facility demand (forecast) - solar power generation amount (forecast)) × fuel cost adjustment unit price) + renewable energy power generation promotion surcharge (energy usage amount (power amount of facility demand (forecast) - solar power generation amount (forecast)) × renewable energy power generation promotion surcharge unit price) Formula 1 Here, since the amount of power generated by solar power generation is proportional to the amount of sunlight irradiating the solar panel 4, it is maximum when the tilt angle α = 30° and minimum when the tilt angle α = 120°, so the amount of power generated M can be calculated using the following equation 2. M = -αX1 + Y1 (*X1 and Y1 are coefficients) Formula 2 Therefore, Equation 1 can be expressed as Equation 3 below. A = Basic charge (basic charge unit price × contracted power) + power factor discount / surcharge + energy charge (energy usage amount (energy amount of facility demand power (forecast) - (-αX1 + Y1)) × energy charge unit price) + fuel cost adjustment amount (energy usage amount (energy amount of facility demand power (forecast) - (-αX1 + Y1)) × fuel cost adjustment unit price) + renewable energy power generation promotion surcharge (energy usage amount (energy amount of facility demand power (forecast) - (-αX1 + Y1)) × renewable energy power generation promotion surcharge unit price) Formula 3

[0065] "Crop sales amount B" can be calculated using the following formula 4. B = price of crop 51 × weight of crop 51 per unit area × area... Equation 4 Here, it is assumed that the price of the crop 51 increases as the amount of sunlight irradiated on the crop 51 increases, and decreases as the amount of sunlight irradiated on the crop 51 decreases. In this case, the price of crop 51 increases as the tilt angle α of solar panel 4 approaches 120°, and decreases as the tilt angle α approaches 30°. Therefore, the price N of crop 51 can be calculated using the following formula 5. N = αX2 + Y2 (*X2 and Y2 are coefficients) Equation 5 Therefore, Equation 4 can be expressed as Equation 6 below. B = (αX2 + Y2) × weight of crop per unit area × area Equation 6 Therefore, the tilt angle α that minimizes the result of subtracting "B" calculated using Equation 6 from "A" calculated using Equation 3 is identified within the range of 30° to 120°, and the identified tilt angle is determined and adjusted as the "tilt angle that minimizes the overall cost." Incidentally, the "contracted power" (see Equation 1, etc.) is determined by "the maximum power demand of the month or the maximum power demand of the previous 11 months, whichever is greater." Therefore, by suppressing the peak of the facility's power demand (consumption), it is possible to suppress the increase in "contract power." Therefore, when the amount of facility power demand is expected to reach a peak value, the tilt angle α of the solar panel 4 can be controlled so that the amount of power generated by solar power generation is increased as a top priority. That is, in this case, the tilt angle α is adjusted to an angle perpendicular to the sunlight. This may temporarily hinder crop growth, but is expected to reduce overall costs in the long term.

[0066] (Variation 5) The role of Drone 6 is not limited to watering and fertilizing, but can also include inspection and pesticide spraying. For example, a drone 6 is used to take surveillance footage as part of an inspection of farmland 5, and the surveillance footage is sent to server 1. The server 1 can perform image recognition and analysis of the received surveillance video to detect diseases in the crops 51 and analyze the type and severity of the disease. When a disease is detected, the server 1 selects a pesticide according to the type and severity of the disease and causes the drone 6 to spray the selected pesticide.

[0067] (Variation 6) The tilt angle α of the solar panel 4 can be adjusted to an optimum angle "according to the season" and "according to the type of crop." For example, there are crops that can only be harvested in a certain season, such as crop A, which is expected to be harvested in spring (March to May), and crop B, which is expected to be harvested in summer (June to September), and these crops are traded at high prices during that season. For example, for crop A, if predicted values ​​for facility electricity consumption, solar power generation, and crop price for the target season, spring (March to May), are obtained in advance, and the tilt angle α of solar panel 4 is set and controlled so that the growth rate of crop A is 100% on the shipping date when crop A is expensive in that season, crop A can be harvested and shipped in an optimal condition. The server 1 is configured such that the tilt angle determination means 160 determines the tilt angle α of the solar panel 4 for each type of crop based on predicted information on the amount of electricity generated by solar power, predicted information on the amount of electricity consumed in the facility, and information on the crop (including information that can identify the type and season of the crop). In detail, the growth rate of crop A is identified (growth rate identification means 131), prediction information for the price of crop A in the target season (spring) is obtained based on the past prices of crop A (crop price information acquisition means 133), a target shipping date is determined based on the prediction information for the price of crop A (target shipping date determination means 134), and the growth speed of crop A is determined (growth speed determination means 135). Then, the inclination angle determination means 160 determines the inclination angle based on predicted information on the amount of electricity generated by solar power in the target season (spring), predicted information on the amount of electricity consumed by the facility in the target season (spring), and the growth rate of crop A. Similar control can be performed for crop B. In this way, according to the present invention, the tilt angle α of the solar panel 4 can be optimally adjusted depending on the season and the type of crop.

[0068] As described above, the panel control system S of the present invention includes a solar power generation information acquisition means 110 that acquires predicted information on the power generated by the solar panel 4, a facility demand power information acquisition means 120 that acquires predicted information on the power consumed in the facility 7, a crop information acquisition means 130 that acquires information on the crops 51 grown in the farmland 5, an inclination angle determination means 160 that determines the angle of inclination α based on the predicted information on the power generated by the solar panel 4, the predicted information on the power consumed in the facility 7, and the information on the crops 51, and a control means 140 that adjusts the inclination angle α to the determined angle. This makes it possible to minimize the electricity cost and maximize the selling price of the crop 51.

[0069] Although the preferred embodiments of the present invention have been described above, it goes without saying that the present invention is not limited to the above-described embodiments, and various modifications can be made within the scope of the present invention. For example, the configuration of the panel control system S is not limited to the above-described embodiment, and part or all of the configuration of one device may be provided in another device. Furthermore, the processing procedures in the panel control method and panel control program are not limited to the above procedures, and some of the procedures may be changed. [Explanation of symbols]

[0070] S: panel control system, 1: server, 110: photovoltaic power generation information acquisition means, 120: facility demand power information acquisition means, 130: crop information acquisition means, 131: growth rate determination means, 132: shipping possible period determination means, 133: crop price information acquisition means, 134: shipping target date determination means, 135: growth rate determination means, 140: control means, 150 database, 151: photovoltaic power generation power DB, 152: weather information DB, 153: facility demand power DB, 154: crop price DB, 160: tilt angle degree determination means, 170: calculation means, 180: determination means, 2: weather information providing device, 4: solar panel, 4S: solar power generation system, 410: tilt angle moving part, 411: rotating shaft, 412: worm, 413: worm wheel, 420: control processing unit, 430: power generation amount management unit, 5: farmland, 51: crops, 6: drone, 7: facility, 7S: facility management system, 710: electrical equipment, 711: power consumption management unit, 81: grid power, 82: solar power generation power, 9: internet, α: tilt angle

Claims

1. A panel control system equipped with solar panels that are installed above farmland and have adjustable tilt angles, a photovoltaic power generation information acquisition means for acquiring prediction information of power to be generated by the photovoltaic panel in the future based on information indicating power generated by the photovoltaic panel in the past; a facility demand power information acquisition means for acquiring prediction information of power to be consumed in the facility in the future based on information indicating power consumed in the facility in the past; a crop information acquisition means for acquiring information about crops grown in the farmland; an inclination angle determination means for determining the inclination angle based on predicted information on the amount of power generated by the solar power generation system, predicted information on the amount of power consumed in the facility, and information on the crops; a control means for adjusting the tilt angle to the determined angle; The facility is: The facility is located adjacent to farmland and is capable of supplying electricity generated by the solar panels. A panel control system comprising:

2. The information about the crop includes information that can identify the type and season of the crop, The tilt angle determining means The tilt angle is determined for each season and type of crop based on forecast information on the power generated by the photovoltaic power generation system in a target season, forecast information on the power consumed by the facility in the season, and information on the crops in the season.

2. The panel control system according to claim 1.

3. The means of obtaining crop information are: a growth rate determination means for determining a growth rate of the crop; a shipping period specifying means for specifying a shipping period of the crop based on the growth rate; a crop price information acquisition means for acquiring predicted information on the price of the crop during the shipping period based on past prices of the crop; a target shipping date determination means for determining a target shipping date based on predicted information on the price of the crop during the shipping period; a growth rate determination means for determining a growth rate of the crop relative to the target shipping date, The tilt angle determining means The tilt angle is determined based on the predicted information on the amount of power generated by the solar panels, the predicted information on the amount of power consumed in the facility, and the growth rate of the crops.

3. The panel control system according to claim 1 or 2.

4. a determination means for determining to prioritize one of the supply of the photovoltaic-generated power to the facility and the growth rate of the crops, based on forecast information on the photovoltaic-generated power, forecast information on the power consumed in the facility, and information on the crops; The tilt angle determining means When the determination means determines that the supply of photovoltaic power is to be prioritized, the tilt angle is determined to be a first angle, and when the determination means determines that the crop growth rate is to be prioritized, the tilt angle is determined to be a second angle; The first angle is an angle at which the amount of sunlight irradiated onto the solar panel is greater than the second angle, The second angle is This is an angle at which the amount of sunlight irradiated onto the solar panel is less than the first angle.

2. The panel control system according to claim 1.

5. The facility can be supplied with electricity based on a power grid operated by a power company, a calculation means for calculating the cost of electricity at the facility and the sales amount of the crops based on the predicted information of the solar-generated electricity, the predicted information of electricity consumed at the facility, and information about the crops; The tilt angle determining means The tilt angle is determined based on the calculation result of the calculation means.

2. The panel control system according to claim 1.

6. The photovoltaic power generation information acquisition means Based on information indicating the power generated by the solar panel in the past and the tilt angle of the solar panel when the power was generated, information indicating the power to be generated by the solar panel in the future and the tilt angle of the solar panel when the power will be generated is obtained.

6. The panel control system according to claim 5.

7. A control method for varying the tilt angle of solar panels installed above farmland, comprising: acquiring prediction information of power to be generated by the solar panel in the future based on information indicating power generated by the solar panel in the past; acquiring prediction information of future power consumption in the facility based on information indicating power consumption in the facility in the past; obtaining information about crops grown on said farmland; determining the tilt angle based on predicted information on the amount of power generated by the solar power plant, predicted information on the amount of power consumed in the facility, and information on the crops; adjusting the tilt angle to the determined angle; The facility is: The facility is located adjacent to farmland and is capable of supplying electricity generated by the solar panels. A panel control method comprising:

8. A computer that variably controls the tilt angle of solar panels installed above the farmland, a photovoltaic power generation information acquisition means for acquiring prediction information of power to be generated by the photovoltaic panel in the future based on information indicating power generated by the photovoltaic panel in the past; a facility demand power information acquisition means for acquiring prediction information of power to be consumed in the facility in the future based on information indicating power consumed in the facility in the past; a crop information acquisition means for acquiring information about crops grown in the farmland; an inclination angle determination means for determining the inclination angle based on predicted information on the amount of power generated by the solar power generation system, predicted information on the amount of power consumed in the facility, and information on the crops; and functioning as a control means for adjusting the tilt angle to the determined angle; The facility is: The facility is located adjacent to farmland and is capable of supplying electricity generated by the solar panels. A panel control program comprising:

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