Electric fishing boat charging system and electric fishing boat charging program

Abstract

To enable the batteries of electric fishing boats to be charged at the appropriate time. [Solution] The system comprises a power generation facility 21 that generates electricity from natural energy including wind power, installed on a sea station 2 located on the sea; a system battery 22 that stores the electricity generated by the power generation facility 21; a charger 23 that charges a fishing vessel battery SB mounted on an electric fishing vessel S with electricity from at least one of the power generation facility 21 and the system battery 22; a drone 3 that photographs the situation of birds B flying above the sea surface; and a management computer 4 that predicts when and where schools of fish F will appear based on the images taken by the drone 3, and plans to charge the fishing vessel battery SB so that fishing can be carried out when the predicted schools of fish F appear.

Description

Technical Field

[0001] The present invention relates to an electric fishing boat charging system and an electric fishing boat charging program for charging electric fishing boats at sea or on the ocean.

Background Art

[0002] In conventional fishing activities, many fishing boats use fossil fuels such as diesel fuel. Therefore, not only is the fuel cost high, but the CO2 emissions are also large, imposing a significant impact on the environment and burden, and sustainability has been an issue. Also, even if an electric fishing boat propelled by electricity is used in the future, it will be necessary to return to land to charge the battery, consuming wasted travel time and energy.

[0003] For this reason, a system for charging a battery at sea is known (see, for example, Patent Document 1). This system includes a removable battery mounted on an operating ship, a mobile battery used as a power source for the operating ship, a mobile charging ship that moves while carrying the mobile battery, and a charging station that floats in the ocean together with the mobile charging ship and charges the mobile battery loaded on the mobile charging ship using the generated electricity.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] By the way, when fishing, it is desirable to predict when and where fish schools will appear and depart the fishing boat according to the prediction. This is the same when fishing using an electric fishing boat, and it is desirable to properly charge the battery of the electric fishing boat (for example, to full charge) before departing for fishing.

[0006] However, the system described in Patent Document 1 can only charge the mobile battery of a mobile charging vessel at a charging station floating in the ocean, and cannot charge the storage battery of an electric fishing vessel at the appropriate time.

[0007] Therefore, the present invention aims to provide an electric fishing boat charging system and an electric fishing boat charging program that enable the charging of the electric fishing boat's battery at the appropriate timing. [Means for solving the problem]

[0008] To solve the above problems, the invention of claim 1 is an electric fishing boat charging system characterized by comprising: a power generation facility installed at a sea station located at sea that generates electricity using natural energy including wind power; a system battery that stores the electricity generated by the power generation facility; a charger that charges a fishing boat battery mounted on an electric fishing boat using electricity from at least one of the power generation facility and the system battery; a camera that photographs the situation of birds flying in the sky above the sea surface; and a charging planning means that predicts when and where schools of fish will appear based on images taken by the camera, and plans to charge the fishing boat battery so that fishing can be carried out when the predicted schools of fish appear.

[0009] The invention of claim 2 is characterized in that, in the electric fishing boat charging system described in claim 1, it comprises an environmental information acquisition means for acquiring environmental information including seawater temperature and ocean currents, and the charging planning means predicts when and where schools of fish will appear based on the environmental information.

[0010] The invention of claim 3 is characterized in that, in the electric fishing boat charging system described in claim 1, the system comprises past information storage means for storing past fish school information, including the time and place when fish schools appeared in the past and the status of birds flying overhead, and the charging planning means predicts when and where fish schools will appear based on the past fish school information.

[0011] The invention of claim 4 is characterized in that, in the electric fishing boat charging system described in claim 1, the charging planning means uses a fish school prediction learning model that has been machine-learned based on past performance data, such that when an image captured by the camera is input, it outputs when and where a school of fish will appear.

[0012] The invention of claim 5 is characterized in that, in the electric fishing boat charging system described in claim 1, the charging planning means plans the charging of the fishing boat battery based on the remaining capacity of the fishing boat battery so that fishing can be carried out when the predicted school of fish appears.

[0013] The invention of claim 6 is characterized in that, in the electric fishing boat charging system described in claim 1, the charging planning means predicts the amount of power generated by the power generation equipment based on weather information, and plans to charge the fishing boat battery based on the predicted amount of power generated and the remaining capacity of the system battery so that fishing can be carried out when the predicted school of fish appears.

[0014] The invention of claim 7 is an electric fishing boat charging program for formulating a charging plan for the fishing boat battery, wherein a station installed at sea is provided with a power generation facility that generates electricity using natural energy including wind power, a system battery that stores the electricity generated by the power generation facility, and a charger that charges a fishing boat battery mounted on an electric fishing boat using electricity from at least one of the power generation facility and the system battery, and the computer functions as a charging planning means that predicts when and where schools of fish will appear based on images taken of birds flying in the sky above the sea surface, and plans to charge the fishing boat battery so that fishing can be carried out when the predicted schools of fish appear.

[0015] The invention of claim 8 is characterized in that, in the electric fishing boat charging program described in claim 7, the charging planning means predicts when and where schools of fish will appear based on environmental information including seawater temperature and ocean currents.

[0016] The invention of claim 9 is characterized in that, in the electric fishing boat charging program described in claim 7, the computer functions as a past information storage means for storing past fish school information, including the time and place when fish schools appeared in the past and the status of birds flying overhead, and the charging planning means predicts when and where fish schools will appear based on the past fish school information.

[0017] The invention of claim 10 is characterized in that, in the electric fishing boat charging program described in claim 7, the charging planning means uses a fish school prediction learning model that has been machine-learned based on past performance data, such that when an image of birds flying above the sea surface is input, it outputs when and where schools of fish will appear.

[0018] The invention of claim 11 is characterized in that, in the electric fishing boat charging program described in claim 7, the charging planning means plans to charge the fishing boat battery based on the remaining capacity of the fishing boat battery so that fishing can be carried out when the predicted school of fish appears.

[0019] The invention of claim 12 is characterized in that, in the electric fishing boat charging program described in claim 7, the charging planning means predicts the amount of power generated by the power generation equipment based on weather information, and plans to charge the fishing boat battery based on the predicted amount of power generated and the remaining capacity of the system battery so that fishing can be carried out when the predicted school of fish appears. [Effects of the Invention]

[0020] According to the inventions described in claims 1 and 7, based on images taken of birds flying above the sea surface, it is possible to predict when and where schools of fish will appear, and the fishing vessel's battery is charged so that fishing can be carried out when the schools of fish are predicted to appear. In other words, the electric fishing vessel's battery is charged before the fishing vessel departs after the schools of fish have appeared. As a result, it is possible to prevent situations where the battery is not charged in time for fishing against schools of fish, or where the fishing vessel's battery is unnecessarily charged when the vessel is not departing to fish, and to charge the electric fishing vessel's battery at the appropriate time.

[0021] In addition, since the fishing boat battery of an electric fishing boat can be charged at an offshore station installed at sea, there is no need to return to land for charging, and it is possible to reduce wasted travel time and energy consumption. Furthermore, since the fishing boat battery of an electric fishing boat is charged with electric power generated from natural energy including wind power, it is possible to reduce fuel costs and CO2 emissions and ensure sustainability.

[0022] According to the inventions described in claim 2 and claim 8, based on factors such as the water temperature and tidal current of the sea, it is possible to predict when and where fish schools will appear, enabling appropriate prediction. As a result, it becomes possible to charge the fishing boat battery of an electric fishing boat at an appropriate timing.

[0023] According to the inventions described in claim 3 and claim 9, based on the time and location when fish schools appeared in the past, the situation of birds flying in the sky, etc., it is possible to predict when and where fish schools will appear, enabling appropriate prediction. As a result, it becomes possible to charge the fishing boat battery of an electric fishing boat at an appropriate timing.

[0024] According to the inventions described in claim 4 and claim 10, by using a learned learning model for fish school prediction that has been machine-learned, it is possible to output when and where fish schools will appear, enabling appropriate prediction. As a result, it becomes possible to charge the fishing boat battery of an electric fishing boat at an appropriate timing.

[0025] According to the inventions described in claim 5 and claim 11, based on the remaining capacity of the fishing boat battery, that is, based on how much time and power are required for charging, the fishing boat battery is charged so that fishing can be carried out when fish schools appear, enabling charging at an appropriate timing.

[0026] According to the inventions described in claim 6 and claim 12, based on the predicted power generation amount and the remaining capacity of the system battery, that is, based on when and how much the fishing boat battery can be charged, the fishing boat battery is charged so that fishing can be carried out when fish schools appear, enabling charging at an appropriate timing. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] [Figure 1] This is a schematic diagram showing an electric fishing boat charging system according to an embodiment of the present invention. [Figure 2] Figure 1 is a schematic block diagram of the electric fishing boat charging system. [Figure 3] Figure 1 is a schematic block diagram showing the management computer for the electric fishing boat charging system. [Figure 4] Figure 3 is a functional block diagram showing the schematic configuration of the learning model for fish school prediction in the management computer. [Modes for carrying out the invention]

[0028] The present invention will be described below based on the illustrated embodiments.

[0029] Figures 1 to 4 illustrate this embodiment, with Figure 1 being a schematic diagram showing the electric fishing vessel charging system 1 according to this embodiment. This electric fishing vessel charging system 1 is a system for charging an electric fishing vessel S at sea, and the electric fishing vessel S is a fishing vessel propelled by the power of an onboard fishing vessel battery SB.

[0030] The electric fishing boat charging system 1 mainly comprises a power generation facility 21, a system battery 22, a charger 23, an environmental sensor (means for acquiring environmental information) 24, a drone (unmanned aerial vehicle) 3 that flies over the sea surface, and a management computer (means for planning charging) 4, etc., all installed at an offshore station 2 located at sea.

[0031] The offshore station 2 can function as a power generation and charging station (ground, foundation) installed in the sea W, and can have any structure or foundation, such as a monopile foundation, jacket foundation, or floating foundation. However, in this embodiment, a floating foundation is used because it allows for relatively free selection of the installation location and can be installed without overlapping with the main shipping lanes of typical fishing vessels. Furthermore, the structure of the float in this embodiment is a semi-submersible type or a barge type, taking into consideration stability and installation flexibility.

[0032] The power generation equipment 21 is a facility that generates electricity using natural energy, including wind power, and in this embodiment, wind power generation equipment and solar power generation equipment are provided. The power generation capacity and number of units installed in this power generation equipment 21 are set based on the expected power demand (such as the amount of charge required for the fishing boat's battery SB). In addition, the power generation status and amount generated by the power generation equipment 21 are measured and monitored and transmitted to the management computer 4 in real time.

[0033] The system battery 22 is a battery that stores electricity generated by the power generation equipment 21, and the stored electricity can be supplied to each charger 23 and lighting fixtures 51, which will be described later. The storage capacity and number of such system batteries 22 are set based on the expected power demand (such as the amount of charge required for the fishing boat battery SB). In addition, a capacity meter is provided to measure the remaining capacity of the system battery 22 based on the voltage and ambient temperature, and the measured remaining capacity is transmitted to the management computer 4 in real time.

[0034] The charger 23 is a charging device that charges the fishing vessel battery SB of the electric fishing vessel S using power from at least one of the power generation equipment 21 and the system battery 22. Multiple chargers 23 are provided so that multiple fishing vessel batteries SB can be charged simultaneously. When charging the fishing vessel batteries SB, the electric fishing vessel S is docked near the charger 23, and the charging cable extending from the charger 23 is connected to the terminal on the electric fishing vessel S to receive power from the charger 23. The charger 23 is also equipped with an input unit for inputting the rated capacity of the fishing vessel battery SB and a capacity meter for measuring the remaining capacity of the fishing vessel battery SB.

[0035] Here, an example of these connections and the flow of power and current will be explained. As shown in Figure 2, the DC power generated by the power generation equipment 21 is converted into DC power and AC power of a predetermined voltage by the first hybrid PCS (power conditioner) 25. The DC power converted by the first hybrid PCS 25 is then converted to a predetermined voltage by the second hybrid PCS 26 and supplied to the system battery 22, and at the same time, the charger 23 converts it to a voltage and current suitable for charging the fishing boat battery SB (electric fishing boat S in the figure) and supplies it to the fishing boat battery SB. Meanwhile, the AC power converted by the first hybrid PCS 25 is supplied to power receiving equipment such as lighting fixtures 51 via the distribution board 50.

[0036] Furthermore, the power discharged from the system battery 22 is supplied as DC to the fishing vessel battery SB via the second hybrid PCS 26 and charger 23, and is also supplied as AC to power receiving equipment such as lighting fixtures 51 via the distribution board 50. Here, the power receiving equipment is located within the living quarters 5 where the crew of the electric fishing vessel S can live, and includes lighting fixtures 51, toilets, a kitchen, and a management computer 4, among other things necessary for living.

[0037] This power flow is controlled by the system battery 22, charger 23, hybrid PCS 25, 26, etc., and power can be supplied from either the power generation equipment 21 or the system battery 22, or from both, based on the power generation status and amount of power generated by the power generation equipment 21, the remaining capacity of the system battery 22, and the required charge amount of the fishing boat battery SB. Furthermore, the electric fishing boat charging system 1 is connected to the power grid, and power can be supplied from the power grid as needed.

[0038] The environmental sensor 24 is a group of sensors that acquire environmental information that affects the behavior and appearance of fish schools F, such as seawater temperature, currents, wind speed, and tides. It acquires environmental information of the waters surrounding the offshore station 2. It also transmits the acquired environmental information to the management computer 4 in real time.

[0039] Drone 3 is an aircraft that flies over the sea surface to photograph the situation and behavior of bird B flying over the sea surface. Specifically, it is equipped with a high-resolution camera (photography device) 31 and an infrared camera (photography device) 32, and flies around and in the distance from the offshore station 2 to photograph and monitor the behavior of bird B (such as flocking or diving) 24 hours a day. It is also designed to transmit the captured images to the management computer 4 in real time.

[0040] Such a drone 3 flies along a pre-set and memorized flight path, and the flight path is configured to photograph and monitor the entire expected fishing area. In this embodiment, the high-resolution camera 31 and infrared camera 32 are mounted on the drone 3, but they may also be placed on top of poles or wind power generation equipment installed on the offshore station 2.

[0041] The management computer 4 is a computer that plans the charging of the fishing vessel's battery SB, and as shown in Figure 3, it mainly comprises an input unit 41, a display unit 42, a communication unit 43, a storage unit 44, a charging task (charging planning means) 45, a learning task 46, and a central processing unit 47 that controls these.

[0042] The input unit 41 is an interface for inputting various information and commands, specifically for inputting the start command for the charging task 45 and inputting charging commands to the charger 23. The display unit 42 is a display that shows various data and information, specifically for displaying the remaining capacity of the system battery 22, the charging status by the charger 23, and the charging plan by the charging task 45. The communication unit 43 is an interface for communicating with the outside world, specifically for sending control commands to the system battery 22 and the charger 23, and receiving images from the drone 3. Furthermore, it can access a weather server that provides weather information, enabling it to acquire weather information in real time.

[0043] The memory unit 44 mainly comprises a historical information database (historical information storage means) 441, a learning model for fish school prediction 442, and a historical data database for fish school prediction 443. Here, the historical information database 441 will be described, and the learning model for fish school prediction 442 and the historical data database for fish school prediction 443 will be described later.

[0044] The historical information database 441 is a database that stores past fish school information, such as the time (season, date and time, etc.) and location when fish schools F appeared in the past. In other words, it stores past fish school information such as when, where, and how large fish schools F (including fish species) appeared in the past, the water temperature, currents, wind speed, and tides of the sea W at that time, and images showing the behavior of birds B flying overhead (whether they were in flocks or diving, etc.). Here, when fish school F appeared, it includes not only the date and time, but also the season, whether it was morning or evening, and whether it was just after sunrise or just before sunset. Where fish school F appeared, it includes not only latitude and longitude, but also the sea area, water depth, and geographical features.

[0045] The charging task 45 is a task program that plans the charging of the fishing vessel battery SB. In this embodiment, it is always activated, but it may also be activated when an activation command is input from the input unit 41, or when the fishing vessel battery SB is connected to the charger 23. First, it predicts when and where the school of fish F will appear based on images taken by the high-resolution camera 31 and the infrared camera 32.

[0046] In other words, if bird B is frequently diving into the water, there is a high probability that a school of fish F is present there; if bird B is circling in a certain location, there is a high probability that a school of fish F is below it; and if many birds B are gathered in one place, that location is likely to be a good fishing ground. Therefore, by analyzing images of the behavior and actions of flying birds B, we can predict when and where schools of fish F will appear. Specifically, we simply accumulate the results of image analysis (when and where schools of fish F appear), statistically predict when and where schools of fish F will appear, and predict when and where schools of fish F will appear in the future. Alternatively, if schools of fish F are currently predicted to be present, we can use the current time and location as the prediction result. Or, we can predict when and where schools of fish F will appear in the future based on the behavior of birds B before they dive into the water.

[0047] Furthermore, in this embodiment, the appearance of fish schools F is predicted based on environmental information. That is, the appearance of fish schools F is predicted not only by images of the birds B, but also by considering factors such as sea temperature, currents, wind speed, and tides. Specifically, the appearance of fish schools F is predicted based on knowledge and experience of when and where fish schools F appear under general conditions of water temperature, currents, wind speed, and tides, as well as images of the birds B. In addition, if fish schools F are currently predicted to be present, the movement speed and direction of fish schools F, or whether fish schools F will remain stationary, are predicted based on water temperature, currents, wind speed, and tides, and the appearance of fish schools F in the future is predicted.

[0048] Furthermore, in this embodiment, the system also predicts when and where schools of fish will appear based on past fish school information stored in the historical information database 441. Specifically, it predicts when and where schools of fish F will appear by considering and taking into account when and where schools of fish F appeared in the past, what the water temperature, currents, wind speed, and tides of the sea W were like at that time, and what the situation was like for birds B flying overhead. More precisely, based on past fish school information, the system statistically predicts where schools of fish F will appear at what time of day, under what water temperature and currents, and under what conditions birds B are, and predicts when and where schools of fish F will appear based on the situation of birds B and future predicted water temperatures and currents.

[0049] This charging task 45 uses a fish school prediction learning model 442 that has been trained on past performance data so that when it receives images of bird B flying overhead, environmental information, and past fish school information (hereinafter referred to as "images of bird B, etc."), it outputs when and where fish school F will appear (hereinafter referred to as "fish school F occurrence information"). This fish school prediction learning model 442 is created by the learning task 46.

[0050] In other words, the learning task 46 creates a learning model 442 for fish school prediction using a known machine learning algorithm such as a neural network, based on past performance data recorded and stored in the fish school prediction performance database 443. This fish school prediction performance database 443 is a database in which performance data is recorded and stored, including information on the occurrence of fish schools F, which has been determined by experts and skilled individuals in fish school search and image analysis based on images of birds B as input information, or the time and location in which fish schools F actually appeared. The past performance data includes data created based on actual images of birds B, information on the occurrence of fish schools F actually determined by experts and skilled individuals, as well as data created through pre-training, etc.

[0051] As shown in Figure 4, this learning task 46 uses machine learning and deep learning with a neural network to create a neural network based on actual data recorded in the fish school prediction database 443. For example, it uses images of bird B as the input layer, fish school F occurrence information as the output layer, and the analysis processing from the input layer to the output layer as the hidden layer. Then, learning task 46 uses the actual data of the fish school prediction learning model 442 as training data to learn various parameters in the hidden layer. In other words, learning task 46 learns various parameters in the hidden layer so that fish school F occurrence information is output appropriately based on images of bird B, etc.

[0052] Next, we plan the charging of the fishing vessel's battery SB so that fishing can begin when the predicted school of fish F appears. In other words, we plan when the fishing vessel's battery SB should be charged so that the electric fishing vessel S can arrive at the location where the predicted school of fish F is expected to appear and begin fishing. Specifically, we determine when the fishing vessel's battery SB needs to be charged (charging completion time, departure time of the electric fishing vessel S) based on when the predicted school of fish F is expected to appear and the travel time to the location where the predicted school of fish F is expected to appear (distance from offshore station 2 ÷ propulsion speed of electric fishing vessel S).

[0053] In this case, the basic premise is to fully charge the fishing boat battery SB, but depending on the power generation status and amount of power generated by the power generation equipment 21 and the remaining capacity of the system battery 22, it is also possible to charge only the amount of power and capacity required for the round trip to the location where the school of fish F appears.

[0054] Furthermore, a charging plan is formulated based on the remaining capacity of the fishing vessel battery SB. Specifically, the amount of power and time required for charging are determined based on the rated capacity and remaining capacity of the fishing vessel battery SB, and the charging start time is determined from this time and the charging completion time. Here, the rated capacity and remaining capacity of the fishing vessel battery SB are obtained by the charger 23 as described above. In addition, the plan is to charge the fishing vessel battery SB at a time when the amount of power required for charging can be supplied from the power generation equipment 21 and the system battery 22.

[0055] Furthermore, based on weather information, the amount of power generated by the power generation equipment 21 is predicted, and based on the predicted amount of power generated and the remaining capacity of the system battery 22, the charging of the fishing vessel battery SB is planned so that fishing can be carried out when the predicted school of fish F appears. In other words, a charging plan is formulated so that the fishing vessel battery SB is fully charged while the power generation equipment 21 is generating power or while the system battery 22 can discharge. For example, if the power generation equipment 21 cannot generate power and the remaining capacity of the system battery 22 is low just before the departure time of the electric fishing vessel S, the charging start time is planned so that the fishing vessel battery SB is charged in advance at a time when the power generation equipment 21 can generate power.

[0056] Furthermore, if there are multiple fishing vessel batteries SB to be charged, a similar charging plan is formulated for each. In this case, if multiple schools of fish F appear, the electric fishing vessel S is assigned to which school of fish F based on the time each school of fish F appears, the distance to each school of fish F, and the time required to charge each fishing vessel battery SB. The charging of the fishing vessel batteries SB is then planned so that fishing can be carried out when each school of fish F appears. In contrast, if multiple electric fishing vessels S are used to fish for a single school of fish F, the plan is to ensure that all fishing vessel batteries SB are fully charged by the departure time.

[0057] Next, the charging plan formulated in this manner is displayed on the display unit 42 or transmitted to the operator's mobile terminal. This allows the operator to control the system battery 22, charger 23, hybrid PCS 25, 26, etc., to charge the fishing vessel battery SB according to the charging plan. In this case, automatic control may be implemented using the management computer 4 or another control device.

[0058] As described above, with this electric fishing boat charging system 1, the timing and location of a school of fish F is predicted based on images taken of birds B flying above the sea surface, and the fishing boat's battery SB is charged so that fishing can be carried out when the school of fish F is predicted to appear. In other words, the fishing boat's battery SB is charged before the electric fishing boat S departs for fishing after the school of fish F appears. As a result, it is possible to prevent the battery SB from being charged in time for fishing for the school of fish F, or from being unnecessarily charged when the fishing boat is not departing for fishing, and to charge the electric fishing boat S's battery SB at the appropriate time.

[0059] On the other hand, since the electric fishing vessel S's battery SB can be charged at the offshore station 2, there is no need to return to land for charging, which reduces wasted travel time and energy consumption. Furthermore, because the electric fishing vessel S's battery SB is charged with electricity generated from renewable energy sources, including wind power, fuel costs and CO2 emissions can be reduced, ensuring sustainability.

[0060] Furthermore, since the appearance and location of fish schools F can be predicted based on factors such as seawater temperature and currents, accurate predictions become possible, and as a result, the electric fishing vessel S's battery SB can be charged at the appropriate time.

[0061] Furthermore, since the timing and location of past appearances of fish schools F, as well as the behavior of birds B flying overhead, can be used to predict when and where fish schools F will appear, accurate predictions become possible. As a result, it becomes possible to charge the electric fishing boat S's battery SB at the appropriate time.

[0062] Furthermore, using the machine learning-developed fish school prediction model 442, the system outputs when and where fish school F will appear, enabling accurate predictions. As a result, it becomes possible to charge the electric fishing vessel S's battery SB at the appropriate time.

[0063] Furthermore, based on the remaining capacity of the fishing vessel's battery SB, that is, based on how much time and power is required for charging, the fishing vessel's battery SB is charged so that fishing can be carried out when a school of fish F appears, thus enabling charging at the appropriate time.

[0064] Furthermore, based on the predicted power generation amount and the remaining capacity of the system battery 22, that is, based on when and how much the fishing vessel battery SB can be charged, the fishing vessel battery SB is charged so that fishing can be carried out when a school of fish F appears, thus enabling charging at the appropriate time.

[0065] Although embodiments of this invention have been described in detail above, the specific configuration is not limited to these embodiments, and any design changes, etc., that do not depart from the gist of this invention are also included. For example, the flow of power and current between the components is not limited to the above embodiments, and for example, supplying power to power receiving equipment such as lighting fixtures 51 necessary for living may be given first priority, or power may be supplied solely within the electric fishing boat charging system 1 without connecting to the power grid.

[0066] Alternatively, the electric fishing boat charging system 1 and management computer 4 described above may be configured by installing the following electric fishing boat charging program on a general-purpose computer.

[0067] An offshore station 2 installed at sea is provided with a power generation facility 21 that generates electricity using natural energy including wind power, a system battery 22 that stores the electricity generated by the power generation facility 21, and a charger 23 that charges the fishing vessel battery SB installed on the electric fishing vessel S using electricity from at least one of the power generation facility 21 and the system battery 22. The electric fishing vessel charging program formulates a charging plan for the fishing vessel battery SB, and the computer functions as a past information storage means (past information database 441) that stores past fish school information including the time and place when fish schools F appeared in the past and the status of birds B flying above the sea surface, and a charging planning means (charging task 45) that predicts when and where fish schools F will appear based on images of birds B flying above the sea surface, and plans the charging of the fishing vessel battery SB so that fishing can be carried out when the predicted fish school F appears. The charging planning means uses a fish school prediction learning model 442 that has been machine-learned based on past performance data to predict when and where a fish school F will appear based on environmental information including seawater temperature and currents in the ocean W, and past fish school information, and outputs information on the occurrence of the fish school F when an image of the bird B or the like is input. Furthermore, it plans to charge the fishing vessel battery SB so that fishing can be carried out when the predicted fish school F appears, based on the remaining capacity of the fishing vessel battery SB. In addition, it predicts the amount of power generated by the power generation equipment 21 based on weather information, and plans to charge the fishing vessel battery SB so that fishing can be carried out when the predicted fish school F appears, based on the predicted amount of power generated and the remaining capacity of the system battery 22. [Explanation of symbols]

[0068] 1. Electric fishing boat charging system 2. Offshore Station 21 Power generation equipment 22 System Battery 23 Charger 24. Environmental sensors (means for acquiring environmental information) 3 Drones 31. High-resolution camera (imaging device) 32. Infrared camera (imaging device) 4. Management Computer 441 Historical Information Database (Historical Information Storage Means) 442 Learning models for fish school prediction 45 Charging Task (Charging Planning Means) S Electric fishing boat SB fishing boat battery W Sea B bird F School of fish

Claims

1. A power generation facility that generates electricity using natural energy, including wind power, installed on a floating station located at sea; a system battery that stores the electricity generated by the power generation facility; and a charger that charges a fishing vessel battery installed on an electric fishing vessel using electricity from at least one of the power generation facility and the system battery. A camera for photographing birds flying above the sea surface, A charging planning means predicts when and where a school of fish will appear based on images captured by the aforementioned camera, and plans the charging of the fishing vessel's battery so that fishing can be carried out when the predicted school of fish appears. An electric fishing boat charging system characterized by comprising the following features.

2. Equipped with means for acquiring environmental information, including sea surface temperature and ocean currents, The charging planning means predicts when and where a school of fish will appear based on the environmental information. The electric fishing boat charging system according to feature 1.

3. It is equipped with a past information storage means that stores past fish school information, including the time and location when schools of fish appeared in the past, and the status of birds flying overhead. The charging planning means predicts when and where a school of fish will appear based on the past school of fish information. The electric fishing boat charging system according to feature 1.

4. The charging planning means uses a machine learning model for predicting fish schools, which is based on past performance data, so that when an image captured by the camera is input, it outputs when and where the fish school will appear. The electric fishing boat charging system according to feature 1.

5. The charging planning means plans the charging of the fishing vessel's battery based on the remaining capacity of the fishing vessel's battery so that fishing can be carried out when the predicted school of fish appears. The electric fishing boat charging system according to feature 1.

6. The charging planning means predicts the amount of power generated by the power generation equipment based on weather information, and plans to charge the fishing vessel's battery based on the predicted amount of power generated and the remaining capacity of the system battery, so that fishing can be carried out when the predicted school of fish appears. The electric fishing boat charging system according to feature 1.

7. An electric fishing vessel charging program is provided, comprising: a power generation facility that generates electricity using natural energy including wind power, a system battery that stores the electricity generated by the power generation facility, and a charger that charges a fishing vessel battery installed on an electric fishing vessel using electricity from at least one of the power generation facility and the system battery, and a charging plan for the fishing vessel battery. Computers, A charging planning means that predicts when and where schools of fish will appear based on images of birds flying above the sea surface, and plans the charging of the fishing vessel's battery so that fishing can be carried out when the predicted schools of fish appear. An electric fishing boat charging program characterized by its function as follows.

8. The charging planning means predicts when and where schools of fish will appear based on environmental information including seawater temperature and ocean currents. The electric fishing boat charging program according to feature 7.

9. Computers, It functions as a historical information storage method that stores past fish school information, including the time and location when schools of fish appeared in the past, and the status of birds flying overhead. The charging planning means predicts when and where a school of fish will appear based on the past school of fish information. The electric fishing boat charging program according to feature 7.

10. The charging planning means uses a machine learning model for predicting fish schools, which is based on past performance data, so that when an image of birds flying over the sea surface is input, it outputs when and where schools of fish will appear. The electric fishing boat charging program according to feature 7.

11. The charging planning means plans the charging of the fishing vessel's battery based on the remaining capacity of the fishing vessel's battery so that fishing can be carried out when the predicted school of fish appears. The electric fishing boat charging program according to feature 7.

12. The charging planning means predicts the amount of power generated by the power generation equipment based on weather information, and plans to charge the fishing vessel's battery based on the predicted amount of power generated and the remaining capacity of the system battery, so that fishing can be carried out when the predicted school of fish appears. The electric fishing boat charging program according to feature 7.

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