Folding photovoltaic array adaptive control system and method based on artificial intelligence

Abstract

According to the folding type photovoltaic array adaptive control system and method based on artificial intelligence, environment information of a folding type photovoltaic use site is collected based on a sensor, an environment information basis is provided for folding type photovoltaic array adaptive control, and the folding type photovoltaic array adaptive control system and method based on historical use data of a folding type photovoltaic array and artificial intelligence are combined. The method comprises the following steps: constructing an optimal state prediction model, constructing an intelligent model for adaptive control of a folding type photovoltaic array, improving adaptive control analysis efficiency and precision, inputting environment information into the optimal state prediction model, determining an optimal folding angle, and controlling the folding type photovoltaic array to perform adaptive adjustment based on the optimal folding angle. The folding type photovoltaic array is adaptively adjusted, so that the performance of the folding type photovoltaic panel is ensured, and the damage to the folding type photovoltaic panel is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation, and particularly to an adaptive control system and method for a foldable photovoltaic array based on artificial intelligence. Background Art

[0002] Compared with ordinary photovoltaic panels, foldable photovoltaic panels adopt a portable design, are light and easy to carry, and can be used anywhere, especially suitable for outdoor activities such as self-driving trips and camping. In addition, foldable photovoltaic panel containers have high mobility and can be quickly deployed anywhere to adapt to various environments and needs. This design not only reduces the large amount of land occupied by traditional solar power generation systems but also facilitates relocation between different locations. High efficiency: Foldable photovoltaic panels also have significant advantages in design and technology. For example, foldable solar cells adopt an innovative folding system that can be easily unfolded through solar rails, reducing the cable length between the panel and the inverter and improving the power generation efficiency of the system.

[0003] How to achieve the adaptive control of foldable photovoltaic panels according to specific requirements, ensure the performance of foldable photovoltaic panels, and reduce the damage of foldable photovoltaic panels is an urgent problem to be solved currently. Summary of the Invention

[0004] The present invention provides an adaptive control system and method for a foldable photovoltaic array based on artificial intelligence to solve the problems raised in the background art.

[0005] An adaptive control system for a foldable photovoltaic array based on artificial intelligence includes:

[0006] A data acquisition module for collecting environmental information of the foldable photovoltaic usage site based on sensors;

[0007] A model construction module for constructing an optimal state prediction model based on the historical usage data of the foldable photovoltaic array in combination with artificial intelligence;

[0008] A prediction module for inputting the environmental information into the optimal state prediction model to determine the optimal folding angle;

[0009] An adjustment module for controlling the foldable photovoltaic array to perform adaptive adjustment based on the optimal folding angle in combination with the user-side power consumption data.

[0010] Preferably, the data acquisition module includes:

[0011] A light intensity monitoring unit for monitoring the light intensity of the foldable photovoltaic usage site based on a light sensor;

[0012] A temperature monitoring unit for monitoring the temperature of the foldable photovoltaic usage site based on a temperature sensor;

[0013] A wind speed monitoring unit for monitoring the wind speed of the folding photovoltaic usage site based on a speed sensor;

[0014] A cloud layer monitoring unit for monitoring the cloud cover of the folding photovoltaic usage site based on a vision sensor;

[0015] A receiving and processing unit for receiving monitoring data from the light intensity monitoring unit, the temperature monitoring unit, the wind speed monitoring unit and the cloud layer monitoring unit, and preprocessing the monitoring data to obtain the environmental information of the usage site.

[0016] Preferably, the model construction module includes:

[0017] A data processing unit for obtaining the historical environmental data and historical folding data of the folding photovoltaic array, and processing the historical environmental data and historical folding data to obtain target training data;

[0018] A model construction unit for training an initial artificial intelligence model based on the target training data to obtain an optimal state prediction model.

[0019] Preferably, the prediction module includes:

[0020] An input unit for obtaining the array layout of the folding photovoltaic array and inputting the array layout and environmental information into the optimal state prediction model;

[0021] An analysis unit for analyzing the array layout and environmental information based on the optimal state prediction model to obtain the optimal folding angle.

[0022] Preferably, the adjustment module includes:

[0023] An electricity consumption prediction unit for determining the user's electricity consumption cycle and the electricity consumption curve within the electricity consumption cycle based on the user-side electricity consumption data, and predicting the user's electricity consumption in a future period of time based on the electricity consumption curve;

[0024] An electricity storage judgment unit for obtaining the stored electricity of the folding photovoltaic array and judging whether the electricity difference between the stored electricity and the electricity consumption is greater than a preset electricity amount;

[0025] If so, determining the adaptive adjustment parameters for the folding photovoltaic array based on the user-side electricity consumption data;

[0026] Otherwise, determining the adaptive adjustment parameters for the folding photovoltaic array based on the optimal folding angle.

[0027] Preferably, the adjustment module further includes:

[0028] An angle analysis unit for determining, when adjusting according to the optimal folding angle, based on the optimal folding angle and in combination with the current angle of the foldable photovoltaic array, determining the angle difference and the angle folding direction;

[0029] A parameter determination unit for determining adjustment parameters for the foldable photovoltaic array based on the angle difference and the angle folding direction.

[0030] Preferably, the adjustment module further includes:

[0031] A first judgment unit for determining, when adjusting based on user-side power consumption data, judging whether the power difference is greater than the maximum preset power;

[0032] If so, keep the current folding angle of the foldable photovoltaic array unchanged;

[0033] Otherwise, based on the environmental prediction model, obtain the temperature prediction curve, wind speed prediction curve and cloud cover prediction curve within a future period of time;

[0034] A second judgment unit for determining the future photovoltaic charging trend based on the temperature prediction curve, wind speed prediction curve and cloud cover prediction curve, in combination with the current angle, and judging whether the future photovoltaic charging trend meets the power consumption curve and the remaining power is greater than the maximum preset power;

[0035] If so, keep the current folding angle of the foldable photovoltaic array unchanged;

[0036] Otherwise, judge whether the remaining power is greater than the preset power;

[0037] If so, based on the optimal state prediction model, determine the predicted optimal angle within a future period of time under the temperature prediction curve, wind speed prediction curve and cloud cover prediction curve, and judge whether the angle difference between the predicted optimal angle and the optimal folding angle is less than the preset angle difference. If so, determine the adaptive adjustment parameters for the foldable photovoltaic array based on the optimal folding angle. Otherwise, select the angle with the smaller angle difference from the predicted optimal angle and the optimal folding angle to the current angle as the adaptive adjustment parameters for the foldable photovoltaic array;

[0038] Otherwise, determine the adaptive adjustment parameters for the foldable photovoltaic array based on the optimal folding angle.

[0039] Preferably, it further includes: an inverter module for adaptively adjusting the output power of the inverter based on the adaptive adjustment parameters of the foldable photovoltaic array and in combination with the operating parameters of the foldable photovoltaic array. Specifically:

[0040] An adjustment determination unit, configured to obtain adaptive adjustment parameters for the foldable photovoltaic array, determine the difference between the collected direct current and the historical collected direct current based on the adaptive adjustment parameters, and determine a first adjustment parameter for the output power of the inverter based on a real-time adjustment strategy;

[0041] A working judgment unit, configured to obtain the voltage, current, power factor, and heating temperature of the inverter itself, obtain predicted target values of the voltage, current, power factor, and heating temperature under the first adjustment parameter, and judge whether the predicted target values are within the normal working value range;

[0042] If so, adjust the output power of the inverter based on the first adjustment parameter;

[0043] Otherwise, continuously reduce the amplitude of the first adjustment parameter until the target value is within the normal working value range, and then determine the adjustment parameter for the output power of the inverter;

[0044] An action determination unit, configured to obtain the power generation efficiency of the foldable photovoltaic array after adjusting the output power of the inverter for a period of time, and judge whether the power generation efficiency is greater than the historical power generation efficiency;

[0045] If so, perform a reward action on the real-time adjustment strategy;

[0046] Otherwise, judge whether the power generation efficiency is greater than the minimum power generation efficiency. If so, do not perform any action on the real-time adjustment strategy. Otherwise, perform a penalty action on the real-time adjustment strategy;

[0047] A strategy update unit, configured to adaptively adjust the real-time adjustment strategy when the real-time adjustment strategy receives a reward action or a penalty action to obtain an updated adjustment strategy, and the updated adjustment strategy is used for the next output power adjustment.

[0048] Preferably, the adjustment determination unit includes:

[0049] A direction determination unit, configured to determine that the first adjustment parameter is an upward adjustment when the difference between the collected direct current and the historical collected direct current is positive, and determine that the first adjustment parameter is a downward adjustment when the difference between the collected direct current and the historical collected direct current is negative;

[0050] An amplitude determination unit, configured to set the real-time adjustment strategy to mainly adjust the amplitude of the first adjustment parameter according to the larger the difference between the collected direct current and the historical collected direct current, and secondly, adaptively fine-tune the adjustment amplitude according to the reward action and the penalty action.

[0051] An adaptive control method for a foldable photovoltaic array based on artificial intelligence, including:

[0052] S1: Collect environmental information of the folding photovoltaic usage site based on sensors;

[0053] S2: Based on the historical usage data of the folding photovoltaic array and combined with artificial intelligence, construct an optimal state prediction model;

[0054] S3: Input the environmental information into the optimal state prediction model to determine the optimal folding angle;

[0055] S4: Based on the optimal folding angle and combined with the user-side power consumption data, control the folding photovoltaic array to perform adaptive adjustment.

[0056] Compared with the prior art, the present invention has achieved the following beneficial effects:

[0057] By collecting environmental information of the folding photovoltaic usage site based on sensors, it provides an environmental information basis for the adaptive control of the folding photovoltaic array. Based on the historical usage data of the folding photovoltaic array and combined with artificial intelligence, an optimal state prediction model is constructed to build an intelligent model for the adaptive control of the folding photovoltaic array, improving the efficiency and accuracy of adaptive control analysis. Input the environmental information into the optimal state prediction model to determine the optimal folding angle, and based on the optimal folding angle, control the folding photovoltaic array to perform adaptive adjustment. By performing adaptive adjustment on the folding photovoltaic array, the performance of the folding photovoltaic panel is guaranteed and the damage of the folding photovoltaic panel is reduced.

[0058] Other features and advantages of the present invention will be described in the following specification, and part of them will become obvious from the specification or be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in this application document.

[0059] The technical solutions of the present invention will be further described in detail below through the drawings and embodiments. Description of the Drawings

[0060] The drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0061] Figure 1 It is the structural diagram of the adaptive control system of the folding photovoltaic array based on artificial intelligence in the embodiment of the present invention;

[0062] Figure 2 It is the structural diagram of the model construction module in the embodiment of the present invention;

[0063] Figure 3 It is the flowchart of the adaptive control method of the folding photovoltaic array based on artificial intelligence in the embodiment of the present invention. Specific Embodiments

[0064] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for explaining and illustrating the present invention, and are not used to limit the present invention.

[0065] Embodiment 1:

[0066] An embodiment of the present invention provides an adaptive control system for a foldable photovoltaic array based on artificial intelligence, as Figure 1 shown, including:

[0067] A data acquisition module for collecting environmental information of the foldable photovoltaic usage site based on sensors;

[0068] A model construction module for constructing an optimal state prediction model based on the historical usage data of the foldable photovoltaic array in combination with artificial intelligence;

[0069] A prediction module for inputting the environmental information into the optimal state prediction model to determine the optimal folding angle;

[0070] An adjustment module for controlling the foldable photovoltaic array to perform adaptive adjustment based on the optimal folding angle in combination with the user-side power consumption data.

[0071] In this embodiment, the environmental information of the usage site includes light intensity, temperature, wind speed, and cloud cover.

[0072] In this embodiment, the historical usage data includes historical environmental data and historical folding data.

[0073] In this embodiment, controlling the foldable photovoltaic array to perform adaptive adjustment is the adjustment of the folding angle.

[0074] In this embodiment, the adaptive adjustment of the foldable photovoltaic array does not necessarily need to be adjusted according to the said minimum angle, and it needs to be further determined according to the user-side power consumption data.

[0075] In this embodiment, the optimal folding angle is the optimal angle determined according to the environmental information for photovoltaic charging, and the adaptive adjustment also needs to be determined according to the actual power consumption demand.

[0076] The beneficial effects of the above design are as follows: By collecting environmental information of the folding photovoltaic use site based on sensors, it provides an environmental information basis for the adaptive control of the folding photovoltaic array. Based on the historical usage data of the folding photovoltaic array and combined with artificial intelligence, an optimal state prediction model is constructed to build an intelligent model for the adaptive control of the folding photovoltaic array, improving the efficiency and accuracy of adaptive control analysis. The environmental information is input into the optimal state prediction model to determine the optimal folding angle. Based on the optimal folding angle, the folding photovoltaic array is controlled for adaptive adjustment. By adaptively adjusting the folding photovoltaic array, the performance of the folding photovoltaic panel is ensured and the damage of the folding photovoltaic panel is reduced.

[0077] Embodiment 2:

[0078] Based on Embodiment 1, an embodiment of the present invention provides an adaptive control system for a folding photovoltaic array based on artificial intelligence. The data acquisition module includes:

[0079] The light intensity monitoring unit is used to monitor the light intensity of the folding photovoltaic use site based on a light sensor;

[0080] The temperature monitoring unit is used to monitor the temperature of the folding photovoltaic use site based on a temperature sensor;

[0081] The wind speed monitoring unit is used to monitor the wind speed of the folding photovoltaic use site based on a speed sensor;

[0082] The cloud layer monitoring unit is used to monitor the cloud cover of the folding photovoltaic use site based on a vision sensor;

[0083] The receiving and processing unit is used to receive the monitoring data from the light intensity monitoring unit, the temperature monitoring unit, the wind speed monitoring unit and the cloud layer monitoring unit, and preprocess the monitoring data to obtain the environmental information of the use site.

[0084] The beneficial effects of the above design are as follows: By receiving the monitoring data from the light intensity monitoring unit, the temperature monitoring unit, the wind speed monitoring unit and the cloud layer monitoring unit, and preprocessing the monitoring data to obtain the environmental information of the use site, it provides an environmental information basis for the adaptive control of the folding photovoltaic array.

[0085] Embodiment 3:

[0086] Based on Embodiment 1, an embodiment of the present invention provides an adaptive control system for a folding photovoltaic array based on artificial intelligence, as Figure 2 shown, the model construction module includes:

[0087] A data processing unit, configured to obtain historical environmental data and historical folding data of a foldable photovoltaic array, and process the historical environmental data and the historical folding data to obtain target training data;

[0088] A model construction unit, configured to train an initial artificial intelligence model based on the target training data to obtain an optimal state prediction model.

[0089] In this embodiment, processing the historical environmental data and the historical folding data includes preprocessing, feature engineering, data extraction, and other methods.

[0090] The beneficial effects of the above design solution are: by obtaining the historical environmental data and the historical folding data of the foldable photovoltaic array, processing the historical environmental data and the historical folding data to obtain target training data, and training the initial artificial intelligence model based on the target training data to obtain an optimal state prediction model, an intelligent model for the adaptive control of the foldable photovoltaic array is constructed, improving the efficiency and accuracy of adaptive control analysis.

[0091] Embodiment 4:

[0092] Based on Embodiment 1, an embodiment of the present invention provides an adaptive control system for a foldable photovoltaic array based on artificial intelligence. The prediction module includes:

[0093] An input unit, configured to obtain the array layout of the foldable photovoltaic array, and input the array layout and environmental information into the optimal state prediction model;

[0094] An analysis unit, configured to analyze the array layout and environmental information based on the optimal state prediction model to obtain the optimal folding angle.

[0095] The beneficial effects of the above design solution are: by obtaining the array layout of the foldable photovoltaic array, inputting the array layout and environmental information into the optimal state prediction model, and analyzing the array layout and environmental information based on the optimal state prediction model to obtain the optimal folding angle, the determination of the optimal state of the foldable photovoltaic array is realized, providing a basis for further adaptive control.

[0096] Embodiment 5:

[0097] Based on Embodiment 1, an embodiment of the present invention provides an adaptive control system for a foldable photovoltaic array based on artificial intelligence. The adjustment module includes:

[0098] A power prediction unit, configured to determine the user's power consumption cycle and the power consumption curve within the power consumption cycle based on the user-side power consumption data, and predict the user's power consumption in a future period of time based on the power consumption curve;

[0099] The power judgment unit is used to obtain the stored power of the foldable photovoltaic array and determine whether the power difference between the stored power and the power consumption is greater than a preset power.

[0100] If so, determine the adaptive adjustment parameters for the foldable photovoltaic array based on the user-side power consumption data.

[0101] Otherwise, determine the adaptive adjustment parameters for the foldable photovoltaic array based on the optimal folding angle.

[0102] In this embodiment, the preset power is set in advance according to the actual situation.

[0103] In this embodiment, the present solution adopts two adaptive adjustment methods to ensure both the user-side power consumption demand and the service life of the foldable photovoltaic array.

[0104] The beneficial effects of the above design solution are as follows: By obtaining the stored power of the foldable photovoltaic array, determining whether the difference between the stored power and the power consumption is greater than the preset power. If so, determine the adaptive adjustment parameters for the foldable photovoltaic array based on the user-side power consumption data. Otherwise, determine the adaptive adjustment parameters for the foldable photovoltaic array based on the optimal folding angle. Through the two adaptive adjustment methods, both the user-side power consumption demand and the service life of the foldable photovoltaic array are ensured.

[0105] Embodiment 6:

[0106] Based on Embodiment 5, an embodiment of the present invention provides an adaptive control system for a foldable photovoltaic array based on artificial intelligence. The adjustment module further includes:

[0107] The angle analysis unit is used to determine the angle difference and the angle folding direction based on the optimal folding angle and in combination with the current angle of the foldable photovoltaic array when adjusting according to the optimal folding angle.

[0108] The parameter determination unit is used to determine the adjustment parameters for the foldable photovoltaic array based on the angle difference and the angle folding direction.

[0109] In this embodiment, the adjustment parameters include the adjustment angle and the adjustment direction.

[0110] The beneficial effects of the above design solution are as follows: Based on the optimal folding angle, in combination with the current angle of the foldable photovoltaic array, determine the angle difference and the angle folding direction. Based on the angle difference and the angle folding direction, determine the adaptive adjustment parameters for the foldable photovoltaic array. By adaptively adjusting the foldable photovoltaic array, the performance of the foldable photovoltaic panel is ensured, and the damage to the foldable photovoltaic panel is reduced.

[0111] Embodiment 7:

[0112] Based on Embodiment 5, an embodiment of the present invention provides an adaptive control system for a foldable photovoltaic array based on artificial intelligence. The adjustment module further includes:

[0113] A first judgment unit, configured to determine whether the power difference is greater than the maximum preset power when adjusting based on the user-side power consumption data;

[0114] If so, keep the current folding angle of the foldable photovoltaic array unchanged;

[0115] Otherwise, based on the environmental prediction model, obtain the temperature prediction curve, wind speed prediction curve, and cloud cover prediction curve within a future period of time;

[0116] A second judgment unit, configured to determine the future photovoltaic charging trend based on the temperature prediction curve, wind speed prediction curve, and cloud cover prediction curve, and in combination with the current angle, and determine whether the future photovoltaic charging trend meets the power consumption curve and the remaining power is greater than the maximum preset power;

[0117] If so, keep the current folding angle of the foldable photovoltaic array unchanged;

[0118] Otherwise, determine whether the remaining power is greater than the preset power;

[0119] If so, based on the optimal state prediction model, determine the predicted optimal angle within a future period of time under the temperature prediction curve, wind speed prediction curve, and cloud cover prediction curve, and determine whether the angle difference between the predicted optimal angle and the optimal folding angle is less than the preset angle difference. If so, determine the adaptive adjustment parameter for the foldable photovoltaic array based on the optimal folding angle. Otherwise, select the angle with a smaller angle difference from the current angle between the predicted optimal angle and the optimal folding angle as the adaptive adjustment parameter for the foldable photovoltaic array;

[0120] Otherwise, determine the adaptive adjustment parameter for the foldable photovoltaic array based on the optimal folding angle.

[0121] In this embodiment, the maximum preset power is preset according to the actual situation, and its value is greater than the preset power.

[0122] In this embodiment, the environmental prediction model is pre-trained based on artificial intelligence.

[0123] In this embodiment, the future period of time is adaptively set based on the power consumption cycle.

[0124] In this embodiment, the power difference being greater than the maximum preset power means that the power is sufficient to meet the power consumption for one cycle, and the angle can be unchanged to avoid damage to the photovoltaic panels.

[0125] In this embodiment, the angle with a smaller difference between the predicted optimal angle and the optimal folding angle and the current angle is selected to improve the adjustment efficiency of the foldable photovoltaic array, and a smaller adjustment range is used to avoid damage to the photovoltaic panel.

[0126] The beneficial effect of the above design scheme is: based on the optimal folding angle, combined with the power consumption on the power consumption side, and the prediction of power consumption and charging conditions in the future, the photovoltaic array is adaptively adjusted based on the principle of avoiding frequent folding of the photovoltaic array as much as possible and making the amplitude of each folding as small as possible while meeting the power demand, thereby ensuring the performance of the foldable photovoltaic panel and reducing damage to the foldable photovoltaic panel.

[0127] Embodiment 8:

[0128] Based on Example 1, the embodiment of the present invention provides an artificial intelligence-based foldable photovoltaic array adaptive control system, which also includes: an inverter module, which is used to adaptively adjust the output power of the inverter based on the adaptive adjustment parameters of the foldable photovoltaic array and the working parameters of the foldable photovoltaic array, specifically:

[0129] An adjustment determination unit, configured to obtain an adaptive adjustment parameter for the foldable photovoltaic array, and determine a first adjustment parameter for the inverter output power based on a difference between the collected DC power determined by the adaptive adjustment parameter and the historical collected DC power and based on a real-time adjustment strategy;

[0130] A working judgment unit, used to obtain the voltage, current, power factor and heating temperature of the inverter itself, obtain the predicted target values of the voltage, current, power factor and heating temperature under the first adjustment parameter, and judge whether the predicted target values are within the normal working value range;

[0131] If so, adjusting the output power of the inverter based on the first adjustment parameter;

[0132] Otherwise, the amplitude of the first adjustment parameter is cyclically reduced until the target value is within the normal operating value range, and then the adjustment parameter for the output power of the inverter is determined;

[0133] an action determination unit, for obtaining the power generation efficiency of the foldable photovoltaic array after adjusting the output power of the inverter for a period of time, and determining whether the power generation efficiency is greater than the historical power generation efficiency;

[0134] If so, performing a reward action on the real-time adjustment strategy;

[0135] Otherwise, determining whether the power generation efficiency is greater than the minimum power generation efficiency, if so, not taking any action on the real-time adjustment strategy, otherwise, taking a penalty action on the real-time adjustment strategy;

[0136] A policy update unit, which is used to adjust the policy in real time. When receiving a reward action or a punishment action, it adaptively adjusts the real-time adjustment policy to obtain the latest adjusted policy, and the latest adjusted policy is used for the next output power adjustment.

[0137] In this embodiment, the real-time adjustment policy is designed based on principles and historical experience.

[0138] In this embodiment, after a reward action is performed on the real-time adjustment policy, the real-time adjustment policy will remember that this adjustment is reasonable and effective, and subsequent adjustments can be based on this. When a punishment action is performed on the real-time adjustment policy, the real-time adjustment policy will remember that this adjustment is not very reasonable and will make further corrections. Through multiple reward and punishment actions, the real-time adjustment policy can better meet the actual needs.

[0139] In this embodiment, the minimum power generation efficiency is the efficiency that cannot be lower than this during the designed operation, and it is set according to the actual situation.

[0140] In this embodiment, the amplitude of the first adjustment parameter is cyclically reduced until the target value is within the normal operating value range, and then the adjustment parameter for the output power of the inverter is determined to avoid the influence of excessive output power on other parameters, and the amplitude of the first adjustment parameter is cyclically reduced to achieve fine adjustment and avoid instability of the operation caused by too large an adjustment amplitude.

[0141] The beneficial effects of the above design are as follows: By adaptively adjusting the parameters based on the foldable photovoltaic array and combining with the operating parameters of the foldable photovoltaic array, the output power of the inverter is adaptively adjusted, so that the operating parameters of the inverter can meet the changes of the foldable photovoltaic array, cooperate with the foldable photovoltaic array, assist the foldable photovoltaic array to better perform adaptive adjustment, ensure the performance of the foldable photovoltaic panel, and reduce the damage of the foldable photovoltaic panel.

[0142] Embodiment 9:

[0143] Based on Embodiment 8, an adaptive control system for a foldable photovoltaic array based on artificial intelligence is provided in this embodiment of the present invention. The adjustment determination unit includes:

[0144] A direction determination unit, which is used to determine that the first adjustment parameter is adjusted upward when the difference between the collected direct current and the historical collected direct current is positive, and determine that the first adjustment parameter is adjusted downward when the difference between the collected direct current and the historical collected direct current is negative;

[0145] An amplitude determination unit is configured to set the real-time adjustment strategy to mainly adjust the amplitude of the first adjustment parameter according to the greater the difference between the currently collected direct current and the historically collected direct current, and secondly, to perform adaptive fine-tuning on the adjustment amplitude according to the reward action and the punishment action.

[0146] In this embodiment, the output power of the inverter is adjusted upward to improve the efficiency of converting direct current of the inverter into alternating current.

[0147] The beneficial effects of the above design are as follows: when the difference between the currently collected direct current and the historically collected direct current is positive, the first adjustment parameter is determined to be adjusted upward; when the difference is negative, the first adjustment parameter is determined to be adjusted downward, thereby determining the adjustment direction. The real-time adjustment strategy is set to mainly adjust the amplitude of the first adjustment parameter according to the greater the difference between the currently collected direct current and the historically collected direct current, and secondly, to perform adaptive fine-tuning on the adjustment amplitude according to the reward action and the punishment action. Based on the real-time adjustment strategy, reasonable numerical adjustment is performed to ensure the rationality and correctness of the obtained first adjustment parameter for the actual situation.

[0148] Embodiment 10:

[0149] An embodiment of the present invention provides an artificial intelligence-based adaptive control method for a foldable photovoltaic array, as Figure 3 shown, including:

[0150] S1: Collecting environmental information of the usage site of the foldable photovoltaic based on sensors;

[0151] S2: Constructing an optimal state prediction model based on the historical usage data of the foldable photovoltaic array in combination with artificial intelligence;

[0152] S3: Inputting the environmental information into the optimal state prediction model to determine the optimal folding angle;

[0153] S4: Based on the optimal folding angle and combined with the user-side power consumption data, controlling the foldable photovoltaic array to perform adaptive adjustment.

[0154] In this embodiment, the environmental information of the usage site includes light intensity, temperature, wind speed, and cloud cover.

[0155] In this embodiment, the historical usage data includes historical environmental data and historical folding data.

[0156] In this embodiment, controlling the foldable photovoltaic array to perform adaptive adjustment is an adjustment of the folding angle.

[0157] In this embodiment, the adaptive adjustment of the foldable photovoltaic array does not necessarily need to be adjusted according to the minimum angle, and further determination is required according to the user-side power consumption data.

[0158] In this embodiment, the optimal folding angle is determined according to the environmental information as the optimal angle for photovoltaic charging, and the adaptive adjustment also needs to be determined according to the actual power consumption requirements.

[0159] The beneficial effects of the above design are as follows: By collecting the environmental information of the folding photovoltaic use site based on sensors, it provides an environmental information basis for the adaptive control of the folding photovoltaic array. Based on the historical usage data of the folding photovoltaic array and combined with artificial intelligence, an optimal state prediction model is constructed to build an intelligent model for the adaptive control of the folding photovoltaic array, improving the efficiency and accuracy of adaptive control analysis. The environmental information is input into the optimal state prediction model to determine the optimal folding angle. Based on the optimal folding angle, the folding photovoltaic array is controlled for adaptive adjustment. By performing adaptive adjustment on the folding photovoltaic array, the performance of the folding photovoltaic panel is ensured, and the damage to the folding photovoltaic panel is reduced.

[0160] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of this application document and its equivalent technologies, the present invention also intends to include these changes and modifications.

Claims

1. A foldable photovoltaic array adaptive control system based on artificial intelligence, characterized in that Including: A data acquisition module for collecting environmental information of the folded photovoltaic usage site based on sensors; A model construction module for constructing an optimal state prediction model based on the historical usage data of the folded photovoltaic array and combining artificial intelligence; A prediction module for inputting the environmental information into the optimal state prediction model to determine the optimal folding angle; An adjustment module for controlling the folded photovoltaic array to perform adaptive adjustment based on the optimal folding angle and combining the user-side power consumption data.

2. The adaptive control system of a foldable photovoltaic array based on artificial intelligence according to claim 1, characterized in that, The data acquisition module includes: A light intensity monitoring unit for monitoring the light intensity of the folded photovoltaic usage site based on a light sensor; A temperature monitoring unit for monitoring the temperature of the folded photovoltaic usage site based on a temperature sensor; A wind speed monitoring unit for monitoring the wind speed of the folded photovoltaic usage site based on a speed sensor; A cloud cover monitoring unit for monitoring the cloud cover of the folded photovoltaic usage site based on a vision sensor; A receiving and processing unit for receiving the monitoring data from the light intensity monitoring unit, temperature monitoring unit, wind speed monitoring unit, and cloud cover monitoring unit, and preprocessing the monitoring data to obtain the environmental information of the usage site.

3. The adaptive control system for a foldable photovoltaic array based on artificial intelligence according to claim 1, wherein, The model construction module includes: A data processing unit for obtaining the historical environmental data and historical folding data of the folded photovoltaic array, and processing the historical environmental data and historical folding data to obtain target training data; A model construction unit for training an initial artificial intelligence model based on the target training data to obtain an optimal state prediction model.

4. The adaptive control system of a foldable photovoltaic array based on artificial intelligence according to claim 1, characterized in that The prediction module includes: An input unit for obtaining the array layout of the folded photovoltaic array, and inputting the array layout and environmental information into the optimal state prediction model; An analysis unit for analyzing the array layout and environmental information based on the optimal state prediction model to obtain the optimal folding angle.

5. The adaptive control system for a foldable photovoltaic array based on artificial intelligence according to claim 1, wherein, The adjustment module includes: A power consumption prediction unit for determining the user's power consumption cycle and power consumption curve within the power consumption cycle based on the user-side power consumption data, and predicting the user's power consumption in the next period of time based on the power consumption curve; A power consumption judgment unit for obtaining the stored power of the folded photovoltaic array, and judging whether the power difference between the stored power and the power consumption is greater than a preset power; If so, determining the adaptive adjustment parameters for the folded photovoltaic array based on the user-side power consumption data; Otherwise, determining the adaptive adjustment parameters for the folded photovoltaic array based on the optimal folding angle.

6. The adaptive control system of a foldable photovoltaic array based on artificial intelligence according to claim 5, characterized in that, The adjustment module further includes: An angle analysis unit for determining the angle difference and angle folding direction based on the optimal folding angle and combining the current angle of the folded photovoltaic array when adjusting according to the optimal folding angle; A parameter determination unit for determining the adjustment parameters for the folded photovoltaic array based on the angle difference and angle folding direction.

7. An adaptive control system for a foldable photovoltaic array based on artificial intelligence according to claim 5, characterized in that, The adjustment module further includes: A first judgment unit for judging whether the power difference is greater than the maximum preset power when adjusting based on the user-side power consumption data; If so, keeping the current folding angle of the folded photovoltaic array unchanged; Otherwise, based on the environmental prediction model, obtain the temperature prediction curve, wind speed prediction curve, and cloud cover prediction curve for a period of time in the future; A second judgment unit, configured to determine the future photovoltaic charging trend based on the temperature prediction curve, wind speed prediction curve, and cloud cover prediction curve, and in combination with the current angle, and determine whether the future photovoltaic charging trend meets the power consumption curve and the remaining power is greater than the maximum preset power; If so, keep the current folding angle of the foldable photovoltaic array unchanged; Otherwise, determine whether the remaining power is greater than the preset power; If so, based on the optimal state prediction model, determine the predicted optimal angle for a period of time in the future under the temperature prediction curve, wind speed prediction curve, and cloud cover prediction curve, and determine whether the angle difference between the predicted optimal angle and the optimal folding angle is less than the preset angle difference. If so, determine the adaptive adjustment parameter for the foldable photovoltaic array based on the optimal folding angle. Otherwise, select the angle with the smaller angle difference from the predicted optimal angle and the optimal folding angle to the current angle as the adaptive adjustment parameter for the foldable photovoltaic array; Otherwise, determine the adaptive adjustment parameter for the foldable photovoltaic array based on the optimal folding angle.

8. The adaptive control system of a foldable photovoltaic array based on artificial intelligence according to claim 1, wherein It further includes: An inverter module, configured to adaptively adjust the output power of the inverter based on the adaptive adjustment parameter of the foldable photovoltaic array and in combination with the operating parameters of the foldable photovoltaic array. Specifically: An adjustment determination unit, configured to obtain the adaptive adjustment parameter for the foldable photovoltaic array, determine the difference between the collected direct current determined based on the adaptive adjustment parameter and the historical collected direct current, and determine the first adjustment parameter for the output power of the inverter based on the real-time adjustment strategy; A working judgment unit, configured to obtain the voltage, current, power factor, and heating temperature of the inverter itself, obtain the predicted target values of the voltage, current, power factor, and heating temperature under the first adjustment parameter, and determine whether the predicted target values are within the normal working value range; If so, adjust the output power of the inverter based on the first adjustment parameter; Otherwise, continuously reduce the amplitude of the first adjustment parameter until the target value is within the normal working value range, and then determine the adjustment parameter for the output power of the inverter; An action determination unit, configured to obtain the power generation efficiency of the foldable photovoltaic array after adjusting the output power of the inverter for a period of time, and determine whether the power generation efficiency is greater than the historical power generation efficiency; If so, perform a reward action on the real-time adjustment strategy; Otherwise, determine whether the power generation efficiency is greater than the minimum power generation efficiency. If so, do not perform any action on the real-time adjustment strategy. Otherwise, perform a punishment action on the real-time adjustment strategy; A strategy update unit, configured to adaptively adjust the real-time adjustment strategy when the real-time adjustment strategy receives a reward action or a punishment action to obtain the latest adjustment strategy, and the latest adjustment strategy is used for the next output power adjustment.

9. The adaptive control system for a foldable photovoltaic array based on artificial intelligence according to claim 8, wherein The adjustment determination unit includes: A direction determination unit, configured to determine that the first adjustment parameter is an upward adjustment when the difference between the collected direct current and the historical collected direct current is positive, and determine that the first adjustment parameter is a downward adjustment when the difference between the collected direct current and the historical collected direct current is negative; An amplitude determination unit, configured to set the real-time adjustment strategy to mainly adjust the first adjustment parameter by a larger amplitude as the difference between the collected direct current and the historical collected direct current is larger, and secondly, adaptively fine-tune the adjustment amplitude according to the reward action and the punishment action.

10. A method for adaptive control of a foldable photovoltaic array based on artificial intelligence, specifically used in the foldable photovoltaic array adaptive control system as described in claim 1, characterized in that, including: S1: Collect the environmental information of the folding photovoltaic usage site based on the sensor; S2: Based on the historical usage data of the folding photovoltaic array and combined with artificial intelligence, construct an optimal state prediction model; S3: Input the environmental information into the optimal state prediction model to determine the optimal folding angle; S4: Based on the optimal folding angle and combined with the user-side power consumption data, control the folding photovoltaic array to perform adaptive adjustment.

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