Photovoltaic power generation control method and system

Abstract

The invention discloses a photovoltaic power generation control method and system, and the system comprises a distributed sensor network which is used for collecting various environmental parameters of a photovoltaic panel in real time, and the environmental parameters comprise light intensity, temperature, humidity, wind speed and wind direction; the central processing unit is used for receiving and processing the environmental parameters and the meteorological prediction information and generating an angle and load adjustment instruction of the photovoltaic panel through an advanced algorithm; the intelligent actuator system comprises at least two actuators and a driving unit and is used for adjusting the position and the load of the photovoltaic panel according to the instruction; the invention discloses a self-adaptive energy storage system. Through cooperative work of the distributed sensor network and the artificial intelligence module, real-time monitoring, intelligent optimization and fault prediction of the photovoltaic system are achieved, the overall efficiency, reliability and safety of the system are remarkably improved, meanwhile, the cloud data processing platform provides remote monitoring and optimization suggestions, and the system is convenient to use. A user can master and manage the system state anytime and anywhere, and efficient operation and long-term stability of the system are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation control, and in particular to a photovoltaic power generation control method and system. Background Art

[0002] The main function of the photovoltaic power generation control system is to ensure that the photovoltaic panels can operate efficiently and stably under various environmental conditions by monitoring and adjusting the various components of the photovoltaic system, while optimizing the generation, storage and distribution of electricity to maximize the overall performance of the system.

[0003] However, the current photovoltaic power generation control system lacks real-time monitoring and intelligent optimization mechanisms, resulting in low system efficiency and the inability to make precise adjustments based on real-time environmental parameters and meteorological forecast information. In addition, the fault prediction capability is insufficient and usually only detection and repair can be performed after a fault occurs, which increases maintenance costs and affects system reliability.

[0004] In response to the above problems, we have introduced a control method and system for photovoltaic power generation. Summary of the invention

[0005] The invention discloses a photovoltaic power generation control method and system, aiming to solve the technical problems in the background technology.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A photovoltaic power generation control system, comprising:

[0008] A distributed sensor network for real-time collection of multiple environmental parameters of photovoltaic panels, including light intensity, temperature, humidity, wind speed and direction;

[0009] A central processing unit, for receiving and processing the environmental parameters and weather forecast information, and generating angle and load adjustment instructions for photovoltaic panels through advanced algorithms;

[0010] an intelligent actuator system, comprising at least two actuators and a drive unit, for adjusting the position and load of the photovoltaic panel according to the instructions;

[0011] An adaptive energy storage system, comprising at least two energy storage units and an energy management system for dynamically managing the charging and discharging process of the energy storage units;

[0012] Smart inverters with adaptive frequency and voltage control to convert the DC power generated by the photovoltaic panels into AC power and adjust the output power according to grid demand;

[0013] Cloud data processing platform for storing and processing historical data and providing remote monitoring and optimization suggestions;

[0014] Artificial intelligence module, used to optimize system operation strategies in real time and predict and prevent potential failures;

[0015] User terminal interface, including mobile device application and computer interface, is used to display system status and make user settings.

[0016] In a preferred solution, the distributed sensor network includes:

[0017] Light intensity sensor, used to measure the light intensity received at different positions of the photovoltaic panel;

[0018] Temperature sensor, used to monitor the temperature of the photovoltaic panel surface and the surrounding environment;

[0019] Humidity sensor, used to measure the humidity of the environment surrounding the photovoltaic panel;

[0020] Wind speed and direction sensor, used to detect wind speed and direction.

[0021] In a preferred embodiment, the central processing unit comprises:

[0022] Data processing module, used to process the data collected by the sensor network in real time and extract key parameters;

[0023] Algorithm optimization module, which uses deep learning and multi-objective optimization algorithms to generate angle and load adjustment instructions for photovoltaic panels;

[0024] The communication module is used to exchange data and transmit instructions with various actuators, smart inverters and cloud data processing platforms.

[0025] In a preferred embodiment, the intelligent actuator system comprises:

[0026] Electric actuators for precise adjustment of the angle of the photovoltaic panels;

[0027] Hydraulic actuators to stabilize the position of photovoltaic panels in adverse conditions such as high winds;

[0028] The drive unit is used to execute the instructions issued by the central processing unit and feedback the adjustment results.

[0029] In a preferred solution, the adaptive energy storage system includes:

[0030] At least two energy storage units, such as lithium batteries and supercapacitors, to store excess electricity;

[0031] The energy management system is used to monitor the status of each energy storage unit and dynamically adjust the charging and discharging process to ensure the continuous operation and efficient utilization of the system.

[0032] In a preferred solution, the smart inverter includes:

[0033] A power conversion module, used to convert the direct current generated by the photovoltaic panel into alternating current;

[0034] The adaptive control module is used to dynamically adjust the parameters of the output power according to the frequency and voltage requirements of the power grid, ensuring high compatibility and stability with the power grid.

[0035] In a preferred solution, the cloud data processing platform includes:

[0036] Data storage module, used to store historical data collected by the sensor network and system operation logs;

[0037] Data analysis module, used to optimize the system's operating strategy through big data analysis technology;

[0038] Remote monitoring module, used to monitor system status in real time, provide fault alarm and remote control functions.

[0039] In a preferred embodiment, the artificial intelligence module includes:

[0040] The fault prediction submodule predicts potential faults through machine learning algorithms and performs maintenance in advance;

[0041] Optimization submodule, used to optimize the angle and load of photovoltaic panels in real time to improve the overall efficiency and reliability of the system;

[0042] The safety submodule is used to monitor the system operating environment and ensure safe operation under extreme conditions.

[0043] A photovoltaic power generation control method comprises the following steps:

[0044] S1. Collect various environmental parameters of photovoltaic panels in real time through distributed sensor networks, including light intensity, temperature, humidity, wind speed and wind direction. The central processing unit receives and processes the environmental parameters and weather forecast information. The central processing unit generates angle and load adjustment instructions for photovoltaic panels through deep learning and multi-objective optimization algorithms. The intelligent actuator system adjusts the position and load of photovoltaic panels according to the instructions. The adaptive energy storage system dynamically manages the charging and discharging process of the energy storage unit. The intelligent inverter adjusts the frequency and voltage of output power according to grid demand. The cloud data processing platform stores and processes historical data and provides remote monitoring and optimization suggestions. The artificial intelligence module optimizes the system operation strategy in real time, predicts and prevents potential failures. The user terminal interface displays the system status and operating parameters, allowing users to set and manage.

[0045] S2, the light intensity sensor measures the light intensity at different positions of the photovoltaic panel and transmits the data to the central processing unit; the temperature sensor monitors the temperature of the photovoltaic panel surface and the surrounding environment and transmits the data to the central processing unit; the humidity sensor measures the humidity of the environment around the photovoltaic panel and transmits the data to the central processing unit; the wind speed and wind direction sensor detects the wind speed and wind direction and transmits the data to the central processing unit, the data processing module processes the data collected by the sensor network in real time and extracts key parameters; the algorithm optimization module generates the angle and load adjustment instructions of the photovoltaic panel through deep learning and multi-objective optimization algorithms; the communication module transmits the instructions to the intelligent actuator system and the intelligent inverter, and exchanges data with the cloud data processing platform at the same time;

[0046] S3, the electric actuator accurately adjusts the angle of the photovoltaic panel according to the instructions; the hydraulic actuator stabilizes the position of the photovoltaic panel under severe conditions such as strong winds; the drive unit performs the adjustment operation according to the instructions and feeds back the adjustment results to the central processing unit, and the energy management system monitors the status of each energy storage unit, including the power and temperature; dynamically adjusts the charging and discharging process of the energy storage unit according to the current output and environmental parameters of the photovoltaic panel; optimizes the utilization efficiency of the energy storage unit through intelligent algorithms to ensure the continuous operation and efficient utilization of the system;

[0047] S4, the power conversion module converts the direct current generated by the photovoltaic panel into alternating current; the adaptive control module dynamically adjusts the parameters of the output power according to the frequency and voltage requirements of the power grid; the intelligent algorithm is used to ensure the operating efficiency and stability of the inverter, and the data storage module stores the historical data collected by the sensor network and the system operation log; the data analysis module optimizes the system operation strategy through big data analysis technology; the remote monitoring module monitors the system status in real time and provides fault alarm and remote control functions;

[0048] S5. The fault prediction submodule predicts potential faults through machine learning algorithms and performs maintenance in advance. The optimization submodule optimizes the angle and load of the photovoltaic panels in real time through deep learning algorithms to improve the overall efficiency and reliability of the system. The safety submodule ensures the safe operation of the system under extreme conditions through environmental monitoring algorithms. The mobile device application displays environmental parameters and system status in real time and provides user setting functions. The computer interface displays detailed data analysis results and system management interface. The sound and light alarm module alerts users when the system is abnormal.

[0049] The photovoltaic power generation control method and system provided by the present invention have the following advantages:

[0050] The present invention realizes real-time monitoring, intelligent optimization and fault prediction of photovoltaic systems through the collaborative work of distributed sensor networks and artificial intelligence modules, significantly improving the overall efficiency, reliability and safety of the system. At the same time, the cloud data processing platform provides remote monitoring and optimization suggestions, allowing users to understand and manage the system status anytime and anywhere, ensuring efficient operation and long-term stability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a schematic structural diagram of a photovoltaic power generation control system proposed by the present invention.

[0052] Figure 2 The figure is a flow chart of a photovoltaic power generation control method proposed by the present invention. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application usually described and marked in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0054] The invention discloses a photovoltaic power generation control method and system.

[0055] Reference Figure 1 and Figure 2 As shown, a photovoltaic power generation control method and system, comprising:

[0056] A distributed sensor network for real-time collection of multiple environmental parameters of photovoltaic panels, including light intensity, temperature, humidity, wind speed and direction;

[0057] A central processing unit, for receiving and processing the environmental parameters and weather forecast information, and generating angle and load adjustment instructions for photovoltaic panels through advanced algorithms;

[0058] an intelligent actuator system, comprising at least two actuators and a drive unit, for adjusting the position and load of the photovoltaic panel according to the instructions;

[0059] An adaptive energy storage system, comprising at least two energy storage units and an energy management system for dynamically managing the charging and discharging process of the energy storage units;

[0060] Smart inverters with adaptive frequency and voltage control to convert the DC power generated by the photovoltaic panels into AC power and adjust the output power according to grid demand;

[0061] Cloud data processing platform for storing and processing historical data and providing remote monitoring and optimization suggestions;

[0062] Artificial intelligence module, used to optimize system operation strategies in real time and predict and prevent potential failures;

[0063] User terminal interface, including mobile device application and computer interface, used to display system status and perform user settings;

[0064] In a preferred embodiment, the distributed sensor network comprises:

[0065] Light intensity sensor, used to measure the light intensity received at different positions of the photovoltaic panel;

[0066] Temperature sensor, used to monitor the temperature of the photovoltaic panel surface and the surrounding environment;

[0067] Humidity sensor, used to measure the humidity of the environment surrounding the photovoltaic panel;

[0068] Wind speed and direction sensor, used to detect wind speed and direction;

[0069] The distributed sensor network includes a light intensity sensor, which is used to measure the light intensity received at different locations of the photovoltaic panel. The receiving formula is:

[0070]

[0071] Among them I i is the light intensity, x i ,y i is the position coordinate of the sensor on the photovoltaic panel;

[0072] The temperature sensor is used to monitor the temperature of the photovoltaic panel surface and the surrounding environment. The formula is:

[0073]

[0074] Where T i is the temperature of the photovoltaic panel surface, x i ,y i is the position coordinate of the sensor on the photovoltaic panel;

[0075] as well as:

[0076] T e =h()

[0077] Where T e is the temperature of the surrounding environment;

[0078] The humidity sensor is used to measure the humidity of the environment around the photovoltaic panel. The formula is:

[0079] H=j()

[0080] Where H is humidity;

[0081] Wind speed and direction sensor is used to detect wind speed. The formula is:

[0082] W s =k()

[0083] Wind direction detection:

[0084] W d = l()

[0085] Where W s is the wind speed, W d It's the wind direction.

[0086] In a preferred embodiment, the central processing unit comprises:

[0087] Data processing module, used to process the data collected by the sensor network in real time and extract key parameters;

[0088] Algorithm optimization module, which uses deep learning and multi-objective optimization algorithms to generate angle and load adjustment instructions for photovoltaic panels;

[0089] Communication module, used for data exchange and command transmission with various actuators, smart inverters and cloud data processing platforms;

[0090] The data processing module is used to process the data collected by the sensor network in real time and extract key parameters. The formula is:

[0091] P k =extract(D)

[0092] Where D is the data set collected by the sensor;

[0093] The algorithm optimization module uses deep learning and multi-objective optimization algorithms to generate the angle θ and load adjustment instruction L of the photovoltaic panel. The formula is:

[0094]

[0095] Where P k is the key parameter for extraction;

[0096] The communication module is used to exchange data and transmit instructions with each actuator, intelligent transformer and cloud data processing platform. The formula is:

[0097]

[0098] Among them, E is the actuator, I is the smart inverter, and C is the cloud data processing platform.

[0099] In a preferred embodiment, the intelligent actuator system comprises:

[0100] Electric actuators for precise adjustment of the angle of the photovoltaic panels;

[0101] Hydraulic actuators to stabilize the position of photovoltaic panels in adverse conditions such as high winds;

[0102] A driving unit, used to execute instructions issued by the central processing unit and feed back adjustment results;

[0103] Electric actuators are used to precisely adjust the angle of the photovoltaic panel. The formula is:

[0104] θ=adjust_angle(I θ )

[0105] Among them I θ It is the angle adjustment command issued by the central processing unit;

[0106] Hydraulic actuators are used to stabilize the position of photovoltaic panels under adverse conditions such as strong winds. The formula is:

[0107]

[0108] Where W s is the wind speed, W d It is the wind direction;

[0109] The drive unit is used to execute the instructions issued by the central processing unit and feedback the adjustment results. Its calculation formula is:

[0110]

[0111] Among them I θ is the angle adjustment instruction, I L is the load adjustment instruction, and R is the adjustment result.

[0112] In a preferred embodiment, the adaptive energy storage system comprises:

[0113] At least two energy storage units, such as lithium batteries and supercapacitors, to store excess electricity;

[0114] Energy management system, which monitors the status of each energy storage unit and dynamically adjusts the charging and discharging process to ensure continuous operation and efficient utilization of the system;

[0115] Energy storage unit, such as lithium battery B i And super capacitor C j, used to store excess electricity, the formula is:

[0116]

[0117] The energy management system is used to monitor the status of each energy storage unit. The formula is:

[0118] S i =monitor(B i )

[0119] and

[0120] S j =monitor(C j )

[0121] The formula for dynamically adjusting the charging and discharging process is:

[0122]

[0123] Ensure continuous operation and efficient utilization of the system.

[0124] In a preferred embodiment, the smart inverter comprises:

[0125] A power conversion module, used to convert the direct current generated by the photovoltaic panel into alternating current;

[0126] Adaptive control module, used to dynamically adjust the parameters of output power according to the frequency and voltage requirements of the power grid, ensuring high compatibility and stability with the power grid;

[0127] The power conversion module is used to convert the DC power generated by the photovoltaic panel into DC Converted to alternating current, the formula is:

[0128] V AC =convert(V DC )

[0129] Adaptive control module, used to adjust the frequency f of the power grid grid and voltage requirement V grid The parameters for dynamically adjusting the output power are as follows:

[0130]

[0131] Ensure high compatibility and stability with the power grid.

[0132] Smart inverters achieve intelligent effects by monitoring grid parameters in real time and using adaptive control algorithms to adjust.

[0133] In a preferred embodiment, the cloud data processing platform includes:

[0134] Data storage module, used to store historical data collected by the sensor network and system operation logs;

[0135] Data analysis module, used to optimize the system's operating strategy through big data analysis technology;

[0136] Remote monitoring module, used to monitor system status in real time, provide fault alarm and remote control functions;

[0137] Data storage module, used to store historical data collected by sensor network hist and system operation log sys , the formula is:

[0138]

[0139] The data analysis module is used to optimize the system's operating strategy through big data analysis technology. The formula is:

[0140]

[0141] Remote monitoring module, used to monitor system status in real time, its formula is:

[0142] S realtime，提供故障报警 A alarm = detect_fault(S realtime )

[0143] Remote control function, the formula is:

[0144] C remote =remote_control(S realtime )

[0145] In a preferred embodiment, the artificial intelligence module includes:

[0146] The fault prediction submodule predicts potential faults through machine learning algorithms and performs maintenance in advance;

[0147] Optimization submodule, used to optimize the angle and load of photovoltaic panels in real time to improve the overall efficiency and reliability of the system;

[0148] Safety submodule, used to monitor the system operating environment and ensure safe operation under extreme conditions;

[0149] The fault prediction submodule predicts potential faults through machine learning algorithms and performs maintenance in advance. The formula is:

[0150] P fault =predict_fault(D scusor )

[0151] The optimization submodule is used to optimize the angle of the photovoltaic panel in real time. The formula is:

[0152] θ opt =optimize_angle(D sensor )

[0153] Load formula:

[0154] L opt =optimize_load(D scnsor )

[0155] To improve the overall efficiency and reliability of the system;

[0156] The safety submodule is used to monitor the system operating environment and ensure safe operation under extreme conditions. The formula is:

[0157] S safe =monitor_environment(D scensor )

[0158] A photovoltaic power generation control method comprises the following steps:

[0159] S1. Collect various environmental parameters of photovoltaic panels in real time through distributed sensor networks, including light intensity, temperature, humidity, wind speed and wind direction. The central processing unit receives and processes the environmental parameters and weather forecast information. The central processing unit generates angle and load adjustment instructions for photovoltaic panels through deep learning and multi-objective optimization algorithms. The intelligent actuator system adjusts the position and load of photovoltaic panels according to the instructions. The adaptive energy storage system dynamically manages the charging and discharging process of the energy storage unit. The intelligent inverter adjusts the frequency and voltage of output power according to grid demand. The cloud data processing platform stores and processes historical data and provides remote monitoring and optimization suggestions. The artificial intelligence module optimizes the system operation strategy in real time, predicts and prevents potential failures. The user terminal interface displays the system status and operating parameters, allowing users to set and manage.

[0160] S2, the light intensity sensor measures the light intensity at different positions of the photovoltaic panel and transmits the data to the central processing unit; the temperature sensor monitors the temperature of the photovoltaic panel surface and the surrounding environment and transmits the data to the central processing unit; the humidity sensor measures the humidity of the environment around the photovoltaic panel and transmits the data to the central processing unit; the wind speed and wind direction sensor detects the wind speed and wind direction and transmits the data to the central processing unit, the data processing module processes the data collected by the sensor network in real time and extracts key parameters; the algorithm optimization module generates the angle and load adjustment instructions of the photovoltaic panel through deep learning and multi-objective optimization algorithms; the communication module transmits the instructions to the intelligent actuator system and the intelligent inverter, and exchanges data with the cloud data processing platform at the same time;

[0161] S3, the electric actuator accurately adjusts the angle of the photovoltaic panel according to the instructions; the hydraulic actuator stabilizes the position of the photovoltaic panel under severe conditions such as strong winds; the drive unit performs the adjustment operation according to the instructions and feeds back the adjustment results to the central processing unit, and the energy management system monitors the status of each energy storage unit, including the power and temperature; dynamically adjusts the charging and discharging process of the energy storage unit according to the current output and environmental parameters of the photovoltaic panel; optimizes the utilization efficiency of the energy storage unit through intelligent algorithms to ensure the continuous operation and efficient utilization of the system;

[0162] S4, the power conversion module converts the direct current generated by the photovoltaic panel into alternating current; the adaptive control module dynamically adjusts the parameters of the output power according to the frequency and voltage requirements of the power grid; the intelligent algorithm is used to ensure the operating efficiency and stability of the inverter, and the data storage module stores the historical data collected by the sensor network and the system operation log; the data analysis module optimizes the system operation strategy through big data analysis technology; the remote monitoring module monitors the system status in real time and provides fault alarm and remote control functions;

[0163] S5. The fault prediction submodule predicts potential faults through machine learning algorithms and performs maintenance in advance. The optimization submodule optimizes the angle and load of the photovoltaic panels in real time through deep learning algorithms to improve the overall efficiency and reliability of the system. The safety submodule ensures the safe operation of the system under extreme conditions through environmental monitoring algorithms. The mobile device application displays environmental parameters and system status in real time and provides user setting functions. The computer interface displays detailed data analysis results and system management interface. The sound and light alarm module alerts users when the system is abnormal.

[0164] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. The replacement may be a replacement of a part of the structure, device, method step, or a complete technical solution. Any equivalent replacement or change according to the technical solution and the inventive concept of the present invention shall be covered within the protection scope of the present invention.

Claims

1. A photovoltaic power generation control system, characterized in that: include: A distributed sensor network for real-time collection of multiple environmental parameters of photovoltaic panels, including light intensity, temperature, humidity, wind speed and direction; A central processing unit, for receiving and processing the environmental parameters and weather forecast information, and generating angle and load adjustment instructions for photovoltaic panels through advanced algorithms; an intelligent actuator system, comprising at least two actuators and a drive unit, for adjusting the position and load of the photovoltaic panel according to the instructions; An adaptive energy storage system, comprising at least two energy storage units and an energy management system for dynamically managing the charging and discharging process of the energy storage units; Smart inverters with adaptive frequency and voltage control to convert the DC power generated by the photovoltaic panels into AC power and adjust the output power according to grid demand; Cloud data processing platform for storing and processing historical data and providing remote monitoring and optimization suggestions; Artificial intelligence module, used to optimize system operation strategies in real time and predict and prevent potential failures; User terminal interface, including mobile device application and computer interface, is used to display system status and make user settings.

2. The photovoltaic power generation control system according to claim 1, characterized in that: The distributed sensor network comprises: Light intensity sensor, used to measure the light intensity received at different positions of the photovoltaic panel; Temperature sensor, used to monitor the temperature of the photovoltaic panel surface and the surrounding environment; Humidity sensor, used to measure the humidity of the environment surrounding the photovoltaic panel; Wind speed and direction sensor, used to detect wind speed and direction.

3. The photovoltaic power generation control system according to claim 1, characterized in that: The central processing unit comprises: Data processing module, used to process the data collected by the sensor network in real time and extract key parameters; Algorithm optimization module, which uses deep learning and multi-objective optimization algorithms to generate angle and load adjustment instructions for photovoltaic panels; The communication module is used to exchange data and transmit instructions with various actuators, smart inverters and cloud data processing platforms.

4. The photovoltaic power generation control system according to claim 1, characterized in that: The smart actuator system comprises: Electric actuators for precise adjustment of the angle of the photovoltaic panels; Hydraulic actuators to stabilize the position of photovoltaic panels in adverse conditions such as high winds; The drive unit is used to execute the instructions issued by the central processing unit and feedback the adjustment results.

5. The photovoltaic power generation control system according to claim 1, characterized in that: The adaptive energy storage system comprises: At least two energy storage units, such as lithium batteries and supercapacitors, to store excess electricity; The energy management system is used to monitor the status of each energy storage unit and dynamically adjust the charging and discharging process to ensure the continuous operation and efficient utilization of the system.

6. The photovoltaic power generation control system according to claim 1, characterized in that: The smart inverter comprises: A power conversion module, used to convert the direct current generated by the photovoltaic panel into alternating current; The adaptive control module is used to dynamically adjust the parameters of the output power according to the frequency and voltage requirements of the power grid, ensuring high compatibility and stability with the power grid.

7. The photovoltaic power generation control system according to claim 1, characterized in that: The cloud data processing platform includes: Data storage module, used to store historical data collected by the sensor network and system operation logs; Data analysis module, used to optimize the system's operating strategy through big data analysis technology; Remote monitoring module, used to monitor system status in real time, provide fault alarm and remote control functions.

8. The photovoltaic power generation control system according to claim 1, characterized in that: The artificial intelligence module includes: The fault prediction submodule predicts potential faults through machine learning algorithms and performs maintenance in advance; Optimization submodule, used to optimize the angle and load of photovoltaic panels in real time to improve the overall efficiency and reliability of the system; The safety submodule is used to monitor the system operating environment and ensure safe operation under extreme conditions.

9. A photovoltaic power generation control method according to any one of claims 1 to 8, characterized in that: The following steps are involved: S1. Collect various environmental parameters of photovoltaic panels in real time through distributed sensor networks, including light intensity, temperature, humidity, wind speed and wind direction. The central processing unit receives and processes the environmental parameters and weather forecast information. The central processing unit generates angle and load adjustment instructions for photovoltaic panels through deep learning and multi-objective optimization algorithms. The intelligent actuator system adjusts the position and load of photovoltaic panels according to the instructions. The adaptive energy storage system dynamically manages the charging and discharging process of the energy storage unit. The intelligent inverter adjusts the frequency and voltage of output power according to grid demand. The cloud data processing platform stores and processes historical data and provides remote monitoring and optimization suggestions. The artificial intelligence module optimizes the system operation strategy in real time, predicts and prevents potential failures. The user terminal interface displays the system status and operating parameters, allowing users to set and manage. S2, the light intensity sensor measures the light intensity at different positions of the photovoltaic panel and transmits the data to the central processing unit; the temperature sensor monitors the temperature of the photovoltaic panel surface and the surrounding environment and transmits the data to the central processing unit; the humidity sensor measures the humidity of the environment around the photovoltaic panel and transmits the data to the central processing unit; the wind speed and wind direction sensor detects the wind speed and wind direction and transmits the data to the central processing unit, the data processing module processes the data collected by the sensor network in real time and extracts key parameters; the algorithm optimization module generates the angle and load adjustment instructions of the photovoltaic panel through deep learning and multi-objective optimization algorithms; the communication module transmits the instructions to the intelligent actuator system and the intelligent inverter, and exchanges data with the cloud data processing platform at the same time; S3, the electric actuator accurately adjusts the angle of the photovoltaic panel according to the instructions; the hydraulic actuator stabilizes the position of the photovoltaic panel under severe conditions such as strong winds; the drive unit performs the adjustment operation according to the instructions and feeds back the adjustment results to the central processing unit, and the energy management system monitors the status of each energy storage unit, including the power and temperature; dynamically adjusts the charging and discharging process of the energy storage unit according to the current output and environmental parameters of the photovoltaic panel; optimizes the utilization efficiency of the energy storage unit through intelligent algorithms to ensure the continuous operation and efficient utilization of the system; S4, the power conversion module converts the direct current generated by the photovoltaic panel into alternating current; The adaptive control module dynamically adjusts the parameters of the output power according to the frequency and voltage requirements of the power grid; the intelligent algorithm ensures the operating efficiency and stability of the inverter; the data storage module stores the historical data collected by the sensor network and the system operation log; the data analysis module optimizes the system operation strategy through big data analysis technology; the remote monitoring module monitors the system status in real time and provides fault alarm and remote control functions; S5, the fault prediction submodule predicts potential faults through machine learning algorithms and performs maintenance in advance; the optimization submodule optimizes the angle and load of photovoltaic panels in real time through deep learning algorithms to improve the overall efficiency and reliability of the system; the safety submodule ensures the safe operation of the system under extreme conditions through environmental monitoring algorithms, and the mobile device application displays environmental parameters and system status in real time and provides user setting functions; the computer interface displays detailed data analysis results and system management interface; The sound and light alarm module warns the user when the system is abnormal.

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