A High-Efficiency and High-Reliability Power Conversion Control Method for Photovoltaic Power Generation

Abstract

The present invention relates to the technical field of power energy storage dispatching. A high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention monitors the environment and equipment status of a photovoltaic power station in real time, and uses an environmental monitoring and early warning model, a maximum power point tracking algorithm, and a power generation power calculation model to dynamically adjust equipment parameters to ensure that photovoltaic cells operate at the maximum power point. If the actual power does not match the expectation, a genetic algorithm is used to optimize the power generation power calculation model and correct the control commands of the photovoltaic power station equipment. The present invention solves the problems of the stability and reliability of the power conversion system in extreme environments, improves the energy conversion efficiency, reduces the operation and maintenance costs and failure rates, and realizes the efficient and stable operation of the photovoltaic power station.

Description

Technical Field

[0001] The present invention relates to the technical field of power energy storage scheduling, and particularly to a method for efficient and highly reliable power conversion control of photovoltaic power generation. Background Art

[0002] The efficient and highly reliable power conversion of photovoltaic power generation means that in a photovoltaic power generation system, through the adoption of advanced technologies and methods, the DC electric energy generated by photovoltaic cells is efficiently and stably converted into AC electric energy to meet the requirements of grid connection or load use. High efficiency means high energy conversion efficiency during the power conversion process, minimizing energy loss as much as possible. High reliability means that the power conversion system can operate stably under various environmental conditions, reducing the failure rate and maintenance cost.

[0003] In the field of photovoltaic power generation, the methods for efficient and highly reliable power conversion control mainly adopt the maximum power point tracking technology and the design of efficient inverters. The maximum power point tracking technology adjusts the working point of the photovoltaic cells in real time by monitoring their working states to keep them at the maximum power output state, thereby improving the energy conversion efficiency. The design of efficient inverters adopts sine wave pulse width modulation or space vector pulse width modulation technology to improve the quality of the output voltage waveform of the inverter and reduce the harmonic content. By increasing the number of output levels of the inverter, the harmonics of the output voltage are further reduced, improving the power quality. The application of soft switching technology in the inverter design reduces the energy loss during the switching process and improves the inversion efficiency.

[0004] The maximum power point tracking technology can improve the energy conversion efficiency, but existing methods such as the perturbation observation method and the incremental conductance method have problems of stable error or slow tracking speed. Under rapidly changing environmental conditions such as a sharp change in light intensity, although the intelligent control system provides real-time monitoring and diagnosis functions, under extreme environmental conditions, such as high temperature, high humidity, and strong electromagnetic interference, the stability and reliability of the power conversion system are affected. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a method for efficient and highly reliable power conversion control of photovoltaic power generation to solve the problem that the stability and reliability of the power conversion system are affected under extreme environmental conditions, such as high temperature, high humidity, and strong electromagnetic interference.

[0006] To solve the above technical problems, the specific technical solution of the present invention is as follows:

[0007] The present invention provides a method for efficient and highly reliable power conversion control of photovoltaic power generation, including:

[0008] Step S101: Obtain the data information of the photovoltaic power station. According to the data information of the photovoltaic power station, determine the photovoltaic power station equipment and the location information of the photovoltaic power station equipment. According to the photovoltaic power station equipment and the location information of the photovoltaic power station equipment, match the corresponding data information to be obtained in the preset knowledge base. According to the data information to be obtained, obtain the power generation operation data, temperature data, humidity data, and electromagnetic field intensity data of the photovoltaic power station equipment;

[0009] Step S102: Receive the photovoltaic power station environmental monitoring parameters, photovoltaic power station warning parameters, and expected photovoltaic power generation. Substitute the photovoltaic power station environmental monitoring parameters into the preset photovoltaic power station environmental monitoring model, and use the preset photovoltaic power station environmental monitoring model to monitor the operation environment data of the equipment in the photovoltaic power station to obtain the photovoltaic power station environmental data monitoring result. Substitute the photovoltaic power station warning parameters into the photovoltaic power station warning model, and use the photovoltaic power station warning model to warn the operation status of the equipment in the photovoltaic power station to obtain the photovoltaic power station warning result;

[0010] Step S103: Substitute the photovoltaic power station environmental data monitoring result and the photovoltaic power station warning result into the maximum power point tracking algorithm to calculate the control adjustment parameters of the equipment in the photovoltaic power station. Convert the control adjustment parameters of the equipment in the photovoltaic power station into the control command of the equipment in the photovoltaic power station, and collect the data information of the equipment in the photovoltaic power station after executing the control command of the equipment in the photovoltaic power station;

[0011] Step S104: Calculate the photovoltaic power generation of the photovoltaic power station after the control command is executed by using the preset photovoltaic power station power generation calculation model for the data information of the equipment in the photovoltaic power station after executing the control command of the equipment in the photovoltaic power station. Compare the photovoltaic power generation of the photovoltaic power station after the control command is executed with the expected photovoltaic power generation to obtain the comparison result of the actual power and the expected power;

[0012] Step S105: If the actual power and the expected power are inconsistent in the comparison result of the actual power and the expected power, extract the features of the data generated during the monitoring of the operation environment data of the equipment in the photovoltaic power station, and extract the features of the data generated during the warning of the operation status of the equipment in the photovoltaic power station by using the photovoltaic power station warning model to obtain the environmental data and the warning data feature set. Use the environmental data and the warning data feature set, the photovoltaic power station environmental monitoring parameters, and the photovoltaic power station warning parameters to optimize the photovoltaic power station power generation calculation model through the genetic algorithm to obtain the optimized photovoltaic power station power generation calculation model. Use the optimized photovoltaic power station power generation calculation model to calculate the data information of the equipment in the photovoltaic power station after executing the control command of the equipment in the photovoltaic power station to obtain the corrected control command of the photovoltaic power station equipment.

[0013] Further, the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S101, includes:

[0014] Determine the interface and communication protocol for data communication with the photovoltaic power station. The communication protocol includes HTTP and MQTT, and obtain the data of the devices in the photovoltaic power station through the interface.

[0015] The data format of the communication protocol adopts XML format, and set the corresponding encryption model and decryption model for the communication protocol data in XML format;

[0016] Receive the data sent by the photovoltaic power station in real time, parse the received data, and extract the data information of the photovoltaic power station. The data information of the photovoltaic power station includes device data and environmental monitoring parameters.

[0017] The extracted device data is classified according to the data type to obtain power generation operation data, temperature data, humidity data, and electromagnetic field strength data.

[0018] Further, the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S101, includes:

[0019] The server identifies the photovoltaic power station device corresponding to each data item through the device identifier. The device identifier includes the device ID and the device serial number;

[0020] The device location information is obtained through the preset location coordinates or the real-time positioning system, and the corresponding location information is queried in the database according to the device identifier;

[0021] According to the photovoltaic power station device and the location information, the server matches the corresponding data information to be obtained in the preset knowledge base. The knowledge base includes the performance parameters, historical operation data, and environmental data of the devices in the photovoltaic power station;

[0022] After obtaining the power generation operation data, temperature data, humidity data, and electromagnetic field strength data of the photovoltaic power station device, the server preprocesses the power generation operation data, temperature data, humidity data, and electromagnetic field strength data of the photovoltaic power station device to obtain the preprocessed operation data.

[0023] Further, the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S102, includes:

[0024] Receive the environmental monitoring parameters from the photovoltaic power station in real time. The environmental monitoring parameters include the temperature of the devices in the photovoltaic power station, the humidity of the devices in the photovoltaic power station, the wind speed of the devices in the photovoltaic power station, and the light intensity of the devices in the photovoltaic power station. The warning parameters include the temperature threshold, the humidity threshold, the device failure warning threshold, and the expected photovoltaic power generation power;

[0025] Pre - deploy and load a photovoltaic power station environmental monitoring model, which is constructed by training machine learning algorithms based on historical data and historical technical solutions and is used to evaluate the operating environment status of equipment in the photovoltaic power station;

[0026] Substitute the received environmental monitoring parameters into the loaded photovoltaic power station environmental monitoring model.

[0027] Furthermore, for the high - efficiency and high - reliability power conversion control method for photovoltaic power generation provided by the present invention, step S102 includes:

[0028] Use the preset photovoltaic power station environmental monitoring model to calculate the input environmental monitoring parameters to monitor the operating environment data of equipment in the photovoltaic power station:

[0029] After the photovoltaic power station environmental monitoring model calculation is completed, output the photovoltaic power station environmental data monitoring result, which includes the operating status of the equipment. The operating status of the equipment includes normal, abnormal, warning, real - time values of environmental parameters, and predicted values of environmental parameters;

[0030] Substitute the received photovoltaic power station early - warning parameters into the photovoltaic power station early - warning model for early - warning analysis of the equipment operating status. The photovoltaic power station early - warning model judges the equipment operating status based on preset thresholds and is used to detect potential equipment failures;

[0031] Integrate the environmental monitoring result and the early - warning result to form the photovoltaic power station environmental data monitoring data, which contains the equipment operating status, environmental parameters, and early - warning information.

[0032] Furthermore, for the high - efficiency and high - reliability power conversion control method for photovoltaic power generation provided by the present invention, step S103 includes:

[0033] Integrate the photovoltaic power station environmental data monitoring result and the early - warning result obtained in step S102. The integrated data set includes real - time monitoring values of environmental parameters such as temperature, humidity, and light intensity, the operating status of the equipment, and early - warning information. The early - warning information includes that the equipment is about to overheat and the power generation is lower than expected;

[0034] Calculate the integrated data set through the maximum power point tracking algorithm. The maximum power point tracking algorithm calculates the optimal operating voltage and current based on environmental data and the real - time status of the equipment, and maximizes the power output of the photovoltaic cells;

[0035] Based on the output of the maximum power point tracking algorithm, calculate the control adjustment parameters of the equipment in the photovoltaic power station. The control adjustment parameters of the equipment in the photovoltaic power station include the output voltage and frequency of the inverter, the tilt angle of the photovoltaic panel, the charging and discharging rates of the battery pack.

[0036] Further, the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S103, includes:

[0037] Convert the calculated control adjustment parameters into device control commands, and send the device control commands to the inverters, tracking systems, and battery management systems in the photovoltaic power station;

[0038] After the devices in the photovoltaic power station receive the control commands, perform corresponding operations, and the corresponding operations include adjusting the output voltage and changing the tilt angle of the photovoltaic panels;

[0039] Collect the data information after the devices execute the control commands, including the actual working status, output power, and current and voltage parameters of the devices.

[0040] Further, the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S104, includes:

[0041] Collect the data information after the devices in the photovoltaic power station execute the control commands, including the output power of the inverter, the voltage and current of the photovoltaic panels, and the charge and discharge status of the battery pack.

[0042] Pre-deploy and load a photovoltaic power station power generation calculation model for predicting or calculating its power generation based on the operating status of the photovoltaic power station;

[0043] Input the preprocessed data into the preset photovoltaic power station power generation calculation model, and the photovoltaic power station power generation calculation model calculates the actual power generation of the photovoltaic power station according to the input data of light intensity, temperature, device status, and the logic of the photovoltaic power station power generation calculation model.

[0044] Further, the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S104, includes:

[0045] Compare the calculated actual power generation with the expected photovoltaic power generation, and the expected photovoltaic power generation is set based on historical data, weather forecasts, or user requirements.

[0046] Analyze the comparison result of the actual power generation and the expected photovoltaic power generation. If the comparison result of the actual power generation and the expected photovoltaic power generation is consistent or the difference between the comparison result of the actual power generation and the expected photovoltaic power generation is within the preset error range, the operating status of the photovoltaic power station is good and the control command is effectively executed. If the difference between the comparison result of the actual power generation and the expected photovoltaic power generation is not within the preset error range, the operating status of the photovoltaic power station is abnormal, and the abnormal operating status of the photovoltaic power station includes equipment failures, environmental condition changes, or control strategy errors.

[0047] Furthermore, the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S105, includes:

[0048] Extract features from the data generated during the process of using a preset environmental monitoring model for a photovoltaic power station to monitor environmental data. The features to be extracted include real-time values, historical change trends, extreme values, etc. of environmental parameters such as temperature, humidity, and light intensity.

[0049] Also extract features from the data generated during the process of using a warning model for a photovoltaic power station to warn of the operating status of equipment, including equipment fault warning signals, abnormal status identifiers, and maintenance history features.

[0050] Integrate the data features extracted from the environmental monitoring and warning processes to form an environmental data and warning data feature set.

[0051] Use a genetic algorithm to optimize the power generation calculation model for a photovoltaic power station. Take the environmental data and warning data feature set, photovoltaic power station environmental monitoring parameters, and warning parameters as the input of the genetic algorithm. The genetic algorithm generates new candidate solutions for the power generation calculation model and evaluates the new candidate solutions for the power generation calculation model. The evaluation is based on the deviation between the actual power and the expected power, the prediction accuracy of the model, and the stability index of the model.

[0052] Through iterative genetic algorithm convergence to the optimal power generation calculation model, verify the optimized power generation calculation model. When the optimized power generation calculation model passes the verification, deploy the optimized power generation calculation model to the server and replace the original power generation calculation model.

[0053] Use the optimized power generation calculation model to calculate the data information after the control command is executed on the equipment in the photovoltaic power station, and calculate the power generation of the photovoltaic power station.

[0054] According to the calculation results of the optimized model, correct the control commands for the photovoltaic power station. The correction includes adjusting the output voltage and frequency of the inverter, changing the tilt angle of the photovoltaic panel, and optimizing the charge and discharge strategy of the battery pack, and send the corrected control commands to the equipment in the photovoltaic power station.

[0055] Advantages of the present invention: By real-time monitoring the operating environment and equipment status of the photovoltaic power station, the present invention can timely discover potential problems under extreme environmental conditions, and give early warnings and handle them, thereby improving the stability and reliability of the power conversion system. Extreme environmental conditions include high temperature, high humidity, and strong electromagnetic interference.

[0056] By adopting the maximum power point tracking algorithm, the present invention can dynamically adjust the working states of the devices in the photovoltaic power station, enabling the photovoltaic cells to always operate at the maximum power output state, thereby improving the energy conversion efficiency and reducing energy losses.

[0057] By optimizing the power generation calculation model of the photovoltaic power station through the genetic algorithm, the present invention can generate new model candidate solutions based on real-time monitoring data and warning information, and conduct evaluation and optimization, enabling the model to adapt to changing environmental conditions and improving the system's adaptability and intelligence level.

[0058] During the control process, the present invention collects the data information of the devices after executing the control commands in real time and conducts feedback control. The real-time monitoring and feedback mechanism enables the system to quickly respond to environmental changes and timely adjust the control strategy, thereby maintaining the stable operation of the system.

[0059] By giving early warnings and timely handling potential problems, the present invention can reduce the occurrence of equipment failures and lower the operation and maintenance costs. At the same time, the efficient and stable power conversion system also helps to improve the overall economic benefits of the photovoltaic power station.

[0060] In summary, the beneficial effects of the present invention are mainly reflected in improving the stability and reliability of the power conversion system, enhancing the energy conversion efficiency, achieving intelligent optimization and adaptive adjustment, strengthening the real-time monitoring and feedback control capabilities, and reducing the operation and maintenance costs and the failure rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions of the present invention, the following will briefly introduce the drawings required in the embodiments. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0062] Figure 1 It is a schematic flowchart of the method provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0063] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions of the present invention in conjunction with the specific embodiments and corresponding drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention. The following will, with reference to the drawings, detail the technical solutions provided by each embodiment of the present invention.

[0064] To better understand the objectives of the present invention, the following will further describe the present invention in detail.

[0065] Please refer to Figure 1 , the present invention provides a method for efficient and highly reliable power conversion control of photovoltaic power generation, including:

[0066] The present invention provides a method for efficient and highly reliable power conversion control of photovoltaic power generation, including:

[0067] Step S101, obtain the data information of the photovoltaic power station. According to the data information of the photovoltaic power station, determine the equipment of the photovoltaic power station and the location information of the photovoltaic power station equipment. According to the photovoltaic power station equipment and the location information of the photovoltaic power station equipment, match the corresponding data information to be obtained in the preset knowledge base. According to the data information to be obtained, obtain the power generation operation data, temperature data, humidity data and electromagnetic field intensity data of the photovoltaic power station equipment;

[0068] First, obtain the data of the equipment in the photovoltaic power station through the preset interface and communication protocol (such as HTTP and MQTT).

[0069] Obtain the data information of the photovoltaic power station in real time, and analyze the data information of the photovoltaic power station to extract useful information.

[0070] The extracted data types include equipment data and environmental monitoring parameters. The equipment data is further classified into power generation operation data, temperature data, humidity data and electromagnetic field intensity data.

[0071] The power generation operation data refers to the data directly related to the power generation performance generated during the operation of the photovoltaic power station, such as the current, voltage, and power generation of the photovoltaic panel.

[0072] The temperature data records the temperature conditions of the equipment in the photovoltaic power station, including the temperatures of key components such as photovoltaic panels, inverters, and batteries, which is very important for evaluating the working state of the equipment and preventing overheating.

[0073] The humidity data reflects the humidity conditions of the operating environment of the photovoltaic power station. High humidity may affect the insulation performance and operating stability of the equipment.

[0074] The electromagnetic field intensity data is used to monitor the electromagnetic environment around the photovoltaic power station. Strong electromagnetic fields may interfere with the normal operation of the equipment.

[0075] The data information of the photovoltaic power station is input into the preset photovoltaic power station environment monitoring model for real-time monitoring of the operating environment state of the equipment in the photovoltaic power station. At the same time, based on the data information of the photovoltaic power station, the photovoltaic power station warning model can give early warnings of potential equipment failures to ensure the stable operation of the photovoltaic power station.

[0076] Power generation operation data, temperature data, humidity data, and electromagnetic field intensity data are also used to calculate the optimal control adjustment parameters of the equipment in the photovoltaic power station, such as the output voltage and frequency of the inverter, the tilt angle of the photovoltaic panels, etc. The dynamic adjustment of the control parameters aims to ensure that the photovoltaic cells operate at the maximum power point, thereby improving the energy conversion efficiency.

[0077] Before the acquired data is used for monitoring, early warning, and control strategy adjustment, it is usually preprocessed to improve the accuracy and reliability of the data. The data information after the execution of the control command is also collected and fed back to evaluate the effect of the control command and make further adjustments and optimizations as needed.

[0078] In summary, the power generation operation data, temperature data, humidity data, and electromagnetic field intensity data of the photovoltaic power station equipment play a crucial role in the monitoring, early warning, and control processes of the photovoltaic power station.

[0079] Step S102, receive the photovoltaic power station environmental monitoring parameters, photovoltaic power station early warning parameters, and expected photovoltaic power generation. Substitute the photovoltaic power station environmental monitoring parameters into the preset photovoltaic power station environmental monitoring model, and use the preset photovoltaic power station environmental monitoring model to monitor the operation environment data of the equipment in the photovoltaic power station to obtain the photovoltaic power station environmental data monitoring result. Substitute the photovoltaic power station early warning parameters into the photovoltaic power station early warning model, and use the photovoltaic power station early warning model to give an early warning of the operation status of the equipment in the photovoltaic power station to obtain the photovoltaic power station early warning result;

[0080] The photovoltaic power station environmental monitoring model is a model used to evaluate the operation environment status of the equipment in the photovoltaic power station. It is constructed by inputting the environmental monitoring parameters of the photovoltaic power station (such as temperature, humidity, wind speed, light intensity, etc.) and training machine learning algorithms using historical data and technical solutions. The main function of the photovoltaic power station environmental monitoring model is to monitor the operation environment data of the equipment in the photovoltaic power station in real time, including calculating the real-time values and predicted values of environmental parameters, and evaluating the operation status of the equipment (such as normal, abnormal, warning, etc.). In the high-efficiency and high-reliability power conversion control method for photovoltaic power generation, the photovoltaic power station environmental monitoring model is used to monitor the operation environment of the photovoltaic power station in real time, providing data support for subsequent power conversion control and optimization.

[0081] The photovoltaic power station early warning model is a model that judges the equipment operation status based on preset thresholds. The photovoltaic power station early warning model gives an early warning of potential equipment failures by analyzing the early warning parameters of the photovoltaic power station (such as temperature thresholds, humidity thresholds, equipment failure early warning thresholds, etc.).

[0082] The main function of the photovoltaic power station warning model is to timely detect potential faults of the equipment in the photovoltaic power station, and improve the stability and reliability of the system through warning analysis. Based on the input warning parameters, it evaluates the operating status of the equipment and generates warning information.

[0083] In the process of photovoltaic power generation control, the warning model is combined with the environmental monitoring model to jointly provide real-time and accurate data support for the maximum power point tracking algorithm and the power generation power calculation model. When the operating status of the equipment is abnormal, the warning model can quickly respond and trigger the corresponding processing mechanism.

[0084] In summary, the photovoltaic power station environmental monitoring model and the warning model improve the stable operation of the photovoltaic power station under various environmental conditions, and enhance the energy conversion efficiency and system reliability through real-time monitoring and warning analysis in the high-efficiency and high-reliability power conversion control of photovoltaic power generation.

[0085] Step S103: Substitute the monitoring results of the photovoltaic power station environmental data and the warning results of the photovoltaic power station into the maximum power point tracking algorithm to calculate the control adjustment parameters of the equipment in the photovoltaic power station, convert the control adjustment parameters of the equipment in the photovoltaic power station into the control commands of the equipment in the photovoltaic power station, and collect the data information of the equipment in the photovoltaic power station after executing the control commands of the equipment in the photovoltaic power station.

[0086] The main purpose of the maximum power point tracking algorithm is to dynamically adjust the operating point of the photovoltaic cell to maintain the maximum power output state, thereby improving the energy conversion efficiency. By real-time monitoring the operating status of the photovoltaic cell and external environmental conditions (such as light intensity, temperature, etc.), the maximum power point tracking algorithm calculates the current maximum power point of the photovoltaic cell and adjusts its operating voltage and current to reach this point. In the photovoltaic power generation system, the MPPT algorithm is used to ensure that the photovoltaic panel can always output the maximum power under changing light conditions.

[0087] After obtaining the monitoring results of the photovoltaic power station environmental data and the warning results, the monitoring results of the photovoltaic power station environmental data and the warning results are substituted into the maximum power point tracking algorithm for calculation. The maximum power point tracking algorithm calculates the optimal operating voltage and current according to the environmental data and the real-time status of the equipment, and maximizes the power output of the photovoltaic cell.

[0088] The generation of the control adjustment parameters is based on the output of the maximum power point tracking algorithm, and calculates the control adjustment parameters of the equipment in the photovoltaic power station. These parameters include the output voltage and frequency of the inverter, the tilt angle of the photovoltaic panel, the charging and discharging rates of the battery pack.

[0089] By dynamically adjusting the operating point of the photovoltaic cell, ensuring it operates at the maximum power point, thus maximizing the utilization of solar energy resources. When environmental conditions such as light intensity and temperature change, the MPPT algorithm can quickly respond and adjust the operating point to maintain maximum power output.

[0090] The maximum power point tracking algorithm is integrated in the photovoltaic inverter or other power electronic devices, which monitors the output voltage and current of the photovoltaic cell in real time and realizes maximum power point tracking by adjusting circuit parameters. During the operation of the maximum power point tracking algorithm, it is necessary to collect the output data of the photovoltaic cell in real time and continuously adjust the operating point according to these data to form a closed-loop control system.

[0091] In summary, the maximum power point tracking algorithm of the photovoltaic power station is one of the key technologies to improve the energy conversion efficiency of the photovoltaic power generation system. By monitoring and adjusting the operating point of the photovoltaic cell in real time, the maximum power point tracking algorithm can maintain the maximum power output of the photovoltaic cell under various environmental conditions.

[0092] Step S104, calculate the power generation power of the photovoltaic power station after the device control command in the photovoltaic power station is executed through a preset photovoltaic power station power generation power calculation model, obtain the power generation power of the photovoltaic power station after the control command is executed, and compare the power generation power of the photovoltaic power station after the control command is executed with the expected photovoltaic power generation power to obtain the comparison result of the actual power and the expected power;

[0093] The photovoltaic power station power generation power calculation model is used to predict or calculate the power generation power of the photovoltaic power station according to the operating state of the photovoltaic power station. By inputting the relevant data of the photovoltaic power station (such as light intensity, temperature, device state, etc.), the photovoltaic power station power generation power calculation model can output the actual power generation power of the photovoltaic power station.

[0094] The data required by the photovoltaic power station power generation power calculation model includes the data information after the device in the photovoltaic power station executes the control command, such as the output power of the inverter, the voltage and current of the photovoltaic panel, the charge and discharge state of the battery pack, etc. After the data is preprocessed, it is used as the input parameter of the photovoltaic power station power generation power calculation model.

[0095] The photovoltaic power station power generation power calculation model calculates the actual power generation power of the photovoltaic power station according to the input data (light intensity, temperature, device state, etc.) and the internal logic algorithm of the photovoltaic power station power generation power calculation model.

[0096] In the case where the actual power is inconsistent with the expected power, the photovoltaic power station power generation power calculation model is optimized through a genetic algorithm. This optimization process extracts the data characteristics in the environmental monitoring and warning process, and combines the real-time monitoring parameters and warning parameters to generate and evaluate new candidate solutions for the power generation power calculation model.

[0097] Through iterative optimization, an optimized power generation calculation model that can adapt to environmental changes and improve prediction accuracy is finally obtained. The optimized power generation calculation model can more accurately predict the power generation of a photovoltaic power station, thereby improving the stability and reliability of the system.

[0098] The application of the power generation calculation model of a photovoltaic power station helps to timely adjust the control strategy of the photovoltaic power station, improve the operation of the photovoltaic cells at the maximum power point, and increase the energy conversion efficiency. The power generation calculation model of a photovoltaic power station is an important part of the high-efficiency and high-reliability power conversion control method for photovoltaic power generation. By real-time analyzing and calculating the operation data of the photovoltaic power station, it provides a key basis for the dynamic adjustment of the system.

[0099] The comparison result between the actual power generation and the expected power generation output by the power generation calculation model of a photovoltaic power station is an important indicator for evaluating the operation status of the system and the execution effect of the control command. If the two are inconsistent, it will trigger the optimization process of the power generation calculation model of the photovoltaic power station to improve the adaptive ability and intelligent level of the system.

[0100] In summary, the power generation calculation model of a photovoltaic power station plays a crucial role in the high-efficiency and high-reliability power conversion control method for photovoltaic power generation. By calculating and real-time optimizing the operation data of the photovoltaic power station, the stability of the system is improved.

[0101] Step S105, if in the comparison result of the actual power and the expected power, the actual power is inconsistent with the expected power, then extract the features of the data generated during the monitoring of the operation environment data of the equipment in the photovoltaic power station, and extract the features of the data generated during the early warning of the operation status of the equipment in the photovoltaic power station using the photovoltaic power station early warning model, to obtain the environmental data and the early warning data feature set. Use the environmental data and the early warning data feature set, the photovoltaic power station environmental monitoring parameters, and the photovoltaic power station early warning parameters to optimize the power generation calculation model of the photovoltaic power station through the genetic algorithm, to obtain the optimized power generation calculation model of the photovoltaic power station. Use the optimized power generation calculation model of the photovoltaic power station to calculate the data information after the equipment in the photovoltaic power station executes the control command for the equipment in the photovoltaic power station, to obtain the corrected control command for the photovoltaic power station equipment.

[0102] When optimizing the power generation calculation model of a photovoltaic power station in the present invention, it is necessary to clarify the optimization objectives, such as improving the prediction accuracy and stability of the model, or maximizing the power generation of the photovoltaic power station, etc. Use the genetic algorithm for optimization. The genetic algorithm is an optimization algorithm that simulates natural selection and genetic mechanisms. By initializing a population, and then through operations such as selection, crossover, and mutation, continuously generate new individuals and evaluate their fitness, so as to find the optimal solution. When optimizing the power generation calculation model of a photovoltaic power station, the genetic algorithm can be used to search for the optimal model parameter configuration.

[0103] During the operation of the genetic algorithm, it is necessary to continuously evaluate the performance of the generated model and optimize the model according to the evaluation results. This usually involves adjusting the parameters and structure of the model to improve the prediction accuracy and stability of the model. When the genetic algorithm finds the optimal model configuration, it is necessary to verify the model to enhance its effectiveness and stability in practical applications. After passing the verification, the optimized model can be deployed to the control system of the photovoltaic power station to improve the power generation efficiency and economic benefits of the photovoltaic power station.

[0104] Specifically, the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S101, includes:

[0105] Determine the interface and communication protocol for data communication with the photovoltaic power station. The communication protocol includes HTTP and MQTT, and obtain the data of the devices in the photovoltaic power station through the interface.

[0106] The communication protocol data format adopts XML format, and set the corresponding encryption model and decryption model for the communication protocol data in XML format;

[0107] Receive the data sent by the photovoltaic power station in real time, parse the received data, and extract the data information of the photovoltaic power station. The data information of the photovoltaic power station includes device data and environmental monitoring parameters.

[0108] The extracted device data is classified according to the data type to obtain power generation operation data, temperature data, humidity data, and electromagnetic field intensity data.

[0109] Specifically, the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S101, includes:

[0110] The server identifies the photovoltaic power station device corresponding to each data item through the device identifier. The device identifier includes the device ID and the device serial number;

[0111] The device location information is obtained through the preset location coordinates or the real-time positioning system, and the corresponding location information is queried in the database according to the device identifier;

[0112] According to the photovoltaic power station device and location information, the server matches the corresponding data information to be obtained in the preset knowledge base. The knowledge base includes the performance parameters, historical operation data, and environmental data of the devices in the photovoltaic power station;

[0113] After obtaining the power generation operation data, temperature data, humidity data, and electromagnetic field intensity data of the photovoltaic power station devices, the server preprocesses the power generation operation data, temperature data, humidity data, and electromagnetic field intensity data of the photovoltaic power station devices to obtain the preprocessed operation data.

[0114] Specifically, the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S102, includes:

[0115] Receiving environmental monitoring parameters from the photovoltaic power station in real time. The environmental monitoring parameters include the temperature of the equipment in the photovoltaic power station, the humidity of the equipment in the photovoltaic power station, the wind speed of the equipment in the photovoltaic power station, the light intensity of the equipment in the photovoltaic power station, and the warning parameters include the temperature threshold, the humidity threshold, the equipment failure warning threshold, and the expected photovoltaic power generation power;

[0116] Pre-deploying and loading a photovoltaic power station environmental monitoring model, which is constructed by training a machine learning algorithm based on historical data and historical technical solutions, and is used to evaluate the operating environment status of the equipment in the photovoltaic power station;

[0117] Substituting the received environmental monitoring parameters into the loaded photovoltaic power station environmental monitoring model.

[0118] Receiving environmental monitoring parameters from the data acquisition system of the photovoltaic power station in real time. These parameters are collected in real time through various sensors installed in the photovoltaic power station (such as temperature sensors, humidity sensors, wind speed sensors, light intensity sensors, etc.).

[0119] The received raw data undergoes preprocessing steps, including data cleaning, outlier detection and processing, data standardization, etc., to ensure the quality and consistency of the data, and provide an accurate and reliable data basis for subsequent environmental monitoring and warning.

[0120] The photovoltaic power station environmental monitoring model is constructed by training a machine learning algorithm based on a large amount of historical data and historical technical solutions, and can learn and identify the relationship between the environmental parameters of the photovoltaic power station and the operating state of the equipment.

[0121] When constructing the model, select suitable machine learning algorithms, such as random forest, support vector machine, neural network, etc., and use historical data for training and optimization to improve the prediction accuracy and generalization ability of the model.

[0122] After training, the model will be deployed to the control system of the photovoltaic power station and loaded when needed to evaluate the operating environment status of the equipment in the photovoltaic power station in real time.

[0123] When real-time environmental monitoring parameters are received from the photovoltaic power station, the parameters will be substituted into the loaded photovoltaic power station environmental monitoring model. The model will evaluate and predict the operating environment status of the equipment in the photovoltaic power station based on the parameter input, combined with the knowledge and rules learned internally.

[0124] The evaluation results can help the control system understand the impact of the current environment on the photovoltaic power generation efficiency, as well as potential risks and problems that may exist.

[0125] In addition to environmental monitoring parameters, the system also receives a series of warning parameters including temperature thresholds, humidity thresholds, equipment failure warning thresholds, etc.

[0126] When the evaluation results output by the environmental monitoring model exceed these warning thresholds, corresponding warning mechanisms are triggered, such as sending alarm messages, starting emergency response procedures, etc., to ensure the safe and stable operation of the photovoltaic power station.

[0127] Specifically, for the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S102 includes:

[0128] Using a preset environmental monitoring model of the photovoltaic power station to calculate the input environmental monitoring parameters to monitor the operating environment data of the equipment in the photovoltaic power station:

[0129] After the calculation of the environmental monitoring model of the photovoltaic power station is completed, the monitoring results of the environmental data of the photovoltaic power station are output. The monitoring results of the environmental data of the photovoltaic power station include the operating status of the equipment, and the operating status of the equipment includes normal, abnormal, warning, real-time values of environmental parameters, and predicted values of environmental parameters;

[0130] Substituting the received warning parameters of the photovoltaic power station into the warning model of the photovoltaic power station for warning analysis of the equipment operating status. The warning model of the photovoltaic power station judges the equipment operating status based on preset thresholds and is used to discover potential equipment failures;

[0131] Integrating the environmental monitoring results and warning results to form monitoring data of the environmental data of the photovoltaic power station. The monitoring data of the environmental data of the photovoltaic power station includes the equipment operating status, environmental parameters, and warning information.

[0132] When the environmental monitoring parameters are input into the environmental monitoring model of the photovoltaic power station, the environmental monitoring model of the photovoltaic power station processes and analyzes these parameters using built-in algorithms and logics.

[0133] The environmental monitoring model of the photovoltaic power station adopts various statistical methods, machine learning techniques or deep learning networks to identify the complex relationship between environmental parameters and equipment operating status. During the calculation process, the environmental monitoring model of the photovoltaic power station combines historical data and real-time data to comprehensively evaluate the operating environment of the equipment, including the impact of factors such as temperature, humidity, wind speed, and light intensity on the equipment performance.

[0134] After the calculation of the environmental monitoring model for the photovoltaic power station is completed, detailed monitoring results of the environmental data of the photovoltaic power station will be output. The monitoring results of the environmental data of the photovoltaic power station not only include the current operating status of the equipment (such as normal, abnormal, warning), but also provide the real-time values of environmental parameters and future values predicted based on the model. The real-time values reflect the actual situation of the current environment, while the predicted values help to understand in advance the possible changes in environmental parameters, providing foresight for the operation and maintenance of the equipment.

[0135] The received warning parameters of the photovoltaic power station will be substituted into the warning model of the photovoltaic power station for warning analysis of the equipment operating status. The warning model of the photovoltaic power station determines whether the operating status of the equipment is close to or exceeds the safe range according to the preset thresholds (such as temperature threshold, humidity threshold, equipment failure warning threshold, etc.). When a potential equipment failure risk is detected, the warning model of the photovoltaic power station immediately issues a warning signal so that preventive measures can be taken in time to avoid the occurrence or expansion of the failure.

[0136] The environmental monitoring results and warning results are integrated together to form comprehensive monitoring data of the environmental data of the photovoltaic power station, which not only includes the real-time operating status of the equipment and the real-time values of environmental parameters, but also integrates warning information, providing the operating status of the photovoltaic power station for the operators of the photovoltaic power station. The operators can more quickly and accurately identify problem areas, optimize the operation and maintenance strategies of the equipment, thereby improving the overall performance and reliability of the photovoltaic power station.

[0137] In summary, step S102 realizes the comprehensive monitoring and warning analysis of the operating environment of the photovoltaic power station equipment by comprehensively using the environmental monitoring model and the warning model, providing key data support and decision-making basis for the subsequent power conversion control.

[0138] Specifically, for the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S103 includes:

[0139] Integrate the monitoring results of the environmental data of the photovoltaic power station and the warning results obtained in step S102. The integrated data set includes the real-time monitoring values of environmental parameters such as temperature, humidity, and light intensity, the operating status of the equipment, and warning information. The warning information includes that the equipment is about to overheat and the power generation is lower than expected;

[0140] Calculate the integrated data set through the maximum power point tracking algorithm. The maximum power point tracking algorithm calculates the optimal operating voltage and current according to the environmental data and the real-time status of the equipment, and maximizes the power output of the photovoltaic cells;

[0141] Based on the output of the maximum power point tracking (MPPT) algorithm, the control adjustment parameters of the equipment in the photovoltaic power station are calculated. The control adjustment parameters of the equipment in the photovoltaic power station include the output voltage and frequency of the inverter, the tilt angle of the photovoltaic panels, the charging and discharging rates of the battery pack.

[0142] The data set integrated from the monitoring results and early warning results of the photovoltaic power station environment data obtained in step S102. The data set not only includes the real-time monitoring values of environmental parameters such as temperature, humidity, and light intensity, but also integrates the operating status of the equipment (such as normal, abnormal, warning, etc.) and specific early warning information (for example, the equipment is about to overheat, the power generation is lower than expected, etc.).

[0143] Before integrating the data, data cleaning and preprocessing work are carried out to ensure the accuracy and consistency of the data, and exclude outlier or noisy data. The integrated data set is input into the maximum power point tracking (MPPT) algorithm.

[0144] The maximum power point tracking algorithm is an optimization technique used to maximize the power output of photovoltaic cells under given environmental conditions. It continuously adjusts the operating point of the photovoltaic system to find the voltage and current combination that can generate the maximum power output. The maximum power point tracking algorithm adopts different strategies such as the perturbation and observation method, the incremental conductance method, etc. to achieve the tracking of the maximum power point. The strategy dynamically adjusts the operating voltage and current according to the environmental data and the real-time status of the equipment.

[0145] Based on the output of the MPPT algorithm, the system calculates the control adjustment parameters of the equipment in the photovoltaic power station. The parameters are designed to optimize the operating status of the equipment to improve the power generation efficiency and reliability of the photovoltaic power station. The specific control adjustment parameters include the adjustment values of the output voltage and frequency of the inverter to improve the power quality and reduce losses.

[0146] For the photovoltaic panels, the optimal tilt angle adjustment value may be calculated to better receive sunlight and improve the photoelectric conversion efficiency. For the battery pack, the appropriate charging and discharging rates are calculated to balance the battery life and performance.

[0147] The calculated control adjustment parameters are applied to the equipment of the photovoltaic power station in real time. Continuously monitor the changes in the operating status of the equipment and environmental conditions, and make dynamic adjustments according to the actual situation. Through this real-time feedback and adjustment mechanism, the system can continuously optimize the power generation performance of the photovoltaic power station and cope with various environmental and operating challenges.

[0148] In summary, step S103 realizes the precise control and optimization adjustment of the equipment in the photovoltaic power station by integrating the monitoring results and early warning results of environmental data and applying the maximum power point tracking algorithm, which not only improves the power generation efficiency and reliability of the photovoltaic power station, but also provides a more intelligent and efficient management means for the operator.

[0149] Specifically, for the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S103 includes:

[0150] Converting the calculated control adjustment parameters into device control commands, and sending the device control commands to the inverters, tracking systems, and battery management systems in the photovoltaic power station;

[0151] After the devices in the photovoltaic power station receive the control commands, they perform corresponding operations, and the corresponding operations include adjusting the output voltage and changing the tilt angle of the photovoltaic panels;

[0152] Collecting the data information of the devices after executing the control commands, including the actual working status, output power, and current and voltage parameters of the devices.

[0153] Specifically, for the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S104 includes:

[0154] Collecting the data information of the devices in the photovoltaic power station after executing the control commands, including the output power of the inverter, the voltage and current of the photovoltaic panels, and the charge and discharge status of the battery pack.

[0155] Pre-deploying and loading a photovoltaic power station power calculation model for predicting or calculating its power generation according to the operating status of the photovoltaic power station;

[0156] Inputting the preprocessed data into a preset photovoltaic power station power calculation model, and the photovoltaic power station power calculation model calculates the actual power generation of the photovoltaic power station according to the input data of light intensity, temperature, device status, and the logic of the photovoltaic power station power calculation model.

[0157] After executing the control commands, collecting the relevant data information of the devices in the photovoltaic power station, including but not limited to the output power of the inverter, the voltage and current of the photovoltaic panels, and the charge and discharge status of the battery pack.

[0158] In order to accurately predict and calculate the power generation of the photovoltaic power station, a photovoltaic power station power calculation model is pre-deployed and loaded. The photovoltaic power station power calculation model predicts or calculates its power generation according to the operating status of the photovoltaic power station, providing data support for subsequent control and adjustment.

[0159] The collected original data undergoes preprocessing steps, including data cleaning, outlier detection and processing, etc., so as to provide a reliable data basis for subsequent power calculation.

[0160] The preprocessed data is input into the loaded power calculation model of the photovoltaic power station. The power calculation model of the photovoltaic power station calculates the actual power generation of the photovoltaic power station according to the input data (such as light intensity, temperature, equipment status, etc.) and the internal logic algorithm. The actual power generation of the photovoltaic power station is used to evaluate the operation efficiency and performance of the photovoltaic power station.

[0161] Compare the calculated actual power generation with the expected photovoltaic power generation. If the two are consistent or the difference is within an acceptable range, it is considered that the photovoltaic power station is in good operating condition and the control command is executed effectively. If the difference is large, it may indicate that there is an abnormality in the operating state of the photovoltaic power station, and the cause needs to be further investigated.

[0162] When it is found that the actual power is inconsistent with the expected power, corresponding abnormal handling measures are taken, such as further inspecting and maintaining the equipment of the photovoltaic power station to ensure its normal operation. At the same time, this inconsistency may also trigger subsequent model optimization processes, such as using genetic algorithms to optimize the power calculation model of the photovoltaic power station to improve the prediction accuracy and control efficiency.

[0163] Specifically, the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S104, includes:

[0164] Compare the calculated actual power generation with the expected photovoltaic power generation, and the expected photovoltaic power generation is set based on historical data, weather forecasts, or user requirements.

[0165] Analyze the comparison result of the actual power generation and the expected photovoltaic power generation. If the comparison result of the actual power generation and the expected photovoltaic power generation is consistent or the difference between the comparison result of the actual power generation and the expected photovoltaic power generation is within the preset error range, the operating state of the photovoltaic power station is good and the control command is executed effectively. If the difference between the comparison result of the actual power generation and the expected photovoltaic power generation is not within the preset error range, the operating state of the photovoltaic power station is abnormal. The abnormal operating state of the photovoltaic power station includes equipment failures, environmental condition changes, or control strategy errors.

[0166] The expected photovoltaic power generation is set based on historical data, weather forecasts, or user requirements. These data are processed and analyzed through specialized algorithms to obtain a reasonable expected power generation value. Compare the actually calculated real-time power generation with this expected value. To evaluate the comparison result, a preset error range is set, and the error range is comprehensively determined based on the historical operation data of the photovoltaic power station, equipment performance, and industry standards. The setting of the error range takes into account various factors, including normal fluctuations of the equipment and minor changes in weather conditions, to ensure the rationality and accuracy of the comparison result.

[0167] If the comparison result between the actual power generation and the expected photovoltaic power generation is consistent, or the difference is within the preset error range, then it can be considered that the operation status of the photovoltaic power station is good and the control command is executed effectively.

[0168] If the difference between the actual power generation and the expected photovoltaic power generation exceeds the preset error range, then the system will determine that the operation status of the photovoltaic power station is abnormal.

[0169] When the abnormal operation status is detected, further analyze the possible causes, which may include equipment failures, changes in environmental conditions (such as sudden cloud cover blocking sunlight), or improper control strategies.

[0170] To accurately identify the cause of the anomaly, an alarm is issued to enable the staff to intervene and handle it in a timely manner.

[0171] Specifically, the high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention, step S105, includes:

[0172] Extract features from the data generated during the environmental data monitoring using a preset photovoltaic power station environmental monitoring model. The features to be extracted include real-time values, historical change trends, extreme values, etc. of environmental parameters such as temperature, humidity, and light intensity.

[0173] Also extract features from the data generated during the equipment operation status warning using a photovoltaic power station warning model, including equipment fault warning signals, abnormal status identifiers, and maintenance history features.

[0174] Integrate the data features extracted from the environmental monitoring and warning processes to form an environmental data and warning data feature set.

[0175] Use the genetic algorithm to optimize the photovoltaic power station power generation calculation model. Take the environmental data and warning data feature set, photovoltaic power station environmental monitoring parameters, and warning parameters as the input of the genetic algorithm. The genetic algorithm generates new candidate solutions for the power generation calculation model and evaluates the new candidate solutions for the power generation calculation model based on the deviation between the actual power and the expected power, the prediction accuracy of the model, and the stability index of the model.

[0176] Through iterative genetic algorithm convergence to the optimal power generation calculation model, verify the optimized power generation calculation model. When the optimized power generation calculation model passes the verification, deploy the optimized power generation calculation model to the server and replace the original power generation calculation model.

[0177] Use the optimized power generation calculation model to calculate the data information after the control command is executed on the equipment in the photovoltaic power station, and calculate the power generation of the photovoltaic power station.

[0178] According to the calculation results of the optimized model, the control commands of the photovoltaic power station are corrected. The correction includes adjusting the output voltage and frequency of the inverter, changing the tilt angle of the photovoltaic panels, and optimizing the charge and discharge strategy of the battery pack. The corrected control commands are sent to the devices in the photovoltaic power station.

[0179] Extract key features from the data generated during the environmental monitoring process. The features include the real-time values of environmental parameters such as temperature, humidity, and light intensity, and also cover important information such as their historical change trends and extreme values.

[0180] Feature extraction is also performed on the data generated during the equipment operation status warning process, mainly extracting features such as the equipment fault warning signal, abnormal status identification, and maintenance history.

[0181] The extracted environmental monitoring and warning data features are integrated to form a comprehensive environmental data and warning data feature set, providing a rich data basis for the subsequent optimization process.

[0182] The genetic algorithm is used to optimize the power generation calculation model of the photovoltaic power station. In this process, the previously constructed feature set, environmental monitoring parameters, and warning parameters are used as the inputs of the genetic algorithm. The genetic algorithm generates new candidate solutions for the power generation calculation model and comprehensively evaluates these candidate solutions based on the deviation between the actual power and the expected power, the prediction accuracy of the model, and the stability index of the model.

[0183] Through continuous iteration, the genetic algorithm gradually converges and finally finds the optimal power generation calculation model. This optimized model will undergo a strict verification process to ensure its effectiveness and stability in practical applications. Only the model that passes the verification will be adopted.

[0184] When the optimized power generation calculation model passes the verification, it is deployed to the server and replaces the original power generation calculation model to play a role in actual operation.

[0185] After the deployment is completed, the new model is used to perform real-time calculations on the data information after the control commands are executed on the devices in the photovoltaic power station to obtain the current power generation of the photovoltaic power station.

[0186] Based on these calculation results, necessary corrections are made to the control commands of the photovoltaic power station, including adjusting the output voltage and frequency of the inverter, changing the tilt angle of the photovoltaic panels, or optimizing the charge and discharge strategy of the battery pack, etc.

[0187] The corrected control commands are immediately sent to the devices in the photovoltaic power station to ensure that the system can quickly respond to environmental changes and maintain stable operation.

[0188] The present invention effectively solves the problems of the stability and reliability of the power conversion system under extreme environmental conditions. By monitoring the operating environment and equipment status of the photovoltaic power station in real time, data including power generation operation data, temperature data, humidity data, and electromagnetic field intensity data are obtained, providing comprehensive information for subsequent monitoring and early warning.

[0189] The preset photovoltaic power station environment monitoring model is used to monitor the real-time environmental data, and combined with the photovoltaic power station early warning model to give early warning of the equipment operation status. This can timely detect potential problems and improve the stability and reliability of the system.

[0190] The environmental monitoring and early warning results are substituted into the maximum power point tracking algorithm to dynamically adjust the working state of the equipment (such as the output voltage and frequency of the inverter, the tilt angle of the photovoltaic panel, etc.), ensuring that the photovoltaic cells operate at the maximum power point and improving the energy conversion efficiency.

[0191] The actual power generation is calculated through the preset photovoltaic power station power generation power calculation model and compared with the expected photovoltaic power generation power, which helps to evaluate the execution effect of the control command, timely detect problems and optimize them.

[0192] If the actual power is inconsistent with the expected power, the genetic algorithm is used to optimize the photovoltaic power station power generation power calculation model. By extracting the data characteristics in the environmental monitoring and early warning process, new candidate solutions for the power generation power calculation model are generated and evaluated, and finally the optimal model adapted to environmental changes is obtained.

[0193] During the whole control process, the data information after the equipment executes the control command is collected in real time and feedback control is carried out. This mechanism ensures that the system can quickly respond to environmental changes, timely adjust the control strategy, and maintain the stable operation of the system.

[0194] In summary, the present invention effectively improves the stability and reliability of the photovoltaic power station under extreme environmental conditions through comprehensive data collection and monitoring, real-time monitoring and early warning, maximum power point tracking and dynamic adjustment, real-time power calculation and comparison, model adaptive optimization, and real-time feedback control.

[0195] 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 the claims of the present invention and their equivalent technologies, the present invention also intends to include these changes and modifications. The above-described embodiments of the present invention do not constitute a limitation on the protection scope of the present invention.

Claims

1. A photovoltaic power generation high efficiency and high reliability power conversion control method, characterized in that: include: Step S101, obtaining photovoltaic power station data information, determining photovoltaic power station equipment and photovoltaic power station equipment location information according to the photovoltaic power station data information, matching corresponding data information to be obtained in a preset knowledge base according to the photovoltaic power station equipment and photovoltaic power station equipment location information, and obtaining power generation operation data, temperature data, humidity data and electromagnetic field strength data of the photovoltaic power station equipment according to the data information to be obtained; Step S102, receiving the environmental monitoring parameters of the photovoltaic power station, the early warning parameters of the photovoltaic power station, and the expected photovoltaic power generation power, substituting the environmental monitoring parameters of the photovoltaic power station into a preset environmental monitoring model of the photovoltaic power station, using the preset environmental monitoring model of the photovoltaic power station to monitor the operating environmental data of the equipment in the photovoltaic power station, and obtaining the monitoring results of the environmental data of the photovoltaic power station, substituting the early warning parameters of the photovoltaic power station into the early warning model of the photovoltaic power station, and using the early warning model of the photovoltaic power station to warn the operating status of the equipment in the photovoltaic power station, and obtaining the early warning results of the photovoltaic power station; Step S103, substituting the environmental data monitoring results of the photovoltaic power station and the early warning results of the photovoltaic power station into the maximum power point tracking algorithm, calculating the control adjustment parameters of the equipment in the photovoltaic power station, converting the control adjustment parameters of the equipment in the photovoltaic power station into the control commands of the equipment in the photovoltaic power station, and collecting data information after the equipment in the photovoltaic power station executes the control commands of the equipment in the photovoltaic power station; Step S104, calculating the data information after the equipment in the photovoltaic power station executes the control command of the equipment in the photovoltaic power station through a preset photovoltaic power station power generation calculation model, obtaining the photovoltaic power station power generation after the control command is executed, and comparing the photovoltaic power station power generation after the control command is executed with the expected photovoltaic power generation to obtain a comparison result between the actual power and the expected power; Step S105, if the actual power is inconsistent with the expected power in the comparison result between the actual power and the expected power, feature extraction is performed on the data generated in the process of monitoring the operating environment data of the equipment in the photovoltaic power station, and feature extraction is performed on the data generated in the process of using the photovoltaic power station early warning model to warn the operating status of the equipment in the photovoltaic power station to obtain environmental data and early warning data feature sets, and the environmental data and early warning data feature sets, the photovoltaic power station environmental monitoring parameters and the photovoltaic power station early warning parameters are used to optimize the photovoltaic power station power generation calculation model through a genetic algorithm to obtain an optimized photovoltaic power station power generation calculation model, and the optimized photovoltaic power station power generation calculation model is used to calculate the data information after the equipment in the photovoltaic power station executes the photovoltaic power station equipment control command to obtain a corrected photovoltaic power station equipment control command.

2. The photovoltaic power generation high efficiency and high reliability power conversion control method according to claim 1, characterized in that: Step S101 includes: Determine the interface and communication protocol for data communication with the photovoltaic power station. The communication protocols include HTTP and MQTT. The data of the equipment in the photovoltaic power station is obtained through the interface. The communication protocol data format adopts XML format, and a corresponding encryption model and decryption model are set for the communication protocol data in XML format; Receive data sent by the photovoltaic power station in real time, analyze the received data, and extract the data information of the photovoltaic power station. The data information of the photovoltaic power station includes equipment data and environmental monitoring parameters; The extracted equipment data is classified according to the data type to obtain power generation operation data, temperature data, humidity data and electromagnetic field strength data.

3. The photovoltaic power generation high efficiency and high reliability power conversion control method according to claim 2, characterized in that: Step S101 includes: The server identifies the photovoltaic power station equipment corresponding to each data item through the equipment identifier, and the equipment identifier includes the equipment ID and the equipment serial number; The device location information is obtained through pre-set location coordinates or a real-time positioning system, and the corresponding location information is queried in the database according to the device identifier; According to the equipment and location information of the photovoltaic power station, the server matches the corresponding data information to be obtained in the preset knowledge base, which includes the performance parameters, historical operation data and environmental data of the equipment in the photovoltaic power station; After acquiring the power generation operation data, temperature data, humidity data and electromagnetic field strength data of the photovoltaic power station equipment, the server preprocesses the power generation operation data, temperature data, humidity data and electromagnetic field strength data of the photovoltaic power station equipment to obtain preprocessed operation data.

4. The photovoltaic power generation high efficiency and high reliability power conversion control method according to claim 1, characterized in that: Step S102 includes: Receive environmental monitoring parameters from the photovoltaic power station in real time. The environmental monitoring parameters include the temperature of the equipment in the photovoltaic power station, the humidity of the equipment in the photovoltaic power station, the wind speed of the equipment in the photovoltaic power station, and the light intensity of the equipment in the photovoltaic power station. The early warning parameters include the temperature threshold, the humidity threshold, the equipment failure early warning threshold, and the expected photovoltaic power generation power; Pre-deploy and load the PV power station environmental monitoring model, which is built by training machine learning algorithms based on historical data and historical technical solutions, and is used to evaluate the operating environment status of equipment in the PV power station; The received environmental monitoring parameters are substituted into the loaded PV power station environmental monitoring model.

5. The photovoltaic power generation high efficiency and high reliability power conversion control method according to claim 4, characterized in that: Step S102 includes: Use the preset PV power station environmental monitoring model to calculate the input environmental monitoring parameters to monitor the operating environment data of the equipment in the PV power station: After the calculation of the photovoltaic power station environment monitoring model is completed, the photovoltaic power station environment data monitoring results are output. The photovoltaic power station environment data monitoring results include the operating status of the equipment. The operating status of the equipment includes normal, abnormal, warning, real-time values ​​of environmental parameters, and predicted values ​​of environmental parameters; Substitute the received PV power station warning parameters into the PV power station warning model to conduct warning analysis of the equipment operation status. The PV power station warning model determines the equipment operation status based on the preset threshold value to detect potential equipment failures; The environmental monitoring results and early warning results are integrated to form the environmental data monitoring data of the photovoltaic power station. The environmental data monitoring data of the photovoltaic power station includes the equipment operation status, environmental parameters and early warning information.

6. The photovoltaic power generation high efficiency and high reliability power conversion control method according to claim 1, characterized in that: Step S103 includes: Integrate the photovoltaic power station environmental data monitoring results and early warning results obtained in step S102, the integrated data set includes real-time monitoring values ​​of temperature, humidity, light intensity environmental parameters, equipment operating status and early warning information, the early warning information includes equipment about to overheat and power generation is lower than expected; The integrated data set is calculated through the maximum power point tracking algorithm, which calculates the optimal operating voltage and current based on environmental data and the real-time status of the equipment, and maximizes the power output of the photovoltaic cell; Based on the output of the maximum power point tracking algorithm, the control adjustment parameters of the equipment in the photovoltaic power station are calculated. The control adjustment parameters of the equipment in the photovoltaic power station include the output voltage and frequency of the inverter, the tilt angle of the photovoltaic panel, and the charging and discharging rate of the battery pack.

7. The photovoltaic power generation high efficiency and high reliability power conversion control method according to claim 6, characterized in that: Step S103 includes: The calculated control adjustment parameters are converted into device control commands, which are sent to the inverter, tracking system, and battery management system in the photovoltaic power station; After receiving the control command, the equipment in the photovoltaic power station performs corresponding operations, including adjusting the output voltage and changing the tilt angle of the photovoltaic panel; Collect data information after the device executes the control command, including the actual working status, output power, current and voltage parameters of the device.

8. The photovoltaic power generation high efficiency and high reliability power conversion control method according to claim 1, characterized in that: Step S104 includes: Collect data information after the equipment in the photovoltaic power station executes the control command, including the output power of the inverter, the voltage and current of the photovoltaic panel, and the charge and discharge status of the battery pack; Pre-deploy and load the photovoltaic power station power generation calculation model to predict or calculate its power generation according to the operating status of the photovoltaic power station; The preprocessed data is input into a preset photovoltaic power station power generation calculation model, and the photovoltaic power station power generation calculation model calculates the actual power generation of the photovoltaic power station based on the input data light intensity, temperature, equipment status and the logic of the photovoltaic power station power generation calculation model.

9. The photovoltaic power generation high efficiency and high reliability power conversion control method according to claim 8, characterized in that: Step S104 includes: Compare the calculated actual power generation with the expected photovoltaic power generation, which is based on historical data, weather forecasts or user demand settings; Analyze the comparison results of actual power generation and expected photovoltaic power generation. If the comparison results of actual power generation and expected photovoltaic power generation are consistent or the difference between the comparison results of actual power generation and expected photovoltaic power generation is within the preset error range, the operation status of the photovoltaic power station is good and the control command execution is effective. If the difference between the comparison results of actual power generation and expected photovoltaic power generation is not within the preset error range, the operation status of the photovoltaic power station is abnormal. The abnormal operation status of the photovoltaic power station includes equipment failure, environmental condition change or control strategy error.

10. The photovoltaic power generation high efficiency and high reliability power conversion control method according to claim 1, characterized in that: Step S105 includes: Extract features from the data generated during environmental data monitoring using a preset photovoltaic power station environmental monitoring model. The features to be extracted include real-time values, historical change trends, and extreme value features of environmental parameters such as temperature, humidity, and light intensity. The data generated in the process of using the photovoltaic power station early warning model to warn about the equipment operation status is also feature extracted, including equipment fault warning signals, abnormal status identification, and maintenance history features; Integrate the data features extracted from the environmental monitoring and early warning process to form a set of environmental data and early warning data features; Use genetic algorithms to optimize the photovoltaic power generation calculation model. Take environmental data and early warning data feature sets, photovoltaic power plant environmental monitoring parameters and early warning parameters as inputs to the genetic algorithm. Genetic algorithms generate new candidate solutions for the power generation calculation model and evaluate the new candidate solutions based on the deviation between actual power and expected power, the prediction accuracy of the model, and the stability index of the model. The optimal power generation calculation model is converged to by iterative genetic algorithm, and the optimized power generation calculation model is verified. When the optimized power generation calculation model is verified, the optimized power generation calculation model is deployed on the server and replaces the original power generation calculation model. Use the optimized power generation calculation model to calculate the data information after the equipment in the photovoltaic power station executes the control command, and calculate the power generation power of the photovoltaic power station; According to the calculation results of the optimized model, the control commands of the photovoltaic power station are corrected. The correction includes adjusting the output voltage and frequency of the inverter, changing the tilt angle of the photovoltaic panel, optimizing the charging and discharging strategy of the battery pack, and sending the corrected control commands to the equipment in the photovoltaic power station.

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