A high-precision method for optimizing transient characteristics and fast grid-connected frequency of photovoltaic power generation systems

Abstract

This invention discloses a high-precision method for optimizing transient characteristics and achieving rapid grid-connected frequency response in photovoltaic (PV) power generation systems, belonging to the field of PV power generation technology. The method includes the following steps: S1: Establishing an electromechanical transient model of the PV power generation system; S2: Real-time detection of the rate of change of frequency and voltage in the PV power generation system; S3: Obtaining the influencing factors leading to transient instability of the PV power generation system; S4: Optimizing transient characteristics based on the analysis results; S5: Achieving steady-state deviation suppression and rapid transient response. This invention solves the problem that existing technologies easily lead to increased frequency deviation or even exceeding limits. This invention can significantly improve the overall performance of PV power generation, thereby enhancing overall operational stability. By combining transient characteristic optimization with rapid frequency response, it can significantly improve the reliability of PV systems and the grid support capability.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic power generation technology, specifically to a high-precision method for optimizing transient characteristics of photovoltaic power generation systems and for rapid response of grid connection frequency. Background Technology

[0002] Photovoltaic power generation is a technology that directly converts light energy into electrical energy by utilizing the photovoltaic effect at the semiconductor interface. With the continuous development of the photovoltaic industry, photovoltaic power generation systems have become an important energy source. Photovoltaic power generation has intermittent and random characteristics. In order to maximize the consumption of photovoltaic power, it is necessary to perform online optimization calculation and control of the grid-connected power of conventional units and new energy power plants based on ultra-short-term photovoltaic power generation forecasts, taking into account the grid's peak shaving, safety and stability, spot trading, and economic and environmental constraints.

[0003] Chinese Patent Publication No. CN119051130B discloses a transient characteristic optimization control strategy for a distributed generation system, comprising the following control structures: an output power measurement unit, a parameter controller, a voltage regulation controller, a primary frequency regulation controller, an output power response optimization controller, and SPWM modulation. Through these control structures, the distributed generation system achieves functions such as output power monitoring, operating parameter setting, voltage control, primary frequency regulation, inertia and damping simulation, rapid oscillation suppression, and inverter shutdown control. This addresses the problem of severe power oscillations caused by frequency fluctuations when grid-connected inverters are connected to the grid end, effectively optimizing the system's grid-connected transient response and achieving rapid suppression of output oscillations.

[0004] In actual use, the photovoltaic output is intermittent and fluctuates due to weather conditions. Without a fast frequency response mechanism, the system cannot quickly adjust the active power in the event of sudden load changes or fault scenarios, which leads to an increase in frequency deviation or even exceeding the limit, threatening the safety of the power grid. Summary of the Invention

[0005] The purpose of this invention is to provide a high-precision method for optimizing transient characteristics and rapidly responding to grid connection frequency in photovoltaic power generation systems. This method can significantly improve the overall performance of photovoltaic power generation, reduce the impact of power output fluctuations on the power grid, and thus enhance overall operational stability. By optimizing the dynamic characteristics of grid connection through transient analysis, it reduces voltage fluctuations and harmonic interference, ensuring seamless integration of photovoltaic power generation with the power grid and reliable power supply, thereby improving the economy and sustainability of photovoltaic power plants. Through high-precision monitoring and active power regulation mechanisms, it enhances the photovoltaic system's ability to cope with grid frequency fluctuations. By combining transient characteristic optimization with rapid frequency response, it can significantly improve the reliability of photovoltaic systems and the grid support capability, thus solving the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a high-precision method for optimizing transient characteristics and rapidly responding to grid connection frequency in a photovoltaic power generation system, comprising the following steps:

[0007] S1: Use the model building module to establish an electromechanical transient model of the photovoltaic power generation system, and verify and optimize the model;

[0008] S2: Real-time detection of the rate of change of frequency and the rate of change of voltage of the photovoltaic power generation system;

[0009] S3: Input the measured rate of change of frequency and rate of change of voltage of the photovoltaic power generation system into the electromechanical transient model to obtain the influencing factors that lead to the transient instability of the photovoltaic power generation system;

[0010] S4: The analysis module analyzes the dynamic response characteristics of the photovoltaic power generation system under transient events and optimizes the transient characteristics based on the analysis results;

[0011] S5: After the transient characteristics are optimized, the fast response module simulates the inertia characteristics of a synchronous generator through a photovoltaic energy storage system to achieve steady-state deviation suppression and transient fast response.

[0012] Preferably, the model building module specifically includes:

[0013] The data acquisition unit is used to acquire the operating data of the photovoltaic power generation system and perform data cleaning, data conversion and data integration.

[0014] The model building unit is used to build an electromechanical transient model of the photovoltaic power generation system using the data collected by the data acquisition unit.

[0015] The model optimization unit is used to verify and optimize the electromechanical transient model of the photovoltaic power generation system through simulation analysis and experimental verification.

[0016] Preferably, the construction process of the model building module specifically includes:

[0017] Connect the photovoltaic power generation system to the power grid system and establish an equivalent connection circuit that includes at least the equivalent impedance of the photovoltaic power generation system connection transformer and the equivalent current source.

[0018] Calculate the values ​​of different parameters in the equivalent circuit, including the equivalent impedance of the photovoltaic power generation system and the parameters of the equivalent current source;

[0019] Based on the calculated parameters, an equivalent access circuit is designed to complete the electromechanical transient modeling of the photovoltaic power generation system;

[0020] Genetic algorithms are used to adjust the electromechanical transient modeling parameters of the photovoltaic power generation system to achieve the highest degree of fit with the actual operating data.

[0021] The effectiveness and feasibility of electromechanical transient modeling of photovoltaic power generation systems are evaluated through simulation analysis and experimental verification.

[0022] Based on simulation and experimental results, the electromechanical transient modeling of the photovoltaic power generation system is optimized, and the electromechanical transient modeling parameters of the photovoltaic power generation system are adjusted.

[0023] Preferably, the data acquisition unit specifically includes:

[0024] The data acquisition unit is used to monitor and record the operating data of the photovoltaic power generation system in real time using high-precision sensors;

[0025] The data processing unit is used to perform data cleaning, data transformation, and data integration on the data collected by the data acquisition unit.

[0026] Preferably, the data processing unit specifically includes:

[0027] Interpolation is used to fill in missing data, machine learning algorithms are used to identify abnormal data and correct or remove them, and wavelet transform is used to filter sensor noise interference.

[0028] Unify the data acquisition frequency of different devices, convert the timestamp format, use Min-Max normalization to eliminate dimensional differences, and generate derived features;

[0029] Align meteorological data and equipment operation data by timestamp, delete duplicate records or invalid fields, check logical relationships, and correct contradictory data.

[0030] Preferably, the analysis module includes:

[0031] Based on the influencing factors of transient instability of photovoltaic power generation systems, the dynamic response characteristics of photovoltaic power generation systems under transient events are analyzed.

[0032] Determine whether a photovoltaic power generation system meets transient stability requirements based on its dynamic response characteristics under transient events.

[0033] If the transient stability requirements are not met, specific transient performance optimization measures for the photovoltaic power generation system will be implemented based on the established optimization control strategy.

[0034] Preferably, the fast response module includes:

[0035] The simulation unit is used to simulate the inertia characteristics of a synchronous generator through a photovoltaic energy storage system. The inverter adopts droop control and virtual inertia compensation to actively support the grid frequency.

[0036] The adjustment unit is used to monitor the irradiance and frequency deviation in real time. It generates active power adjustment commands through fuzzy weighting and defuzzification processing to achieve steady-state deviation suppression and transient rapid response.

[0037] Preferably, the adjustment unit specifically includes:

[0038] Continuously monitor solar irradiance and the frequency deviation and frequency change rate of the power system, convert the collected precise values ​​into fuzzy linguistic variables, and define the degree to which they belong to a specific fuzzy set through membership functions;

[0039] Weighted fusion of multi-input fuzzy linguistic variables is performed, and weights are assigned according to the importance of different input fuzzy linguistic variables;

[0040] The output fuzzy set of each rule is calculated by a fuzzy inference engine, and then all rules are integrated to generate a comprehensive output fuzzy set. The output fuzzy set is then converted into a specific active power adjustment value using the maximum value averaging method.

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] This invention can significantly improve the overall performance of photovoltaic power generation. Optimizing transient characteristics can effectively analyze and predict the dynamic behavior of photovoltaic systems under fluctuations in light and temperature, reduce the impact of power output fluctuations on the power grid, thereby enhancing overall operational stability, improving system operating efficiency and response accuracy, quickly identifying problems and providing protection mechanisms, reducing the risk of failure and downtime, optimizing the dynamic characteristics of grid connection through transient analysis, reducing voltage fluctuations and harmonic interference, ensuring seamless integration of photovoltaic power generation with the grid and reliable power supply, improving the economy and sustainability of photovoltaic power plants, and enhancing the photovoltaic system's ability to cope with grid frequency fluctuations through high-precision monitoring and active power regulation mechanisms. Combining transient characteristic optimization with rapid frequency response can significantly improve the reliability of photovoltaic systems and grid support capabilities. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of a high-precision photovoltaic power generation system transient characteristic optimization and grid connection frequency fast response method according to the present invention;

[0044] Figure 2 This is a schematic diagram of a module for a high-precision photovoltaic power generation system transient characteristic optimization and grid connection frequency fast response method according to the present invention. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] To address the issue that existing photovoltaic (PV) power output is intermittent and fluctuating due to weather conditions, and without a rapid frequency response mechanism, the system struggles to quickly adjust active power in the event of sudden load changes or faults, leading to increased frequency deviations or even exceeding limits, thus threatening grid security, please refer to [link to relevant documentation]. Figures 1-2 This embodiment provides the following technical solution:

[0047] A high-precision method for optimizing transient characteristics and rapidly responding to grid connection frequency in a photovoltaic power generation system includes the following steps:

[0048] S1: Utilize the model building module to establish an electromechanical transient model of the photovoltaic power generation system, and verify and optimize the model. Based on the electromechanical transient modeling of the photovoltaic power generation system, the system operating efficiency and response accuracy can be improved. The optimized electromechanical transient modeling of the photovoltaic power generation system can accurately simulate the transient process under faults such as short circuit and open circuit, quickly identify problems and provide protection mechanisms, and reduce the risk of failure shutdown.

[0049] S2: Real-time detection of the rate of change of frequency and the rate of change of voltage of the photovoltaic power generation system;

[0050] S3: Input the measured rate of change of frequency and rate of change of voltage of the photovoltaic power generation system into the electromechanical transient model to obtain the influencing factors that lead to transient instability of the photovoltaic power generation system. By monitoring the rate of change of frequency and voltage in real time, the dynamic impact of grid disturbances on system stability can be quickly identified. This quantitative indicator can better reflect the essential characteristics of the transient process than static parameters. High-frequency acquisition of rate of change data can realize early instability warning.

[0051] S4: The analysis module analyzes the dynamic response characteristics of the photovoltaic power generation system under transient events and optimizes the transient characteristics based on the analysis results. Optimizing the transient characteristics can effectively analyze and predict the dynamic behavior of the photovoltaic system under fluctuations in light and temperature, reduce the impact of power output fluctuations on the power grid, thereby enhancing the overall operational stability. By optimizing the dynamic characteristics of grid connection through transient analysis, voltage fluctuations and harmonic interference are reduced, ensuring seamless integration of photovoltaic power generation with the power grid and reliable power supply, and improving the economy and sustainability of photovoltaic power plants.

[0052] S5: After the transient characteristics are optimized, the fast response module simulates the inertia characteristics of a synchronous generator through a photovoltaic energy storage system to achieve steady-state deviation suppression and transient fast response.

[0053] By combining transient characteristic optimization with rapid frequency response in photovoltaic (PV) power generation systems, the dynamic processes of the system can be better analyzed and predicted, thereby improving system stability. Electromechanical transient modeling methods can help monitor the dynamic processes of PV power generation systems in real time, reducing power fluctuations caused by factors such as light intensity and temperature, and enhancing system stability. Transient characteristic optimization can provide a theoretical basis for the control strategy of PV power generation systems, enabling the design of more reasonable control strategies and improving system operating efficiency. The optimized control strategy can better adapt to the dynamic changes of PV power generation systems, reducing system fluctuations caused by improper control. Transient characteristic optimization can help analyze the transient processes during fault occurrence, providing a theoretical basis for fault diagnosis and protection. This allows for timely detection and handling of system faults, reducing system downtime caused by faults and ensuring continuous system operation. Electromechanical transient modeling of PV power generation systems allows for better analysis of their grid-connected performance, providing technical support for grid-connected operation. The optimized system can better synchronize with the power grid, reduce grid fluctuations caused by grid connection issues, and improve grid connection performance. By understanding the system's operating characteristics, targeted equipment selection and system design can be carried out to reduce system costs. The optimized system can reduce unnecessary investment and maintenance costs while ensuring performance.

[0054] The model building module specifically includes:

[0055] The data acquisition unit is used to acquire the operating data of the photovoltaic power generation system and perform data cleaning, data conversion and data integration.

[0056] The model building unit is used to build an electromechanical transient model of the photovoltaic power generation system using the data collected by the data acquisition module.

[0057] The model optimization unit is used to verify and optimize the electromechanical transient model of the photovoltaic power generation system through simulation analysis and experimental verification.

[0058] The construction process of the model building module specifically includes:

[0059] Connect the photovoltaic power generation system to the power grid system and establish an equivalent connection circuit that includes at least the equivalent impedance of the photovoltaic power generation system connection transformer and the equivalent current source.

[0060] Calculate the values ​​of different parameters in the equivalent circuit, including the equivalent impedance of the photovoltaic power generation system and the parameters of the equivalent current source;

[0061] Based on the calculated parameters, an equivalent access circuit is designed to complete the electromechanical transient modeling of the photovoltaic power generation system;

[0062] Genetic algorithms are used to adjust the electromechanical transient modeling parameters of the photovoltaic power generation system to achieve the highest degree of fit with the actual operating data.

[0063] Through simulation analysis and experimental verification, the effectiveness and feasibility of electromechanical transient modeling of photovoltaic power generation system are evaluated. The dynamic characteristics of electromechanical transient and electromagnetic transient models are compared through simulation to ensure the rationality of the model.

[0064] Based on simulation and experimental results, the electromechanical transient modeling of the photovoltaic power generation system is optimized, the electromechanical transient modeling parameters of the photovoltaic power generation system are adjusted, and the accuracy and applicability of the electromechanical transient modeling of the photovoltaic power generation system are improved.

[0065] The data acquisition unit specifically includes:

[0066] The data acquisition unit is used to monitor and record the operating data of the photovoltaic power generation system in real time using high-precision sensors, including parameters such as light intensity, temperature, voltage, and current, to ensure the accuracy and integrity of the data.

[0067] The data processing unit is used to perform data cleaning, data transformation, and data integration on the data collected by the data acquisition unit.

[0068] Electromechanical transient modeling allows for better analysis and prediction of the dynamic characteristics of photovoltaic power generation systems, thereby improving system stability. Modeling analysis provides a theoretical basis for control strategies of photovoltaic power generation systems, enabling the design of more reasonable control strategies and improving system operating efficiency. Electromechanical transient modeling can also help analyze the transient processes when faults occur, providing a theoretical basis for fault diagnosis and protection. By analyzing the grid connection performance of photovoltaic power generation systems, the stable operation of the power grid can be better supported. Understanding the operating characteristics of the system allows for targeted equipment selection and system design, thereby reducing system costs.

[0069] The data processing unit specifically includes:

[0070] Interpolation is used to fill in missing data to ensure the continuity of the time series. Machine learning algorithms are used to identify abnormal data and correct or remove them. Wavelet transform is used to filter out sensor noise interference.

[0071] The data acquisition frequency of different devices is unified, the timestamp format is converted, Min-Max normalization is used to eliminate the difference in units, and derived features such as the ratio of irradiance to temperature and the moving average of historical power generation are generated to enhance the expressive power of the model.

[0072] Align meteorological data and equipment operation data by timestamp, delete duplicate records or invalid fields, check logical relationships, and correct contradictory data.

[0073] The analysis module includes:

[0074] Based on the influencing factors of transient instability of photovoltaic power generation systems, the dynamic response characteristics of photovoltaic power generation systems under transient events are analyzed.

[0075] Determine whether a photovoltaic power generation system meets transient stability requirements based on its dynamic response characteristics under transient events.

[0076] If the transient stability requirements are not met, the control strategy should consider factors such as system stability, efficiency, and cost. By adjusting the control parameters, the system can maintain its optimal operating state under various operating conditions. Based on the established optimization control strategy, specific transient performance optimization measures for the photovoltaic power generation system should be implemented, including adjusting the inverter parameter settings, improving the installation angle and direction of the solar panels, and optimizing the configuration of the solar modules.

[0077] The rapid response module includes:

[0078] The simulation unit is used to simulate the inertia characteristics of a synchronous generator through a photovoltaic energy storage system. The inverter adopts droop control and virtual inertia compensation to actively support the grid frequency.

[0079] The adjustment unit is used to monitor the irradiance and frequency deviation in real time. It generates active power adjustment commands through fuzzy weighting and defuzzification processing to achieve steady-state deviation suppression and transient rapid response.

[0080] The adjustment unit specifically includes:

[0081] Continuous monitoring of solar irradiance and frequency deviation and frequency change rate of the power system. Frequency-related variables are used to reflect the steady-state / transient fluctuations of the power grid. The collected precise values ​​are converted into fuzzy linguistic variables, and the degree to which they belong to a specific fuzzy set is defined by the membership function.

[0082] Weighted fusion of multi-input fuzzy linguistic variables is performed, and weights are assigned according to the importance of different input fuzzy linguistic variables;

[0083] The output fuzzy set of each rule is calculated by a fuzzy inference engine, and then all rules are integrated to generate a comprehensive output fuzzy set. The output fuzzy set is then converted into a specific active power adjustment value using the maximum value averaging method.

[0084] Fuzzy control technology is used to monitor solar irradiance and frequency deviation in real time. Through weighted output by multiple controllers, it can quickly respond to load or power generation changes during transient processes and suppress drastic frequency fluctuations. This method is more adaptable to the uncertainty of photovoltaic output than traditional PID control and shortens the adjustment lag time. Defuzzification processing converts fuzzy output into precise power commands. Through a smooth connection mechanism, steady-state frequency deviation is reduced, and coordinated control with steady-state fine adjustment and rapid transient support is achieved.

[0085] In summary, the high-precision photovoltaic (PV) power generation system transient characteristic optimization and grid-connected frequency fast response method of this invention can significantly improve the overall performance of PV power generation. Optimizing transient characteristics can effectively analyze and predict the dynamic behavior of PV systems under fluctuations in light and temperature, reducing the impact of power output fluctuations on the power grid, thereby enhancing overall operational stability. Based on electromechanical transient modeling of the PV power generation system, it can improve system operating efficiency and response accuracy. The optimized electromechanical transient modeling of the PV power generation system can accurately simulate transient processes under faults such as short circuits and open circuits, quickly identify problems and provide protection mechanisms, and reduce the risk of fault outages. By optimizing the dynamic characteristics of grid connection through transient analysis, voltage fluctuations and harmonic interference are reduced, ensuring seamless integration of PV power generation with the grid and reliable power supply, improving the economy and sustainability of PV power plants. Through high-precision monitoring and active power regulation mechanisms, the PV system's ability to cope with grid frequency fluctuations is improved. Combining transient characteristic optimization with fast frequency response can significantly improve the reliability of PV systems and grid support capabilities. On the one hand, transient modeling reduces the transient impact of power output fluctuations on the grid; on the other hand, the fast frequency response mechanism enhances the tolerance to grid fault frequency anomalies, jointly promoting the efficient integration of new energy into the smart grid.

[0086] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0087] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A high-precision method for optimizing transient characteristics and rapidly responding to grid connection frequency in a photovoltaic power generation system, characterized in that, Includes the following steps: S1: Use the model building module to establish an electromechanical transient model of the photovoltaic power generation system, and verify and optimize the model; S2: Real-time detection of the rate of change of frequency and the rate of change of voltage of the photovoltaic power generation system; S3: Input the measured rate of change of frequency and rate of change of voltage of the photovoltaic power generation system into the electromechanical transient model to obtain the influencing factors that lead to the transient instability of the photovoltaic power generation system; S4: The analysis module analyzes the dynamic response characteristics of the photovoltaic power generation system under transient events and optimizes the transient characteristics based on the analysis results; The analysis module includes: Based on the influencing factors of transient instability of photovoltaic power generation systems, the dynamic response characteristics of photovoltaic power generation systems under transient events are analyzed. Determine whether a photovoltaic power generation system meets transient stability requirements based on its dynamic response characteristics under transient events. If the transient stability requirements are not met, specific transient performance optimization measures for the photovoltaic power generation system shall be implemented according to the established optimization control strategy. S5: After the transient characteristics are optimized, the fast response module simulates the inertia characteristics of a synchronous generator through a photovoltaic energy storage system to achieve steady-state deviation suppression and transient fast response; The rapid response module includes: The simulation unit is used to simulate the inertia characteristics of a synchronous generator through a photovoltaic energy storage system. The inverter adopts droop control and virtual inertia compensation to actively support the grid frequency. The adjustment unit is used to monitor the irradiance and frequency deviation in real time, and generate active power adjustment commands through fuzzy weighting and defuzzification processing to achieve steady-state deviation suppression and transient rapid response. The adjustment unit specifically includes: Continuously monitor solar irradiance and the frequency deviation and frequency change rate of the power system, convert the collected precise values ​​into fuzzy linguistic variables, and define the degree to which they belong to a specific fuzzy set through membership functions; Weighted fusion of multi-input fuzzy linguistic variables is performed, and weights are assigned according to the importance of different input fuzzy linguistic variables; The output fuzzy set of each rule is calculated by a fuzzy inference engine, and then all rules are integrated to generate a comprehensive output fuzzy set. The output fuzzy set is then converted into a specific active power adjustment value using the maximum value averaging method.

2. The method for optimizing transient characteristics and rapidly responding to grid connection frequency of a high-precision photovoltaic power generation system according to claim 1, characterized in that, The model building module specifically includes: The data acquisition unit is used to acquire the operating data of the photovoltaic power generation system and perform data cleaning, data conversion and data integration. The model building unit is used to build an electromechanical transient model of the photovoltaic power generation system using the data collected by the data acquisition module. The model optimization unit is used to verify and optimize the electromechanical transient model of the photovoltaic power generation system through simulation analysis and experimental verification.

3. The method for optimizing transient characteristics and rapidly responding to grid connection frequency of a high-precision photovoltaic power generation system according to claim 2, characterized in that, The construction process of the model building module specifically includes: Connect the photovoltaic power generation system to the power grid system and establish an equivalent connection circuit that includes at least the equivalent impedance of the photovoltaic power generation system connection transformer and the equivalent current source. Calculate the values ​​of different parameters in the equivalent circuit, including the equivalent impedance of the photovoltaic power generation system and the parameters of the equivalent current source; Based on the calculated parameters, an equivalent access circuit is designed to complete the electromechanical transient modeling of the photovoltaic power generation system; Genetic algorithms are used to adjust the electromechanical transient modeling parameters of the photovoltaic power generation system to achieve the highest degree of fit with the actual operating data. The effectiveness and feasibility of electromechanical transient modeling of photovoltaic power generation systems are evaluated through simulation analysis and experimental verification. Based on simulation and experimental results, the electromechanical transient modeling of the photovoltaic power generation system is optimized, and the electromechanical transient modeling parameters of the photovoltaic power generation system are adjusted.

4. The method for optimizing transient characteristics and rapidly responding to grid connection frequency of a high-precision photovoltaic power generation system according to claim 2, characterized in that, The data acquisition unit specifically includes: The data acquisition unit is used to monitor and record the operating data of the photovoltaic power generation system in real time using high-precision sensors; The data processing unit is used to perform data cleaning, data transformation, and data integration on the data collected by the data acquisition unit.

5. The method for optimizing transient characteristics and rapidly responding to grid connection frequency of a high-precision photovoltaic power generation system according to claim 4, characterized in that, The data processing unit specifically includes: Interpolation is used to fill in missing data, machine learning algorithms are used to identify abnormal data and correct or remove them, and wavelet transform is used to filter sensor noise interference. Unify the data acquisition frequency of different devices, convert the timestamp format, use Min-Max normalization to eliminate dimensional differences, and generate derived features; Align meteorological data and equipment operation data by timestamp, delete duplicate records or invalid fields, check logical relationships, and correct contradictory data.

6. The method for optimizing transient characteristics and rapidly responding to grid connection frequency of a high-precision photovoltaic power generation system according to claim 1, characterized in that, The analysis module includes: Based on the influencing factors of transient instability of photovoltaic power generation systems, the dynamic response characteristics of photovoltaic power generation systems under transient events are analyzed. Determine whether a photovoltaic power generation system meets transient stability requirements based on its dynamic response characteristics under transient events. If the transient stability requirements are not met, specific transient performance optimization measures for the photovoltaic power generation system will be implemented based on the established optimization control strategy.

7. The method for optimizing transient characteristics and rapidly responding to grid connection frequency of a high-precision photovoltaic power generation system according to claim 1, characterized in that, The fast response module includes: The simulation unit is used to simulate the inertia characteristics of a synchronous generator through a photovoltaic energy storage system. The inverter adopts droop control and virtual inertia compensation to actively support the grid frequency. The adjustment unit is used to monitor the irradiance and frequency deviation in real time. It generates active power adjustment commands through fuzzy weighting and defuzzification processing to achieve steady-state deviation suppression and transient rapid response.

8. The method for optimizing transient characteristics and rapidly responding to grid connection frequency of a high-precision photovoltaic power generation system according to claim 7, characterized in that, The adjustment unit specifically includes: Continuously monitor solar irradiance and the frequency deviation and frequency change rate of the power system, convert the collected precise values ​​into fuzzy linguistic variables, and define the degree to which they belong to a specific fuzzy set through membership functions; Weighted fusion of multi-input fuzzy linguistic variables is performed, and weights are assigned according to the importance of different input fuzzy linguistic variables; The output fuzzy set of each rule is calculated by a fuzzy inference engine, and then all rules are integrated to generate a comprehensive output fuzzy set. The output fuzzy set is then converted into a specific active power adjustment value using the maximum value averaging method.

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