Performance detection system of photovoltaic power generation system

Abstract

The invention discloses a performance detection system of a photovoltaic power generation system, which relates to the technical field of photovoltaic power generation and comprises a data acquisition module, a data transmission module, a data analysis and processing module and a monitoring and display module. The data acquisition module is used for acquiring key parameter data of the photovoltaic power generation system, collecting analog signals and converting the analog signals into digital signals, and the data comprises the steps of measuring the surface illumination intensity of a photovoltaic module, monitoring the temperature of the photovoltaic module and measuring the output current and voltage of a photovoltaic array. According to the performance detection system of the photovoltaic power generation system, the data acquisition module can accurately measure the illumination intensity and temperature of a photovoltaic module and the output current and voltage parameters of a photovoltaic array, analog signals are converted into digital signals, basic data are provided for follow-up processing, the data transmission module supports multiple transmission modes, and the performance of the photovoltaic power generation system is improved. Stable and efficient transmission between the data acquisition equipment and the upper computer is ensured, and operation and maintenance personnel can know the system operation condition and historical data conveniently.

Description

Technical Field

[0001] The invention relates to the technical field of photovoltaic power generation, and in particular to a performance detection system for a photovoltaic power generation system. Background Art

[0002] With the continuous development and popularization of photovoltaic power generation technology, the performance detection of photovoltaic power generation systems has become increasingly important. The traditional performance detection methods of photovoltaic power generation systems have problems such as low detection efficiency, insufficient accuracy, and untimely fault diagnosis, which directly affects the operating efficiency and stability of photovoltaic power generation systems.

[0003] In order to solve these problems, the current market is in urgent need of an efficient, accurate and real-time monitoring system for the performance of photovoltaic power generation systems. During the operation of photovoltaic power generation systems, their performance is affected by many factors, such as light intensity, temperature, aging of photovoltaic components, and conversion efficiency of inverters. Therefore, a performance detection system needs to be able to collect these key parameter data in real time and perform accurate analysis and processing to evaluate the overall performance of the photovoltaic power generation system. In addition, the timely discovery and diagnosis of photovoltaic power generation system faults is also the key to improving system stability and reliability. Traditional fault diagnosis methods often rely on manual inspections and experience judgments, which is not only time-consuming and labor-intensive, but also easy to miss fault points. In this regard, we propose a performance detection system for photovoltaic power generation systems. Summary of the invention

[0004] In order to solve the above technical problems, a performance detection system for a photovoltaic power generation system is provided. This technical solution solves the above problems.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] The performance detection system of the photovoltaic power generation system includes: a data acquisition module, a data transmission module, a data analysis and processing module, and a monitoring and display module;

[0007] The data acquisition module is used to collect key parameter data of the photovoltaic power generation system and collect analog signals and convert them into digital signals. The data includes: measuring the light intensity on the surface of the photovoltaic module, monitoring the temperature of the photovoltaic module, and measuring the output current and voltage of the photovoltaic array;

[0008] The data transmission module is used to realize data transmission between the data acquisition device and the host computer;

[0009] The data analysis and processing module is used to pre-process the collected data, calculate performance indicators and conduct fault diagnosis and early warning. Data pre-processing includes filtering, denoising and calibration data; performance indicator calculation includes calculating the power generation power and efficiency based on voltage and current data and analyzing power quality parameters; by establishing a fault diagnosis model, it is determined whether the system has a fault and an early warning is issued in the event of an abnormality;

[0010] The monitoring and display module is used to display the key parameters of the photovoltaic power generation system in real time and provide historical data query and report generation functions.

[0011] Preferably, the data acquisition module comprises: a sensor unit and a data acquisition unit;

[0012] The sensor unit is used to obtain real-time information on light intensity, temperature, current and voltage;

[0013] The data acquisition unit is used to collect the analog signals from the sensors and convert them into digital signals.

[0014] Preferably, the data transmission module comprises: a signal modulation unit, a transmission medium interface unit and a signal amplification and relay unit;

[0015] The signal modulation unit is used to modulate the digital signal transmitted from the data acquisition module so that it can be transmitted in the communication channel;

[0016] The transmission medium interface unit is used to connect different transmission media, including: Ethernet interface and RS-485 interface for wired transmission, Wi-Fi interface, Bluetooth interface, Zigbee interface and communication module interface for wireless transmission;

[0017] The signal amplification and relay unit is used to amplify the signal strength in the case of long-distance transmission and weak signal. The amplification and relay determination method of free space wireless signal transmission is:

[0018]

[0019] Where P r Represents the received power, P t Indicates the transmit power, G t represents the gain of the transmitting antenna, G r represents the gain of the receiving antenna, λ represents the signal wavelength, L represents the system loss factor, and d represents the distance between the transmitting antenna and the receiving antenna. When the signal strength is lower than the receiving threshold, the signal amplification and relay unit needs to intervene;

[0020] Among them, the amplification and relay determination method for wired transmission is:

[0021] A=k×d

[0022] In the formula, A represents signal attenuation, and k represents the attenuation coefficient related to the transmission medium. When the attenuation causes the signal to be unable to be received normally, signal amplification and relay units need to intervene.

[0023] Preferably, the data analysis and processing module includes: a data filtering unit, a data denoising unit, an analysis and calculation unit and a fault diagnosis model unit;

[0024] The data filtering unit is used to filter out high-frequency noise and low-frequency interference in the collected data;

[0025] The data denoising unit is used to reduce random noise in the data;

[0026] The analysis and calculation unit is used to calculate the generated power, calculate the efficiency of the photovoltaic power generation system and analyze the power quality parameters according to the collected output voltage and current data of the photovoltaic array;

[0027] The fault diagnosis model unit is used to establish a fault diagnosis model and determine whether there is a fault in the system.

[0028] Preferably, filtering out high-frequency noise and low-frequency interference in the collected data specifically includes:

[0029] Select a second-order Butterworth low-pass filter and determine the filter's cutoff frequency. For filtering out high-frequency noise, the cutoff frequency is lower than the noise frequency. For filtering out low-frequency interference, the cutoff frequency is higher than the interference frequency.

[0030] For discrete-time signals, the filtered output signal is calculated using the filter's difference equation;

[0031] Among them, the difference equation of the second-order Butterworth low-pass filter is:

[0032] y[n]=b0x[n]+b1x[n-1]+b2x[n-2]-a1y[n-1]-a2y[n-2]

[0033] Where y[n] represents the output signal after filtering, x[n] represents the input signal, n represents a discrete time point, and the coefficients b0, b1, b2, a1, and a2 are related to the cutoff frequency and the sampling frequency;

[0034] The coefficient calculation method is:

[0035] Calculate the normalized medium frequency:

[0036] ω c =2πf c / f s

[0037] In the formula, ω c represents the normalized cutoff frequency, f c represents the normalized cutoff frequency, fs Indicates the sampling frequency;

[0038]

[0039] b1=-(1+cosω c )

[0040]

[0041] a1=-2cosω c

[0042] a2=1.

[0043] Preferably, calculating the power generation and the efficiency of the photovoltaic power generation system according to the collected photovoltaic array output voltage and current data specifically includes:

[0044] The voltage and current values ​​output by the photovoltaic array are obtained through the data acquisition module;

[0045] Substitute the collected voltage and current values ​​into the power calculation formula for calculation:

[0046] P=UI

[0047] In the formula, P represents the generated power, U represents the voltage, and I represents the current;

[0048] The theoretical maximum output power of the photovoltaic module is determined by the rated power of the photovoltaic module under standard test conditions.

[0049] The current light intensity, photovoltaic module temperature and calculated actual power generation are obtained through the data acquisition module;

[0050] Considering the influence of temperature and light on power, the theoretical power is corrected according to the power temperature coefficient and light intensity coefficient of the photovoltaic module;

[0051] Among them, the corrected theoretical power calculation formula is:

[0052]

[0053] Where P theoretical Represents the corrected theoretical power, P STC It represents the rated power under standard test conditions, α represents the power temperature coefficient of the PV module, T represents the temperature of the PV module, and E represents the current light intensity.

[0054] Preferably, analyzing the power quality parameters specifically includes:

[0055] According to the fixed acquisition frequency, the discrete data of the photovoltaic array output voltage within a certain period of time is obtained, where the sequence of discrete data {U n} is expressed as, n = 1, 2, ..., N;

[0056] Calculate the voltage average:

[0057]

[0058] In the formula, represents the average voltage, and N represents the number of sample points collected;

[0059] Calculate the voltage fluctuation value at each sample point:

[0060]

[0061] In the formula, ΔU n Indicates the voltage fluctuation value;

[0062] Calculate the root mean square value of the voltage fluctuation. If the root mean square value exceeds the range specified by the grid access standard, it means that there is a power quality problem. The root mean square value of the voltage fluctuation is calculated as follows:

[0063]

[0064] Where U RMS Indicates the RMS value of voltage.

[0065] Preferably, establishing a fault diagnosis model and determining whether the system has a fault specifically includes:

[0066] Obtain various parameter data of the photovoltaic power generation system during normal operation and failure from the data storage system, including the light intensity and temperature on the surface of the photovoltaic module, and the output current and voltage of the photovoltaic array;

[0067] Label the collected data to clarify whether the data is in normal operation or fault state. For fault data, label the fault type, which includes: PV module short circuit, open circuit and inverter fault;

[0068] Preprocessing the data using a data filtering unit and a data denoising unit;

[0069] Extract features related to fault diagnosis from the preprocessed data, and build a fault diagnosis model based on the extracted features;

[0070] The labeled data set is divided into a training set and a validation set. The selected fault diagnosis model is trained using the training set, and the performance of the model is evaluated on the validation set. The model is optimized based on the validation results. When the model performance reaches a satisfactory effect, the model is deployed to the actual fault diagnosis system to determine in real time whether there is a fault in the photovoltaic power generation system.

[0071] Preferably, the expression of the fault diagnosis model is:

[0072] f(x)=sign(w T x+b)

[0073] Where w represents the weight vector and b represents the bias term.

[0074] Preferably, the monitoring and display module comprises: a data receiving unit, a real-time monitoring unit and a historical data storage unit;

[0075] The data receiving unit is used to receive the key parameter data of the photovoltaic power generation system from the data analysis and processing module;

[0076] The real-time monitoring unit is used to display the received key parameter data in real time and present it to the user in an intuitive way;

[0077] The historical data storage unit is responsible for storing the historical key parameter data of the photovoltaic power generation system.

[0078] Compared with the prior art, the present invention has the following beneficial effects:

[0079] The data acquisition module of the performance detection system of the photovoltaic power generation system proposed in the present invention can accurately measure the light intensity, temperature and output current and voltage parameters of the photovoltaic components, convert analog signals into digital signals, and provide basic data for subsequent processing. The data transmission module supports multiple transmission modes to ensure stable and efficient transmission between the data acquisition equipment and the host computer, which is convenient for operation and maintenance personnel to remotely monitor the operation status of the power generation system and handle problems. The data analysis and processing module has data preprocessing, performance index calculation and fault diagnosis and early warning, which can improve data reliability and accuracy, calculate the power generation power and efficiency, analyze the power quality parameters, and establish a fault diagnosis model and issue early warning. The monitoring and display module can display key parameters in real time, provide historical data query and report generation functions, which is convenient for operation and maintenance personnel to understand the system operation status and historical data, and is conducive to system maintenance and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 This is a module composition diagram of the present invention. DETAILED DESCRIPTION

[0081] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0082] Reference Figure 1 As shown, the performance detection system of the photovoltaic power generation system includes: a data acquisition module, a data transmission module, a data analysis and processing module and a monitoring and display module;

[0083] The data acquisition module is responsible for collecting key parameter data of the photovoltaic power generation system. It can collect analog signals and convert them into digital signals. The module can measure the light intensity on the surface of the photovoltaic module, providing a basis for evaluating the energy input of the photovoltaic power generation system. At the same time, it can monitor the temperature of the photovoltaic module, which has an impact on the performance of the photovoltaic module. In addition, the output current and voltage of the photovoltaic array can be measured, which are important parameters for analyzing the working status and performance of the photovoltaic power generation system.

[0084] The data transmission module plays a bridging role in the photovoltaic power generation system. It is dedicated to realizing data transmission between the data acquisition device and the host computer. Through the data transmission channel, it ensures that the collected data can be transmitted to the host computer for analysis and processing.

[0085] The data analysis and processing module plays a core role in the photovoltaic power generation system. It pre-processes the collected data, including filtering, denoising and calibrating the data. In terms of performance index calculation, it can calculate the power generation power and efficiency based on the voltage and current data, providing indicators for evaluating the performance of the photovoltaic power generation system. At the same time, it can analyze the power quality parameters to ensure that the power output of the photovoltaic power generation system meets the standards. In addition, by establishing a fault diagnosis model, it can determine whether there is a fault in the photovoltaic power generation system, and issue an early warning when the system is abnormal, so that personnel can take measures for repair and maintenance.

[0086] The monitoring and display module provides monitoring and query functions for the operation of the photovoltaic power generation system. It can display the key parameters of the photovoltaic power generation system in real time, allowing users to understand the working status. At the same time, it provides historical data query function, so that users can review the operation of the photovoltaic power generation system. In addition, it has a report generation function, which can generate photovoltaic power generation system operation reports according to user needs, providing data support for system evaluation and optimization.

[0087] The amplification and relay determination method for free space wireless signal transmission is:

[0088]

[0089] Where P r Represents the received power, P t Indicates the transmit power, G t represents the gain of the transmitting antenna, G r represents the gain of the receiving antenna, λ represents the signal wavelength, L represents the system loss factor, and d represents the distance between the transmitting antenna and the receiving antenna. When the signal strength is lower than the receiving threshold, the signal amplification and relay unit needs to intervene;

[0090] The determination method for amplification and relay of wired transmission is:

[0091] A=k×d

[0092] In the formula, A represents signal attenuation, and k represents the attenuation coefficient related to the transmission medium. When the attenuation causes the signal to be unable to be received normally, signal amplification and relay units need to intervene.

[0093] Filtering out high-frequency noise and low-frequency interference in the collected data specifically includes:

[0094] Select a second-order Butterworth low-pass filter. The Butterworth filter has the characteristic of maximum flatness in the passband and can filter out high-frequency noise and low-frequency interference. When selecting a filter, you need to determine the cutoff frequency. To filter out high-frequency noise, the cutoff frequency is lower than the noise frequency. To filter out low-frequency interference, the cutoff frequency is higher than the interference frequency. By setting the cutoff frequency reasonably, you can remove low-frequency interference and retain useful signal components.

[0095] For discrete-time signals, the filter's difference equation is used to calculate the filtered output signal. Discrete-time signals are common in digital signal processing, and the filter's difference equation provides a method for calculating the filtered output signal. Substituting the input signal into the difference equation, the filtered output signal can be calculated point by point. This method can effectively implement filtering operations in digital signal processing systems, improving data processing speed and accuracy.

[0096] Filtering out high-frequency noise and low-frequency interference in the collected data is a key task. By selecting appropriate filters and using differential equations to calculate the output signal, the data quality can be improved, providing a reliable basis for subsequent data analysis and processing.

[0097] Among them, the difference equation of the second-order Butterworth low-pass filter is:

[0098] y[n]=b0x[n]+b1x[n-1]+b2x[n-2]-a1y[n-1]-a2y[n-2]

[0099] Where y[n] represents the output signal after filtering, x[n] represents the input signal, n represents a discrete time point, and the coefficients b0, b1, b2, a1, and a2 are related to the cutoff frequency and the sampling frequency;

[0100] The coefficient calculation method is:

[0101] Calculate the normalized medium frequency:

[0102] ω c =2πf c / f s

[0103] In the formula, ω c represents the normalized cutoff frequency, f c represents the normalized cutoff frequency, f s Indicates the sampling frequency;

[0104]

[0105] b1=-(1+cosω c )

[0106]

[0107] a1=-2cosω c

[0108] a2=1.

[0109] The calculation of the power generation and the efficiency of the photovoltaic power generation system based on the collected photovoltaic array output voltage and current data specifically includes:

[0110] The voltage and current values ​​output by the photovoltaic array are obtained through the data acquisition module;

[0111] Substitute the collected voltage and current values ​​into the power calculation formula for calculation:

[0112] P=UI

[0113] In the formula, P represents the generated power, U represents the voltage, and I represents the current;

[0114] The rated power of PV modules under standard test conditions determines the theoretical maximum output power determined by the module specifications. Under standard test conditions, the performance of PV modules is stable and predictable, and the rated power can be used as an important reference indicator to calculate the theoretical maximum output power under specific specifications.

[0115] The data acquisition module is used to obtain the current light intensity, PV module temperature, and calculated actual power generation. The data acquisition module can accurately measure and collect these key parameters, providing a reliable data basis for subsequent analysis and processing. Light intensity and PV module temperature are important factors affecting PV power generation, and actual power generation reflects the actual operation of the PV system under current conditions.

[0116] Considering the impact of temperature and light on power, the theoretical power is corrected according to the power temperature coefficient and light intensity coefficient of the photovoltaic module. Temperature changes will have a significant impact on the performance of photovoltaic modules, and the power temperature coefficient can be used to quantify this impact. Similarly, changes in light intensity will also affect the power generation, and the light intensity coefficient can be used to correct the theoretical power to more accurately reflect the actual situation. By correcting the theoretical power, a power prediction value that is closer to the actual situation can be obtained, providing a more valuable reference for the optimization and management of photovoltaic systems.

[0117] Among them, the corrected theoretical power calculation formula is:

[0118]

[0119] Where P theoretical Represents the corrected theoretical power, P STC It represents the rated power under standard test conditions, α represents the power temperature coefficient of the PV module, T represents the temperature of the PV module, and E represents the current light intensity.

[0120] The power quality parameters analyzed include:

[0121] According to the fixed acquisition frequency, the discrete data of the photovoltaic array output voltage within a certain period of time is obtained, where the sequence of discrete data {U n} is expressed as, n = 1, 2, ..., N;

[0122] Calculate the voltage average:

[0123]

[0124] In the formula, represents the average voltage, and N represents the number of sample points collected;

[0125] Calculate the voltage fluctuation value at each sample point:

[0126]

[0127] In the formula, ΔU n Indicates the voltage fluctuation value;

[0128] Calculate the root mean square value of the voltage fluctuation. If the root mean square value exceeds the range specified by the grid access standard, it means that there is a power quality problem. The root mean square value of the voltage fluctuation is calculated as follows:

[0129]

[0130] Where U RMS Indicates the RMS value of voltage.

[0131] Establishing a fault diagnosis model and determining whether the system has a fault specifically includes:

[0132] Obtain various parameter data of the photovoltaic power generation system in different states from the data storage system. Including the light intensity on the surface of the photovoltaic module, which is important for evaluating the energy input of the photovoltaic power generation system. The temperature of the photovoltaic module, the temperature change has an impact on the performance of the photovoltaic module. The output current and voltage of the photovoltaic array, these parameters can reflect the working status and performance of the photovoltaic power generation system. The data of normal operation and failure are collected to provide a data basis for subsequent analysis and processing.

[0133] Label the collected data. Make it clear whether each set of data is in normal operation or fault state. Label the fault state data with the specific fault type, which includes PV module short circuit, open circuit and inverter fault. Labeling provides a classification basis for subsequent fault diagnosis, making fault diagnosis more accurate and efficient.

[0134] The data filtering unit and the data denoising unit are used to pre-process the data. The data filtering unit removes specific frequency components in the data, such as high-frequency noise, to make the data smoother and more stable. The data denoising unit reduces noise interference in the data and improves data quality and reliability. The two units work together to provide more accurate and reliable data for subsequent fault diagnosis.

[0135] Extract features related to fault diagnosis from the preprocessed data. Features can be voltage and current change trends, abnormal temperature fluctuations, etc. Build a fault diagnosis model based on the extracted features. The model determines whether there is a fault in the photovoltaic power generation system and the specific fault type based on the input feature data.

[0136] The labeled data set is divided into a training set and a validation set. The fault diagnosis model is trained using the training set to allow the model to learn the data features under normal operation and different fault conditions. The model performance is evaluated on the validation set, and the model accuracy, recall rate and other indicators are calculated by comparing the model prediction results with the actual annotation results. The model is optimized according to the validation results, and the parameters and structure are adjusted to improve the performance. When the model performance reaches a satisfactory effect, the model is deployed to the actual fault diagnosis system to determine whether there is a fault in the photovoltaic power generation system in real time, so that repair and maintenance measures can be taken in time to ensure the stable operation of the photovoltaic power generation system.

[0137] The expression of the fault diagnosis model is:

[0138] f(x)=sign(w T x+b)

[0139] Where w represents the weight vector and b represents the bias term.

[0140] The use process of the present invention is as follows: the data acquisition module collects the key parameter data of the photovoltaic power generation system in real time and converts it into digital signals; the data transmission module transmits the collected digital signals to the host computer to realize the remote transmission and reception of data; the data analysis and processing module pre-processes the received data, calculates performance indicators and performs fault diagnosis and early warning; the monitoring and display module displays the key parameters of the photovoltaic power generation system in real time, and provides historical data query and report generation functions to facilitate user monitoring and management.

[0141] In summary, the advantages of the present invention are: through the data acquisition module, the parameters of the photovoltaic components are accurately measured, the analog signals are converted into digital signals, and accurate data is provided for subsequent processing; the data transmission module supports wired and wireless methods to ensure stable and efficient data transmission and realize remote monitoring; the data analysis and processing module has the functions of preprocessing, performance index calculation and fault diagnosis and early warning, improves data reliability, evaluates system performance, judges faults in real time and issues early warnings; the monitoring and display module displays key parameters in real time, provides historical data query and report generation, and facilitates system maintenance and management.

[0142] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A performance detection system for a photovoltaic power generation system, characterized in that: include: Data acquisition module, data transmission module, data analysis and processing module and monitoring and display module; The data acquisition module is used to collect key parameter data of the photovoltaic power generation system and collect analog signals and convert them into digital signals. The data includes: measuring the light intensity on the surface of the photovoltaic module, monitoring the temperature of the photovoltaic module, and measuring the output current and voltage of the photovoltaic array; The data transmission module is used to realize data transmission between the data acquisition device and the host computer; The data analysis and processing module is used to pre-process the collected data, calculate performance indicators and conduct fault diagnosis and early warning. Data pre-processing includes filtering, denoising and calibration data; performance indicator calculation includes calculating the power generation power and efficiency based on voltage and current data and analyzing power quality parameters; by establishing a fault diagnosis model, it is determined whether the system has a fault and an early warning is issued in the event of an abnormality; The monitoring and display module is used to display the key parameters of the photovoltaic power generation system in real time and provide historical data query and report generation functions.

2. The performance detection system of the photovoltaic power generation system according to claim 1, characterized in that: The data acquisition module includes: a sensor unit and a data acquisition unit; The sensor unit is used to obtain real-time information on light intensity, temperature, current and voltage; The data acquisition unit is used to collect the analog signals from the sensors and convert them into digital signals.

3. The performance detection system of the photovoltaic power generation system according to claim 1, characterized in that: The data transmission module includes: a signal modulation unit, a transmission medium interface unit and a signal amplification and relay unit; The signal modulation unit is used to modulate the digital signal transmitted from the data acquisition module so that it can be transmitted in the communication channel; The transmission medium interface unit is used to connect different transmission media, including: Ethernet interface and RS-485 interface for wired transmission, Wi-Fi interface, Bluetooth interface, Zigbee interface and communication module interface for wireless transmission; The signal amplification and relay unit is used to amplify the signal strength in the case of long-distance transmission and weak signal. The amplification and relay determination method of free space wireless signal transmission is: Where P r Represents the received power, P t Indicates the transmit power, G t represents the gain of the transmitting antenna, G r represents the gain of the receiving antenna, λ represents the signal wavelength, L represents the system loss factor, and d represents the distance between the transmitting antenna and the receiving antenna. When the signal strength is lower than the receiving threshold, the signal amplification and relay unit needs to intervene; Among them, the amplification and relay determination method for wired transmission is: A=k×d In the formula, A represents signal attenuation, and k represents the attenuation coefficient related to the transmission medium. When the attenuation causes the signal to be unable to be received normally, signal amplification and relay units need to intervene.

4. The performance detection system of the photovoltaic power generation system according to claim 1, characterized in that: The data analysis and processing module includes: data filtering unit, data denoising unit, analysis and calculation unit and fault diagnosis model unit; The data filtering unit is used to filter out high-frequency noise and low-frequency interference in the collected data; The data denoising unit is used to reduce random noise in the data; The analysis and calculation unit is used to calculate the generated power, calculate the efficiency of the photovoltaic power generation system and analyze the power quality parameters according to the collected output voltage and current data of the photovoltaic array; The fault diagnosis model unit is used to establish a fault diagnosis model and determine whether there is a fault in the system.

5. The performance detection system of the photovoltaic power generation system according to claim 4, characterized in that: Filtering out high-frequency noise and low-frequency interference in the collected data specifically includes: Select a second-order Butterworth low-pass filter and determine the filter's cutoff frequency. For filtering out high-frequency noise, the cutoff frequency is lower than the noise frequency. For filtering out low-frequency interference, the cutoff frequency is higher than the interference frequency. For discrete-time signals, the filtered output signal is calculated using the filter's difference equation; Among them, the difference equation of the second-order Butterworth low-pass filter is: y[n]=b0x[n]+b1x[n-1]+b2x[n-2]-a1y[n-1]-a2y[n-2] Where y[n] represents the output signal after filtering, x[n] represents the input signal, n represents a discrete time point, and the coefficients b0, b1, b2, a1, and a2 are related to the cutoff frequency and the sampling frequency; The coefficient calculation method is: Calculate the normalized medium frequency: oh c =2πf c / f s In the formula, ω c represents the normalized cutoff frequency, f c represents the normalized cutoff frequency, f s Indicates the sampling frequency; b1=-(1+cosω c ) a1=-2cosω c a2＝1。 6. The performance detection system of the photovoltaic power generation system according to claim 4, characterized in that: The calculation of the power generation and the efficiency of the photovoltaic power generation system based on the collected photovoltaic array output voltage and current data specifically includes: The voltage and current values ​​output by the photovoltaic array are obtained through the data acquisition module; Substitute the collected voltage and current values ​​into the power calculation formula for calculation: P=UI In the formula, P represents the generated power, U represents the voltage, and I represents the current; The theoretical maximum output power of the photovoltaic module is determined by the rated power of the photovoltaic module under standard test conditions. The current light intensity, photovoltaic module temperature and calculated actual power generation are obtained through the data acquisition module; Considering the influence of temperature and light on power, the theoretical power is corrected according to the power temperature coefficient and light intensity coefficient of the photovoltaic module; Among them, the corrected theoretical power calculation formula is: Where P theoretical Represents the corrected theoretical power, P STC It represents the rated power under standard test conditions, α represents the power temperature coefficient of the PV module, T represents the temperature of the PV module, and E represents the current light intensity.

7. The performance detection system of the photovoltaic power generation system according to claim 4, characterized in that: The power quality parameters analyzed include: According to the fixed acquisition frequency, the discrete data of the photovoltaic array output voltage within a certain period of time is obtained, where the sequence of discrete data {U n } is expressed as, n = 1, 2, ..., N; Calculate the voltage average: In the formula, represents the average voltage, and N represents the number of sample points collected; Calculate the voltage fluctuation value at each sample point: In the formula, ΔU n Indicates the voltage fluctuation value; Calculate the root mean square value of the voltage fluctuation. If the root mean square value exceeds the range specified by the grid access standard, it means that there is a power quality problem. The root mean square value of the voltage fluctuation is calculated as follows: Where U RMS Indicates the RMS value of voltage.

8. The performance detection system of the photovoltaic power generation system according to claim 4, characterized in that: Establishing a fault diagnosis model and determining whether the system has a fault specifically includes: Obtain various parameter data of the photovoltaic power generation system during normal operation and failure from the data storage system, including the light intensity and temperature on the surface of the photovoltaic module, and the output current and voltage of the photovoltaic array; Label the collected data to clarify whether the data is in normal operation or fault state. For fault data, label the fault type, which includes: PV module short circuit, open circuit and inverter fault; Preprocessing the data using a data filtering unit and a data denoising unit; Extract features related to fault diagnosis from the preprocessed data, and build a fault diagnosis model based on the extracted features; The labeled data set is divided into a training set and a validation set. The selected fault diagnosis model is trained using the training set, and the performance of the model is evaluated on the validation set. The model is optimized based on the validation results. When the model performance reaches a satisfactory effect, the model is deployed to the actual fault diagnosis system to determine in real time whether there is a fault in the photovoltaic power generation system.

9. The performance detection system of the photovoltaic power generation system according to claim 8, characterized in that: The expression of the fault diagnosis model is: f(x)=sign(w T x+b) Where w represents the weight vector and b represents the bias term.

10. The performance detection system of the photovoltaic power generation system according to claim 1, characterized in that: The monitoring and display module includes: a data receiving unit, a real-time monitoring unit and a historical data storage unit; The data receiving unit is used to receive the key parameter data of the photovoltaic power generation system from the data analysis and processing module; The real-time monitoring unit is used to display the received key parameter data in real time and present it to the user in an intuitive way; The historical data storage unit is responsible for storing the historical key parameter data of the photovoltaic power generation system.

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