Environmental assessment method and system for photovoltaic power station

Abstract

The invention discloses an environment assessment method and system for a photovoltaic power station, and the method comprises the steps: firstly obtaining the environment data of a to-be-assessed photovoltaic power station in real time through at least one environment information collection device; preprocessing the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; constructing an evaluation index system of the environment characteristic data; determining evaluation parameters and evaluation factors of the environment characteristic data based on the environment characteristic data and an evaluation index system; and determining an environment evaluation result of the photovoltaic power station to be evaluated based on the evaluation parameters and the evaluation factors of the environment characteristic data. Through the above mode, effective integration and analysis of the environmental data are realized, and the method is of great significance in improving the operation efficiency of a photovoltaic power station, reducing the operation and maintenance cost, prolonging the service life of equipment and guaranteeing the operation safety.

Description

Technical Field

[0001] The present invention belongs to the technical field of environmental assessment, and in particular to an environmental assessment method and system for a photovoltaic power station. Background Art

[0002] As the global demand for renewable energy continues to grow, the construction and application of photovoltaic power stations as a clean and renewable energy supply method has been widely promoted around the world. However, the power generation efficiency and operational stability of photovoltaic power stations are significantly affected by a variety of environmental factors, including but not limited to light intensity, temperature, humidity, wind speed, wind direction, atmospheric pressure, precipitation, and air quality. These environmental factors not only directly affect the conversion efficiency of photovoltaic panels, but may also pose a potential threat to the operation and maintenance management, equipment life and safety of photovoltaic power stations.

[0003] Traditionally, environmental assessment of photovoltaic power plants relies on manual on-site surveys and regular monitoring, which is not only time-consuming and labor-intensive, but also difficult to achieve real-time and comprehensive monitoring of environmental factors. In addition, due to the diversity and complexity of environmental data, how to effectively integrate and analyze these data to scientifically and systematically evaluate the operating environment of photovoltaic power plants has become an urgent problem to be solved. Summary of the invention

[0004] The purpose of the present invention is to provide an environmental assessment method and system for a photovoltaic power station to address the deficiencies in the prior art. The method develops a method that can obtain environmental data of a photovoltaic power station in real time, and finally obtains a scientific and accurate environmental assessment result through steps such as preprocessing, building an assessment index system, and determining assessment parameters. The method is of great significance for improving the operating efficiency of photovoltaic power stations, reducing operation and maintenance costs, extending equipment life, and ensuring operational safety.

[0005] An embodiment of the present application provides an environmental assessment method for a photovoltaic power station, the method comprising: Acquire environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information collection device; Preprocessing the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; Constructing an evaluation index system for the environmental characteristic data; Based on the environmental characteristic data and the evaluation index system, determining the evaluation parameters and evaluation factors of the environmental characteristic data; Based on the evaluation parameters and evaluation factors of the environmental characteristic data, an environmental evaluation result of the photovoltaic power station to be evaluated is determined.

[0006] Optionally, the step of acquiring environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information collection device includes: The visual data of the photovoltaic power station to be evaluated is collected by the intelligent image acquisition component in the environmental information acquisition device; the visual data includes the cleanliness, damage and shadow occlusion of the surface of the photovoltaic panels monitored by the photovoltaic power station to be evaluated; Collecting basic meteorological data of the photovoltaic power station to be evaluated through the meteorological data sensing component in the environmental information collection device; the basic meteorological data includes the ambient temperature, ambient humidity and wind speed data of the photovoltaic power station to be evaluated; and The solar radiation data of the photovoltaic power station to be evaluated is collected by the radiation data collection component in the environmental information collection device; the solar radiation data includes the total radiation, scattered radiation and albedo radiation data of the photovoltaic power station to be evaluated.

[0007] Optionally, the preprocessing of the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data includes: Evaluate the environmental data of each photovoltaic power station to be evaluated through preset environmental parameters, and build an environmental characteristic evaluation matrix; Perform normalization test on environmental characteristic assessment matrix; According to the normalized and verified environmental feature evaluation matrix, feature extraction of environmental data is performed to achieve high entropy data formed by screening out key feature information from the environmental data as environmental feature data.

[0008] Optionally, constructing an evaluation index system for the environmental feature data includes: Determine the risk factors of PV power plants and their associated characteristics based on the assessment scope and evaluation scale of environmental characteristic data; Each of the photovoltaic power station risk factors and their associated characteristics are assembled into a two-dimensional matrix as an input data set for training the environmental assessment neural network model to form an assessment index system for environmental characteristic data.

[0009] Optionally, determining the evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system includes: dividing the environmental characteristic data into evaluation index layer data, evaluation element layer data and evaluation target layer data; Based on the evaluation index system, pairwise comparisons are performed on the data of each layer to obtain the importance of the data of each layer; According to the importance of each layer of elements and the data of the previous layer, the importance is compared to obtain the evaluation parameters and evaluation factors of the determined environmental characteristic data.

[0010] Optionally, the determining the environmental assessment result of the photovoltaic power station to be assessed based on the assessment parameters and assessment factors of the environmental characteristic data includes: Based on the assessment parameters and assessment factors of the environmental characteristic data, the entropy weight method is adopted to calculate the environmental assessment risk value of the photovoltaic power station to be assessed, so as to obtain the overall environmental assessment risk value of the photovoltaic power station to be assessed and quantify the environmental assessment result of the photovoltaic power station to be assessed.

[0011] Another embodiment of the present application provides an environmental assessment system for a photovoltaic power station, the system comprising: An acquisition module, used to acquire environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information acquisition device; An execution module, used to perform preprocessing of the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; A construction module, used to construct an evaluation index system for the environmental characteristic data; A first determination module, used to determine the evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system; The second determination module is used to determine the environmental assessment result of the photovoltaic power station to be assessed based on the assessment parameters and assessment factors of the environmental characteristic data.

[0012] Optionally, the acquisition module includes: A visual data acquisition unit, used to collect visual data of the photovoltaic power station to be evaluated through the intelligent image acquisition component in the environmental information acquisition device; the visual data includes the cleanliness, damage and shadow occlusion of the surface of the photovoltaic panels monitored by the photovoltaic power station to be evaluated; A meteorological data acquisition unit, used to collect basic meteorological data of the photovoltaic power station to be evaluated through a meteorological data sensing component in an environmental information acquisition device; the basic meteorological data includes ambient temperature, ambient humidity and wind speed data of the photovoltaic power station to be evaluated; and The radiation data acquisition unit is used to collect solar radiation data of the photovoltaic power station to be evaluated through the radiation data acquisition component in the environmental information acquisition device; the solar radiation data includes the total radiation, scattered radiation and albedo radiation data of the photovoltaic power station to be evaluated.

[0013] Yet another embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the method described above.

[0014] Yet another embodiment of the present application provides a storage medium, wherein the storage medium stores a computer program, wherein the computer program is configured to execute the above-mentioned method when running.

[0015] Compared with the prior art, the present invention firstly acquires the environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information collection device; performs preprocessing of the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; constructs an evaluation index system for the environmental characteristic data; determines the evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system; determines the environmental evaluation results of the photovoltaic power station to be evaluated based on the evaluation parameters and evaluation factors of the environmental characteristic data. Through the above-mentioned methods, effective integration and analysis of environmental data are achieved, which is of great significance for improving the operating efficiency of photovoltaic power stations, reducing operation and maintenance costs, extending equipment life, and ensuring operational safety. Description of the drawings Figure 1 A hardware structure block diagram of a computer terminal for an environmental assessment method for a photovoltaic power station provided by an embodiment of the present invention; Figure 2 A schematic diagram of a flow chart of an environmental assessment method for a photovoltaic power station provided by an embodiment of the present invention; Figure 3 A schematic diagram of the structure of an environmental assessment system for a photovoltaic power station provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, but should not be construed as limiting the present invention.

[0017] An embodiment of the present invention provides an environmental assessment method for a photovoltaic power station. The method can be applied to electronic devices, such as computer terminals, specifically ordinary computers, tablets, etc.

[0018] The following describes it in detail by taking running on a computer terminal as an example. Figure 1 The hardware structure block diagram of a computer terminal of a photovoltaic power station environmental assessment method provided by an embodiment of the present invention. Figure 1 As shown, the computer terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the computer terminal may also include a transmission device 106 for communication functions and an input and output device 108. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above-mentioned computer terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0019] The memory 104 can be used to store software programs and modules of application software, such as program instructions / modules corresponding to the environmental assessment method of the photovoltaic power station in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0020] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0021] In recent years, with the rapid development of technologies such as the Internet of Things, big data, and cloud computing, environmental information collection equipment has been widely used, and can collect various environmental data around photovoltaic power stations in real time and accurately. These devices have achieved all-round and high-precision monitoring of the photovoltaic power station environment through sensor networks, providing a solid foundation for the preprocessing and in-depth analysis of environmental data. However, simply collecting environmental data is not enough to directly guide the optimized operation and scientific management of photovoltaic power stations. In order to make full use of these valuable data resources, it is necessary to build a scientific and reasonable evaluation index system to comprehensively and objectively reflect the operating environment of photovoltaic power stations. At the same time, it is also necessary to develop corresponding algorithm models to determine the evaluation factors of each evaluation parameter based on environmental feature data and its evaluation index system, and obtain accurate environmental evaluation results based on this. In summary, the automation and intelligence level of photovoltaic power station environmental assessment needs to be improved, especially in the real-time collection, preprocessing, construction of evaluation index system, and generation of evaluation results of environmental data. Therefore, developing a method that can obtain real-time environmental data of photovoltaic power stations and finally obtain scientific and accurate environmental assessment results through preprocessing, construction of evaluation index system and determination of evaluation parameters is of great significance for improving the operating efficiency of photovoltaic power stations, reducing operation and maintenance costs, extending equipment life and ensuring operation safety.

[0022] See also Figure 2 , Figure 2 A schematic flow chart of an environmental assessment method for a photovoltaic power station provided by an embodiment of the present invention may include the following steps: S201: Acquire environmental data of a photovoltaic power station to be evaluated in real time through at least one environmental information collection device.

[0023] Specifically, real-time acquisition of environmental data of the PV power plant to be evaluated is an important prerequisite for ensuring efficient operation and optimized maintenance of the PV power plant. This can usually be achieved by installing professional PV environmental monitoring equipment that can collect and transmit key environmental parameters in real time.

[0024] For example, obtaining the environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information collection device may include: The visual data of the photovoltaic power station to be evaluated is collected by the intelligent image acquisition component in the environmental information acquisition device; the visual data includes the cleanliness, damage and shadow occlusion of the surface of the photovoltaic panels monitored by the photovoltaic power station to be evaluated; Collecting basic meteorological data of the photovoltaic power station to be evaluated through the meteorological data sensing component in the environmental information collection device; the basic meteorological data includes the ambient temperature, ambient humidity and wind speed data of the photovoltaic power station to be evaluated; and The solar radiation data of the photovoltaic power station to be evaluated is collected by the radiation data collection component in the environmental information collection device; the solar radiation data includes the total radiation, scattered radiation and albedo radiation data of the photovoltaic power station to be evaluated.

[0025] Specifically, the intelligent image acquisition component in the environmental information acquisition device can capture the visual data of the photovoltaic power plant to be evaluated in real time. This data is not limited to static images, but may also include video streams for detailed monitoring of various conditions on the surface of photovoltaic panels. Specifically, the collection of visual data covers the following aspects: Cleanliness monitoring: By analyzing the image of the photovoltaic panel surface, its cleanliness can be judged. Dust, dirt or other contaminants will reduce the light transmittance and power generation efficiency of the photovoltaic panel.

[0026] Damage detection: Image acquisition components can capture cracks, breaks or other physical damage on photovoltaic panels. Timely detection and repair of these damages can prevent further performance degradation and safety hazards.

[0027] Shadow analysis: Shadows on photovoltaic panels can significantly reduce their power generation efficiency. Intelligent image acquisition components can be used to monitor in real time whether photovoltaic panels are blocked by trees, buildings or other obstacles, thereby optimizing the layout and maintenance strategy of photovoltaic power stations.

[0028] The meteorological data sensing component in the environmental information collection device is responsible for collecting the basic meteorological data of the photovoltaic power station to be evaluated. The basic meteorological data mainly includes: ambient temperature, ambient humidity and wind speed data. Among them, the power generation efficiency of photovoltaic panels is significantly affected by the ambient temperature. High temperature will increase the internal resistance of photovoltaic panels, thereby reducing power generation efficiency. Excessive ambient humidity may affect the heat dissipation effect of photovoltaic panels, thereby affecting their performance. Wind speed not only affects the heat dissipation of photovoltaic panels, but also may bring pollutants such as sand, dust, and debris, causing damage to photovoltaic panels.

[0029] Through the radiation data acquisition component in the environmental information acquisition device, the solar radiation data of the photovoltaic power station to be evaluated can be obtained in real time. These data directly determine the power generation potential of the photovoltaic power station and are important parameters for evaluating its performance. Solar radiation data mainly include: total radiation, diffuse radiation and albedo radiation, among which total radiation is the total amount of solar radiation on the horizontal plane, including direct radiation and diffuse radiation. Diffuse radiation refers to the solar radiation that reaches the ground after being scattered by the atmosphere. Albedo radiation refers to the radiation energy reflected back to the sky from the surface. In a photovoltaic power station, the size of the albedo radiation is related to the reflection characteristics of the ground cover (such as vegetation, buildings, etc.).

[0030] In summary, the environmental data of the photovoltaic power station to be evaluated can be obtained in real time through environmental information collection equipment, covering multiple aspects such as visual data, basic meteorological data and solar radiation data. These data provide comprehensive and accurate information support for the operation management, performance evaluation and fault warning of photovoltaic power stations.

[0031] S202: Preprocessing the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data.

[0032] Specifically, preprocessing the environmental data of the photovoltaic power station to be evaluated is an important step in the data analysis and evaluation process. The purpose of preprocessing is to clean and organize the original data, extract useful information, and generate environmental characteristic data that can be used for subsequent analysis.

[0033] First, the collected environmental data needs to be cleaned to remove noise, outliers, and missing values. For example, through statistical analysis, domain value setting, or machine learning-based methods, identify and process those abnormal data points that are significantly deviated from the normal range. These outliers may be caused by equipment failure, extreme weather conditions, or data collection errors. Then for missing data points, appropriate filling strategies can be selected according to the characteristics of the data, such as using the mean, median, mode, or model-based predicted values ​​to fill. If there are too many missing values ​​or they cannot be filled reasonably, you may need to delete the records containing missing values. Finally, for some continuously changing data (such as temperature, humidity, etc.), smoothing can be used to reduce random fluctuations and improve the stability and analyzability of the data. Commonly used smoothing methods include moving average, exponential smoothing, etc.

[0034] After data cleaning, data from different acquisition devices or at different time points need to be integrated to form a unified data set. At the same time, the data also needs to be converted as necessary to meet the needs of subsequent analysis. For example, through time synchronization, ensure that data from different acquisition devices are consistent in time to facilitate subsequent time series analysis or data comparison. Or unify the units of all relevant data to the same standard to avoid analysis errors caused by inconsistent units. For high-dimensional data (such as data sets containing multiple environmental parameters), dimensionality reduction can be performed through principal component analysis (PCA), factor analysis and other methods to extract the main environmental characteristics.

[0035] Feature extraction is a key step in generating environmental feature data. By extracting key features that can reflect the operating environment and performance of photovoltaic power stations, it can provide strong support for subsequent analysis and evaluation. Specific methods may include: calculating the statistics of environmental parameters (such as mean, variance, standard deviation, extreme value, etc.) to reflect the overall characteristics and distribution of the data. For time series data (such as temperature, humidity, etc.), trend features, periodic features, seasonal features, etc. can be extracted to reveal the law of data changes over time. For image data obtained by intelligent image acquisition components, image processing techniques (such as edge detection, texture analysis, shape recognition, etc.) can be used to extract features such as cleanliness, damage, and shadow occlusion on the surface of photovoltaic panels.

[0036] After extracting a large number of features, feature selection is required to screen out the most valuable features for subsequent analysis and evaluation. Feature selection methods include filtering, packaging, and embedding. Through feature selection, data redundancy and noise can be reduced, and the accuracy and efficiency of the analysis model can be improved. After the above steps, the final generated environmental feature data will contain a series of cleaned, integrated, converted, and feature-extracted data sets. These data sets will serve as inputs for subsequent analysis and evaluation to evaluate the operating performance of photovoltaic power plants, predict power generation potential, identify potential problems, and develop corresponding optimization strategies.

[0037] Exemplarily, the preprocessing of the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data may include: 1. Evaluate the environmental data of each photovoltaic power station to be evaluated by pre-setting environmental parameters, and construct an environmental characteristic evaluation matrix; 2. Perform normalization test on the environmental feature evaluation matrix; 3. Based on the normalized and verified environmental feature evaluation matrix, feature extraction of environmental data is performed to achieve high entropy data formed by screening out key feature information from the environmental data as environmental feature data.

[0038] Specifically, a set of preset environmental parameters are first defined, which should be able to fully reflect the key environmental factors of the operation of photovoltaic power stations. These parameters may include but are not limited to light intensity, temperature, humidity, wind speed, shadow occlusion, photovoltaic panel cleanliness, etc. Then, for each photovoltaic power station to be evaluated, these preset environmental parameters are evaluated based on the results of its environmental data collection. The evaluation process may involve data conversion, calculation of statistical indicators (such as mean, median, standard deviation, etc.) or application of specific evaluation models. After the evaluation is completed, the evaluation results are organized into an environmental feature evaluation matrix. Each row of this matrix represents the evaluation result of an environmental parameter, and each column represents the evaluation data of a photovoltaic power station.

[0039] Since the dimensions and ranges of different environmental parameters may be different, direct comparison or analysis may lead to bias. Therefore, it is necessary to normalize the environmental characteristic assessment matrix to eliminate the impact of dimension and range differences. The purpose of normalization is to convert each element in the matrix to the same numerical range, usually between 0 and 1. This can be achieved through different normalization methods, such as minimum-maximum normalization, Z-score normalization, etc. After completing the normalization process, the normalization results need to be tested to ensure that no new bias or errors are introduced during the processing.

[0040] After the normalization test is passed, the next step is to perform feature extraction of environmental data. The purpose of feature extraction is to filter out the most valuable key feature information for the operation performance and evaluation of photovoltaic power plants from a large amount of environmental data. This process may involve a variety of methods and techniques, such as principal component analysis (PCA), linear discriminant analysis (LDA), feature selection algorithms (such as filtering, packaging, embedding, etc.). Through these methods, the environmental features that have the greatest impact on the performance of photovoltaic power plants can be identified, and a high-entropy (i.e., large amount of information) environmental feature data set can be constructed.

[0041] Finally, the key feature information screened out through the feature extraction process will form high-entropy environmental feature data. These data not only have a high amount of information, but also can accurately reflect the operating environment and performance status of the photovoltaic power station. The high-entropy environmental feature data will be used as input for subsequent analysis and evaluation, and will be used for performance evaluation, power generation potential prediction, fault diagnosis, and optimization strategy formulation of photovoltaic power stations. In summary, by performing pre-processing steps such as preset environmental parameter evaluation, normalization test, and feature extraction on the environmental data of the photovoltaic power station to be evaluated, high-entropy environmental feature data can be generated, providing strong support for subsequent analysis and evaluation work.

[0042] S203: Constructing an evaluation index system for the environmental characteristic data.

[0043] Specifically, the construction of the evaluation index system for the environmental characteristic data may include: Based on the assessment scope and evaluation scale of the environmental characteristic data, the risk factors of the photovoltaic power station and their associated characteristics are determined; each of the risk factors of the photovoltaic power station and their associated characteristics are pieced together into a two-dimensional matrix as an input data set for training the environmental assessment neural network model to form an assessment index system for the environmental characteristic data.

[0044] First, determine the scope and scale of the assessment, and clarify which environmental characteristic data will be included in the assessment scope, which usually includes but is not limited to meteorological conditions (such as temperature, humidity, wind speed, radiation, etc.), geographical location characteristics (such as latitude, altitude, terrain, etc.), surrounding environmental conditions (such as shadows, air quality, etc.) and photovoltaic panel status (such as cleanliness, damage, etc.). The evaluation scale includes setting one or more evaluation scales for each environmental characteristic. These scales can be quantitative (such as a specific numerical range), semi-quantitative or qualitative. The selection of the evaluation scale should be based on its impact on the operational risk of the photovoltaic power station and its quantifiability.

[0045] Then, based on the empirical data and professional knowledge of photovoltaic power station operation, identify the risk factors that may affect the power generation efficiency, operation stability and maintenance cost of photovoltaic power stations. These risk factors may include but are not limited to extreme weather, shadowing, equipment aging, insufficient cleaning, etc. For each risk factor, analyze its correlation with environmental characteristic data to determine which environmental characteristic data can directly or indirectly reflect or predict the probability of occurrence or impact of the risk factor.

[0046] Construct a two-dimensional matrix as the input data set, and organize the identified risk factors and their associated features into the form of a two-dimensional matrix. The rows of the matrix represent different risk factors, and the columns represent different evaluation indicators or features related to the environmental characteristic data. Fill in the corresponding positions in the two-dimensional matrix according to the actual collected environmental characteristic data. For missing data, interpolation, prediction or default values ​​can be used to fill it.

[0047] Secondly, train the environment evaluation neural network model and select a suitable neural network model (such as multi-layer perceptron, convolutional neural network, recurrent neural network, etc.) for environment evaluation. The choice of model should be based on the characteristics of the data, the complexity of the evaluation, and the limitation of computing resources. Use the constructed two-dimensional matrix as the input data set to train the neural network model. During the training process, adjust the parameters and structure of the model to minimize the prediction error or maximize the evaluation accuracy. Evaluate the performance of the model through methods such as cross-validation, and perform parameter tuning and model structure optimization as needed.

[0048] Finally, an evaluation index system is formed, and key evaluation indicators are extracted from the trained neural network model. These indicators can be the input features of the model, hidden layer nodes or prediction results of the output layer. Based on the extracted evaluation indicators, a complete set of environmental feature data evaluation index system is constructed. The system should be able to comprehensively and accurately reflect the risk status of the operating environment of the photovoltaic power station and provide a scientific basis for subsequent decision support and optimization.

[0049] Through the above steps, a complete risk assessment indicator system can be built based on environmental characteristic data, and the accuracy and efficiency of the assessment can be improved by training the environmental assessment neural network model. This is of great significance for the operation management and risk prevention and control of photovoltaic power stations.

[0050] S204: Determine evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system.

[0051] Specifically, determining the evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system may include: Step 1: Divide the environmental characteristic data into evaluation index layer data, evaluation element layer data and evaluation target layer data; Step 2: Based on the evaluation index system, pairwise comparisons are performed on the data of each layer to obtain the importance of the data of each layer; Step 3: Compare the importance of each layer of elements with the data of the previous layer to obtain the evaluation parameters and evaluation factors of the environmental characteristic data.

[0052] Exemplarily, the environmental characteristic data can first be divided into three levels, such as evaluation index layer data, evaluation factor layer data and evaluation target layer data. Among them, the evaluation target layer data represents the overall goal of the entire evaluation system, such as "comprehensive evaluation of environmental characteristics of photovoltaic power stations". The evaluation factor layer data contains the main aspects or elements that constitute the evaluation target, such as "weather conditions", "geographic location", "surrounding environment" and "photovoltaic panel status". The evaluation index layer data includes quantifiable evaluation indicators, such as "temperature", "humidity", "wind speed", "radiation", etc.

[0053] For the evaluation index layer data, each index is compared in pairs to evaluate their relative importance. For example, the influence of "temperature" and "radiation" on the power generation efficiency of photovoltaic power stations is compared.

[0054] For the evaluation factor layer data, pairwise comparisons are also performed to evaluate the contribution of different factors to the overall evaluation target. For example, the impact of "weather conditions" and "geographic location" on the operating environment of photovoltaic power stations is compared.

[0055] Use tools such as the analytic hierarchy process (AHP) to construct a judgment matrix to represent the relative importance of each element. The elements of the judgment matrix can be obtained through expert scoring, questionnaires, etc. Perform a consistency test on the judgment matrix to ensure the consistency and rationality of the comparison results. Then, based on the importance of each layer of elements, select several parameters that have the greatest impact on the evaluation target as evaluation parameters. These parameters should be able to fully reflect the environmental characteristics of the photovoltaic power station and have high representativeness and sensitivity.

[0056] The importance of the evaluation parameters of the evaluation index layer data is compared with the evaluation factor layer data to further determine the position and weight of the evaluation parameters in the overall evaluation system. At the same time, the evaluation elements of the evaluation factor layer data are compared with the evaluation target layer data to ensure the logic and consistency of the entire evaluation system.

[0057] For each evaluation parameter, determine the corresponding evaluation factor according to its characteristics and evaluation requirements. The evaluation factor can be a quantitative value range, a grade classification, or a qualitative description. For example, for the evaluation parameter "temperature", "temperature < 25℃ is excellent, 25℃ ≤ temperature < 35℃ is good, and temperature ≥ 35℃ is poor" can be set as the evaluation factor.

[0058] Finally, the various evaluation parameters and their evaluation factors are combined for evaluation. This can be achieved through weighted summation, fuzzy comprehensive evaluation and other methods. According to the specific situation and evaluation requirements of the photovoltaic power station, appropriate weights are assigned to different evaluation parameters and evaluation factors, and they are calculated and sorted according to a certain algorithm to obtain a comprehensive evaluation result.

[0059] Through the above steps, we can systematically determine the evaluation parameters and evaluation factors of environmental characteristic data, and provide a scientific basis for the operation management and risk prevention and control of photovoltaic power stations.

[0060] 205: Determine an environmental assessment result of the photovoltaic power station to be assessed based on the assessment parameters and assessment factors of the environmental characteristic data.

[0061] Specifically, the determining the environmental assessment result of the photovoltaic power station to be assessed based on the assessment parameters and assessment factors of the environmental characteristic data may include: Based on the assessment parameters and assessment factors of the environmental characteristic data, the entropy weight method is adopted to calculate the environmental assessment risk value of the photovoltaic power station to be assessed, so as to obtain the overall environmental assessment risk value of the photovoltaic power station to be assessed and quantify the environmental assessment result of the photovoltaic power station to be assessed.

[0062] Among them, the entropy weight method is an effective method to calculate the environmental assessment risk value of the photovoltaic power station to be assessed. It can determine the weight of each assessment parameter in the overall assessment by quantifying its information entropy, thereby obtaining a more objective and accurate assessment result. The following are the steps for calculating the environmental assessment risk value using the entropy weight method based on the assessment parameters and assessment factors of the environmental characteristic data: First, collect the environmental characteristic data of the PV power plant to be evaluated. These data should cover all the determined evaluation parameters and evaluation factors. Since the units and dimensions of different evaluation parameters may be different, the collected data needs to be standardized for subsequent calculation and analysis. The standardization method can be selected according to the nature of the data, such as linear transformation, normalization, etc.

[0063] Secondly, the standardized data is constructed into a decision matrix, where the rows represent different evaluation parameters (or evaluation factors) and the columns represent different samples (such as different time periods, different monitoring points, etc.). Each element in the decision matrix is ​​normalized to obtain a probability matrix. The normalization method is usually to divide the elements of a column by the sum of the elements of the column so that the sum of the elements of each column is 1. Finally, the information entropy of each evaluation parameter is calculated based on the probability matrix. Information entropy is a measure of information uncertainty, and its calculation formula is: in, Indicates The information entropy of the evaluation parameters, represents the number of samples, Indicates The sample in The probability value of the evaluation parameter.

[0064] Then the weight of each evaluation parameter is calculated, and the calculation formula is: in, Indicates The weights of the evaluation parameters, Indicates The importance of each evaluation parameter in the evaluation is met , represents the number of evaluation parameters, The sequence number representing the evaluation parameter.

[0065] According to the weights of each assessment parameter and the standardized data, the environmental assessment risk value of the photovoltaic power station to be assessed is calculated using the following formula: in, represents the environmental assessment risk value, Indicates The sample in The value after the evaluation parameters are standardized. It should be noted that in actual applications, it may be necessary to calculate the risk value for different samples (such as different time periods, different monitoring points), and then take the average value or maximum value as the final risk value. According to the calculated environmental assessment risk value, the environmental risk of the photovoltaic power station to be evaluated is evaluated and explained. The higher the risk value, the greater the environmental risk faced by the photovoltaic power station, and corresponding measures need to be taken to prevent and respond.

[0066] Through the above steps, the entropy weight method is used to quantify the environmental assessment results of the photovoltaic power station to be assessed, providing a scientific basis for the operation management and risk prevention and control of photovoltaic power stations.

[0067] It can be seen that the present invention first obtains the environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information collection device; performs preprocessing of the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; constructs an evaluation index system for environmental characteristic data; determines the evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system; determines the environmental evaluation results of the photovoltaic power station to be evaluated based on the evaluation parameters and evaluation factors of the environmental characteristic data. Through the above methods, effective integration and analysis of environmental data are achieved, which is of great significance for improving the operating efficiency of photovoltaic power stations, reducing operation and maintenance costs, extending equipment life, and ensuring operational safety.

[0068] Another embodiment of the present application provides an environmental assessment system for a photovoltaic power station, such as Figure 3 The structure diagram of an environmental assessment system for a photovoltaic power station is shown, and the system includes: An acquisition module 301 is used to acquire environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information acquisition device; An execution module 302 is used to perform preprocessing of the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; A construction module 303 is used to construct an evaluation index system for the environmental characteristic data; A first determination module 304 is used to determine the evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system; The second determination module 305 is used to determine the environmental assessment result of the photovoltaic power station to be assessed based on the assessment parameters and assessment factors of the environmental characteristic data.

[0069] Specifically, the acquisition module 301 includes: A visual data acquisition unit, used to collect visual data of the photovoltaic power station to be evaluated through the intelligent image acquisition component in the environmental information acquisition device; the visual data includes the cleanliness, damage and shadow occlusion of the surface of the photovoltaic panels monitored by the photovoltaic power station to be evaluated; A meteorological data acquisition unit, used to collect basic meteorological data of the photovoltaic power station to be evaluated through a meteorological data sensing component in an environmental information acquisition device; the basic meteorological data includes ambient temperature, ambient humidity and wind speed data of the photovoltaic power station to be evaluated; and The radiation data acquisition unit is used to collect solar radiation data of the photovoltaic power station to be evaluated through the radiation data acquisition component in the environmental information acquisition device; the solar radiation data includes the total radiation, scattered radiation and albedo radiation data of the photovoltaic power station to be evaluated.

[0070] Compared with the prior art, the present invention firstly obtains the environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information collection device; performs preprocessing of the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; constructs an evaluation index system for environmental characteristic data; determines the evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system; determines the environmental evaluation results of the photovoltaic power station to be evaluated based on the evaluation parameters and evaluation factors of the environmental characteristic data. Through the above-mentioned methods, effective integration and analysis of environmental data are achieved, which is of great significance for improving the operating efficiency of photovoltaic power stations, reducing operation and maintenance costs, extending equipment life, and ensuring operational safety.

[0071] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0072] Specifically, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0073] Specifically, in this embodiment, the processor may be configured to perform the following steps through a computer program: S201: Acquire environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information collection device; S202: Preprocessing the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; S203: constructing an evaluation index system for the environmental characteristic data; S204: Determine evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system; S205: Determine an environmental assessment result of the photovoltaic power station to be assessed based on the assessment parameters and assessment factors of the environmental characteristic data.

[0074] Compared with the prior art, the present invention firstly obtains the environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information collection device; performs preprocessing of the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; constructs an evaluation index system for environmental characteristic data; determines the evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system; determines the environmental evaluation results of the photovoltaic power station to be evaluated based on the evaluation parameters and evaluation factors of the environmental characteristic data. Through the above-mentioned methods, effective integration and analysis of environmental data are achieved, which is of great significance for improving the operating efficiency of photovoltaic power stations, reducing operation and maintenance costs, extending equipment life, and ensuring operational safety.

[0075] An embodiment of the present invention further provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0076] Specifically, in this embodiment, the above storage medium may be configured to store a computer program for performing the following steps: S201: Acquire environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information collection device; S202: Preprocessing the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; S203: constructing an evaluation index system for the environmental characteristic data; S204: Determine evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system; S205: Determine an environmental assessment result of the photovoltaic power station to be assessed based on the assessment parameters and assessment factors of the environmental characteristic data.

[0077] Specifically, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0078] Compared with the prior art, the present invention first obtains the environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information collection device; performs preprocessing of the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; constructs an evaluation index system for environmental characteristic data; determines the evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system; determines the environmental evaluation results of the photovoltaic power station to be evaluated based on the evaluation parameters and evaluation factors of the environmental characteristic data. Through the above-mentioned method, effective integration and analysis of environmental data are achieved, which is of great significance for improving the operating efficiency of photovoltaic power stations, reducing operation and maintenance costs, extending equipment life and ensuring operational safety. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, some steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0079] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0080] In the several embodiments provided by the present invention, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0081] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0082] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0083] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present invention. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0084] The embodiments of the present invention are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for environmental assessment of a photovoltaic power station, characterized in that: The method comprises: Acquire environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information collection device; Preprocessing the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; Constructing an evaluation index system for the environmental characteristic data; Based on the environmental characteristic data and the evaluation index system, determining the evaluation parameters and evaluation factors of the environmental characteristic data; Based on the evaluation parameters and evaluation factors of the environmental characteristic data, an environmental evaluation result of the photovoltaic power station to be evaluated is determined.

2. The method according to claim 1, characterized in that The step of acquiring environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information collection device includes: The visual data of the photovoltaic power station to be evaluated is collected by the intelligent image acquisition component in the environmental information acquisition device; the visual data includes the cleanliness, damage and shadow occlusion of the surface of the photovoltaic panels monitored by the photovoltaic power station to be evaluated; Collecting basic meteorological data of the photovoltaic power station to be evaluated through the meteorological data sensing component in the environmental information collection device; the basic meteorological data includes the ambient temperature, ambient humidity and wind speed data of the photovoltaic power station to be evaluated; and The solar radiation data of the photovoltaic power station to be evaluated is collected by the radiation data collection component in the environmental information collection device; the solar radiation data includes the total radiation, scattered radiation and albedo radiation data of the photovoltaic power station to be evaluated.

3. The method according to claim 2, characterized in that The performing of preprocessing of the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data includes: Evaluate the environmental data of each photovoltaic power station to be evaluated through preset environmental parameters, and build an environmental characteristic evaluation matrix; Perform normalization test on environmental characteristic assessment matrix; According to the normalized and verified environmental feature evaluation matrix, feature extraction of environmental data is performed to achieve high entropy data formed by screening out key feature information from the environmental data as environmental feature data.

4. The method according to claim 3, characterized in that The construction of the evaluation index system for the environmental characteristic data includes: Determine the risk factors of PV power plants and their associated characteristics based on the assessment scope and evaluation scale of environmental characteristic data; Each of the photovoltaic power station risk factors and their associated characteristics are assembled into a two-dimensional matrix as an input data set for training the environmental assessment neural network model to form an assessment index system for environmental characteristic data.

5. The method according to claim 4, characterized in that Determining the evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system includes: Dividing the environmental characteristic data into evaluation index layer data, evaluation element layer data and evaluation target layer data; Based on the evaluation index system, pairwise comparisons are performed on the data of each layer to obtain the importance of the data of each layer; The importance of each layer of elements is compared with the data of the previous layer to obtain the evaluation parameters and evaluation factors of the determined environmental characteristic data.

6. The method according to claim 5, characterized in that The determining of the environmental assessment result of the photovoltaic power station to be assessed based on the assessment parameters and assessment factors of the environmental characteristic data includes: Based on the assessment parameters and assessment factors of the environmental characteristic data, the entropy weight method is adopted to perform the environmental assessment risk value calculation of the photovoltaic power station to be assessed, so as to obtain the overall environmental assessment risk value of the photovoltaic power station to be assessed and quantify the environmental assessment result of the photovoltaic power station to be assessed.

7. An environmental assessment system for a photovoltaic power station, characterized in that: The system comprises: An acquisition module, used to acquire environmental data of the photovoltaic power station to be evaluated in real time through at least one environmental information acquisition device; An execution module, used to perform preprocessing of the environmental data of the photovoltaic power station to be evaluated to generate environmental characteristic data; A construction module, used to construct an evaluation index system for the environmental characteristic data; A first determination module, used to determine the evaluation parameters and evaluation factors of the environmental characteristic data based on the environmental characteristic data and the evaluation index system; The second determination module is used to determine the environmental assessment result of the photovoltaic power station to be assessed based on the assessment parameters and assessment factors of the environmental characteristic data.

8. The system according to claim 7, characterized in that The acquisition module comprises: A visual data acquisition unit, used to collect visual data of the photovoltaic power station to be evaluated through the intelligent image acquisition component in the environmental information acquisition device; the visual data includes the cleanliness, damage and shadow occlusion of the surface of the photovoltaic panels monitored by the photovoltaic power station to be evaluated; A meteorological data acquisition unit, used to collect basic meteorological data of the photovoltaic power station to be evaluated through a meteorological data sensing component in an environmental information acquisition device; the basic meteorological data includes ambient temperature, ambient humidity and wind speed data of the photovoltaic power station to be evaluated; and The radiation data acquisition unit is used to collect solar radiation data of the photovoltaic power station to be evaluated through the radiation data acquisition component in the environmental information acquisition device; the solar radiation data includes the total radiation, scattered radiation and albedo radiation data of the photovoltaic power station to be evaluated.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 6.

10. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method according to any one of claims 1 to 6 when executed.

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