System operation evaluation method and system based on photovoltaic theoretical generating capacity

Abstract

The invention discloses a system operation evaluation method and system based on photovoltaic theoretical generating capacity, and the method comprises the steps: obtaining and analyzing the historical meteorological data of a local place where a photovoltaic system is located, and determining the meteorological parameter characteristics related to the generating capacity of the photovoltaic system; constructing a theoretical generating capacity prediction model of the photovoltaic system based on the meteorological parameter characteristics and a preset neural network model, and performing prediction to obtain theoretical generating capacity prediction data; acquiring actual generating capacity data of the photovoltaic system, performing data difference analysis on the actual generating capacity data and the theoretical generating capacity data, and determining data difference characteristics between the generating capacities of the photovoltaic system; and evaluating the operation condition of the photovoltaic system based on the data difference characteristics to obtain an operation evaluation value of the photovoltaic system so as to determine the operation condition of the photovoltaic system. Through data analysis, prediction model prediction and operation evaluation, comprehensive and accurate evaluation of the operation condition of the photovoltaic system can be realized, and optimization of the performance of the photovoltaic system, improvement of the power generation efficiency and reduction of the operation cost are facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation, and particularly to a system operation evaluation method and system based on the theoretical power generation of photovoltaic. Background Art

[0002] A photovoltaic power generation system is a clean energy system that uses solar photovoltaic cells to convert solar energy into electrical energy. To ensure the efficient operation and stability of the photovoltaic system, system operation evaluation is required. The operation evaluation of the photovoltaic system aims to evaluate the operation status and performance of the system through the comparison and analysis between the actual power generation of the system and the theoretical power generation.

[0003] However, traditional methods usually only evaluate the operation status of the photovoltaic system based on the difference between the actual power generation and the theoretical power generation at a single time point, and the evaluation value at a single time point cannot comprehensively reflect the operation status of the photovoltaic system, having the limitation of being unable to comprehensively reflect the overall operation status of the system. Therefore, it is necessary to accurately evaluate the operation status of the photovoltaic system through multi-stage analysis. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a system operation evaluation method and system based on the theoretical power generation of photovoltaic, including: Obtain the historical meteorological data of the location where the photovoltaic system is located, and perform data analysis on the historical meteorological data to determine the meteorological parameter characteristics related to the power generation of the photovoltaic system; Construct a theoretical power generation prediction model of the photovoltaic system based on the meteorological parameter characteristics and a preset neural network model, and perform prediction based on the theoretical power generation prediction model to obtain theoretical power generation prediction data; Obtain the actual power generation data of the photovoltaic system, and perform data difference analysis on the actual power generation data and the theoretical power generation data to determine the data difference characteristics between the power generations of the photovoltaic system; Evaluate the operation status of the photovoltaic system based on the data difference characteristics to obtain an operation evaluation value of the photovoltaic system, and evaluate the operation status of the photovoltaic system according to the operation evaluation value.

[0005] Further, the obtaining the historical meteorological data of the location where the photovoltaic system is located, and performing data analysis on the historical meteorological data to determine the meteorological parameter characteristics related to the power generation of the photovoltaic system includes: Obtain the historical meteorological data of the location where the photovoltaic system is located and the historical power generation data of the photovoltaic system, and determine several meteorological parameter types included in the historical meteorological data; Determine the data corresponding to each meteorological parameter type, and analyze the correlation between the data corresponding to each meteorological parameter type and the historical power generation data of the photovoltaic system; Select the meteorological parameter types with a relevance greater than a preset value, and for each meteorological parameter type, determine the change in the generated power corresponding to this meteorological parameter type when other meteorological parameter types are the same; Select the meteorological parameter types with a change greater than a preset value and determine them as the meteorological parameter characteristics related to the generated power of the photovoltaic system.

[0006] Further, build a theoretical generated power prediction model for the photovoltaic system based on the meteorological parameter characteristics and a preset neural network model, and perform prediction based on the theoretical generated power prediction model to obtain theoretical generated power prediction data, including: Build a data set based on the meteorological parameter characteristics and the corresponding historical blending data, and input the data set into the preset neural network model to build an initial theoretical generated power prediction model; Divide the data set into a training set and a test set according to a certain ratio, and input the training set and the test set into the initial theoretical generated power prediction model; Train and test the initial theoretical generated power prediction model until the initial theoretical generated power prediction model meets the preset convergence condition to obtain the theoretical generated power prediction model; Obtain the current meteorological data, input the current meteorological data into the theoretical generated power prediction model, and perform prediction by the theoretical generated power prediction model to obtain theoretical generated power prediction data.

[0007] Further, obtain the actual generated power data of the photovoltaic system, perform data difference analysis on the actual generated power data and the theoretical generated power data, and determine the data difference characteristics between the generated powers of the photovoltaic system, including: Obtain the actual generated power data and the theoretical generated power prediction data of the photovoltaic system, and calculate the difference between the actual generated power data and the theoretical generated power prediction data to obtain the generated power difference data; Perform stage analysis on the generated power difference data, and determine the difference stage between the actual generated power data and the theoretical generated power prediction data according to the analysis result; Determine the actual generated power data and the theoretical generated power prediction data corresponding to each difference stage, calculate the average value of the actual generated power data and the average value of the theoretical generated power prediction data respectively, and calculate the difference between the average value of the actual generated power data and the average value of the theoretical generated power prediction data; Build curves of the time progress based on the actual generated power data and the theoretical generated power prediction data respectively to obtain the actual generated power curve and the theoretical generated power curve, draw the actual generated power curve and the theoretical generated power curve into the same coordinate graph according to the time correspondence relationship to obtain the actual-theoretical generated power curve graph, and determine the sum of the areas of the figures enclosed by the actual generated power curve and the theoretical generated power curve corresponding to each difference stage in the actual-theoretical generated power curve graph; The difference between the average value of the actual power generation data corresponding to each difference stage and the average value of the theoretical power generation prediction data, as well as the area sum enclosed by the actual power generation curve and the theoretical power generation curve, are determined as the data difference characteristics between the power generations of the photovoltaic system.

[0008] Further, the power generation difference data is analyzed stage by stage, and according to the analysis results, the power generation difference data is divided into several difference stages, including: Calculate the average value of the power generation difference data, and based on the power generation difference data, construct a curve of the time progress to obtain a power generation difference data curve; Draw a straight line corresponding to the average value of the power generation difference data in the power generation difference data curve, and based on this straight line, divide the power generation difference data curve into several curve segments; Determine the time span corresponding to each curve segment, and divide the power generation difference data into several difference stages according to the time span corresponding to each curve segment.

[0009] Further, the operation status of the photovoltaic system is evaluated based on the data difference characteristics to obtain an operation evaluation value of the photovoltaic system, including: Obtain the difference between the average value of the actual power generation data corresponding to each difference stage and the average value of the theoretical power generation prediction data, as well as the area sum enclosed by the actual power generation curve and the theoretical power generation curve, and respectively evaluate and obtain values for the difference between the average value of the actual power generation data corresponding to each difference stage and the average value of the theoretical power generation prediction data, and the area sum enclosed by the actual power generation curve and the theoretical power generation curve, to respectively obtain a data difference evaluation value and an area sum evaluation value corresponding to each difference stage; Determine the time length corresponding to each difference stage and the total time length of all difference stages, respectively calculate the ratio between the time length corresponding to each difference stage and the total time length of all difference stages, and use this ratio as the weight corresponding to each difference stage; Determine the operation evaluation value of the photovoltaic system based on the data difference evaluation value, the area sum evaluation value, and the weight corresponding to each difference stage.

[0010] Further, determining the operation evaluation value of the photovoltaic system based on the data difference evaluation value, the area sum evaluation value, and the weight corresponding to each difference stage includes: Calculate the operation evaluation value of the photovoltaic system according to the data difference evaluation value, the area sum evaluation value, and the weight corresponding to each difference stage. The calculation formula for the operation evaluation value of the photovoltaic system is: , Wherein, P is the operation evaluation value of the photovoltaic system, αi is the weight corresponding to the i-th difference stage, Ai is the data difference evaluation value corresponding to the i-th difference stage, Bi is the area and evaluation value corresponding to the i-th difference stage, and n is the number of difference stages.

[0011] The present invention also provides a system operation evaluation system based on the theoretical power generation of a photovoltaic system, including: An acquisition module, configured to acquire historical meteorological data of the location where the photovoltaic system is located, perform data analysis on the historical meteorological data, and determine meteorological parameter characteristics related to the power generation of the photovoltaic system; A prediction module, configured to construct a theoretical power generation prediction model of the photovoltaic system based on the meteorological parameter characteristics and a preset neural network model, and perform prediction based on the theoretical power generation prediction model to obtain theoretical power generation prediction data; An analysis module, configured to acquire the actual power generation data of the photovoltaic system, perform data difference analysis on the actual power generation data and the theoretical power generation data, and determine the data difference characteristics between the power generations of the photovoltaic system; An evaluation module, configured to evaluate the operation status of the photovoltaic system based on the data difference characteristics to obtain the operation evaluation value of the photovoltaic system, and evaluate the operation status of the photovoltaic system according to the line evaluation value.

[0012] Compared with the prior art, the system operation evaluation method and system based on the theoretical power generation of a photovoltaic system in an embodiment of the present invention have the following beneficial effects: The theoretical power generation prediction model constructed by the present invention based on historical meteorological data and a neural network model can help predict the theoretical power generation of the photovoltaic system and provide an estimate of the system's power generation situation; The present invention performs data difference analysis and system operation status evaluation based on the comparison between the actual power generation data and the theoretical power generation prediction data, helping to understand the actual power generation situation and performance of the system; By evaluating the operation status of the photovoltaic system, the present invention can determine the operation status of the photovoltaic system, and further provide strategies for optimizing the operation of the system, improving power generation efficiency and system stability; The present invention provides accurate theoretical power generation prediction and system operation evaluation results, providing data support for managers and decision-makers, and helping managers formulate reasonable operation plans and maintenance strategies. Description of the Drawings

[0013] Figure 1 is a schematic flow structure diagram of the system operation evaluation method based on the theoretical power generation of a photovoltaic system in an embodiment of the present invention; Figure 2 is a schematic composition diagram of the system operation evaluation system based on the theoretical power generation of a photovoltaic system in an embodiment of the present invention. Detailed Embodiments

[0014] The specific implementation manners of the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention.

[0015] In the description of the present application, it should be understood that the orientation or positional relationship indicated by terms such as "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the platform or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation to the present application.

[0016] The terms "first", "second" are only used for descriptive purposes, and cannot be understood as indicating or implying a relative importance coefficient or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first", "second" may explicitly or implicitly include one or more of such features. In the description of the present application, unless otherwise specified, the meaning of "a plurality" is two or more.

[0017] In the description of the present application, it should be noted that unless otherwise clearly specified and limited, the terms "installed", "connected", "coupled" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected, or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific situations.

[0018] As Figure 1 shown, in the embodiment of the present application, a method for evaluating the operation of a system based on the theoretical power generation of a photovoltaic system is provided, including: S100: obtaining the historical meteorological data of the location where the photovoltaic system is located, and performing data analysis on the historical meteorological data to determine the meteorological parameter characteristics related to the power generation of the photovoltaic system; S200: constructing a theoretical power generation prediction model of the photovoltaic system based on the meteorological parameter characteristics and a preset neural network model, and performing prediction based on the theoretical power generation prediction model to obtain theoretical power generation prediction data; S300: obtaining the actual power generation data of the photovoltaic system, and performing data difference analysis on the actual power generation data and the theoretical power generation data to determine the data difference characteristics between the power generations of the photovoltaic system; S400: evaluating the operation status of the photovoltaic system based on the data difference characteristics to obtain an operation evaluation value of the photovoltaic system, and evaluating the operation status of the photovoltaic system according to the operation evaluation value.

[0019] Furthermore, the theoretical power generation prediction model constructed by the present invention based on historical meteorological data and neural network models can help predict the theoretical power generation of the photovoltaic system and provide an estimate of the system's power generation situation; based on the comparison between the actual power generation data and the theoretical power generation prediction data, the present invention conducts data difference analysis and system operation status evaluation to help understand the actual power generation situation and performance of the system; through the evaluation of the operation status of the photovoltaic system, the present invention can determine the operation status of the photovoltaic system, and then provide strategies for optimizing the system operation to improve power generation efficiency and system stability; the present invention provides accurate theoretical power generation prediction and system operation evaluation results, providing data support for managers and decision-makers to help managers formulate reasonable operation plans and maintenance strategies.

[0020] In an embodiment of the present application, a system operation evaluation method based on the theoretical power generation of a photovoltaic system is provided. The method includes: obtaining historical meteorological data of the location where the photovoltaic system is located, and performing data analysis on the historical meteorological data to determine meteorological parameter characteristics related to the power generation of the photovoltaic system, including: obtaining historical meteorological data of the location where the photovoltaic system is located and historical power generation data of the photovoltaic system, and determining several meteorological parameter types included in the historical meteorological data; determining the data corresponding to each meteorological parameter type, and analyzing the correlation between the data corresponding to each meteorological parameter type and the historical power generation data of the photovoltaic system; selecting meteorological parameter types with a correlation greater than a preset value, and for each selected meteorological parameter type, determining the change in power generation corresponding to this meteorological parameter type when other meteorological parameter types are the same; selecting meteorological parameter types with a change greater than a preset value, and determining them as meteorological parameter characteristics related to the power generation of the photovoltaic system.

[0021] Specifically, collect historical meteorological data of the area where the photovoltaic system is located and historical power generation data of the photovoltaic system for subsequent analysis; analyze the historical meteorological data to determine the meteorological parameter types included therein, such as light intensity, temperature, wind speed, etc.; conduct a correlation analysis between the data of each meteorological parameter type and the historical power generation data of the photovoltaic system to determine the degree of association between them; select meteorological parameter types with a correlation greater than a preset value, as these parameters have a significant impact on the power generation of the photovoltaic system; for the selected meteorological parameter types, analyze the change in power generation corresponding to this parameter type when other meteorological parameter types are the same, and select meteorological parameter types with a change greater than a preset value as the key parameter characteristics related to the power generation of the photovoltaic system. This step can help deeply understand the influence degree of different meteorological factors on the system performance by analyzing the correlation between meteorological parameters and the power generation of the photovoltaic system, and help identify key influencing factors; after determining the meteorological parameter characteristics related to power generation, the prediction model can be optimized to improve the accurate prediction ability of the power generation of the photovoltaic system.

[0022] In an embodiment of the present application, a method for evaluating the operation of a system based on the theoretical power generation of a photovoltaic system is provided. A theoretical power generation prediction model of the photovoltaic system is constructed based on meteorological parameter characteristics and a preset neural network model, and prediction is performed based on the theoretical power generation prediction model to obtain theoretical power generation prediction data, including: constructing a data set based on meteorological parameter characteristics and corresponding historical blending data, and inputting the data set into the preset neural network model to construct an initial theoretical power generation prediction model; dividing the data set into a training set and a test set according to a certain ratio, and inputting the training set and the test set into the initial theoretical power generation prediction model; training and testing the initial theoretical power generation prediction model until the initial theoretical power generation prediction model meets the preset convergence condition to obtain a theoretical power generation prediction model; obtaining current meteorological data, and inputting the current meteorological data into the theoretical power generation prediction model, and performing prediction by the theoretical power generation prediction model to obtain theoretical power generation prediction data.

[0023] Specifically, based on the determined meteorological parameter characteristics and historical power generation data, a data set is constructed, including meteorological parameter characteristics as inputs and historical power generation as outputs; a neural network model is designed and constructed as the initial framework of the theoretical power generation prediction model; the constructed data set is divided into a training set and a test set according to a certain ratio for model training and verification, and the training set and the test set are input into the preset neural network model for model training and testing until the model meets the preset convergence condition to obtain a preliminary theoretical power generation prediction model; the meteorological data at the current moment is obtained as input features, and the current meteorological data is input into the trained theoretical power generation prediction model to allow the model to perform prediction to obtain the theoretical power generation prediction data at the current moment. This step can achieve accurate prediction of the theoretical power generation of the photovoltaic system, improve prediction accuracy and reliability by constructing a neural network model and training it with historical data; inputting the current meteorological data into the trained model can achieve real-time prediction of the power generation at the current moment, helping system managers adjust operation strategies in a timely manner; by establishing a theoretical power generation prediction model, it can help managers better understand the performance of the photovoltaic system, optimize system operation and maintenance strategies, and improve system efficiency and stability; based on the analysis of historical data and neural network models, it can provide data support for the management and operation of the photovoltaic power generation system, helping to make more scientific decisions.

[0024] In an embodiment of the present application, a method for evaluating system operation based on the theoretical power generation of a photovoltaic system is provided. The method includes obtaining the actual power generation data of the photovoltaic system, performing data difference analysis on the actual power generation data and the theoretical power generation data, and determining the data difference characteristics between the power generations of the photovoltaic system, including: obtaining the actual power generation data and the theoretical power generation prediction data of the photovoltaic system, calculating the difference between the actual power generation data and the theoretical power generation prediction data to obtain power generation difference data; performing stage analysis on the power generation difference data, and determining the difference stage between the actual power generation data and the theoretical power generation prediction data according to the analysis result; determining the actual power generation data and the theoretical power generation prediction data corresponding to each difference stage, respectively calculating the average value of the actual power generation data and the average value of the theoretical power generation prediction data, and calculating the difference between the average value of the actual power generation data and the average value of the theoretical power generation prediction data; respectively constructing curves of time progress based on the actual power generation data and the theoretical power generation prediction data to obtain an actual power generation curve and a theoretical power generation curve, plotting the actual power generation curve and the theoretical power generation curve into the same coordinate graph according to the time correspondence relationship to obtain an actual-theoretical power generation curve graph, and determining the sum of the areas of the figures enclosed by the actual power generation curve and the theoretical power generation curve corresponding to each difference stage in the actual-theoretical power generation curve graph; determining the difference between the average value of the actual power generation data and the average value of the theoretical power generation prediction data corresponding to each difference stage and the sum of the areas of the figures enclosed by the actual power generation curve and the theoretical power generation curve as the data difference characteristics between the power generations of the photovoltaic system.

[0025] Specifically, calculating the difference between the actual power generation data and the theoretical power generation prediction data to obtain power generation difference data for subsequent analysis; performing stage analysis on the power generation difference data to identify the difference characteristics in different stages; determining the difference stage between the actual power generation data and the theoretical power generation prediction data according to the analysis result for further analysis in different stages; respectively calculating the average values of the actual power generation data and the theoretical power generation prediction data corresponding to each difference stage and calculating the difference between the two average values to quantify the degree of difference; respectively constructing curves of time progress based on the actual power generation data and the theoretical power generation prediction data to obtain an actual power generation curve and a theoretical power generation curve, plotting the actual power generation curve and the theoretical power generation curve into the same coordinate graph according to the time correspondence relationship to obtain an actual-theoretical power generation curve graph; in the actual-theoretical power generation curve graph, determining the sum of the areas of the figures enclosed by the actual power generation curve and the theoretical power generation curve corresponding to each difference stage to quantify the difference characteristics. By determining and evaluating the difference in average values and the sum of areas, this step can quantify the difference characteristics between the actual power generation and the predicted power generation, which helps to deeply understand the system performance; by deeply analyzing the difference characteristics, it can help the system manager optimize the operation strategy and improve the power generation efficiency and stability of the photovoltaic system.

[0026] In an embodiment of the present application, a method for evaluating system operation based on the theoretical power generation of a photovoltaic system is provided. The method includes performing a phased analysis on the power generation difference data and dividing the power generation difference data into several difference stages according to the analysis results, including: calculating the average value of the power generation difference data, and constructing a curve of the time progress based on the power generation difference data to obtain a power generation difference data curve; drawing a straight line corresponding to the average value of the power generation difference data in the power generation difference data curve, and dividing the power generation difference data curve into several curve segments based on the straight line; determining the time span corresponding to each curve segment, and dividing the power generation difference data into several difference stages according to the time span corresponding to each curve segment.

[0027] Specifically, calculating the average value of the power generation difference data, which will be an indicator of the overall difference degree; based on the power generation difference data, drawing a curve of the time progress to obtain a power generation difference data curve, showing the change trend of the power generation difference over time; drawing a straight line corresponding to the average value of the power generation difference data in the power generation difference data curve, which helps to compare the actual difference with the average difference; based on the straight line corresponding to the average value, dividing the power generation difference data curve into several curve segments, each curve segment representing a different difference degree; determining the time span corresponding to each curve segment, that is, the change of the power generation difference in different time periods, and dividing the power generation difference data into several difference stages according to these time spans. By dividing the power generation difference data curve into curve segments, this step can analyze the difference characteristics in different time periods more carefully; determining the time span corresponding to each curve segment helps the system manager understand the change trend of the power generation difference and take corresponding measures in time; dividing the power generation difference data into several difference stages helps to analyze the characteristics of each stage and determine the power generation status of each stage; through this method, the difference characteristics of the power generation data can be identified more accurately, helping to optimize the system operation and improve the power generation efficiency.

[0028] In an embodiment of the present application, a method for evaluating the operation of a system based on the theoretical power generation of a photovoltaic system is provided. The operation status of the photovoltaic system is evaluated based on data difference characteristics to obtain an operation evaluation value of the photovoltaic system, including: obtaining the difference between the average value of the actual power generation data corresponding to each difference stage and the average value of the theoretical power generation prediction data, and the sum of the areas of the figures enclosed by the actual power generation curve and the theoretical power generation curve, and respectively evaluating and obtaining values for the difference between the average value of the actual power generation data corresponding to each difference stage and the average value of the theoretical power generation prediction data, and the sum of the areas of the figures enclosed by the actual power generation curve and the theoretical power generation curve, to respectively obtain a data difference evaluation value and an area sum evaluation value corresponding to each difference stage; determining the time length corresponding to each difference stage and the total time length of all difference stages, respectively calculating the ratio between the time length corresponding to each difference stage and the total time length of all difference stages, and using this ratio as the weight corresponding to each difference stage; determining the operation evaluation value of the photovoltaic system based on the data difference evaluation value, the area sum evaluation value, and the weight corresponding to each difference stage.

[0029] Specifically, for each difference stage, calculate the difference between the average value of the actual power generation data and the average value of the theoretical power generation prediction data, which reflects the deviation degree between the actual power generation and the predicted power generation; for each difference stage, calculate the area between the actual power generation curve and the theoretical power generation curve, which can be used to quantify the overall difference between the actual power generation and the predicted power generation; according to specific circumstances, evaluate and obtain values for the data difference and the area for each difference stage to better understand the influence degree of the difference; determine the time length corresponding to each difference stage, calculate the total time length of all difference stages, and calculate the ratio of the time length of each difference stage to the total time length as the weight to reflect the importance of each stage; combine the data difference evaluation value, the area sum evaluation value, and the weight to determine the operation evaluation value of the photovoltaic system in each difference stage, helping the system manager to more comprehensively evaluate the operation status of the system. This step can quantitatively evaluate the system performance by calculating the difference value and the area between the actual data and the theoretical prediction data, helping the system manager to understand the operation of the system; according to the weight allocation of the time length, it can more accurately reflect the influence of different stages on the overall performance of the system, helping to prioritize the handling of key issues; comprehensively considering the data difference value, the area sum evaluation value, and the time length weight to determine the operation evaluation value of the system, providing comprehensive feedback and decision-making basis for the system manager; by analyzing the operation evaluation values of different stages, targeted system optimization can be carried out to improve the efficiency and performance of the system and ensure the stable operation of the photovoltaic system.

[0030] In an embodiment of the present application, a method for evaluating the operation of a system based on the theoretical power generation of a photovoltaic system is provided. The operation evaluation value of the photovoltaic system is determined based on the data difference evaluation value, the area sum evaluation value, and the weight corresponding to each difference stage, including: Calculate the operation evaluation value of the photovoltaic system according to the data difference evaluation value, the area sum evaluation value, and the weight corresponding to each difference stage. The calculation formula for the operation evaluation value of the photovoltaic system is: , where P is the operation evaluation value of the photovoltaic system, αi is the weight corresponding to the i-th difference stage, Ai is the data difference evaluation value corresponding to the i-th difference stage, Bi is the area sum evaluation value corresponding to the i-th difference stage, and n is the number of difference stages.

[0031] As Figure 2 shown, in an embodiment of the present application, a system for evaluating the operation of a system based on the theoretical power generation of a photovoltaic system is provided, including: an acquisition module, configured to acquire historical meteorological data of the location where the photovoltaic system is located, and perform data analysis on the historical meteorological data to determine meteorological parameter characteristics related to the power generation of the photovoltaic system; a prediction module, configured to construct a theoretical power generation prediction model of the photovoltaic system based on the meteorological parameter characteristics and a preset neural network model, and perform prediction based on the theoretical power generation prediction model to obtain theoretical power generation prediction data; an analysis module, configured to acquire the actual power generation data of the photovoltaic system, and perform data difference analysis on the actual power generation data and the theoretical power generation data to determine the data difference characteristics between the power generations of the photovoltaic system; an evaluation module, configured to evaluate the operation status of the photovoltaic system based on the data difference characteristics to obtain the operation evaluation value of the photovoltaic system, and evaluate the operation status of the photovoltaic system according to the operation evaluation value.

[0032] In summary, an embodiment of the present invention provides a method and a system for evaluating the operation of a system based on the theoretical power generation of a photovoltaic system, including: acquiring and analyzing historical meteorological data of the location where the photovoltaic system is located to determine meteorological parameter characteristics related to the power generation of the photovoltaic system; constructing a theoretical power generation prediction model of the photovoltaic system based on the meteorological parameter characteristics and a preset neural network model, and performing prediction to obtain theoretical power generation prediction data; acquiring the actual power generation data of the photovoltaic system, and performing data difference analysis on it and the theoretical power generation data to determine the data difference characteristics between the power generations of the photovoltaic system; evaluating the operation status of the photovoltaic system based on the data difference characteristics to obtain the operation evaluation value of the photovoltaic system, so as to determine the operation status of the photovoltaic system. Through data analysis, prediction model prediction, and operation evaluation, the present invention can achieve a comprehensive and accurate evaluation of the operation status of the photovoltaic system, which helps to optimize the performance of the photovoltaic system, improve the power generation efficiency, and reduce the operation cost.

[0033] Finally, it should be noted that: Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

[0034] The above is only an embodiment of the present invention, but it should not be used to limit the scope of the present invention. Any structural changes made in accordance with the present invention, as long as the essence of the present invention is not lost, should be regarded as falling within the protection scope of the present invention and being restricted. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process and related descriptions of the above-described platform can refer to the corresponding process in the foregoing platform embodiment, and will not be repeated here.

[0035] The term "comprising" or any other similar term is intended to cover non-exclusive inclusion, so that a process, platform, article or device / platform comprising a series of elements not only includes those elements, but also includes other elements not explicitly listed, or also includes elements inherent in these processes, platforms, articles or devices / platforms.

[0036] So far, the technical solutions of the present invention have been described in combination with the further embodiments shown in the drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to closely related technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present invention.

[0037] The above is only the preferred embodiment of the present invention, and is not used to limit the protection scope of the present invention.

Claims

1. A system operation evaluation method based on the theoretical power generation of photovoltaic, characterized in that, Including: Obtain the historical meteorological data of the location where the photovoltaic system is located, and perform data analysis on the historical meteorological data to determine the meteorological parameter characteristics related to the power generation of the photovoltaic system; Construct a theoretical power generation prediction model for the photovoltaic system based on the meteorological parameter characteristics and a preset neural network model, and perform prediction based on the theoretical power generation prediction model to obtain theoretical power generation prediction data; Obtain the actual power generation data of the photovoltaic system, and perform data difference analysis on the actual power generation data and the theoretical power generation data to determine the data difference characteristics between the power generations of the photovoltaic system; Evaluate the operating status of the photovoltaic system based on the data difference characteristics to obtain an operating evaluation value of the photovoltaic system, and evaluate the operating status of the photovoltaic system according to the operating evaluation value.

2. A system operation evaluation method based on the theoretical power generation of photovoltaic as described in claim 1, characterized in that The obtaining the historical meteorological data of the location where the photovoltaic system is located, and performing data analysis on the historical meteorological data to determine the meteorological parameter characteristics related to the power generation of the photovoltaic system includes: Obtain the historical meteorological data of the location where the photovoltaic system is located and the historical power generation data of the photovoltaic system, and determine several meteorological parameter types included in the historical meteorological data; Determine the data corresponding to each meteorological parameter type, and analyze the correlation between the data corresponding to each meteorological parameter type and the historical power generation data of the photovoltaic system; Select the meteorological parameter types with a correlation greater than a preset value, and for each meteorological parameter type, determine the change amount of the power generation corresponding to this meteorological parameter type when other meteorological parameter types are the same; Select the meteorological parameter types with a change amount greater than a preset value and determine them as the meteorological parameter characteristics related to the power generation of the photovoltaic system.

3. A method for evaluating system operation based on photovoltaic theoretical power generation according to claim 2, characterized in that, The constructing a theoretical power generation prediction model for the photovoltaic system based on the meteorological parameter characteristics and a preset neural network model, and performing prediction based on the theoretical power generation prediction model to obtain theoretical power generation prediction data includes: Construct a data set based on the meteorological parameter characteristics and the corresponding historical blending data, and input the data set into the preset neural network model to construct an initial theoretical power generation prediction model; Divide the data set into a training set and a test set according to a certain ratio, and input the training set and the test set into the initial theoretical power generation prediction model; Train and test the initial theoretical power generation prediction model until the initial theoretical power generation prediction model meets the preset convergence condition to obtain a theoretical power generation prediction model; Obtain the current meteorological data, and input the current meteorological data into the theoretical power generation prediction model, and perform prediction by the theoretical power generation prediction model to obtain theoretical power generation prediction data.

4. A system operation evaluation method based on the theoretical power generation of photovoltaic according to claim 3, characterized in that The obtaining the actual power generation data of the photovoltaic system, and performing data difference analysis on the actual power generation data and the theoretical power generation data to determine the data difference characteristics between the power generations of the photovoltaic system includes: Obtain the actual power generation data and the theoretical power generation prediction data of the photovoltaic system, and calculate the difference between the actual power generation data and the theoretical power generation prediction data to obtain power generation difference data; Perform stage analysis on the power generation difference data, and determine the difference stage between the actual power generation data and the theoretical power generation prediction data according to the analysis result. Determine the actual power generation data and the predicted theoretical power generation data corresponding to each difference stage, calculate the average value of the actual power generation data and the average value of the predicted theoretical power generation data respectively, and calculate the difference between the average value of the actual power generation data and the average value of the predicted theoretical power generation data; Based on the actual power generation data and the predicted theoretical power generation data, construct curves of the time progress respectively, obtain the actual power generation curve and the theoretical power generation curve respectively, draw the actual power generation curve and the theoretical power generation curve into the same coordinate graph according to the time correspondence relationship, obtain the actual-theoretical power generation curve graph, and determine the sum of the areas of the figures enclosed by the actual power generation curve and the theoretical power generation curve corresponding to each difference stage in the actual-theoretical power generation curve graph; Determine the difference value between the average value of the actual power generation data and the average value of the predicted theoretical power generation data corresponding to each difference stage and the sum of the areas of the figures enclosed by the actual power generation curve and the theoretical power generation curve as the data difference characteristics between the power generations of the photovoltaic system.

5. A method for evaluating the operation of a system based on the theoretical power generation of photovoltaic, according to claim 4, characterized in that, The phased analysis of the power generation difference data and the division of the power generation difference data into several difference stages according to the analysis results include: Calculate the average value of the power generation difference data and construct a curve of the time progress based on the power generation difference data to obtain the power generation difference data curve; Draw a straight line corresponding to the average value of the power generation difference data in the power generation difference data curve, and divide the power generation difference data curve into several curve segments based on this straight line; Determine the time span corresponding to each curve segment, and divide the power generation difference data into several difference stages according to the time span corresponding to each curve segment.

6. A system operation evaluation method based on the theoretical power generation of photovoltaic as described in claim 4, characterized in that The evaluation of the operating condition of the photovoltaic system based on the data difference characteristics to obtain the operating evaluation value of the photovoltaic system includes: Obtain the difference value between the average value of the actual power generation data and the average value of the predicted theoretical power generation data corresponding to each difference stage and the sum of the areas of the figures enclosed by the actual power generation curve and the theoretical power generation curve, and respectively evaluate and obtain values for the difference value between the average value of the actual power generation data and the average value of the predicted theoretical power generation data corresponding to each difference stage and the sum of the areas of the figures enclosed by the actual power generation curve and the theoretical power generation curve, and respectively obtain the data difference evaluation value and the area sum evaluation value corresponding to each difference stage; Determine the time length corresponding to each difference stage and the total time length of all difference stages, calculate the ratio between the time length corresponding to each difference stage and the total time length of all difference stages respectively, and use this ratio as the weight corresponding to each difference stage; Determine the operating evaluation value of the photovoltaic system based on the data difference evaluation value, the area sum evaluation value and the weight corresponding to each difference stage.

7. A system operation evaluation method based on the theoretical power generation of photovoltaic according to claim 6, characterized in that, The determination of the operating evaluation value of the photovoltaic system based on the data difference evaluation value, the area sum evaluation value and the weight corresponding to each difference stage includes: Calculate the operating evaluation value of the photovoltaic system according to the data difference evaluation value, the area sum evaluation value and the weight corresponding to each difference stage. The calculation formula of the operating evaluation value of the photovoltaic system is: ， Among them, P is the operation evaluation value of the photovoltaic system, αi is the weight corresponding to the i-th difference stage, Ai is the data difference evaluation value corresponding to the i-th difference stage, Bi is the area sum evaluation value corresponding to the i-th difference stage, and n is the number of difference stages.

8. A system operation evaluation system based on the theoretical power generation of photovoltaic, characterized in that, Including: An acquisition module, configured to acquire historical meteorological data of the location where the photovoltaic system is located, perform data analysis on the historical meteorological data, and determine meteorological parameter characteristics related to the power generation of the photovoltaic system; A prediction module, configured to construct a theoretical power generation prediction model of the photovoltaic system based on the meteorological parameter characteristics and a preset neural network model, and perform prediction based on the theoretical power generation prediction model to obtain theoretical power generation prediction data; An analysis module, configured to acquire the actual power generation data of the photovoltaic system, perform data difference analysis on the actual power generation data and the theoretical power generation data, and determine the data difference characteristics between the power generations of the photovoltaic system; An evaluation module, configured to evaluate the operation status of the photovoltaic system based on the data difference characteristics, obtain the operation evaluation value of the photovoltaic system, and evaluate the operation status of the photovoltaic system according to the line evaluation value.

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