Photovoltaic panel operation state monitoring method and system

Abstract

The invention discloses a photovoltaic panel operation state monitoring method and system, and the method comprises the steps: obtaining and analyzing the historical operation monitoring data of a photovoltaic panel, and determining the monitoring characteristic parameters affecting the power output of the photovoltaic panel; constructing a power output prediction model of the photovoltaic panel based on the monitoring characteristic parameters to predict power output prediction data; acquiring real-time power output data of the photovoltaic panel, and comparing the real-time power output data with the power output prediction data to determine a power difference condition; based on the power difference condition, the operation state of the photovoltaic panel is evaluated and calculated to obtain an operation state evaluation value; and determining the operation state grade of the photovoltaic panel according to the operation state evaluation value, and judging whether the operation state of the photovoltaic panel is normal or not according to the operation state grade. According to the invention, the running state of the photovoltaic panel is monitored in an objective and intelligent comprehensive comparison and evaluation mode, the current running state of the photovoltaic panel can be monitored timely and accurately, the running state monitoring efficiency is improved, and the monitoring cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic panel monitoring, and in particular to a photovoltaic panel operating status monitoring method and system. Background Art

[0002] With the rapid development of renewable energy, photovoltaic power generation, as an important form of clean energy, has received extensive attention and application. However, photovoltaic panels are affected by many factors in actual operation, such as light intensity, temperature, wind speed, etc. These factors will directly affect the power output and operating status of photovoltaic panels. Therefore, it is particularly important to monitor and evaluate the operating status of photovoltaic panels in real time.

[0003] However, traditional photovoltaic panel monitoring methods usually rely on manual inspections and experience-based judgments, lack objective data support, and are easily affected by the subjective opinions of supervisors, resulting in monitoring results that are not objective and reliable. At the same time, the monitoring cycle of traditional methods is usually long, and it is impossible to achieve timely monitoring and feedback on the operating status of photovoltaic panels, and it is difficult to discover and handle sudden failures and abnormal situations. Moreover, traditional methods require a lot of manpower and material resources for inspections and monitoring, which is costly and inefficient. Especially in large-scale photovoltaic power stations, monitoring is more difficult. Traditional methods are also difficult to fully consider the various factors that affect the power output of photovoltaic panels, such as light intensity, temperature, wind speed, etc., and it is difficult to make a comprehensive operating status assessment, resulting in inaccurate monitoring and judgment of the operating status of photovoltaic panels. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a photovoltaic panel operation status monitoring method and system, comprising:

[0005] Obtain historical operation monitoring data of photovoltaic panels, analyze the historical operation monitoring data, and determine the monitoring characteristic parameters that affect the power output of photovoltaic panels;

[0006] A power output prediction model of the photovoltaic panel is constructed based on the monitoring characteristic parameters and the preset neural network model, and prediction is performed according to the power output prediction model to obtain power output prediction data;

[0007] Obtain the real-time power output data of the photovoltaic panels, and compare and analyze the real-time power output data with the power output prediction data to determine the power difference;

[0008] Evaluate and calculate the operating status of the photovoltaic panel based on the power difference to obtain an operating status evaluation value of the photovoltaic panel;

[0009] The operation status level of the photovoltaic panel is determined according to the operation status evaluation value, and whether the operation status of the photovoltaic panel is normal is judged according to the operation status level.

[0010] Furthermore, the acquisition of historical operation monitoring data of the photovoltaic panel and analysis of the historical operation monitoring data to determine monitoring characteristic parameters affecting the power output of the photovoltaic panel include:

[0011] Obtaining historical operation monitoring data of the photovoltaic panel after preprocessing, and dividing the historical operation monitoring data into several groups of monitoring parameter data groups according to parameter types;

[0012] Obtain historical power output data of photovoltaic panels, and analyze the correlation between each set of monitoring parameter data and historical power output data;

[0013] The monitoring parameter data groups whose correlation exceeds the preset threshold are selected, and the parameters corresponding to the selected monitoring parameter data groups are used as monitoring characteristic parameters.

[0014] Furthermore, the power output prediction model of the photovoltaic panel is constructed based on the monitoring characteristic parameters and the preset neural network model, and prediction is performed according to the power output prediction model to obtain power output prediction data, including:

[0015] Building a data set based on monitoring characteristic parameters and historical power output data, and inputting the data set into a preset neural network model to build an initial model for power output prediction;

[0016] The data set is divided into a training set and a test set according to a certain ratio, and the training set and the test set are input into the initial model for power output prediction;

[0017] Training and testing the initial power output prediction model until the initial power output prediction model meets a preset convergence condition, thereby obtaining a power output prediction model;

[0018] The real-time monitoring characteristic parameters of the photovoltaic panel are obtained, and the real-time monitoring characteristic parameters are input into the power output prediction model. The power output prediction model performs prediction to obtain the power output prediction data of the photovoltaic panel.

[0019] Furthermore, the real-time power output data of the photovoltaic panel is obtained, and the real-time power output data is compared and analyzed with the power output prediction data to determine the power difference, including:

[0020] Acquire the real-time power output data and power output prediction data of the photovoltaic panel, and perform difference calculation between the real-time power output data and the power output prediction data to obtain power difference data;

[0021] Draw a time series curve graph based on the power difference data to obtain a power difference curve, and determine curve segments greater than or equal to zero and curve segments less than zero in the power difference curve;

[0022] The average value of the power difference data in each curve segment is calculated, and the maximum value of the power difference data in each curve segment and the amount of data exceeding the average value are determined.

[0023] Furthermore, the operating state of the photovoltaic panel is evaluated and calculated based on the power difference to obtain an operating state evaluation value of the photovoltaic panel, including:

[0024] Obtaining the maximum value of the power difference data in each curve segment, and evaluating each maximum value to obtain a difference evaluation value of each curve segment;

[0025] Obtaining the amount of power difference data exceeding the average value in each curve segment and determining the total amount of power difference data, and calculating the ratio of the amount of power difference data exceeding the average value to the total amount of data in each curve segment to obtain a first ratio of each curve segment;

[0026] Obtaining the time length of each curve segment and the total time length of the power difference curve, and calculating the ratio of the time length of each curve segment to the total time length of the power difference curve to obtain a second ratio of each curve segment;

[0027] The weight coefficient of each curve segment is determined based on the first ratio and the second ratio, and the difference evaluation value of each curve segment is weightedly added to the corresponding weight coefficient to obtain the operation status evaluation value of the photovoltaic panel.

[0028] Further, determining the weight coefficient of each curve segment based on the first ratio and the second ratio includes:

[0029] The weight coefficient of each curve segment is calculated according to the first ratio and the second ratio. The calculation formula of the weight coefficient of each curve segment is:

[0030] Q = α * X + β * Y,

[0031] Wherein, Q is the weight coefficient of each curve segment, α is the coefficient of the first ratio, X is the first ratio, β is the coefficient of the second ratio, and Y is the second ratio.

[0032] Further, determining the operation status level of the photovoltaic panel according to the operation status evaluation value includes:

[0033] A corresponding relationship between an operating state level and an operating state evaluation value interval is preset, and the corresponding relationship between an operating state level and an operating state evaluation value interval is associated with a corresponding operating state level for each operating state evaluation value interval;

[0034] The operating state evaluation value of the photovoltaic panel is obtained, and based on the mapping relationship between the operating state evaluation value interval to which the operating state evaluation value belongs and the operating state level corresponding to the operating state evaluation value interval, the operating state level corresponding to the operating state evaluation value interval is selected.

[0035] Further, judging whether the operation state of the photovoltaic panel is normal according to the operation state level includes:

[0036] Obtaining a preset threshold level, and judging whether the operation state of the photovoltaic panel is normal based on the relationship between the operation state level and the threshold level;

[0037] If the operating status level is greater than the threshold level, the operating status of the photovoltaic panel is abnormal;

[0038] If the operating status level is less than or equal to the threshold level, the photovoltaic panel is operating normally.

[0039] The present invention also provides a photovoltaic panel operation status monitoring system, comprising:

[0040] An acquisition module is used to acquire historical operation monitoring data of photovoltaic panels, analyze the historical operation monitoring data, and determine monitoring characteristic parameters that affect the power output of photovoltaic panels;

[0041] A prediction module is used to build a power output prediction model of the photovoltaic panel based on the monitoring characteristic parameters and the preset neural network model, and to perform prediction according to the power output prediction model to obtain power output prediction data;

[0042] The comparison module is used to obtain the real-time power output data of the photovoltaic panel, and compare and analyze the real-time power output data with the power output prediction data to determine the power difference;

[0043] A calculation module is used to evaluate and calculate the operating status of the photovoltaic panel based on the power difference to obtain an operating status evaluation value of the photovoltaic panel;

[0044] The early warning module is used to determine the operation status level of the photovoltaic panel according to the operation status evaluation value, and judge whether the operation status of the photovoltaic panel is normal according to the operation status level.

[0045] Compared with the prior art, the photovoltaic panel operation status monitoring method and system according to the embodiment of the present invention have the following beneficial effects:

[0046] The present invention can accurately predict the power output of photovoltaic panels in the future time period by establishing a prediction model for photovoltaic panel power output, help optimize the operation and management of photovoltaic panels, and prepare for power fluctuations in advance, thereby improving the utilization efficiency of photovoltaic panels;

[0047] The present invention compares and analyzes the real-time power output data with the predicted data, and evaluates and calculates the operating status of the photovoltaic panel in combination with the power difference, so as to obtain the operating status evaluation value of the photovoltaic panel, timely discover the abnormal operating status of the photovoltaic panel, and provide a basis for subsequent fault diagnosis and maintenance;

[0048] The present invention can realize automatic monitoring and management of the operating status of photovoltaic panels by establishing a prediction model and a real-time monitoring system. Once the system detects an abnormal situation, an alarm can be issued in time, thereby improving the reliability and stability of the photovoltaic panels.

[0049] The present invention can provide data support for the operation and maintenance decision-making of photovoltaic panels by analyzing historical monitoring data and establishing a prediction model. Decision-making based on data-driven can manage the operation of photovoltaic panels more scientifically and effectively, reduce operation and maintenance costs, and improve the overall performance of photovoltaic panels. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a schematic diagram of the process structure of a method for monitoring the operating status of a photovoltaic panel in an embodiment of the present invention;

[0051] Figure 2 Schematic diagram of the composition of the photovoltaic panel operation status monitoring system in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0053] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the platform or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0054] The terms "second" and "second" are used for descriptive purposes only and should not be understood as indicating or implying a relative degree of importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined with "second" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "multiple" means two or more.

[0055] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technical personnel in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0056] like Figure 1 As shown, in an embodiment of the present application, a method for monitoring the operating status of a photovoltaic panel is provided, including: S100: obtaining historical operating monitoring data of a photovoltaic panel, and analyzing the historical operating monitoring data to determine monitoring characteristic parameters that affect the power output of the photovoltaic panel; S200: constructing a power output prediction model of the photovoltaic panel based on the monitoring characteristic parameters and a preset neural network model, and performing prediction according to the power output prediction model to obtain power output prediction data; S300: obtaining real-time power output data of the photovoltaic panel, and comparing and analyzing the real-time power output data with the power output prediction data to determine the power difference; S400: evaluating and calculating the operating status of the photovoltaic panel based on the power difference to obtain an operating status evaluation value of the photovoltaic panel; S500: determining the operating status level of the photovoltaic panel according to the operating status evaluation value, and judging whether the operating status of the photovoltaic panel is normal according to the operating status level.

[0057] Furthermore, the present invention can accurately predict the power output of photovoltaic panels in future time periods by establishing a prediction model for photovoltaic panel power output, help optimize the operation and management of photovoltaic panels, prepare for power fluctuations in advance, and thus improve the utilization efficiency of photovoltaic panels; the present invention can obtain an evaluation value of the operation status of photovoltaic panels by comparing and analyzing real-time power output data with prediction data, and evaluating and calculating the operation status of photovoltaic panels in combination with power differences, so as to timely discover abnormal operation status of photovoltaic panels and provide a basis for subsequent fault diagnosis and maintenance; the present invention can realize automatic monitoring and management of the operation status of photovoltaic panels by establishing a prediction model and a real-time monitoring system, and once the system detects an abnormal situation, it can issue an alarm in time, thereby improving the reliability and stability of photovoltaic panels; the present invention can provide data support for operation and maintenance decisions of photovoltaic panels by analyzing historical monitoring data and establishing a prediction model, and data-driven decisions can be used to more scientifically and effectively manage the operation of photovoltaic panels, reduce operation and maintenance costs, and improve the overall performance of photovoltaic panels.

[0058] In an embodiment of the present application, a method for monitoring the operating status of a photovoltaic panel is provided, wherein historical operating monitoring data of the photovoltaic panel is obtained, and the historical operating monitoring data is analyzed to determine monitoring characteristic parameters that affect the power output of the photovoltaic panel, including: obtaining historical operating monitoring data of the photovoltaic panel after preprocessing, and dividing the historical operating monitoring data into several groups of monitoring parameter data groups according to parameter type; obtaining historical power output data of the photovoltaic panel, and analyzing the correlation between each group of monitoring parameter data groups and the historical power output data; selecting monitoring parameter data groups whose correlation exceeds a preset threshold, and using parameters corresponding to the selected monitoring parameter data groups as monitoring characteristic parameters.

[0059] Specifically, the historical operation monitoring data of the photovoltaic panels are obtained, which may include monitoring parameters such as light intensity, temperature, wind speed, and corresponding power output data; the historical operation monitoring data obtained are preprocessed, including data cleaning, missing value processing, outlier processing, etc., to ensure data quality and accuracy; the historical operation monitoring data are divided into different data groups according to parameter types, such as light intensity data group, temperature data group, wind speed data group, etc.; the historical power output data are correlated with each group of monitoring parameter data groups, and statistical methods such as correlation coefficients are used to measure the degree of correlation between them; based on the monitoring parameter data groups whose correlation exceeds the preset threshold, the monitoring parameter data groups with higher correlation are selected, and the parameters corresponding to the selected monitoring parameter data groups are used as monitoring feature parameters, which will play an important role in subsequent modeling and prediction.

[0060] In an embodiment of the present application, a method for monitoring the operating status of a photovoltaic panel is provided, wherein a power output prediction model of the photovoltaic panel is constructed based on monitoring characteristic parameters and a preset neural network model, and prediction is performed according to the power output prediction model to obtain power output prediction data, including: constructing a data set based on the monitoring characteristic parameters and historical power output data, and inputting the data set into a preset neural network model to construct an initial power output 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 power output prediction model; training and testing the initial power output prediction model until the initial power output prediction model meets the preset convergence conditions to obtain the power output prediction model; acquiring real-time monitoring characteristic parameters of the photovoltaic panel, and inputting the real-time monitoring characteristic parameters into the power output prediction model, and predicting by the power output prediction model to obtain power output prediction data of the photovoltaic panel.

[0061] Specifically, based on the selected monitoring characteristic parameters and historical power output data, a data set is constructed. This data set will include the monitoring characteristic parameters as input features and the historical power output data as output labels. The data set is input into a preset neural network model to construct an initial power output prediction model. Through the neural network model, the system can learn the complex nonlinear relationship between the characteristic parameters and the power output, thereby realizing the prediction of the power output; the constructed data set is divided into a training set and a test set according to a certain ratio. The training set is used to train the model, and the test set is used to evaluate the performance of the model. The training set and the test set are input into the initial power output prediction model to perform the model prediction. Training and testing. During the training process, the model will continuously adjust parameters to minimize the difference between the predicted output and the actual output until the preset convergence conditions are met. Through training and testing, the model can continuously optimize parameters and improve the prediction accuracy of power output. The performance on the test set can reflect the generalization ability and prediction performance of the model. Obtain the real-time monitoring characteristic parameters of the photovoltaic panel, and input these parameters into the trained power output prediction model to perform real-time prediction of power output. By inputting the real-time monitoring characteristic parameters into the prediction model, the system can realize the real-time prediction of the power output of the photovoltaic panel, helping managers to monitor and adjust the operating status of the photovoltaic panel in a timely manner. In general, this step finally realizes the real-time prediction of the power output of the photovoltaic panel by constructing a data set, training a neural network model, dividing the training set and the test set, and training and testing the model. It can improve the intelligence level of photovoltaic panel operation management, help optimize the operating efficiency of photovoltaic panels, reduce maintenance costs, and improve the reliability and stability of the system.

[0062] In an embodiment of the present application, a method for monitoring the operating status of a photovoltaic panel is provided, wherein real-time power output data of the photovoltaic panel is obtained, and the real-time power output data is compared and analyzed with power output prediction data to determine a power difference situation, including: obtaining the real-time power output data and power output prediction data of the photovoltaic panel, and performing a difference calculation between the real-time power output data and the power output prediction data to obtain power difference data; drawing a time series graph based on the power difference data to obtain a power difference curve, and determining curve segments greater than or equal to zero and curve segments less than zero in the power difference curve; calculating the average value of the power difference data in each curve segment, and determining the maximum value of the power difference data in each curve segment and the amount of data exceeding the average value.

[0063] Specifically, the real-time power output data of the photovoltaic panel and the power output prediction data obtained by using the above model are obtained; the real-time power output data and the power output prediction data are calculated by difference calculation to obtain power difference data, which represent the deviation between the actual power output and the predicted power output; the power difference data are plotted into a time series curve graph in chronological order to obtain a power difference curve, and the curve segments greater than or equal to zero and less than zero are determined by analyzing the power difference curve, which represent the positive deviation and negative deviation between the power output prediction and the actual output; for each determined curve segment, the average value of the power difference data and the maximum value (maximum value or minimum value) are calculated, and at the same time, the amount of data exceeding the average value can be calculated to further understand the distribution of the deviation data. This step can analyze the difference between the actual power output and the predicted power output, thereby evaluating the accuracy of the prediction model and the stability of the system operation. By drawing the power difference curve and calculating the statistical data in each curve segment, the deviation of the power prediction can be more intuitively understood, which helps to timely discover the abnormal situation of the photovoltaic panel system and further guide the operation and maintenance personnel to make adjustments and management.

[0064] In an embodiment of the present application, a method for monitoring the operating status of a photovoltaic panel is provided, wherein the operating status of the photovoltaic panel is evaluated and calculated based on the power difference situation to obtain an operating status evaluation value of the photovoltaic panel, including: obtaining the maximum value of the power difference data in each curve segment, and evaluating each maximum value to obtain a difference evaluation value for each curve segment; obtaining the amount of power difference data in each curve segment that exceeds the average value and determining the total amount of power difference data, and calculating the ratio of the amount of power difference data in each curve segment that exceeds the average value to the total amount of data to obtain a first ratio for each curve segment; obtaining the time length of each curve segment and the total time length of the power difference curve, and calculating the ratio of the time length of each curve segment to the total time length of the power difference curve to obtain a second ratio for each curve segment; determining a weight coefficient for each curve segment based on the first ratio and the second ratio, and performing weighted addition calculation on the difference evaluation value of each curve segment and the corresponding weight coefficient to obtain an operating status evaluation value of the photovoltaic panel.

[0065] Specifically, for each curve segment, the maximum value of the power difference data therein, that is, the maximum value or the minimum value, is obtained, and then these maximum values ​​are evaluated to understand the deviation of the power prediction in different time periods; the amount of power difference data in each curve segment that exceeds the average value is counted, and the total amount of power difference data in each curve segment is determined, and the ratio of the amount of power difference data in each curve segment that exceeds the average value to the total amount of data is calculated to obtain a first ratio for each curve segment, and the ratio of the time length of each curve segment to the total time length of the power difference curve is calculated to obtain a second ratio for each curve segment; based on the first ratio and the second ratio, the weight coefficient of each curve segment is determined, and these weight coefficients can reflect the relative importance of the power difference data in different time periods; the difference evaluation value of each curve segment is weightedly added with the corresponding weight coefficient to obtain an operating status evaluation value of the photovoltaic panel, which will comprehensively consider the deviation of the power prediction in different time periods and give a comprehensive operating status evaluation. This step evaluates the maximum value of the power difference data in each curve segment, and calculates the amount of data exceeding the average value, the time length ratio and the weight coefficient, so as to have a more comprehensive understanding of the deviation of power forecast in different time periods and its relative importance. The final evaluation value of the operating status of the photovoltaic panel will be more representative and comprehensive, which will help managers make more accurate decisions when monitoring and adjusting the photovoltaic panel system in real time.

[0066] In an embodiment of the present application, a method for monitoring the operating status of a photovoltaic panel is provided, wherein determining the weight coefficient of each curve segment based on the first ratio and the second ratio comprises: calculating the weight coefficient of each curve segment according to the first ratio and the second ratio, and the calculation formula of the weight coefficient of each curve segment is:

[0067] Q = α * X + β * Y,

[0068] Wherein, Q is the weight coefficient of each curve segment, α is the coefficient of the first ratio, X is the first ratio, β is the coefficient of the second ratio, and Y is the second ratio.

[0069] In an embodiment of the present application, a method for monitoring the operating status of a photovoltaic panel is provided, wherein the operating status level of the photovoltaic panel is determined according to the operating status evaluation value, comprising: presetting an operating status level-operating status evaluation value interval correspondence relationship, wherein each operating status evaluation value interval is associated with a corresponding operating status level in the operating status level-operating status evaluation value interval correspondence relationship; obtaining the operating status evaluation value of the photovoltaic panel, and selecting the operating status level corresponding to the operating status evaluation value interval based on a mapping relationship between the operating status evaluation value interval to which the operating status evaluation value belongs within the operating status level-operating status evaluation value interval correspondence relationship.

[0070] Specifically, different operating status levels and operating status evaluation value intervals corresponding to these levels are pre-set in the system. These intervals can be set according to actual conditions, usually determined based on experience and historical data; the operating status evaluation value of the photovoltaic panel is calculated through the previous steps, the operating status level is determined based on the interval to which the operating status evaluation value belongs, the operating status evaluation value of the photovoltaic panel is mapped to the pre-set operating status evaluation value interval, and then the operating status level corresponding to the operating status evaluation value interval is selected according to the mapping relationship of this interval within the pre-set operating status level-operating status evaluation value interval correspondence relationship. This step can map continuous operating status evaluation values ​​to discrete operating status levels by setting the operating status level-operating status evaluation value interval correspondence relationship, and can convert complex evaluation values ​​into more intuitive and easier to understand operating status levels, which helps managers quickly understand the overall operating status of the photovoltaic panel system. At the same time, according to different operating status levels, corresponding operation and maintenance strategies and adjustment plans can be formulated to optimize the operating efficiency and stability of the system.

[0071] In an embodiment of the present application, a method for monitoring the operating status of a photovoltaic panel is provided, and the method of judging whether the operating status of the photovoltaic panel is normal according to the operating status level includes: obtaining a pre-set threshold level, and judging whether the operating status of the photovoltaic panel is normal based on the relationship between the operating status level and the threshold level; if the operating status level is greater than the threshold level, the operating status of the photovoltaic panel is abnormal; if the operating status level is less than or equal to the threshold level, the operating status of the photovoltaic panel is normal.

[0072] Specifically, a threshold level of the photovoltaic panel operating status is set, and the threshold level is set according to the system characteristics; the photovoltaic panel operating status level is compared with the pre-set threshold level. If the operating status level is greater than the threshold level, the photovoltaic panel operating status is judged to be abnormal; if the operating status level is less than or equal to the threshold level, the photovoltaic panel operating status is judged to be normal. By setting the threshold level, this step can quickly determine whether the system is operating normally according to the operating status level of the photovoltaic panel, and can timely detect system anomalies and take corresponding measures for maintenance and repair. At the same time, this method also helps to establish a simple and effective operating status monitoring system to ensure the safe and stable operation of the photovoltaic panel system.

[0073] like Figure 2As shown, in an embodiment of the present application, a photovoltaic panel operation status monitoring system is provided, including: an acquisition module, used to acquire historical operation monitoring data of the photovoltaic panel, and analyze the historical operation monitoring data to determine the monitoring characteristic parameters that affect the power output of the photovoltaic panel; a prediction module, used to construct a power output prediction model of the photovoltaic panel based on the monitoring characteristic parameters and a preset neural network model, and predict according to the power output prediction model to obtain power output prediction data; a comparison module, used to acquire real-time power output data of the photovoltaic panel, and compare and analyze the real-time power output data with the power output prediction data to determine the power difference; a calculation module, used to evaluate and calculate the operation status of the photovoltaic panel based on the power difference to obtain an operation status evaluation value of the photovoltaic panel; an early warning module, used to determine the operation status level of the photovoltaic panel according to the operation status evaluation value, and judge whether the operation status of the photovoltaic panel is normal according to the operation status level.

[0074] In summary, the embodiment of the present invention provides a method and system for monitoring the operation status of a photovoltaic panel, which includes: acquiring and analyzing the historical operation monitoring data of the photovoltaic panel, determining the monitoring characteristic parameters that affect the power output of the photovoltaic panel; constructing a power output prediction model of the photovoltaic panel based on the monitoring characteristic parameters to predict the power output prediction data; acquiring the real-time power output data of the photovoltaic panel, and comparing it with the power output prediction data to determine the power difference; evaluating and calculating the operation status of the photovoltaic panel based on the power difference to obtain an operation status evaluation value; determining the operation status level of the photovoltaic panel according to the operation status evaluation value, and judging whether the operation status of the photovoltaic panel is normal according to the operation status level. The present invention monitors the operation status of the photovoltaic panel through an objective and intelligent comprehensive comparison and evaluation method, which can timely and accurately monitor the current operation status of the photovoltaic panel, improve the operation status monitoring efficiency, and reduce the monitoring cost.

[0075] Finally, it should be noted that: Obviously, a person skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalent technology, the present invention is also intended to include these modifications and variations.

[0076] The above is only an example of implementation of the present invention, but it cannot be used to limit the scope of the present invention. Any structural changes made according to the present invention, as long as they do not lose the essence of the present invention, should be regarded as falling within the scope of protection of the present invention and being restricted. Technical personnel in the relevant technical field can clearly understand that for the convenience and simplicity of description, the specific working process and related instructions of the platform described above can refer to the corresponding process in the aforementioned platform embodiment, and will not be repeated here.

[0077] The term "comprises" or any other similar term is intended to cover a non-exclusive inclusion such that a process, platform, article, or apparatus / platform that includes a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, platform, article, or apparatus / platform.

[0078] So far, the technical solutions of the present invention have been described in conjunction with the further embodiments shown in the accompanying drawings. However, it is easy for a person 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, a person 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 fall within the protection scope of the present invention.

[0079] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A method for monitoring the operating status of a photovoltaic panel, characterized in that: include: Obtain historical operation monitoring data of photovoltaic panels, analyze the historical operation monitoring data, and determine the monitoring characteristic parameters that affect the power output of photovoltaic panels; A power output prediction model of the photovoltaic panel is constructed based on the monitoring characteristic parameters and the preset neural network model, and prediction is performed according to the power output prediction model to obtain power output prediction data; Obtain the real-time power output data of the photovoltaic panels, and compare and analyze the real-time power output data with the power output prediction data to determine the power difference; Evaluate and calculate the operating status of the photovoltaic panel based on the power difference to obtain an operating status evaluation value of the photovoltaic panel; The operation status level of the photovoltaic panel is determined according to the operation status evaluation value, and whether the operation status of the photovoltaic panel is normal is judged according to the operation status level.

2. A photovoltaic panel operating status monitoring method according to claim 1, characterized in that: The obtaining of historical operation monitoring data of the photovoltaic panel and analyzing the historical operation monitoring data to determine monitoring characteristic parameters affecting the power output of the photovoltaic panel include: Obtaining historical operation monitoring data of the photovoltaic panel after preprocessing, and dividing the historical operation monitoring data into several groups of monitoring parameter data groups according to parameter types; Obtain historical power output data of photovoltaic panels, and analyze the correlation between each set of monitoring parameter data and historical power output data; The monitoring parameter data groups whose correlation exceeds the preset threshold are selected, and the parameters corresponding to the selected monitoring parameter data groups are used as monitoring characteristic parameters.

3. A photovoltaic panel operating status monitoring method according to claim 2, characterized in that: The power output prediction model of the photovoltaic panel is constructed based on the monitoring characteristic parameters and the preset neural network model, and prediction is performed according to the power output prediction model to obtain power output prediction data, including: Building a data set based on monitoring characteristic parameters and historical power output data, and inputting the data set into a preset neural network model to build an initial model for power output prediction; The data set is divided into a training set and a test set according to a certain ratio, and the training set and the test set are input into the initial model for power output prediction; Training and testing the initial power output prediction model until the initial power output prediction model meets a preset convergence condition, thereby obtaining a power output prediction model; The real-time monitoring characteristic parameters of the photovoltaic panel are obtained, and the real-time monitoring characteristic parameters are input into the power output prediction model. The power output prediction model performs prediction to obtain the power output prediction data of the photovoltaic panel.

4. A photovoltaic panel operating status monitoring method according to claim 3, characterized in that: The real-time power output data of the photovoltaic panel is obtained, and the real-time power output data is compared and analyzed with the power output prediction data to determine the power difference, including: Acquire the real-time power output data and power output prediction data of the photovoltaic panel, and perform difference calculation between the real-time power output data and the power output prediction data to obtain power difference data; Draw a time series curve graph based on the power difference data to obtain a power difference curve, and determine curve segments greater than or equal to zero and curve segments less than zero in the power difference curve; The average value of the power difference data in each curve segment is calculated, and the maximum value of the power difference data in each curve segment and the amount of data exceeding the average value are determined.

5. A photovoltaic panel operating status monitoring method according to claim 4, characterized in that: The operating state of the photovoltaic panel is evaluated and calculated based on the power difference to obtain an operating state evaluation value of the photovoltaic panel, including: Obtaining the maximum value of the power difference data in each curve segment, and evaluating each maximum value to obtain a difference evaluation value of each curve segment; Obtaining the amount of power difference data exceeding the average value in each curve segment and determining the total amount of power difference data, and calculating the ratio of the amount of power difference data exceeding the average value to the total amount of data in each curve segment to obtain a first ratio of each curve segment; Obtaining the time length of each curve segment and the total time length of the power difference curve, and calculating the ratio of the time length of each curve segment to the total time length of the power difference curve to obtain a second ratio of each curve segment; The weight coefficient of each curve segment is determined based on the first ratio and the second ratio, and the difference evaluation value of each curve segment is weightedly added to the corresponding weight coefficient to obtain the operation status evaluation value of the photovoltaic panel.

6. A method for monitoring the operating status of a photovoltaic panel according to claim 5, characterized in that: The step of determining a weight coefficient of each curve segment based on the first ratio and the second ratio comprises: The weight coefficient of each curve segment is calculated according to the first ratio and the second ratio. The calculation formula of the weight coefficient of each curve segment is: Q = α * X + β * Y, Among them, Q is the weight coefficient of each curve segment, α is the coefficient of the first ratio, X is the first ratio, β is the coefficient of the second ratio, and Y is the second ratio.

7. A method for monitoring the operating status of a photovoltaic panel according to claim 5, characterized in that: Determining the operation status level of the photovoltaic panel according to the operation status evaluation value includes: A corresponding relationship between an operating state level and an operating state evaluation value interval is preset, and the corresponding relationship between an operating state level and an operating state evaluation value interval is associated with a corresponding operating state level for each operating state evaluation value interval; The operating state evaluation value of the photovoltaic panel is obtained, and based on the mapping relationship between the operating state evaluation value interval to which the operating state evaluation value belongs and the operating state level corresponding to the operating state evaluation value interval, the operating state level corresponding to the operating state evaluation value interval is selected.

8. A method for monitoring the operating status of a photovoltaic panel according to claim 7, characterized in that: The step of judging whether the operation state of the photovoltaic panel is normal according to the operation state level includes: Obtaining a preset threshold level, and judging whether the operation state of the photovoltaic panel is normal based on the relationship between the operation state level and the threshold level; If the operating status level is greater than the threshold level, the operating status of the photovoltaic panel is abnormal; If the operating status level is less than or equal to the threshold level, the photovoltaic panel is operating normally.

9. A photovoltaic panel operation status monitoring system, characterized in that: include: An acquisition module is used to acquire historical operation monitoring data of photovoltaic panels, analyze the historical operation monitoring data, and determine monitoring characteristic parameters that affect the power output of photovoltaic panels; A prediction module is used to build a power output prediction model of the photovoltaic panel based on the monitoring characteristic parameters and the preset neural network model, and to perform prediction according to the power output prediction model to obtain power output prediction data; The comparison module is used to obtain the real-time power output data of the photovoltaic panel, and compare and analyze the real-time power output data with the power output prediction data to determine the power difference; A calculation module is used to evaluate and calculate the operating status of the photovoltaic panel based on the power difference to obtain an operating status evaluation value of the photovoltaic panel; The early warning module is used to determine the operation status level of the photovoltaic panel according to the operation status evaluation value, and judge whether the operation status of the photovoltaic panel is normal according to the operation status level.

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