Solar photovoltaic power generation equipment and system for combined roof steel frame

Abstract

The invention relates to the technical field of solar photovoltaic power generation, and particularly discloses a solar photovoltaic power generation device and system for a combined roof steel frame, and the device specifically comprises a temperature data collection module which carries out the partitioning of a solar photovoltaic panel, obtains the temperature value data of each sub-region, carries out the processing, and calculates the temperature judgment value of each region; the abnormal sub-region acquisition module is used for comparing the temperature judgment value with a temperature judgment threshold value to acquire an abnormal sub-region; and the influence correlation calculation module is used for acquiring and processing the illumination intensity value data of each sub-region. Therefore, the temperature condition of the solar photovoltaic panel can be effectively monitored, a temperature abnormal area is obtained through comprehensive calculation, potential fault problems are found in time, corresponding measures are taken for maintenance, and the situation that the power generation efficiency of the solar photovoltaic panel is reduced due to the fact that the temperature is too high is reduced. And the stable operation service life of the solar photovoltaic panel power generation equipment can be prolonged.

Description

Technical Field

[0001] The invention relates to the technical field of solar photovoltaic power generation, and in particular to a solar photovoltaic power generation device and system for a combined roof steel frame. Background Art

[0002] With the continuous growth of global energy demand, the depletion of fossil energy and environmental pollution are becoming increasingly serious. As a clean and renewable energy source, solar energy has received extensive attention and development. Photovoltaic power generation systems use solar panels to convert solar energy into electrical energy, which is one of the important forms of solar energy utilization. As a building support structure with a simple structure and easy installation, modular roof steel frames have been widely used in the installation of solar photovoltaic power generation systems. Since the temperature of solar photovoltaic panels has a certain impact on the power generation efficiency, it is important to monitor the temperature conditions of photovoltaic panels in real time and diagnose abnormalities. However, traditional temperature monitoring methods often only focus on the overall temperature or single-point temperature of photovoltaic panels, and cannot accurately reflect the temperature distribution of each sub-area of ​​the photovoltaic panel. At the same time, when judging temperature abnormalities, they also calculate and judge through single data. Summary of the invention

[0003] The object of the present invention is to provide a solar photovoltaic power generation device and system for a modular roof steel frame to solve the technical problems in the above background.

[0004] The purpose of the present invention can be achieved through the following technical solutions: In the first aspect, the present invention provides a solar photovoltaic power generation system for a modular roof steel frame, specifically including: a temperature data acquisition module: partitioning the solar photovoltaic panels, obtaining the temperature value data of each sub-area, and processing it to calculate the temperature judgment value of each area; an abnormal sub-area acquisition module: comparing the temperature judgment value with the temperature judgment threshold to obtain the abnormal sub-area; an impact correlation calculation module: obtaining the light intensity value data of each sub-area, and processing it to calculate the impact correlation value between the light intensity anomaly and the temperature anomaly, comparing the impact correlation value with the impact correlation threshold, if the impact correlation value is greater than the impact correlation threshold, generating a correlation signal; other influencing factor judgment module: based on the generated correlation signal, judging whether there are other influencing factors.

[0005] As a further solution of the present invention: the process of obtaining the temperature judgment value is: Obtain the temperature mean deviation ratio, temperature anomaly time ratio, and temperature anomaly area ratio; Substitute into the formula , the temperature judgment value WD is calculated, where JZ represents the temperature mean deviation ratio, SJ represents the temperature abnormality time ratio, MJ represents the temperature abnormality area ratio, and a1, a2, and a3 are preset proportional coefficients.

[0006] As a further solution of the present invention: the process of obtaining the temperature mean deviation ratio, temperature abnormality time proportion and temperature abnormality area proportion is as follows: Divide the solar photovoltaic panel into several sub-areas in a grid-like manner, and obtain the real-time temperature value of each sub-area; With time as the X-axis and temperature as the Y-axis, a two-dimensional model is established, the real-time temperature value is substituted into the two-dimensional model, a real-time temperature curve is drawn, a temperature standard range is preset, and the maximum and minimum values ​​of the temperature standard range are taken as Y values. Two parallel lines parallel to the X-axis are drawn respectively, and marked as the first temperature standard line and the second temperature standard line; The area of ​​the temperature curve located above the first temperature standard line and below the second temperature standard line is marked as an over-limit temperature area, and the area of ​​the temperature area located below the first temperature standard line and above the second temperature standard line is marked as a normal temperature area; A monitoring period is preset, and within the monitoring period, the real-time temperature values ​​of the period are summed and averaged to obtain a temperature mean value, the temperature mean value is calculated as a ratio difference with the temperature standard value, the difference is taken as an absolute value to obtain a temperature standard deviation value, and the temperature standard deviation value is calculated as a ratio with the temperature standard value to obtain a temperature mean deviation ratio; During the monitoring period, the time period when the temperature curve is in the temperature exceeding limit area is obtained, which is marked as the temperature abnormality time period. All the temperature abnormality time periods are summed up to obtain the total temperature abnormality time. The total temperature abnormality time is ratioed with the monitoring period to obtain the temperature abnormality time ratio. During the monitoring period, the area value of the temperature curve in the temperature limit area is obtained, marked as the temperature abnormality area value, all abnormal area values ​​are summed up to obtain the total temperature abnormality area, and the ratio of the total temperature abnormality area to the standard area value is calculated to obtain the temperature abnormality area ratio.

[0007] As a further solution of the present invention: the process of obtaining the abnormal sub-region is: In each monitoring period, a temperature judgment value of each sub-area is obtained, and the temperature judgment value is compared with a temperature judgment threshold value respectively; If the temperature judgment value is greater than the temperature judgment threshold, an abnormal signal is generated; During the monitoring period, the sub-region corresponding to the generated abnormal signal is obtained and marked as an abnormal sub-region.

[0008] As a further solution of the present invention: the process of obtaining the impact association value is: Obtain the total overlap time, total temperature anomaly time, and total light intensity anomaly time; Substitute into the formula , the impact correlation value GL is calculated, where CT represents the total overlap time, WT represents the total temperature abnormality time, and GT represents the total light intensity abnormality time.

[0009] As a further solution of the present invention: the acquisition process of the total overlap time and the total abnormal illumination intensity time is as follows: Obtain the real-time light intensity value of each sub-area, and compare the real-time light intensity value with the light intensity threshold; If the real-time light intensity value is less than the light intensity threshold, a light intensity abnormality signal is generated; During the monitoring period, the duration period of generating the abnormal light intensity signal is obtained, marked as the abnormal light intensity time period, all the abnormal light intensity time periods are summed up to obtain the total abnormal light intensity time, the abnormal temperature time period is obtained, the overlapping time period of the abnormal light intensity time period and the abnormal temperature time period is obtained, all the overlapping time periods are summed up to obtain the total overlapping time.

[0010] As a further solution of the present invention: the process of determining whether there are other influencing factors is: Obtaining a value of the proportion of the number of proximity signals, and comparing the value of the proportion of the number of proximity signals with a threshold value of the proportion of the number of proximity signals; If the value of the proximity signal number ratio is less than the proximity signal number ratio threshold, a signal with other influencing factors is generated; If the value of the proximity signal number ratio is greater than or equal to the proximity signal number ratio threshold, a signal without other influencing factors is generated.

[0011] As a further solution of the present invention: the process of obtaining the value of the proportion of the number of proximity signals is as follows: Obtain the influence coefficient ratios of all analysis time points, sum and average the influence coefficient ratios of all analysis time points to obtain the influence coefficient ratio mean, perform difference calculation on all influence coefficient ratios and the influence coefficient ratio mean to obtain the influence coefficient ratio deviation value, and compare the influence coefficient deviation value with the influence coefficient deviation threshold; If the influence coefficient deviation value is less than or equal to the influence coefficient deviation threshold, a proximity signal is generated; The number of generated proximity signals is obtained, and the ratio of the number of generated proximity signals to the total number of values ​​at the analysis time point is calculated to obtain the ratio of the number of proximity signals.

[0012] As a further solution of the present invention: the process of obtaining the influence coefficient ratio is: When generating the correlation signal, the overlapping time period is divided into several analysis time points, the light intensity value corresponding to each analysis time point is obtained, the light intensity value is calculated to be different from the light intensity threshold to obtain the light intensity deviation value, and the light intensity deviation value is processed by ratio with the light intensity deviation threshold to obtain the light intensity deviation coefficient; Obtain the temperature value corresponding to each analysis time point, and compare the temperature value with the maximum and minimum values ​​obtained in the temperature standard range; If the temperature value is greater than the maximum value of the temperature standard range, the temperature value and the maximum value of the temperature standard range are calculated to obtain the temperature deviation value, and the temperature deviation value is ratioed with the temperature standard value to obtain the temperature deviation coefficient; If the temperature value is less than the minimum value of the temperature standard range, the difference between the minimum value of the temperature standard range and the temperature value is calculated to obtain the temperature deviation value, and the temperature deviation value is ratioed with the temperature standard value to obtain the temperature deviation coefficient; The light intensity deviation coefficient and the temperature deviation coefficient at the same analysis time point are ratio processed to obtain the influence coefficient ratio.

[0013] In a second aspect, the present invention provides a solar photovoltaic device for a modular roof steel frame, wherein the device is provided with the above-mentioned solar photovoltaic system for a modular roof steel frame.

[0014] Beneficial effects of the present invention: (1) The present invention divides a solar photovoltaic panel into several sub-areas, monitors the temperature value of each sub-area in real time, processes the temperature value data to draw a real-time temperature curve, and calculates the temperature mean deviation ratio, temperature abnormality time ratio and temperature abnormality area ratio. The temperature judgment value is calculated by weighted summation based on the temperature mean deviation ratio, temperature abnormality time ratio and temperature abnormality area ratio, and the temperature judgment value is compared with the temperature judgment threshold. If the temperature judgment value is greater than the temperature judgment threshold, an abnormal signal is generated, and the sub-area where the abnormal signal is generated is marked as an abnormal sub-area, so that the temperature condition of the solar photovoltaic panel can be effectively monitored, and the temperature abnormal area can be obtained through comprehensive calculation, potential fault problems can be discovered in time, and corresponding measures can be taken for maintenance, thereby reducing the reduction in solar photovoltaic panel power generation efficiency caused by excessive temperature, thereby increasing the stable operation life of the solar photovoltaic panel power generation equipment; (2) After obtaining the abnormal sub-area, the present invention monitors the light intensity of the sub-area of ​​the solar photovoltaic panel in real time, analyzes the overlap time period of the time period of the abnormal light intensity and the time period of the temperature abnormality, calculates the impact correlation value based on the total overlap time, the total time of the abnormal light intensity and the total time of the temperature abnormality, compares the impact correlation value with the impact correlation threshold, and generates a correlation signal if the impact correlation value is greater than the impact correlation threshold, thereby determining that the temperature abnormality of the sub-area of ​​the solar photovoltaic panel is associated with the abnormal light intensity, and then performing targeted optimization and adjustment; (3) When generating a correlation signal, the present invention calculates an influence coefficient ratio, and based on the influence coefficient ratio, calculates a deviation value between the influence coefficient ratio of all analysis time points and the influence coefficient ratio mean value, and based on the influence coefficient ratio deviation value and the influence coefficient ratio deviation threshold value, obtains a value of the number of generated proximity signals, calculates a value of the proportion of the number of proximity signals, and determines whether there are other influencing factors. If the value of the proportion of the number of proximity signals is less than the threshold value of the proportion of the number of proximity signals, there are other influencing factors. If the proportion of the number of proximity signals is greater than or equal to the threshold value of the proportion of the number of proximity signals, there are no other influencing factors. Thus, by determining whether there are other influencing factors, a more accurate diagnosis of abnormal temperature factors can be performed, thereby improving management effects and power generation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below in conjunction with the accompanying drawings.

[0016] Figure 1 It is a flow chart of a solar photovoltaic power generation system for a modular roof steel frame of the present invention; Figure 2 The present invention is a flowchart of a process for obtaining a temperature judgment value in a solar photovoltaic power generation system for a combined roof steel frame. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Embodiment 1: See also Figure 1 and Figure 2 As shown, a solar photovoltaic power generation system for a combined roof steel frame according to an embodiment of the present invention specifically includes: Temperature data acquisition module: divide the solar photovoltaic panels into different areas, obtain the temperature value data of each sub-area, process it, and calculate the temperature judgment value of each area; In some embodiments, the solar photovoltaic panel is divided into a plurality of sub-areas in a mesh manner, and a real-time temperature value of each sub-area is obtained; With time as the X-axis and temperature as the Y-axis, a two-dimensional model is established, the real-time temperature value is substituted into the two-dimensional model, a real-time temperature curve is drawn, a temperature standard range is preset, and the maximum and minimum values ​​of the temperature standard range are taken as Y values. Two parallel lines parallel to the X-axis are drawn respectively, and marked as the first temperature standard line and the second temperature standard line; The preset temperature standard range is set by technicians in this field based on historical experimental data. The area of ​​the temperature curve located above the first temperature standard line and below the second temperature standard line is marked as an over-limit temperature area, and the area of ​​the temperature area located below the first temperature standard line and above the second temperature standard line is marked as a normal temperature area; A monitoring period is preset, and within the monitoring period, the real-time temperature values ​​of the period are summed and averaged to obtain a temperature mean value, the temperature mean value is calculated as a ratio difference with the temperature standard value, the difference is taken as an absolute value to obtain a temperature standard deviation value, and the temperature standard deviation value is calculated as a ratio with the temperature standard value to obtain a temperature mean deviation ratio; The temperature standard value is calculated by summing and averaging the maximum and minimum values ​​within the temperature standard range. During the monitoring period, the time period when the temperature curve is in the temperature exceeding limit area is obtained, which is marked as the temperature abnormality time period. All the temperature abnormality time periods are summed up to obtain the total temperature abnormality time. The total temperature abnormality time is ratioed with the monitoring period to obtain the temperature abnormality time ratio. During the monitoring period, the area value of the temperature curve in the temperature exceeding limit area is obtained, marked as the temperature abnormal area value, all abnormal area values ​​are summed up to obtain the total temperature abnormal area, and the total temperature abnormal area is calculated by ratio with the standard area value to obtain the temperature abnormal area ratio; Exemplarily, the standard area value is the product of the time difference of the monitoring period and the temperature standard range difference, wherein the time difference of the monitoring period is the difference between the end time point and the start time point of the monitoring period, and the temperature standard range difference is the difference between the maximum value and the minimum value of the temperature standard range; Substitute into the formula , the temperature judgment value WD is calculated, where JZ represents the temperature mean deviation ratio, SJ represents the temperature abnormality time ratio, MJ represents the temperature abnormality area ratio, and a1, a2, and a3 are preset proportional coefficients; It needs to be explained that the meaning reflected by the temperature judgment value is: the temperature judgment value is calculated by the temperature mean deviation ratio, the temperature abnormality time ratio and the temperature abnormality area ratio, that is, the larger the temperature mean deviation ratio is, the larger the deviation between the temperature mean of the photovoltaic panel sub-area and the temperature standard value during the monitoring period, and the more abnormal the overall temperature during the monitoring period is, that is, the larger the temperature abnormality time ratio is, the longer the photovoltaic panel is in the temperature over-limit area during the monitoring period, and the more abnormal the overall temperature during the monitoring period is, that is, the larger the temperature abnormality area ratio is, the longer the photovoltaic panel is in the temperature over-limit area during the monitoring period or the degree of deviation from the temperature standard range is, and the more abnormal the overall temperature during the monitoring period is; Abnormal sub-region acquisition module: compares the temperature judgment value with the temperature judgment threshold to obtain the abnormal sub-region; In some embodiments, in each monitoring period, a temperature judgment value of each sub-region is obtained, and the temperature judgment value is compared with a temperature judgment threshold value, wherein the temperature judgment threshold value is a critical value used to judge whether the temperature of the sub-region is abnormal during the monitoring period, and is summarized and set by a person skilled in the art based on historical experimental data; If the temperature judgment value is less than or equal to the temperature judgment threshold, it means that the temperature of the sub-area during the monitoring period is in a normal state, and a normal signal is generated; If the temperature judgment value is greater than the temperature judgment threshold, it means that the temperature of the sub-area during the monitoring period is in an abnormal state, and an abnormal signal is generated; During the monitoring period, the sub-region corresponding to the generated abnormal signal is obtained and marked as an abnormal sub-region; The technical solution of the embodiment of the present invention is mainly as follows: by dividing a solar photovoltaic panel into several sub-areas, the temperature value of each sub-area is monitored in real time, and the temperature value data is processed to draw a real-time temperature curve, and the temperature mean deviation ratio, the temperature abnormality time ratio and the temperature abnormality area ratio are calculated and obtained, and the temperature judgment value is calculated by weighted summation based on the temperature mean deviation ratio, the temperature abnormality time ratio and the temperature abnormality area ratio, and the temperature judgment value is compared with the temperature judgment threshold. If the temperature judgment value is greater than the temperature judgment threshold, an abnormal signal is generated, and the sub-area where the abnormal signal is generated is marked as an abnormal sub-area, so that the temperature condition of the solar photovoltaic panel can be effectively monitored, and the temperature abnormal area can be obtained through comprehensive calculation, potential fault problems can be discovered in time, and corresponding measures can be taken for maintenance, thereby reducing the reduction in solar photovoltaic panel power generation efficiency caused by excessive temperature, and thus increasing the stable operation life of the solar photovoltaic panel power generation equipment.

[0019] Embodiment 2: On the basis of Example 1, when the light intensity increases, the radiation energy absorbed by the photovoltaic panel increases, part of which is converted into electrical energy, but the other part is lost in the form of heat energy, resulting in an increase in the temperature of the photovoltaic panel. Under strong sunlight, the surface temperature of the photovoltaic panel will rise rapidly, thereby increasing the internal temperature of the photovoltaic panel. The solar photovoltaic power generation system for a combined roof steel frame described in the embodiment of the present invention specifically includes: Impact correlation calculation module: obtains the light intensity value data of each sub-area, processes it, calculates the impact correlation value between the light intensity anomaly and the temperature anomaly, and determines whether the light intensity is the cause of the temperature anomaly; In some embodiments, the real-time light intensity value of each sub-area is obtained, and the real-time light intensity value is compared with a light intensity threshold, wherein the light intensity threshold is a critical value, which is summarized and set by a person skilled in the art based on historical multiple experimental data; Among them, the real-time light intensity value is measured by the light intensity sensor installed in each sub-area of ​​the solar photovoltaic panel; If the real-time light intensity value is greater than or equal to the light intensity threshold, a light intensity normal signal is generated; If the real-time light intensity value is less than the light intensity threshold, a light intensity abnormality signal is generated; It should be noted that higher light intensity is conducive to the power generation of solar photovoltaic panels, while lower light intensity may lead to lower power generation efficiency. Therefore, in most cases, when the light intensity is higher than the light intensity threshold, we will consider it a normal condition that is conducive to power generation, while it is considered abnormal when it is lower than the light intensity threshold. During the monitoring period, the duration of the light intensity abnormality signal is obtained, marked as the light intensity abnormality time period, all light intensity abnormality time periods are summed up to obtain the total light intensity abnormality time, the temperature abnormality time period is obtained, the overlapping time period of the light intensity abnormality time period and the temperature abnormality time period is obtained, and all the overlapping time periods are summed up to obtain the total overlapping time; Substitute into the formula , the impact correlation value GL is calculated, where CT represents the total overlap time, WT represents the total temperature abnormality time, and GT represents the total light intensity abnormality time; It needs to be explained that the meaning reflected by the impact correlation value is: the impact correlation value is calculated by summing the ratio of the total overlap time to the total temperature anomaly time and the ratio of the total overlap time to the total light intensity anomaly time, wherein the larger the ratio of the total overlap time to the total temperature anomaly time, that is, the larger the proportion of the total overlap time in the total temperature anomaly time, the larger the impact correlation value, the greater the correlation between the temperature anomaly and the light intensity anomaly, the larger the ratio of the total overlap time to the light intensity anomaly, that is, the larger the proportion of the total overlap time in the light intensity anomaly time, the larger the impact correlation value, the greater the correlation between the temperature anomaly and the light intensity anomaly; Compare the impact correlation value with the impact correlation threshold, wherein the impact correlation threshold is a critical value used to determine the correlation between temperature anomaly and light intensity anomaly, and is summarized and set by technicians in this field based on historical experimental data; If the impact correlation value is less than or equal to the impact correlation threshold, it means that the correlation between the temperature anomaly and the light intensity anomaly is smaller, and an uncorrelated signal is generated; If the impact correlation value is greater than the impact correlation threshold, it means that the correlation between the temperature anomaly and the light intensity anomaly is greater, and a correlation signal is generated; Other influencing factors judgment module: based on the generated correlation signal, judge whether there are other influencing factors; In some embodiments, when generating the correlation signal, the overlapping time period is divided into a number of analysis time points, the light intensity value corresponding to each analysis time point is obtained, the light intensity value is calculated to be different from the light intensity threshold to obtain the light intensity deviation value, and the light intensity deviation value is processed by ratio with the light intensity deviation threshold to obtain the light intensity deviation coefficient; Obtain the temperature value corresponding to each analysis time point, and compare the temperature value with the maximum and minimum values ​​obtained in the temperature standard range; If the temperature value is greater than the maximum value of the temperature standard range, the temperature value and the maximum value of the temperature standard range are calculated to obtain the temperature deviation value, and the temperature deviation value is ratioed with the temperature standard value to obtain the temperature deviation coefficient; If the temperature value is less than the minimum value of the temperature standard range, the difference between the minimum value of the temperature standard range and the temperature value is calculated to obtain the temperature deviation value, and the temperature deviation value is ratioed with the temperature standard value to obtain the temperature deviation coefficient; The light intensity deviation coefficient and the temperature deviation coefficient at the same analysis time point are processed by ratio to obtain the influence coefficient ratio; The influence coefficient ratios of all analysis time points are summed and averaged to obtain the influence coefficient ratio mean, all influence coefficient ratios are calculated to be different from the influence coefficient ratio mean to obtain the influence coefficient ratio deviation value, and the influence coefficient deviation value is compared with the influence coefficient deviation threshold value, wherein the influence coefficient deviation threshold value is summarized and set by a person skilled in the art based on historical experimental data; If the influence coefficient deviation value is less than or equal to the influence coefficient deviation threshold, it means that the deviation between the influence coefficient ratio at the analysis time point and the influence coefficient ratio mean is small, and a close signal is generated; If the influence coefficient deviation value is greater than the influence coefficient deviation threshold, it means that the deviation between the influence coefficient ratio at the analysis time point and the influence coefficient ratio mean is large, and a distance signal is generated; Obtain the number of generated proximity signals, calculate the ratio of the number of generated proximity signals to the total number of values ​​at the analysis time point, and obtain the ratio of the number of proximity signals; It should be explained that the meaning reflected by the value of the proportion of the number of proximity signals is: the value of the proportion of the number of proximity signals is the proportion of the number of proximity signals generated in all analysis time points. The generation of proximity signals indicates that the deviation between the influence coefficient ratio and the influence coefficient ratio mean is small, that is, the ratio of the light intensity deviation coefficient to the temperature deviation coefficient at the analysis time point is not much different. The larger the value of the proportion of the number of proximity signals is, the less other influencing factors are, and the smaller the value of the proportion of the number of proximity signals is, the more other influencing factors are present. Compare the proximity signal number ratio value with the proximity signal number ratio threshold, wherein the proximity signal number ratio threshold is summarized and set by a person skilled in the art based on historical experimental data; If the value of the proportion of the number of close signals is less than the threshold value of the proportion of the number of close signals, it means that the number of analysis time points with a small deviation between the influence coefficient ratio and the influence coefficient ratio threshold is small, and other influencing factor signals are generated; Based on the generation of other influencing factor signals, other influencing factors are analyzed, and other influencing factors include but are not limited to: environmental factors, inverter failure and photovoltaic panel component failure; If the value of the proportion of the number of close signals is greater than or equal to the threshold value of the proportion of the number of close signals, it means that there are more analysis time points with smaller deviations between the influence coefficient ratio and the influence coefficient ratio threshold, and a signal without other influencing factors is generated; Based on the generation of a signal without other influencing factors, the orientation, angle or cleaning frequency of the photovoltaic panel can be adjusted to improve the lighting conditions and heat dissipation effect; The technical solution of the embodiment of the present invention is mainly as follows: after obtaining the abnormal sub-area, the light intensity of the sub-area of ​​the solar photovoltaic panel is monitored in real time, and the overlapping time period of the time period of the abnormal light intensity and the time period of the temperature abnormality is analyzed, and the impact correlation value is calculated based on the total overlap time, the total time of the abnormal light intensity and the total time of the abnormal temperature, and the impact correlation value is compared with the impact correlation threshold. If the impact correlation value is greater than the impact correlation threshold, a correlation signal is generated, so that it can be judged that the temperature abnormality of the solar photovoltaic panel sub-area is related to the abnormal light intensity, and then targeted optimization and adjustment can be performed; When generating a correlation signal, the influence coefficient ratio is calculated. Based on the influence coefficient ratio, the deviation value of the influence coefficient ratio of all analysis time points from the mean influence coefficient ratio is calculated. Based on the influence coefficient ratio deviation value and the influence coefficient ratio deviation threshold, the number of generated proximity signals is obtained, and the proportion of the number of proximity signals is calculated to determine whether there are other influencing factors. If the proportion of the number of proximity signals is less than the threshold of the proportion of the number of proximity signals, there are other influencing factors. If the proportion of the number of proximity signals is greater than or equal to the threshold of the proportion of the number of proximity signals, there are no other influencing factors. Therefore, by determining whether there are other influencing factors, a more accurate diagnosis of abnormal temperature factors can be made to improve management effects and power generation efficiency.

[0020] Embodiment 3: On the basis of Example 1 and Example 2, a solar photovoltaic power generation device for a modular roof steel frame described in an embodiment of the present invention is provided with a solar photovoltaic power generation system for a modular roof steel frame described in the above-mentioned Example 1 and Example 2.

[0021] The size of the above threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the cardinality set by technical personnel in this field for each group of sample data; for example: in the actual process, there are many groups of temperature mean deviation ratios, temperature anomaly time proportions and temperature anomaly area proportions. Many groups of temperature mean deviation ratios, temperature anomaly time proportions and temperature anomaly area proportions are processed to obtain the temperature judgment values ​​of the corresponding groups. The staff evaluates the temperature state of the solar photovoltaic panel based on so many groups of temperature judgment values, thereby obtaining a corresponding relationship between a temperature judgment value and the temperature state of the solar photovoltaic panel, and then derives and divides the threshold of the temperature judgment value according to the temperature state of the solar photovoltaic panel, thereby obtaining the temperature judgment threshold, and compares the obtained temperature judgment value with the temperature judgment threshold, that is, completes the identification of the temperature state of the solar photovoltaic panel corresponding to the temperature judgment value.

[0022] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A solar photovoltaic power generation system for a combined roof steel frame, characterized in that: Specifically include: Temperature data acquisition module: divide the solar photovoltaic panels into different areas, obtain the temperature value data of each sub-area, process it, and calculate the temperature judgment value of each area; Abnormal sub-region acquisition module: compares the temperature judgment value with the temperature judgment threshold to obtain the abnormal sub-region; Impact correlation calculation module: obtains the light intensity value data of each sub-area, processes it, calculates the impact correlation value between the light intensity anomaly and the temperature anomaly, compares the impact correlation value with the impact correlation threshold, and generates a correlation signal if the impact correlation value is greater than the impact correlation threshold; Other influencing factors judgment module: based on the generated correlation signal, judge whether there are other influencing factors.

2. A solar photovoltaic power generation system for a combined roof steel frame according to claim 1, characterized in that: The process of obtaining the temperature judgment value is as follows: Obtain the temperature mean deviation ratio, temperature anomaly time ratio, and temperature anomaly area ratio; Substitute into the formula , the temperature judgment value WD is calculated, where JZ represents the temperature mean deviation ratio, SJ represents the temperature abnormality time ratio, MJ represents the temperature abnormality area ratio, and a1, a2, and a3 are preset proportional coefficients.

3. A solar photovoltaic power generation system for a combined roof steel frame according to claim 2, characterized in that: The process of obtaining the temperature mean deviation ratio, temperature anomaly time ratio and temperature anomaly area ratio is as follows: Divide the solar photovoltaic panel into several sub-areas in a grid-like manner, and obtain the real-time temperature value of each sub-area; With time as the X-axis and temperature as the Y-axis, a two-dimensional model is established, the real-time temperature value is substituted into the two-dimensional model, a real-time temperature curve is drawn, a temperature standard range is preset, and the maximum and minimum values ​​of the temperature standard range are taken as Y values. Two parallel lines parallel to the X-axis are drawn respectively, and marked as the first temperature standard line and the second temperature standard line; The area of ​​the temperature curve located above the first temperature standard line and below the second temperature standard line is marked as an over-limit temperature area, and the area of ​​the temperature area located below the first temperature standard line and above the second temperature standard line is marked as a normal temperature area; A monitoring period is preset, and within the monitoring period, the real-time temperature values ​​of the period are summed and averaged to obtain a temperature mean value, the temperature mean value is calculated as a ratio difference with the temperature standard value, the difference is taken as an absolute value to obtain a temperature standard deviation value, and the temperature standard deviation value is calculated as a ratio with the temperature standard value to obtain a temperature mean deviation ratio; During the monitoring period, the time period when the temperature curve is in the temperature exceeding limit area is obtained, which is marked as the temperature abnormality time period. All the temperature abnormality time periods are summed up to obtain the total temperature abnormality time. The total temperature abnormality time is ratioed with the monitoring period to obtain the temperature abnormality time ratio. During the monitoring period, the area value of the temperature curve in the temperature limit area is obtained, marked as the temperature abnormality area value, all abnormal area values ​​are summed up to obtain the total temperature abnormality area, and the ratio of the total temperature abnormality area to the standard area value is calculated to obtain the temperature abnormality area ratio.

4. A solar photovoltaic power generation system for a combined roof steel frame according to claim 1, characterized in that: The process of obtaining the abnormal sub-region is as follows: In each monitoring period, a temperature judgment value of each sub-area is obtained, and the temperature judgment value is compared with a temperature judgment threshold value respectively; If the temperature judgment value is greater than the temperature judgment threshold, an abnormal signal is generated; During the monitoring period, the sub-region corresponding to the generated abnormal signal is obtained and marked as an abnormal sub-region.

5. A solar photovoltaic power generation system for a combined roof steel frame according to claim 3, characterized in that: The process of obtaining the impact association value is as follows: Obtain the total overlap time, total temperature anomaly time, and total light intensity anomaly time; Substitute into the formula , the impact correlation value GL is calculated, where CT represents the total overlap time, WT represents the total temperature abnormality time, and GT represents the total light intensity abnormality time.

6. A solar photovoltaic power generation system for a combined roof steel frame according to claim 5, characterized in that: The acquisition process of the total overlap time and the total abnormal light intensity time is as follows: Obtain the real-time light intensity value of each sub-area, and compare the real-time light intensity value with the light intensity threshold; If the real-time light intensity value is less than the light intensity threshold, a light intensity abnormality signal is generated; During the monitoring period, the duration period of generating the abnormal light intensity signal is obtained, marked as the abnormal light intensity time period, all the abnormal light intensity time periods are summed up to obtain the total abnormal light intensity time, the abnormal temperature time period is obtained, the overlapping time period of the abnormal light intensity time period and the abnormal temperature time period is obtained, all the overlapping time periods are summed up to obtain the total overlapping time.

7. A solar photovoltaic power generation system for a combined roof steel frame according to claim 1, characterized in that: The process of determining whether there are other influencing factors is as follows: Obtaining a value of the proportion of the number of proximity signals, and comparing the value of the proportion of the number of proximity signals with a threshold value of the proportion of the number of proximity signals; If the value of the proximity signal number ratio is less than the proximity signal number ratio threshold, a signal with other influencing factors is generated; If the value of the proximity signal number ratio is greater than or equal to the proximity signal number ratio threshold, a signal without other influencing factors is generated.

8. A solar photovoltaic power generation system for a combined roof steel frame according to claim 1, characterized in that: The process of obtaining the value of the proportion of the number of proximity signals is as follows: Obtain the influence coefficient ratios of all analysis time points, sum and average the influence coefficient ratios of all analysis time points to obtain the influence coefficient ratio mean, perform difference calculation on all influence coefficient ratios and the influence coefficient ratio mean to obtain the influence coefficient ratio deviation value, and compare the influence coefficient deviation value with the influence coefficient deviation threshold; If the influence coefficient deviation value is less than or equal to the influence coefficient deviation threshold, a proximity signal is generated; The number of generated proximity signals is obtained, and the ratio of the number of generated proximity signals to the total number of values ​​at the analysis time point is calculated to obtain the ratio of the number of proximity signals.

9. A solar photovoltaic power generation system for a combined roof steel frame according to claim 1, characterized in that: The process of obtaining the influence coefficient ratio is as follows: When generating the correlation signal, the overlapping time period is divided into several analysis time points, the light intensity value corresponding to each analysis time point is obtained, the light intensity value is calculated to be different from the light intensity threshold to obtain the light intensity deviation value, and the light intensity deviation value is processed by ratio with the light intensity deviation threshold to obtain the light intensity deviation coefficient; Obtain the temperature value corresponding to each analysis time point, and compare the temperature value with the maximum and minimum values ​​obtained in the temperature standard range; If the temperature value is greater than the maximum value of the temperature standard range, the temperature value and the maximum value of the temperature standard range are calculated to obtain the temperature deviation value, and the temperature deviation value is ratioed with the temperature standard value to obtain the temperature deviation coefficient; If the temperature value is less than the minimum value of the temperature standard range, the difference between the minimum value of the temperature standard range and the temperature value is calculated to obtain the temperature deviation value, and the temperature deviation value is ratioed with the temperature standard value to obtain the temperature deviation coefficient; The light intensity deviation coefficient and the temperature deviation coefficient at the same analysis time point are ratio processed to obtain the influence coefficient ratio.

10. A solar photovoltaic device for a modular roof steel frame, characterized in that: The device is provided with the system described in any one of claims 1 to 9.

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