Intelligent management system of photovoltaic power station

Abstract

The invention discloses a photovoltaic power station intelligent management system, which relates to the field of photovoltaic power station intelligent management, and comprises a server, and the server is in communication connection with a data acquisition unit, an apparent analysis unit, a performance inspection unit, a judgment early warning unit and a display terminal. The method comprises the following steps: performing photovoltaic power station area apparent state judgment analysis processing on previous unit photovoltaic bracket system information, silicon battery piece information and photovoltaic module information to obtain area apparent grade signal judgment and a corresponding performance inspection instruction, receiving the performance inspection instruction, and performing detection area performance state analysis processing. According to the method, performance evaluation area grade judgment is obtained, the comprehensive state of the photovoltaic power station is judged according to the area apparent signal grade and the performance evaluation area grade, early warning display corresponding to different photovoltaic power stations is obtained, operation faults of the photovoltaic power station can be recognized timely and accurately, the service life of equipment can be prolonged, the power generation efficiency can be ensured, and the system safety can be guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of intelligent management of photovoltaic power stations, and in particular to an intelligent management system for photovoltaic power stations. Background Art

[0002] With the growing demand for renewable energy, photovoltaic power stations have been applied and developed as a clean and environmentally friendly way of generating energy. However, in the management of traditional photovoltaic power stations, they rely too much on personnel inspections, resulting in untimely fault detection and incomplete and inaccurate data collection. Therefore, an intelligent management system for photovoltaic power stations has emerged.

[0003] In the process of intelligent management of photovoltaic power stations, the identification of photovoltaic power station operation faults is an important way to extend equipment life, ensure power generation efficiency and ensure system safety. It is crucial to accurately analyze the identification of photovoltaic power station operation faults.

[0004] When operating, traditional photovoltaic power station intelligent management systems find it difficult to quickly and accurately identify photovoltaic power station operation faults, and it is also difficult to determine and analyze the operating status of photovoltaic power stations from multiple levels, which increases the cost of corporate photovoltaic power station management.

[0005] In order to solve the above defects, a technical solution is now provided. Summary of the invention

[0006] In order to solve the technical problems raised by the above background technology, the present invention is proposed. An embodiment of the present invention provides an intelligent management system for a photovoltaic power station.

[0007] The purpose of the present invention can be achieved through the following technical solutions: A photovoltaic power station intelligent management system includes a server, the server is communicatively connected to a data acquisition unit, an appearance analysis unit, a performance inspection unit, a judgment and early warning unit and a display terminal.

[0008] The data acquisition unit is used to collect photovoltaic support system information, silicon cell appearance information, photovoltaic module information, concrete base information and silicon cell performance information in the operation of the photovoltaic power station, and send it to the appearance analysis unit and the performance inspection unit respectively through the server;

[0009] The appearance analysis unit performs an analysis and processing of the photovoltaic power station regional appearance state determination on the previous unit photovoltaic support system information, silicon cell information and photovoltaic module information to obtain a regional appearance level signal determination and a corresponding performance inspection instruction;

[0010] The performance inspection unit receives the performance inspection instruction and performs performance status analysis and processing in the detection area to obtain a performance evaluation area level determination;

[0011] The determination and early warning unit determines the comprehensive state of the photovoltaic power station based on the regional apparent signal level and the performance evaluation regional level, and obtains early warning displays corresponding to different photovoltaic power stations.

[0012] Furthermore, the regional apparent level signal determination and the corresponding performance test instruction operation steps are as follows:

[0013] Setting the gradient reference intervals Q1, Q2 and Q3 of the regional apparent state value, and substituting the apparent state value of each region into the preset gradient reference intervals Q1, Q2 and Q3 for comparative analysis, wherein Q1, Q2 and Q3 increase in a gradient manner;

[0014] When the regional apparent state value is within the preset gradient reference interval Q1, a third-level regional apparent signal is generated and a performance inspection instruction is triggered. When the regional apparent state value is within the preset gradient reference interval Q2, a second-level regional apparent signal is generated and a performance inspection instruction is triggered. When the regional apparent state value is within the preset gradient reference interval Q3, a first-level regional apparent signal is generated, and there are no other related operations.

[0015] Furthermore, the operation steps of the regional apparent state value are as follows:

[0016] The photovoltaic module state value gfz of each area, the color evaluation value scp of the silicon cell of each area and the fractal dimension value fs of the photovoltaic support system of each area are processed according to the graph construction to obtain the apparent state value of each area.

[0017] Furthermore, the fractal dimension values ​​of the photovoltaic support systems in each region and the color evaluation values ​​of the silicon cells in each region are operated as follows:

[0018] The photovoltaic power station is divided into several areas, and acoustic emission sensors are installed on the photovoltaic support systems in each area. The oscilloscope is used to monitor the waveform of the acoustic emission signal in continuous time. The continuous time is divided into several unit intervals, and the maximum and minimum values ​​of the signal in the unit interval in each area are obtained. The difference is calculated to obtain the signal amplitude value fd in the unit interval. i , according to the set formula nl i =u×fd i 2 , get the energy value nl in each interval time period i , where i is the number of the unit interval time, i = 1, 2, 3...I, I is the maximum value of the time scale, and u is the correction factor coefficient, which is used to improve the accuracy of the calculation and obtain the time scale that increases continuously from the monitoring time. According to the formula Get the total energy value E of n unit interval time scale X x , where n≤I, the time scale X and the total energy value E xTake the logarithm of each to get log X and log E x Function data, with log X as the horizontal axis and log E as the horizontal axis x is the ordinate, x = 1, 2, 3...n, n is the maximum number of time scale intervals, and the coordinate points of the total energy logarithm changing with the time scale n are established. The specific coordinate points are (log X1, log E1), (log X2, log E2), ..., (log Xn, log En), according to the set formula The fractal dimension value fs of the photovoltaic support system in each area is calculated, where A1 is the average value of the logarithm of the time scale, and A2 is the average value of the logarithm of the total energy;

[0019] The angle of diffracted light in the silicon cell at each monitoring time in each region is obtained by a grating spectrometer, and the wavelength of the silicon cell in each region is obtained by formula calculation. The wavelength of the silicon cell in each region is multiplied by the corresponding adjustment factor to obtain the hue value of the silicon cell in each region. The contrast value and pixel value in the silicon cell image at each monitoring time in each region are obtained by formula calculation to obtain the hue change trend value sq, the contrast change trend value dq and the pixel change trend value xq. The silicon cell image in each region is converted into a grayscale image, and the parts with pixel values ​​greater than 200 in the grayscale image in each region are obtained and marked as matching parts. The number of matching parts and the proportion of the total area of ​​the matching parts to the area of ​​the grayscale image are identified, and normalized with the hue change trend value sq, the contrast change trend value dq and the pixel change trend value xq are analyzed to obtain the color evaluation value scp of the silicon cell in each region.

[0020] Furthermore, the steps for operating the photovoltaic module status values ​​in each area are as follows:

[0021] A beam of parallel light is focused on the surface of the frame to obtain the area, focus depth and clutter value of the light spot, and the frame roughness value is obtained by formula calculation;

[0022] The transmittance of the tempered glass in each area, the water vapor transmittance of the back panel surface and the back panel thickness variation value are obtained, and the formula is used to calculate the photovoltaic module status value in each area with the frame roughness value.

[0023] Furthermore, the performance evaluation area level determination operation steps are as follows:

[0024] The detection area comprehensive assessment value is compared with the set reference threshold. When the detection area comprehensive assessment value is greater than the set reference threshold, the detection area corresponds to the first-level performance evaluation area. When the detection area comprehensive assessment value is equal to the set reference threshold, the detection area corresponds to the second-level performance evaluation area. When the detection area comprehensive assessment value is less than the set reference threshold, the detection area corresponds to the third-level performance evaluation area.

[0025] Furthermore, the detection regional comprehensive evaluation value determination operation steps are as follows:

[0026] A thermal image is generated by the infrared radiation emitted by the thermal imager on the surface of the concrete base in the detection area. The thermal image is divided into several parts, and the pixel value of each part is obtained and compared with the set reference pixel value. When the pixel value of a part is greater than the set reference pixel value, the part corresponds to the temperature abnormal part. The number of temperature abnormal parts is obtained and divided by the headquarters score to obtain the abnormal temperature part ratio yc. Several detection points are selected on the surface of the concrete base in the detection area, and phenolphthalein reagent is sprayed on the selected detection points. The images of the concrete surface before and after detection are taken by the camera. By analyzing the brightness values ​​of the images before and after detection, when the brightness value change of the detection point is greater than the set reference brightness threshold, the detection point corresponds to the uncarbonized detection point, marked as th, and the propagation speed cv of the ultrasonic wave in the concrete base in the detection area is obtained. The abnormal temperature part ratio yc, the number of uncarbonized detection points th and the ultrasonic wave propagation speed cv are normalized according to the set formula The concrete base shape estimate zgz of the detection area is obtained, where μ is the preset correction factor, and y1, y2 and y3 are the preset weight factors of the abnormal temperature proportion, the number of uncarbonized detection points and the ultrasonic propagation velocity respectively;

[0027] Obtain the maximum power of the silicon cell, the filling factor of the silicon cell and the light conversion rate value in the silicon cell performance information, analyze the formula, and obtain the silicon cell property estimation dgz;

[0028] The estimated condition of the concrete base and the estimated condition of the silicon cell in the inspection area are weighted and multiplied by the corresponding weight factor to obtain the comprehensive estimated condition value of the inspection area.

[0029] Furthermore, the warning display operation steps corresponding to the different photovoltaic power stations are as follows:

[0030] Count the number of primary area apparent signals, secondary area apparent signals and tertiary area apparent signals, count the number of primary performance evaluation areas, secondary performance evaluation areas and tertiary performance evaluation areas, calculate by formula, and obtain the photovoltaic power station comprehensive value gzz;

[0031] Compare and analyze the comprehensive status value of the photovoltaic power station with the set comparison threshold value TT1. When the comprehensive status value of the photovoltaic power station is less than the set comparison threshold value TT1, an abnormal status alarm of the photovoltaic power station is issued and sent to the display terminal in the form of a label-text description for display description;

[0032] When the overall status value of the photovoltaic power station is greater than or equal to the set comparison threshold TT1, the photovoltaic power station status is generated to be normal, and is sent to the display terminal in the form of a label second text description for display description.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] 1. The present invention collects the photovoltaic support system information, silicon cell apparent information and photovoltaic module information in the operation of the photovoltaic power station, and performs regional apparent state determination and analysis processing on the photovoltaic support system information, silicon cell information and photovoltaic module information of the previous unit, obtains the regional apparent level signal determination and the corresponding performance inspection instruction, receives the performance inspection instruction and performs performance state analysis processing on the detection area, obtains the performance evaluation area level determination, can first analyze and determine the apparent state of the photovoltaic power station, and perform performance analysis on the area with abnormal state, can not only analyze from multiple levels, but also perform targeted performance determination and analysis, saves management costs to a certain extent, and the data collection and analysis are also comprehensive and accurate.

[0035] 2. The present invention determines the comprehensive status of the photovoltaic power station by the regional apparent signal level and the performance evaluation regional level, and obtains the corresponding early warning display of different photovoltaic power stations. It can quickly and accurately identify the failure of the operation of the photovoltaic power station, reduce the cost of the enterprise photovoltaic power station management, and extend the life of the equipment, ensure the power generation efficiency and protect the system safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. The following drawings are not intentionally scaled according to the actual sizes, and the focus is on illustrating the main purpose of the present invention.

[0037] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work also fall within the scope of protection of the present invention.

[0039] like Figure 1 As shown, a photovoltaic power station intelligent management system includes a server, and the server is communicatively connected with a data acquisition unit, an appearance analysis unit, a performance inspection unit, a judgment and early warning unit and a display terminal;

[0040] The data acquisition unit is used to collect photovoltaic support system information, silicon cell appearance information, photovoltaic module information, concrete base information and silicon cell performance information during the operation of the photovoltaic power station, and send it to the appearance analysis unit and performance inspection unit respectively through the server.

[0041] When the apparent analysis unit receives the photovoltaic support system information, silicon cell information and photovoltaic module information of the previous unit, it performs the apparent state determination and analysis of the photovoltaic power station area based on the information, and obtains the regional apparent level signal determination and corresponding performance inspection instructions. The specific operation process is as follows:

[0042] The photovoltaic power station is divided into several areas, and acoustic emission sensors are installed on the photovoltaic support systems in each area. The oscilloscope is used to monitor the waveform of the acoustic emission signal in continuous time. The continuous time is divided into several unit intervals, and the maximum and minimum values ​​of the signal in the unit interval in each area are obtained. The difference is calculated to obtain the signal amplitude value fd in the unit interval. i , according to the set formula nl i =u×fd i 2 , get the energy value nl in each interval time period i , where i is the number of the unit interval time, i = 1, 2, 3...I, I is the maximum value of the time scale, and u is the correction factor coefficient, which is used to improve the accuracy of the calculation and obtain the time scale that increases continuously from the monitoring time. According to the formula Get the total energy value E of n unit interval time scale X x , where n≤I, the time scale X and the total energy value E x Take the logarithm of each to get log X and log E x Function data, with log X as the horizontal axis and log E as the horizontal axis x is the ordinate, x = 1, 2, 3...n, n is the maximum number of time scale intervals, and the coordinate points of the total energy logarithm changing with the time scale n are established. The specific coordinate points are (log X1, log E1), (log X2, log E2), ..., (log Xn, log En), according to the set formula The fractal dimension value fs of the photovoltaic support system in each region is calculated, where A1 is the average value of the logarithm of the time scale, and A2 is the average value of the logarithm of the total energy. It should be noted that the higher the fractal dimension value, the more complex the signal, and the more cracks there are in the support system;

[0043] The angle of diffracted light in the silicon cell in each area and monitoring time is obtained by a grating spectrometer, and the formula bc m =d×(sinθ1 m +sinθ2m ) / a1, and get the wavelength bc of the silicon cell in each area m , where θ1 is the angle between the incident light and the grating normal, θ1 is the angle between the diffracted light and the grating normal, m is the number of the monitoring time, m = 1, 2, 3...m1, d is the grating constant, the reciprocal of the number of notches per unit length, a1 is the diffraction order, and the wavelength of the silicon cell in each region is multiplied by the corresponding adjustment factor to obtain the hue value xs of the silicon cell in each region m , obtain the contrast value and pixel value in the silicon cell image of each area and each monitoring time, marked as db m and xsz m , according to the set formula The hue change trend value sq, contrast change trend value dq and pixel change trend value xq are obtained, where A3 is the average hue value of the silicon cell in each region, A4 is the average contrast value of the silicon cell in each region, and A5 is the average pixel value of the silicon cell in each region. The silicon cell images in each region are converted into grayscale images, and the parts with pixel values ​​greater than 200 in the grayscale images in each region are obtained and marked as matching parts. The number of matching parts and the proportion of the total area of ​​the matching parts to the area of ​​the grayscale image are identified, marked as gs and zb respectively, and normalized with the hue change trend value sq, the contrast change trend value dq and the pixel change trend value xq. According to the set formula

[0044] , the color evaluation value scp of the silicon cell in each area is obtained, where h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11, h12, h13, h14 and h15 are the set weight factor coefficients, h1>h6>h11, h2>h7>h12, h3>h8>h13, h14>h9>h4, h15>h10>h5, e is a natural constant with a value of 2.718. It should be noted that the pixel value range of the normal part is 100-200, and the pixel value of the hot spot part is above 200;

[0045] Obtain the transmittance of tempered glass in each area, the water vapor transmittance of the back panel surface, the back panel thickness variation value and the frame roughness value, and mark them as tgl, tsl, fbz and ccz respectively, normalize them and substitute them into the formula The photovoltaic module state value gfz of each area is calculated, where UO1, UO2, UO3 and UO4 are respectively the preset weight factors of the light transmittance of the tempered glass, the water vapor transmittance of the back sheet surface, the back sheet thickness variation value and the frame roughness value, and σ is the preset correction factor;

[0046] It should be noted that the light transmittance of tempered glass refers to the ratio of the intensity of transmitted light to the intensity of incident light when a spectrophotometer irradiates a beam of light of a specific wavelength onto the tempered glass; the water vapor transmittance of the back panel surface refers to the value obtained by the water vapor sensor; the back panel thickness variation value refers to the sum of the absolute values ​​of the difference between the back panel thickness ranked first and the back panel thickness ranked last in the order of monitoring time;

[0047] It should also be pointed out that the process of solving the border roughness value is as follows:

[0048] A beam of parallel light is focused on the surface of the frame to obtain the area, focus depth and clutter value of the light spot, which are marked as gmj, jsz and glz respectively, and normalized. According to the set formula ccz=TO1×gmj+TO2 / jsz+TO3×glz, the frame roughness value ccz is obtained, where TO1, TO2 and TO3 are the set weight factor coefficients of the area, focus depth and clutter value of the light spot respectively, and the specific values ​​are determined by personnel in this professional field;

[0049] It should be noted that the clutter value of the light spot refers to the maximum length values ​​Ls and Lc of the light spot in the horizontal and vertical directions, and the absolute value of the difference between the ratio of Ls and Lc and the value 1;

[0050] The photovoltaic module state value gfz of each region and the color evaluation value scp of the silicon cell of each region are converted into length according to a certain ratio, and an ellipse is constructed with the length of the photovoltaic module state value gfz of each region and the color evaluation value scp of the silicon cell of each region as the major axis and minor axis of the ellipse; the fractal dimension value fs of the photovoltaic support system of each region is converted into length according to a certain ratio, and a square is constructed inside the ellipse with the length of the fractal dimension value fs of the photovoltaic support system of each region as the side length of the square, and the center of the square coincides with the center of the ellipse, and the non-overlapping area formed by the square and the ellipse is identified and marked as the apparent state value of each region;

[0051] Setting the gradient reference intervals Q1, Q2 and Q3 of the regional apparent state value, and substituting the apparent state value of each region into the preset gradient reference intervals Q1, Q2 and Q3 for comparative analysis, wherein Q1, Q2 and Q3 increase in a gradient manner;

[0052] When the regional apparent state value is within the preset gradient reference interval Q1, a third-level regional apparent signal is generated and a performance inspection instruction is triggered; when the regional apparent state value is within the preset gradient reference interval Q2, a second-level regional apparent signal is generated and a performance inspection instruction is triggered; when the regional apparent state value is within the preset gradient reference interval Q3, a first-level regional apparent signal is generated, and no other related operations are performed;

[0053] When the performance inspection unit receives the performance inspection instruction, it performs performance status analysis and processing on the detection area to obtain the performance evaluation area level determination. The specific operation process is as follows:

[0054] A thermal image is generated by the infrared radiation emitted by the thermal imager on the surface of the concrete base in the detection area. The thermal image is divided into several parts, and the pixel value of each part is obtained and compared with the set reference pixel value. When the pixel value of a part is greater than the set reference pixel value, the part corresponds to the temperature abnormal part. The number of temperature abnormal parts is obtained and divided by the headquarters score to obtain the abnormal temperature part ratio yc. Several detection points are selected on the surface of the concrete base in the detection area, and phenolphthalein reagent is sprayed on the selected detection points. The images of the concrete surface before and after detection are taken by the camera. By analyzing the brightness values ​​of the images before and after detection, when the brightness value change of the detection point is greater than the set reference brightness threshold, the detection point corresponds to the uncarbonized detection point, marked as th, and the propagation speed cv of the ultrasonic wave in the concrete base in the detection area is obtained. The abnormal temperature part ratio yc, the number of uncarbonized detection points th and the ultrasonic wave propagation speed cv are normalized according to the set formula The concrete base shape estimate zgz of the detection area is obtained, where μ is the preset correction factor and μ is taken as 0.376, and y1, y2 and y3 are the preset weight factors of the abnormal temperature proportion, the number of uncarbonized detection points and the ultrasonic propagation velocity respectively;

[0055] Get the maximum power of silicon cells, silicon cell fill factor and light conversion rate in the silicon cell performance information, and calibrate them as zg, ty and gz respectively, and analyze them by formula. The estimated value dgz of the silicon cell is obtained, where f1, f2 and f3 are correction factor coefficients of the maximum power of the silicon cell, the filling factor of the silicon cell and the light conversion value, respectively, and f1, f2 and f3 are all natural numbers greater than 0;

[0056] It should be noted that the silicon cell fill factor refers to the product of the open circuit voltage and short circuit current of the silicon cell, and the ratio of the maximum power value to the product value; the light conversion rate refers to the product of the light intensity and the light receiving area of ​​the cell, and the ratio of the maximum power value to the product value;

[0057] The estimated condition of the concrete base and the estimated condition of the silicon cell in the detection area are weighted and multiplied by the corresponding weight factor to obtain the comprehensive estimated condition value of the detection area;

[0058] Compare the set reference threshold of the detection regional comprehensive evaluation value. When the detection regional comprehensive evaluation value is greater than the set reference threshold, the detection area corresponds to the first-level performance evaluation area. When the detection regional comprehensive evaluation value is equal to the set reference threshold, the detection area corresponds to the second-level performance evaluation area. When the detection regional comprehensive evaluation value is less than the set reference threshold, the detection area corresponds to the third-level performance evaluation area.

[0059] When the early warning unit receives the apparent signal level of the area and the performance evaluation area level, it determines the comprehensive status of its photovoltaic power station and obtains the early warning display corresponding to different photovoltaic power stations. The specific analysis is as follows:

[0060] The number of apparent signals in the first-level region, the second-level region and the third-level region are counted, marked as ys, es and ss respectively, and the number of apparent signals in the first-level performance evaluation area, the second-level performance evaluation area and the third-level performance evaluation area are counted, marked as yn, en and sn respectively, according to the set formula The photovoltaic power station comprehensive value gzz is obtained, and h1, h2, h3 and h4 are the set reference weight factor coefficients respectively;

[0061] Compare and analyze the comprehensive status value of the photovoltaic power station with the set comparison threshold TT1. When the comprehensive status value of the photovoltaic power station is less than the set comparison threshold TT1, an abnormal status alarm of the photovoltaic power station is issued, and the alarm is sent to the display terminal for display in the form of a text description of "the status value of the photovoltaic power station is abnormal, and the maintenance personnel should diagnose and repair the fault as soon as possible";

[0062] When the photovoltaic power station comprehensive status value is greater than or equal to the set comparison threshold TT1, the photovoltaic power station status is normal, and is sent to the display terminal for display description in the form of a text description of "photovoltaic power station status value is normal".

[0063] The present invention collects photovoltaic support system information, silicon cell apparent information and photovoltaic module information in operation of the photovoltaic power station, and performs regional apparent state determination and analysis processing on the photovoltaic support system information, silicon cell information and photovoltaic module information of the previous unit, obtains regional apparent level signal determination and corresponding performance inspection instructions, receives the performance inspection instructions and performs performance state analysis processing on the detection area, obtains performance evaluation regional level determination, can first analyze and determine the apparent state of the photovoltaic power station, and perform performance analysis on the area in abnormal state, can not only perform multi-level analysis, but also perform targeted performance determination and analysis, saves management costs to a certain extent, and at the same time, data collection and analysis are comprehensive and accurate.

[0064] The present invention determines the comprehensive status of the photovoltaic power station by using the regional apparent signal level and the performance evaluation regional level, and obtains early warning displays corresponding to different photovoltaic power stations. It can quickly and accurately identify faults in the operation of the photovoltaic power station, reduce the cost of enterprise photovoltaic power station management, and extend the life of the equipment, ensure power generation efficiency and protect system safety.

[0065] The above is an explanation of the present invention and should not be considered as a limitation thereof. Although several exemplary embodiments of the present invention have been described, it will be readily appreciated by those skilled in the art that many modifications may be made to the exemplary embodiments without departing from the novel teachings and advantages of the present invention. Therefore, all such modifications are intended to be included within the scope of the present invention as defined in the claims. It should be understood that the above is an explanation of the present invention and should not be considered as being limited to the specific embodiments disclosed, and modifications to the disclosed embodiments and other embodiments are intended to be included within the scope of the appended claims. The present invention is defined by the claims and their equivalents.

Claims

1. A photovoltaic power station intelligent management system, comprising a server, characterized in that: The server communication connections are: The data acquisition unit is used to collect the photovoltaic support system information, silicon cell appearance information, photovoltaic module information, concrete base information and silicon cell performance information in the operation of the photovoltaic power station, and send it to the appearance analysis unit and the performance inspection unit respectively through the server; The appearance analysis unit performs an analysis and processing of the appearance state determination of the photovoltaic power station area based on the photovoltaic support system information, silicon cell information and photovoltaic module information of the previous unit, and obtains the regional appearance level signal determination and the corresponding performance inspection instruction; The performance inspection unit receives the performance inspection instruction and performs performance status analysis and processing in the detection area to obtain a performance evaluation area level determination; The judgment and early warning unit judges the comprehensive status of the photovoltaic power station based on the regional apparent signal level and the performance evaluation regional level, and obtains the corresponding early warning display for different photovoltaic power stations.

2. A photovoltaic power station intelligent management system according to claim 1, characterized in that: The steps of determining the regional apparent level signal and the corresponding performance test instruction are as follows: Substitute the apparent state value of each region into the preset gradient reference intervals Q1, Q2 and Q3 for comparative analysis, generate a third-level regional apparent signal and trigger a performance inspection instruction, or generate a second-level regional apparent signal and trigger a performance inspection instruction, or generate a first-level regional apparent signal.

3. A photovoltaic power station intelligent management system according to claim 2, characterized in that: The operation steps of the regional apparent state value are as follows: The photovoltaic module status values ​​of each area, the color evaluation values ​​of the silicon cells of each area and the fractal dimension values ​​of the photovoltaic support systems of each area are processed according to the graph construction to obtain the apparent status values ​​of each area.

4. A photovoltaic power station intelligent management system according to claim 3, characterized in that: The steps for calculating the fractal dimension value of the photovoltaic support system in each region and the color evaluation value of the silicon cell in each region are as follows: The photovoltaic power station is divided into several areas, and acoustic emission sensors are installed on the photovoltaic support systems in each area. The oscilloscope is used to monitor the waveform of the acoustic emission signal in continuous time. The continuous time is divided into several unit intervals, and the maximum and minimum values ​​of the signal in the unit interval in each area are obtained. The difference is calculated to obtain the signal amplitude value fd in the unit interval. i , according to the set formula nl i =u×fd i 2 , get the energy value nl in each interval time period i , where i is the number of the unit interval time, i = 1, 2, 3...I, I is the maximum value of the time scale, and u is the correction factor coefficient, which is used to improve the accuracy of the calculation and obtain the time scale that increases continuously from the monitoring time. According to the formula Get the total energy value E of n unit interval time scale X x , where n≤I, the time scale X and the total energy value E x Take the logarithm of each to get log X and log E x Function data, with log X as the horizontal axis and log E as the horizontal axis x is the ordinate, x = 1, 2, 3...n, n is the maximum number of time scale intervals, and the coordinate points of the total energy logarithm changing with the time scale n are established. The specific coordinate points are (logX1, log E1), (log X2, log E2), ..., (log Xn, log En), according to the set formula The fractal dimension value fs of the photovoltaic support system in each area is calculated, where A1 is the average value of the logarithm of the time scale, and A2 is the average value of the logarithm of the total energy; The angle of diffracted light in the silicon solar cell in each area and each monitoring time is obtained by a grating spectrometer, and the wavelength of the silicon solar cell in each area is obtained by formula calculation. The wavelength of the silicon solar cell in each area is multiplied by the corresponding adjustment factor to obtain the hue value of the silicon solar cell in each area, and the contrast value and pixel value in the silicon solar cell image in each area and each monitoring time are obtained. The hue change value, contrast change value and pixel change value are calculated, and the silicon solar cell image in each area is converted into a grayscale image. The parts with pixel values ​​greater than 200 in the grayscale image in each area are obtained and marked as matching parts. The number of matching parts and the proportion of the total area of ​​the matching parts to the area of ​​the grayscale image are identified, and normalized with the hue change value, contrast change value and pixel change value. The color evaluation value of the silicon solar cell in each area is obtained by analysis.

5. The photovoltaic power station intelligent management system according to claim 3, characterized in that: The steps for operating the photovoltaic module status values ​​in each area are as follows: A beam of parallel light is focused on the frame surface to obtain the area, focus depth and clutter value of the light spot, and the frame roughness value is calculated; The transmittance of the tempered glass in each area, the water vapor transmittance of the back panel surface and the back panel thickness variation value are obtained, and then combined with the frame roughness value to calculate the photovoltaic module status value in each area.

6. The photovoltaic power station intelligent management system according to claim 1, characterized in that: The performance evaluation area level determination operation steps are as follows: The detection area comprehensive assessment value is compared with the set reference threshold. When the detection area comprehensive assessment value is greater than the set reference threshold, the detection area corresponds to the first-level performance evaluation area. When the detection area comprehensive assessment value is equal to the set reference threshold, the detection area corresponds to the second-level performance evaluation area. When the detection area comprehensive assessment value is less than the set reference threshold, the detection area corresponds to the third-level performance evaluation area.

7. A photovoltaic power station intelligent management system according to claim 6, characterized in that: The steps of determining the regional comprehensive evaluation value are as follows: A thermal image is generated by the infrared radiation emitted by the thermal imager on the surface of the concrete base in the detection area. The thermal image is divided into several parts, and the pixel value of each part is obtained and compared with the set reference pixel value. When the pixel value of a part is greater than the set reference pixel value, the part corresponds to the temperature abnormal part. The number of temperature abnormal parts is obtained and divided by the headquarters score to obtain the abnormal temperature part ratio yc. Several detection points are selected on the surface of the concrete base in the detection area, and phenolphthalein reagent is sprayed on the selected detection points. The images of the concrete surface before and after detection are taken by the camera. By analyzing the brightness values ​​of the images before and after detection, when the brightness value change of the detection point is greater than the set reference brightness threshold, the detection point corresponds to the uncarbonized detection point, marked as th, and the propagation speed cv of the ultrasonic wave in the concrete base in the detection area is obtained. The abnormal temperature part ratio yc, the number of uncarbonized detection points th and the ultrasonic wave propagation speed cv are normalized according to the set formula The concrete base shape estimate zgz of the detection area is obtained, where μ is the preset correction factor, and y1, y2 and y3 are the preset weight factors of the abnormal temperature proportion, the number of uncarbonized detection points and the ultrasonic propagation velocity respectively; Obtain the maximum power of the silicon cell, the filling factor of the silicon cell and the light conversion rate value in the silicon cell performance information, and analyze and obtain the silicon cell property estimation; The estimated condition of the concrete base and the estimated condition of the silicon cell in the inspection area are weighted and multiplied by the corresponding weight factor to obtain the comprehensive estimated condition value of the inspection area.

8. The photovoltaic power station intelligent management system according to claim 1, characterized in that: The warning display operation steps corresponding to different photovoltaic power stations are as follows: The number of values ​​of the primary regional apparent signal, the secondary regional apparent signal and the tertiary regional apparent signal is counted, and the number of values ​​of the primary performance evaluation area, the secondary performance evaluation area and the tertiary performance evaluation area is counted to calculate the comprehensive status value of the photovoltaic power station; The photovoltaic power station comprehensive status value is compared and analyzed with the set comparison threshold value TT1, and an abnormal photovoltaic power station status alarm is issued and a label one text description method or a label two text description method is displayed on the display terminal for explanation.

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