Early warning processing method and system for real-time operation data of photovoltaic power station

Abstract

The invention relates to the technical field of photovoltaic power station safety monitoring, and comprises a real-time operation data early warning processing method and system for a photovoltaic power station, and the method comprises the steps: obtaining the temperature detection data of each connection cable group in a first operation monitoring region on an inverter in the photovoltaic power station, screening out the connection cable group with abnormal cable temperature, and carrying out the early warning processing of the real-time operation data of the photovoltaic power station. Recording the cable group as an abnormal cable group; acquiring operation temperature detection data of a to-be-evaluated mainboard area corresponding to the abnormal cable group in a second operation monitoring area on the inverter, and judging whether the to-be-evaluated mainboard area is in a mainboard temperature abnormal state or not; and if the judgment result is no, obtaining mainboard dust retention detection data, generating a mainboard dust retention estimated value according to the mainboard dust retention detection data, judging whether the mainboard area to be evaluated is in a dust retention abnormal state, and if the judgment result is yes, generating a dust retention risk early warning. According to the invention, fine monitoring and high-precision safety early warning during operation of the inverter in the photovoltaic power station are realized, and the safety performance is improved.

Description

Technical Field

[0001] The present application relates to the technical field of photovoltaic power station safety monitoring, and in particular to a method and system for early warning processing of real-time operation data of a photovoltaic power station. Background Art

[0002] Photovoltaic power station is a system that uses solar energy to generate electricity and is a green power development energy project. Monitoring and early warning of photovoltaic power stations during operation are crucial. For example, the Chinese invention patent with publication number CN117609953A disclosed on February 27, 2024 a photovoltaic power station operation status monitoring method based on a multi-source signal feature extraction algorithm, including establishing a power station status analysis model, collecting multi-source signals of the photovoltaic power station, pre-processing the collected multi-source signals, and using the multi-source signal feature extraction algorithm to extract feature parameters related to the operation status of the photovoltaic power station from the pre-processed data. The extracted feature parameters are combined with the pre-established power station status analysis model to analyze the operation status of the photovoltaic power station. According to the analysis results, early warning information is issued when necessary. The multi-source signal feature extraction algorithm can be used to monitor the operation status of the photovoltaic power station and can extract features from multiple sensors or monitoring devices at the same time.

[0003] Although the technical solution in the above patent document can achieve the fusion and supplementation of the extracted features that may have different amounts of information and focus points, it has similar problems as other monitoring and early warning of photovoltaic power stations in the prior art. Specifically, the collected data is relatively broad, and the core part is not monitored in a refined manner. Therefore, there are problems such as over-broad monitoring, insufficient refinement and low security. Summary of the invention

[0004] Based on this, it is necessary to provide a real-time operation data warning processing method and system for photovoltaic power stations that can achieve refined monitoring, high-precision warning and high-safety warning in response to the above technical problems.

[0005] The technical solution of the present invention is as follows:

[0006] A method for early warning processing of real-time operation data of a photovoltaic power station, the method comprising:

[0007] Acquire temperature detection data of each connection cable group in a first operation monitoring area on an inverter in a photovoltaic power station, filter out connection cable groups with abnormal cable temperatures according to the temperature detection data, and record them as abnormal cable groups;

[0008] Acquire the operating temperature detection data of the mainboard area to be evaluated corresponding to the abnormal cable group in the second operating monitoring area on the inverter, and determine whether the mainboard area to be evaluated is in an abnormal mainboard temperature state according to the operating temperature detection data;

[0009] If the judgment is no, then controlling the dust accumulation detection auxiliary module to perform dust accumulation detection on the to-be-evaluated mainboard area and obtaining mainboard dust accumulation detection data, wherein the dust accumulation detection auxiliary module is pre-set in the to-be-evaluated mainboard area;

[0010] A mainboard dust accumulation estimated value is generated according to the mainboard dust accumulation detection data, and whether the mainboard area to be evaluated is in an abnormal dust accumulation state is determined according to the mainboard dust accumulation estimated value. If the determination is yes, a dust accumulation risk warning is generated.

[0011] Optionally, obtaining temperature detection data of each connection cable group in the first operation monitoring area of ​​the inverter in the photovoltaic power station, screening out connection cable groups with abnormal cable temperatures according to each temperature detection data, and recording them as abnormal cable groups, includes:

[0012] Acquire each temperature detection data of each connection cable group in the first operation monitoring area of ​​the inverter in the photovoltaic power station and the corresponding inverter operation power data, and acquire the normal operating temperature range pre-stored in each of the connection cable groups, wherein one connection cable group corresponds to one normal operating temperature range, and the normal operating temperature range corresponds to the normal operating power of the inverter;

[0013] Extracting the real-time operating power matching the normal operating power from the inverter operating power data, and recording the time period corresponding to the real-time operating power as the data collection time period;

[0014] Extracting the temperature data to be analyzed from the temperature detection data according to the data collection time period, and generating a real-time operating temperature range according to the temperature data to be analyzed;

[0015] Calculating an abnormal temperature range in which the real-time operating temperature range exceeds the normal operating temperature range, and generating an operating temperature deviation ratio according to the abnormal temperature range;

[0016] Determining whether the operating temperature deviation ratio is less than or equal to a preset standard temperature deviation ratio;

[0017] If the judgment is no, it is judged that the temperature of the corresponding connecting cable group is abnormal, and the corresponding connecting cable group is set as an abnormal cable group;

[0018] If the judgment is yes, then obtaining a pre-marked cable combination pre-marked in each of the connection cable groups, and obtaining the temperature data to be analyzed corresponding to the connection cable group in the pre-marked cable combination;

[0019] According to the to-be-analyzed temperature data corresponding to the connected cable groups in the pre-marked cable combination, the connected cable groups with abnormal cable temperatures are screened out and recorded as abnormal cable groups.

[0020] Optionally, the pre-marked cable combination includes a first marked cable group and a second marked cable group, the temperature data to be analyzed corresponding to the first marked cable group is recorded as first operating temperature data, and the temperature data to be analyzed corresponding to the second marked cable group is recorded as second operating temperature data;

[0021] Screening out the connected cable groups with abnormal cable temperatures according to the to-be-analyzed temperature data corresponding to the connected cable groups in the pre-marked cable combination includes:

[0022] Extracting temperature values ​​of first operating temperature data corresponding to a first marked cable group in the pre-marked cable combination according to a preset collection time point, and generating first temperature sequence data, wherein the first temperature sequence data includes a plurality of first temperature values;

[0023] Extracting the temperature value of the second operating temperature data corresponding to the second marked cable group in the pre-marked cable combination according to the preset collection time point, and generating second temperature sequence data, wherein the second temperature sequence includes a plurality of second temperature values;

[0024] Calculating an operating temperature difference between a first temperature value and a second temperature value corresponding to each acquisition time point in the first temperature series data and the second temperature series data;

[0025] generating a temperature difference change trend according to each of the operating temperature differences;

[0026] Determine whether the temperature difference change trend is a stable trend;

[0027] If it is determined that the temperature difference change trend is a stable trend, the corresponding first marked cable group and the second marked cable group are not set as the connection cable group with abnormal cable temperature;

[0028] If it is determined that the temperature difference variation trend is not a stable trend, the corresponding first marked cable group and the second marked cable group are set as connection cable groups with abnormal cable temperatures.

[0029] Optionally, each of the operating temperature differences constitutes a temperature difference sequence, and the temperature change trend includes a stable trend, an upward trend and a downward trend;

[0030] Generating a temperature difference change trend according to each of the operating temperature differences includes:

[0031] Calculating the adjacent temperature difference between two adjacent operating temperature differences in the temperature difference sequence;

[0032] Summing each of the adjacent temperature difference values ​​and generating an adjacent temperature difference total value;

[0033] Determine whether the total value of the adjacent temperature difference belongs to a preset stable trend range value, wherein the stable trend range value includes a stable trend minimum value and a stable trend maximum value, the stable trend minimum value is less than 0, and the stable trend maximum value is greater than 0;

[0034] If the judgment is yes, then the temperature difference change trend is judged to be a stable trend;

[0035] When it is determined that the total value of the adjacent temperature differences is less than the minimum value of the stable trend, it is determined that the temperature difference change trend is a downward trend;

[0036] If it is determined that the total value of the adjacent temperature differences is greater than the maximum value of the stable trend, then the temperature difference change trend is determined to be an upward trend.

[0037] Optionally, obtaining operating temperature detection data of the to-be-evaluated mainboard region corresponding to the abnormal cable group, and judging whether the to-be-evaluated mainboard region is in an abnormal mainboard temperature state according to the operating temperature detection data, includes:

[0038] Obtain a pre-stored cable motherboard area association table, and determine the pre-stored monitoring motherboard area corresponding to the abnormal cable group according to the cable motherboard area association table, and record it as the motherboard area to be evaluated, wherein the cable motherboard area association table is provided with a plurality of pre-stored monitoring motherboard areas, and each of the pre-stored monitoring motherboard areas corresponds to a connection cable group;

[0039] Acquire operating temperature detection data collected by a first temperature detection sensor in the motherboard region to be evaluated, and acquire an adjacent motherboard region corresponding to the motherboard region to be evaluated, wherein the operating temperature detection data includes a plurality of actual operating temperatures;

[0040] Acquire the adjacent area temperature data collected by the second temperature detection sensor in the adjacent mainboard area, wherein the adjacent area temperature data includes a plurality of adjacent area temperatures;

[0041] generating a first average temperature and a first temperature standard deviation according to each actual operating temperature in the operating temperature detection data;

[0042] Generate a second average temperature and a second temperature standard deviation according to the temperature of each adjacent area in the adjacent area temperature data;

[0043] Generate a mainboard area temperature evaluation value according to the first average temperature, the first temperature standard deviation, the second average temperature, and the first temperature standard deviation;

[0044] Determine whether the temperature evaluation value of the mainboard area is greater than a preset temperature evaluation total threshold;

[0045] If the judgment is yes, then judging whether the motherboard area to be evaluated is in an abnormal motherboard temperature state;

[0046] If the judgment is no, then it is determined that the to-be-evaluated mainboard area is not in an abnormal mainboard temperature state.

[0047] Optionally, the dust accumulation detection auxiliary module includes a plurality of light auxiliary modules and brightness detection sensors, each of the light auxiliary modules is radially arranged in the mainboard area to be evaluated, and a brightness detection sensor is provided on the side of each light auxiliary module;

[0048] The mainboard dust accumulation detection data includes a plurality of single-point brightness detection data;

[0049] Controlling the dust accumulation detection auxiliary module to perform dust accumulation detection on the mainboard area to be evaluated and obtaining mainboard dust accumulation detection data, including:

[0050] Control each lighting auxiliary module to light up in turn, and obtain the single-point brightness detection data detected by the brightness detection sensor next to each lighting auxiliary module respectively, wherein one lighting auxiliary module corresponds to one single-point brightness detection data, and the single-point brightness detection data are summarized to be the mainboard dust accumulation detection data.

[0051] Optionally, generating a mainboard dust accumulation estimation value according to the mainboard dust accumulation detection data, and judging whether the mainboard area to be evaluated is in an abnormal dust accumulation state according to the mainboard dust accumulation estimation value includes:

[0052] According to the single-point brightness detection data in the mainboard dust accumulation detection data, brightness collection is performed at a preset data collection point and multiple single-point brightness values ​​are obtained, wherein one single-point brightness detection data corresponds to M single-point brightness values;

[0053] Acquire the number of electronic components around each of the light auxiliary modules, and generate a dust accumulation influence coefficient according to the number of electronic components, wherein one light auxiliary module corresponds to one dust accumulation influence coefficient, and the sum of the dust accumulation influence coefficients is 1;

[0054] Generate an estimated value for motherboard dust accumulation based on the following formula:

[0055]

[0056] Wherein, Ctotal is the estimated value of dust accumulation on the mainboard, N is the number of single-point brightness detection data, wj is the dust accumulation influence coefficient corresponding to the j-th lighting auxiliary module, M is the number of single-point brightness values, Ijk is the k-th single-point brightness value in the j-th single-point brightness detection data, and Is is the reference brightness value;

[0057] Determining whether the mainboard dust accumulation estimated value is greater than or equal to a mainboard dust accumulation threshold value;

[0058] If the answer is yes, then the to-be-evaluated mainboard area is judged to be in an abnormal dust accumulation state;

[0059] If the judgment is no, it is determined that the mainboard area to be evaluated is not in an abnormal dust accumulation state.

[0060] Optionally, a real-time operation data early warning processing system for a photovoltaic power station is also provided, the system comprising:

[0061] The abnormal cable screening module is used to obtain the temperature detection data of each connection cable group in the first operation monitoring area of ​​the inverter in the photovoltaic power station, and screen out the connection cable group with abnormal cable temperature according to each temperature detection data, and record it as an abnormal cable group;

[0062] A mainboard state judgment module is used to obtain the operating temperature detection data of the mainboard area to be evaluated corresponding to the abnormal cable group in the second operating monitoring area on the inverter, and judge whether the mainboard area to be evaluated is in an abnormal mainboard temperature state according to the operating temperature detection data;

[0063] A dust accumulation data detection module, which is used to control the dust accumulation detection auxiliary module to perform dust accumulation detection on the mainboard area to be evaluated and obtain mainboard dust accumulation detection data if the judgment is no, wherein the dust accumulation detection auxiliary module is pre-set in the mainboard area to be evaluated;

[0064] The risk warning generation module is used to generate a mainboard dust accumulation estimation value according to the mainboard dust accumulation detection data, and judge whether the mainboard area to be evaluated is in an abnormal dust accumulation state according to the mainboard dust accumulation estimation value. If it is judged to be so, a dust accumulation risk warning is generated.

[0065] Optionally, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps described in the above-mentioned method for processing real-time operation data early warning of a photovoltaic power station when executing the computer program.

[0066] Optionally, a computer-readable storage medium is also provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned method for processing real-time operation data early warning of a photovoltaic power station are implemented.

[0067] The technical effects achieved by the present invention are as follows:

[0068] The real-time operation data early warning processing method and system of the above-mentioned photovoltaic power station obtains each temperature detection data of each connection cable group in the first operation monitoring area on the inverter in the photovoltaic power station, and screens out the connection cable group with abnormal cable temperature according to each temperature detection data, and records it as an abnormal cable group; obtains the operation temperature detection data of the mainboard area to be evaluated corresponding to the abnormal cable group in the second operation monitoring area on the inverter, and judges whether the mainboard area to be evaluated is in an abnormal mainboard temperature state according to the operation temperature detection data; if it is judged to be no, controls the dust accumulation detection auxiliary module to perform dust accumulation detection on the mainboard area to be evaluated, and obtains the mainboard dust accumulation detection data, wherein the dust accumulation detection auxiliary module is pre-set in the mainboard area to be evaluated; Generate a mainboard dust accumulation estimate value according to the mainboard dust accumulation detection data, and judge whether the mainboard area to be evaluated is in an abnormal dust accumulation state according to the mainboard dust accumulation estimate value. If it is judged to be, generate a dust accumulation risk warning. In order to monitor the status and safety warning of the inverter of the photovoltaic power station, and to perform refined warning, the present invention delineates the monitoring area of ​​the inverter, specifically divides the first operation monitoring area and the second operation monitoring area. When monitoring the operation data, first obtain the temperature detection data of each connection cable group in the first operation monitoring area on the inverter in the photovoltaic power station, and then filter out the connection cable group with abnormal cable temperature according to each temperature detection data, and record it as an abnormal cable group, and the abnormal cable group is a cable with abnormal temperature. The temperature of the cable is abnormal, which may be due to the wear of the cable itself, or it may be due to the failure or possible failure of the components on the main control board in the inverter directly connected to the cable. In the case of wear or aging of the cable itself, the risk is low, and it can be manually checked by the maintenance personnel of the photovoltaic power station. Therefore, it is mainly necessary to further analyze the operation data to determine whether there is a possibility that the components of the main control board in the inverter are about to fail. Therefore, the operating temperature detection data of the mainboard area to be evaluated corresponding to the abnormal cable group in the second operating monitoring area on the inverter is then obtained, wherein the mainboard area to be evaluated is a pre-marked main control board area directly connected to the abnormal cable group, and there are many electronic components in this area. If such electronic components have a tendency to fail, they may cause their own temperature to rise and the temperature of the connected cables to rise. Therefore, according to the operating temperature detection data, it is judged whether the mainboard area to be evaluated is in an abnormal mainboard temperature state. If it is judged to be no, it means that the components on the main control board at this time are not currently faulty and have no tendency to fail temporarily. Therefore, it is necessary to further judge other risks, specifically to perform dust accumulation monitoring. Considering that as the inverter increases in use time, problems such as aging and dust accumulation may occur in the inverter, and dust accumulation is likely to cause risks such as abnormal internal temperature and low heat dissipation efficiency, therefore, after excluding the main control board itself, it is necessary to eliminate the risk of dust accumulation, so as to further eliminate all risks that may cause temperature abnormalities.Specifically, the preset dust accumulation detection auxiliary module is controlled to perform dust accumulation detection on the mainboard area to be evaluated, and mainboard dust accumulation detection data is obtained, wherein the dust accumulation detection auxiliary module is set on the mainboard area to be evaluated to achieve more accurate detection of dust accumulation data. Then, a mainboard dust accumulation estimation value is generated according to the mainboard dust accumulation detection data, and whether the mainboard area to be evaluated is in an abnormal dust accumulation state is determined according to the mainboard dust accumulation estimation value. If it is determined to be yes, a dust accumulation risk warning is generated, thereby starting with the detection of cable abnormalities, and sequentially arranging the risks of temperature abnormalities from the outside to the inside of the inverter, thereby achieving refined monitoring and high-precision safety warnings during the operation of the inverter in the photovoltaic power station, and improving safety performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is a flowchart of a method for early warning processing of real-time operation data of a photovoltaic power station in one embodiment;

[0070] Figure 2 The structure block diagram of a real-time operation data early warning processing system of a photovoltaic power station in one embodiment. DETAILED DESCRIPTION

[0071] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0072] In one embodiment, a terminal is provided, which is used to: obtain temperature detection data of each connecting cable group in a first operation monitoring area on an inverter in a photovoltaic power station, screen out connecting cable groups with abnormal cable temperatures according to each temperature detection data, and record them as abnormal cable groups; obtain operation temperature detection data of a mainboard area to be evaluated corresponding to the abnormal cable group in a second operation monitoring area on the inverter, and judge whether the mainboard area to be evaluated is in an abnormal mainboard temperature state according to the operation temperature detection data; if it is judged as no, control a dust accumulation detection auxiliary module to perform dust accumulation detection on the mainboard area to be evaluated, and obtain mainboard dust accumulation detection data, wherein the dust accumulation detection auxiliary module is pre-set in the mainboard area to be evaluated; generate a mainboard dust accumulation estimated value according to the mainboard dust accumulation detection data, judge whether the mainboard area to be evaluated is in an abnormal dust accumulation state according to the mainboard dust accumulation estimated value, and if it is judged as yes, generate a dust accumulation risk warning.

[0073] The terminal may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices.

[0074] In one embodiment, Figure 1As shown, a method for early warning processing of real-time operation data of a photovoltaic power station is provided, the method comprising:

[0075] Step S100: acquiring temperature detection data of each connection cable group in the first operation monitoring area of ​​the inverter in the photovoltaic power station, screening out connection cable groups with abnormal cable temperatures according to the temperature detection data, and recording them as abnormal cable groups;

[0076] Step S200: obtaining operating temperature detection data of the mainboard area to be evaluated corresponding to the abnormal cable group in the second operating monitoring area on the inverter, and determining whether the mainboard area to be evaluated is in an abnormal mainboard temperature state according to the operating temperature detection data;

[0077] Step S300: If the judgment is no, then control the dust accumulation detection auxiliary module to perform dust accumulation detection on the to-be-evaluated mainboard area, and obtain mainboard dust accumulation detection data, wherein the dust accumulation detection auxiliary module is pre-set in the to-be-evaluated mainboard area;

[0078] Step S400: generating a mainboard dust accumulation estimation value according to the mainboard dust accumulation detection data, judging whether the mainboard area to be evaluated is in an abnormal dust accumulation state according to the mainboard dust accumulation estimation value, and generating a dust accumulation risk warning if the judgment is yes.

[0079] In this embodiment, in order to perform status monitoring and safety warning on the inverter of the photovoltaic power station and to perform refined warning, the monitoring area of ​​the inverter is demarcated, specifically, divided into a first operation monitoring area and a second operation monitoring area.

[0080] In the present application, the inverter includes an inverter body, a lead box and a plurality of connecting cable groups, wherein the lead box is arranged at the bottom of the inverter body. A lead portion is arranged at the bottom of the inverter body, and the lead portion is accommodated in the lead box. The lead box has the function of protecting the lead portion.

[0081] One end of each connecting cable group extends into the lead box and is connected to the lead part, and the other end of each connecting cable group is connected to other electrical components, such as an AC distribution cabinet. That is, the cable connection group is a cable used to output the AC power of the inverter to the AC distribution cabinet.

[0082] The first operation monitoring area is arranged inside the lead box. The second operation monitoring area is the area where the inverter main control board is located in the inverter body.

[0083] There are multiple connecting cable groups, and the connecting cable groups are arranged in sequence in the lead box. Each connecting cable group includes multiple connecting wires. A temperature detection sensor is correspondingly arranged in one connecting cable group, and the temperature detection sensor is arranged between each of the connecting wires, that is, each of the connecting wires surrounds the temperature detection sensor, so that the temperature monitoring sensor can be accurately detected in the middle of the connecting cable group, which overcomes the problem of inaccurate monitoring caused by the sensor being arranged on the side in the prior art.

[0084] When monitoring the operation data, first obtain the temperature detection data of each connection cable group in the first operation monitoring area on the inverter in the photovoltaic power station, and then screen out the connection cable group with abnormal cable temperature according to each of the temperature detection data, and record it as an abnormal cable group, where the abnormal cable group is a cable with abnormal temperature. The temperature abnormality of the cable may be due to the wear of the cable itself, or it may be due to the failure or possible failure of the components on the main control board in the inverter directly connected to the cable. In the case of wear or aging of the cable itself, the risk is relatively low, and it can be manually checked by the maintenance personnel of the photovoltaic power station. Therefore, it is mainly necessary to conduct further analysis of the operation data to determine whether there is a possibility that the components of the main control board in the inverter are about to fail. Therefore, the operating temperature detection data of the mainboard area to be evaluated corresponding to the abnormal cable group in the second operating monitoring area on the inverter is then obtained, wherein the mainboard area to be evaluated is a pre-marked main control board area directly connected to the abnormal cable group, and there are many electronic components in this area. If such electronic components have a tendency to fail, they may cause their own temperature to rise and the temperature of the connected cables to rise. Therefore, according to the operating temperature detection data, it is judged whether the mainboard area to be evaluated is in an abnormal mainboard temperature state. If it is judged to be no, it means that the components on the main control board at this time are not currently faulty and have no tendency to fail temporarily. Therefore, it is necessary to further judge other risks, specifically to perform dust accumulation monitoring. Considering that as the inverter increases in use time, problems such as aging and dust accumulation may occur in the inverter, and dust accumulation is likely to cause risks such as abnormal internal temperature and low heat dissipation efficiency, therefore, after excluding the main control board itself, it is necessary to eliminate the risk of dust accumulation, so as to further eliminate all risks that may cause temperature abnormalities. Specifically, the preset dust accumulation detection auxiliary module is controlled to perform dust accumulation detection on the mainboard area to be evaluated, and mainboard dust accumulation detection data is obtained, wherein the dust accumulation detection auxiliary module is set on the mainboard area to be evaluated to achieve more accurate detection of dust accumulation data. Then, a mainboard dust accumulation estimation value is generated according to the mainboard dust accumulation detection data, and whether the mainboard area to be evaluated is in an abnormal dust accumulation state is determined according to the mainboard dust accumulation estimation value. If it is determined to be yes, a dust accumulation risk warning is generated, thereby starting with the detection of cable abnormalities, and sequentially arranging the risks of temperature abnormalities from the outside to the inside of the inverter, thereby achieving refined monitoring and high-precision safety warnings during the operation of the inverter in the photovoltaic power station, and improving safety performance.

[0085] Further, in step S100, after acquiring each temperature detection data of each connection cable group, if each temperature detection data of each connection cable group does not indicate abnormal cable temperature, no warning indication is made, and continuous monitoring is performed.

[0086] In step S200, it is determined whether the motherboard area to be evaluated is in an abnormal motherboard temperature state according to the operating temperature detection data, and then the following steps are further included:

[0087] If it is determined that the mainboard area to be evaluated is in an abnormal mainboard temperature state, a mainboard abnormality warning indication is generated, and the photovoltaic power station maintenance personnel are guided to repair the mainboard of the inverter according to the mainboard abnormality warning indication.

[0088] In step S400, judging whether the to-be-evaluated mainboard area is in an abnormal dust accumulation state according to the mainboard dust accumulation estimated value, further comprising:

[0089] If it is determined that the mainboard area to be evaluated is not in an abnormal dust accumulation state, it means that there is no risk of dust accumulation at this time, and only the cable temperature is abnormal, so a cable troubleshooting instruction is generated, and the photovoltaic power station maintenance personnel are guided to perform manual troubleshooting according to the cable troubleshooting instruction.

[0090] In another embodiment, step S100: acquiring temperature detection data of each connection cable group in the first operation monitoring area on the inverter in the photovoltaic power station, screening out the connection cable group with abnormal cable temperature according to each temperature detection data, and recording it as an abnormal cable group, including:

[0091] Step S110: acquiring temperature detection data of each connection cable group in the first operation monitoring area of ​​the inverter in the photovoltaic power station and corresponding inverter operation power data, and acquiring a normal operating temperature range pre-stored in each connection cable group, wherein one connection cable group corresponds to one normal operating temperature range, and the normal operating temperature range corresponds to the normal operating power of the inverter;

[0092] Step S120: extracting the real-time operating power matching the normal operating power from the inverter operating power data, and recording the time period corresponding to the real-time operating power as the data collection time period;

[0093] Step S130: extracting the temperature data to be analyzed from the temperature detection data according to the data collection time period, and generating a real-time operating temperature range according to the temperature data to be analyzed;

[0094] Step S140: calculating an abnormal temperature range in which the real-time operating temperature range exceeds the normal operating temperature range, and generating an operating temperature deviation ratio according to the abnormal temperature range;

[0095] Step S150: determining whether the operating temperature deviation ratio is less than or equal to a preset standard temperature deviation ratio;

[0096] Step S160: If the judgment is no, then the corresponding connection cable group is judged to have abnormal cable temperature, and the corresponding connection cable group is set as an abnormal cable group;

[0097] Step S170: If the judgment is yes, then obtaining a pre-marked cable combination pre-marked in each of the connection cable groups, and obtaining the to-be-analyzed temperature data corresponding to the connection cable group in the pre-marked cable combination;

[0098] Step S180: Filter out the connected cable groups with abnormal cable temperatures according to the to-be-analyzed temperature data corresponding to the connected cable groups in the pre-marked cable combination, and record them as abnormal cable groups.

[0099] In this embodiment, in order to accurately screen the cable group with abnormal cable temperature, first obtain the temperature detection data of each cable group in the first operation monitoring area of ​​the inverter in the photovoltaic power station and the corresponding inverter operation power data. The inverter operation power data is the power data of the inverter detected in the same time period as the temperature detection data. Then obtain the normal operating temperature range pre-stored in each cable group. Each cable group has different cable working temperatures because it is connected to the main control board in different areas of the inverter. When the cable is normal and the main control board in the corresponding area is normal, the temperature at this time is recorded, stored and set as the normal operating temperature range. That is, one cable group corresponds to a normal operating temperature range. Of course, the temperature of the inverter is different at different powers, so the normal operating temperature range corresponds to the normal operating power of the inverter. Then, by screening out the actual temperature and normal temperature under the same power state for accurate comparison, the real-time operating power matching the normal operating power is extracted from the inverter operation power data. When judging whether the data in the inverter operation power data matches the normal operating power, it is set to match when the power is exactly the same. When the power approximation is greater than 95% and above, it is also determined to be a match. In order to extract the corresponding actual temperature, the time period corresponding to the real-time operating power is recorded as the data collection time period, and then the temperature data to be analyzed is extracted from the temperature detection data according to the data collection time period, and the real-time operating temperature range is generated according to the temperature data to be analyzed. The maximum value in the temperature data to be analyzed is set as the maximum value of the real-time operating temperature range, and the minimum value in the temperature data to be analyzed is set as the minimum value of the real-time operating temperature range.

[0100] Next, in order to determine the deviation value between the actual operating temperature and the normal temperature, it is necessary to first calculate the abnormal temperature range in which the real-time operating temperature range exceeds the normal operating temperature range, and generate the operating temperature deviation ratio according to the abnormal temperature range.

[0101] For example, the normal operating temperature range is 20°C to 40°C, and the real-time operating temperature range is 22°C to 25°C. The real-time operating temperature range is completely within the normal operating temperature range, so there is no abnormal temperature range where the real-time operating temperature range exceeds the normal operating temperature range. At this time, the operating temperature deviation ratio is set to 0.

[0102] If the real-time operating temperature range is 30°C to 42°C, then 30°C to 40°C in the real-time operating temperature range belongs to the normal operating temperature range, and 40°C to 42°C in the real-time operating temperature range does not belong to the normal operating temperature range, that is, 40°C to 42°C is the abnormal temperature range. Next, the abnormal temperature length a of the abnormal temperature range and the normal temperature length A of the normal operating temperature range are calculated, a is 2°C, and A is 20°C. Calculate the ratio of the abnormal temperature length a to the normal temperature length A, and it is the temperature deviation ratio, which is 10% in this embodiment. Because the longer the equipment is used, the greater the loss, and the fluctuation of the working parameters is inevitable, so the standard temperature deviation ratio is preset. By judging whether the operating temperature deviation ratio is less than or equal to the preset standard temperature deviation ratio, it is judged whether the cable temperature is abnormal. When it is judged that the operating temperature deviation ratio is greater than the preset standard temperature deviation ratio, it means that the current real-time operating temperature is greater than the normal temperature fluctuation, so it is judged that the corresponding connection cable group is abnormal in cable temperature, so the corresponding connection cable group is set as an abnormal cable group. If it is determined that the operating temperature deviation ratio is less than or equal to the preset standard temperature deviation ratio, it is not directly determined that there is no problem with the corresponding cable, but it is further necessary to determine whether there is a potential abnormality. Specifically, by obtaining a pre-marked cable combination pre-marked in each of the connecting cable groups, and obtaining the temperature data to be analyzed corresponding to the connecting cable group in the pre-marked cable combination, and then filtering out the connecting cable groups with abnormal cable temperatures according to the temperature data to be analyzed corresponding to the connecting cable groups in the pre-marked cable combination, and recording them as abnormal cable groups.

[0103] In another embodiment, the pre-marked cable combination includes a first marked cable group and a second marked cable group, the temperature data to be analyzed corresponding to the first marked cable group is recorded as the first operating temperature data, and the temperature data to be analyzed corresponding to the second marked cable group is recorded as the second operating temperature data;

[0104] Step S180: Screening out the connected cable groups with abnormal cable temperatures according to the to-be-analyzed temperature data corresponding to the connected cable groups in the pre-marked cable combination, including:

[0105] Step S181: extracting temperature values ​​of first operating temperature data corresponding to a first marked cable group in the pre-marked cable combination according to a preset collection time point, and generating first temperature sequence data, wherein the first temperature sequence data includes a plurality of first temperature values;

[0106] Step S182: extracting the temperature value of the second operating temperature data corresponding to the second marked cable group in the pre-marked cable combination according to the preset collection time point, and generating second temperature sequence data, wherein the second temperature sequence includes a plurality of second temperature values;

[0107] Step S183: calculating the operating temperature difference between the first temperature value and the second temperature value corresponding to each acquisition time point in the first temperature series data and the second temperature series data;

[0108] Step S184: generating a temperature difference change trend according to each of the operating temperature differences;

[0109] Step S185: determining whether the temperature difference change trend is a stable trend;

[0110] Step S186: if it is determined that the temperature difference change trend is a stable trend, the corresponding first marked cable group and the second marked cable group are not set as the connection cable group with abnormal cable temperature;

[0111] Step S187: If it is determined that the temperature difference variation trend is not a stable trend, the corresponding first marked cable group and second marked cable group are set as connection cable groups with abnormal cable temperatures.

[0112] In this embodiment, the pre-marked cable combination includes a first marked cable group and a second marked cable group, and the first marked cable group and the second marked cable group are cable groups selected from each of the connection cable groups and pre-marked. For the convenience of description, the temperature data to be analyzed corresponding to the first marked cable group is recorded as the first operating temperature data, and the temperature data to be analyzed corresponding to the second marked cable group is recorded as the second operating temperature data.

[0113] In the present application, the first marked cable group and the second marked cable group are set as two adjacent connecting cable groups. During normal operation, the first marked cable group and the second marked cable group respectively have corresponding normal operating temperatures. If there is no abnormality in the cable itself and there is no abnormality in the main control board area corresponding to the cable, the temperature difference between the first marked cable group and the second marked cable group will always tend to be stable. If the temperature difference shows an upward or downward trend, there may be an abnormality in the cable or the main control board area corresponding to the cable, and further data analysis and troubleshooting are required. Based on this principle, the first operating temperature data corresponding to the first marked cable group in the pre-marked cable combination is first extracted according to a preset acquisition time point, and a first temperature sequence data is generated, wherein the first temperature sequence data includes multiple first temperature values, and then the second operating temperature data corresponding to the second marked cable group in the pre-marked cable combination is extracted according to a preset acquisition time point, and a second temperature sequence data is generated, wherein the second temperature sequence includes multiple second temperature values. Next, the operating temperature difference between the first temperature value and the second temperature value corresponding to each acquisition time point in the first temperature series data and the second temperature series data is calculated, and then the temperature difference change trend is generated according to each of the operating temperature differences, and then it is determined whether the temperature difference change trend is a stable trend. If the temperature difference change trend is determined to be a stable trend, the corresponding first marked cable group and the second marked cable group are not set as the connection cable group with abnormal cable temperature. If it is determined that the temperature difference change trend is not a stable trend, that is, it is an upward or downward trend, the corresponding first marked cable group and the second marked cable group are set as the connection cable group with abnormal cable temperature for further risk warning and investigation.

[0114] In another embodiment, each of the operating temperature differences constitutes a temperature difference sequence, and the temperature change trend includes a stable trend, an increasing trend, and a decreasing trend;

[0115] Step S184: generating a temperature difference change trend according to each of the operating temperature differences, including:

[0116] Step S1841: calculating the adjacent temperature difference between two adjacent operating temperature differences in the temperature difference sequence;

[0117] Step S1842: summing up the adjacent temperature differences and generating a total adjacent temperature difference value;

[0118] Step S1843: determining whether the total value of the adjacent temperature differences is within a preset stable trend range value, wherein the stable trend range value includes a stable trend minimum value and a stable trend maximum value, the stable trend minimum value is less than 0, and the stable trend maximum value is greater than 0;

[0119] Step S1844: If the judgment is yes, then determine that the temperature difference change trend is a stable trend;

[0120] Step S1845: when it is determined that the total value of the adjacent temperature differences is less than the minimum value of the stable trend, it is determined that the temperature difference change trend is a downward trend;

[0121] Step S1846: If it is determined that the total value of the adjacent temperature differences is greater than the maximum value of the stable trend, then the temperature difference change trend is determined to be an upward trend.

[0122] In this embodiment, in step S183, after calculating the operating temperature difference between the first temperature value and the second temperature value corresponding to each acquisition time point in the first temperature series data and the second temperature series data, a temperature difference sequence consisting of the operating temperature differences is generated.

[0123] In step S184, specifically, a temperature difference change trend is generated according to the temperature difference value sequence.

[0124] There are three situations of the temperature difference change trend, the first situation is a stable trend, the second situation and the third situation are an upward trend and a downward trend. Both the upward trend and the downward trend are within the range of a non-steady trend.

[0125] When generating the temperature difference change trend, or when determining whether the temperature difference change trend is a steady trend, an upward trend, or a downward trend, the following steps are adopted:

[0126] First, the adjacent temperature difference between two adjacent operating temperature differences in the temperature difference sequence is calculated; then, each adjacent temperature difference is summed to generate an adjacent temperature difference total value;

[0127] Determine whether the total value of the adjacent temperature difference belongs to a preset stable trend range value, wherein the stable trend range value includes a stable trend minimum value and a stable trend maximum value, the stable trend minimum value is less than 0, and the stable trend maximum value is greater than 0;

[0128] If the judgment is yes, then the temperature difference change trend is judged to be a stable trend.

[0129] If the judgment is no, it is determined that the temperature difference change trend is not a steady trend.

[0130] Further, when it is determined that the total value of adjacent temperature differences is less than the minimum value of the stable trend, it is determined that the temperature difference change trend is a downward trend.

[0131] If it is determined that the total value of the adjacent temperature differences is greater than the maximum value of the stable trend, it is determined that the temperature difference change trend is an upward trend.

[0132] Therefore, in the present application, not only a single cable group is checked for temperature anomalies, but also potential temperature anomalies and risks are eliminated by pre-calibrating the first marked cable group and the second marked cable group, and analyzing the temperature data based on the calibrated cable groups, thereby screening out potential cable groups that may have temperature anomalies, thereby improving the accuracy and precision of subsequent risk inspections and further improving safety.

[0133] In another embodiment, step S200: obtaining operating temperature detection data of the to-be-evaluated motherboard region corresponding to the abnormal cable group, and judging whether the to-be-evaluated motherboard region is in an abnormal motherboard temperature state according to the operating temperature detection data, comprises:

[0134] Step S210: obtaining a pre-stored cable motherboard area association table, and determining the pre-stored monitoring motherboard area corresponding to the abnormal cable group according to the cable motherboard area association table, and recording it as the motherboard area to be evaluated, wherein the cable motherboard area association table is provided with a plurality of pre-stored monitoring motherboard areas, and each of the pre-stored monitoring motherboard areas corresponds to a connection cable group;

[0135] Step S220: acquiring operating temperature detection data collected by a first temperature detection sensor in the motherboard region to be evaluated, and acquiring an adjacent motherboard region corresponding to the motherboard region to be evaluated, wherein the operating temperature detection data includes a plurality of actual operating temperatures;

[0136] Step S230: Acquire the adjacent area temperature data collected by the second temperature detection sensor in the adjacent mainboard area, wherein the adjacent area temperature data includes a plurality of adjacent area temperatures;

[0137] Step S240: generating a first average temperature and a first temperature standard deviation according to each actual operating temperature in the operating temperature detection data;

[0138] Step S250: generating a second average temperature and a second temperature standard deviation according to the temperature of each adjacent area in the adjacent area temperature data;

[0139] Step S260: generating a mainboard area temperature evaluation value according to the first average temperature, the first temperature standard deviation, the second average temperature and the first temperature standard deviation;

[0140] Specifically, the motherboard area temperature evaluation value is generated based on the following formula:

[0141]

[0142] Among them, Stas is the temperature evaluation value of the mainboard area, μ1 is the temperature difference proportional coefficient, Tod is the temperature difference threshold, Tai is the i-th actual operating temperature in the operating temperature detection data, Tbi is the i-th adjacent area temperature in the adjacent area temperature data, μ2 is the temperature offset proportional coefficient, Tau is the first average temperature, Tbu is the second average temperature, σ1 is the first temperature standard deviation, and σ2 is the second temperature standard deviation.

[0143] Furthermore, it should be noted that max(a, b) is an operation for finding the larger value of a or b.

[0144] In this step, the temperature difference threshold, the temperature difference proportional coefficient, and the temperature offset proportional coefficient are all set in advance by a person skilled in the art, and can also be understood as weights. The temperature difference proportional coefficient and the temperature offset proportional coefficient are added to 1. For example, the temperature difference proportional coefficient is set to 0.63, and the temperature offset proportional coefficient is set to 0.37.

[0145] Step S270: determining whether the temperature evaluation value of the mainboard area is greater than a preset total temperature evaluation threshold;

[0146] Step S280: If the answer is yes, determine whether the motherboard area to be evaluated is in an abnormal motherboard temperature state;

[0147] Step S290: If the judgment is no, it is determined that the motherboard area to be evaluated is not in an abnormal motherboard temperature state.

[0148] In this embodiment, when judging whether the motherboard area to be evaluated is in an abnormal motherboard temperature state, not only the temperature of the motherboard area to be evaluated is collected, but also the temperature of the adjacent motherboard area corresponding to the motherboard area to be evaluated is combined for comprehensive evaluation. Specifically, firstly, a pre-stored cable motherboard area association table is obtained, and the pre-stored monitoring motherboard area corresponding to the abnormal cable group is determined according to the cable motherboard area association table, and recorded as the motherboard area to be evaluated, and then the adjacent motherboard area corresponding to the motherboard area to be evaluated is obtained, and then the corresponding temperature data is obtained respectively, specifically, the operating temperature detection data collected by the first temperature detection sensor in the motherboard area to be evaluated is obtained, and the adjacent area temperature data collected by the second temperature detection sensor in the adjacent motherboard area is obtained. In order to comprehensively evaluate whether the temperature is abnormal, the mean and standard deviation are first calculated, specifically, the first average temperature and the first temperature standard deviation are generated according to each actual operating temperature in the operating temperature detection data, and the second average temperature and the second temperature standard deviation are generated according to each adjacent area temperature in the adjacent area temperature data. Finally, the motherboard area temperature evaluation value is comprehensively generated according to the first average temperature, the first temperature standard deviation, the second average temperature and the first temperature standard deviation. The motherboard area temperature evaluation value is used to measure the abnormal degree of the temperature of the motherboard area to be evaluated. The larger the motherboard area temperature evaluation value, the higher the abnormal degree of the temperature of the motherboard area to be evaluated. In order to further evaluate, a total temperature evaluation threshold is set. When it is judged that the motherboard area temperature evaluation value is greater than the preset total temperature evaluation threshold, it is judged whether the motherboard area to be evaluated is in an abnormal motherboard temperature state. When it is judged that the motherboard area temperature evaluation value is less than or equal to the total temperature evaluation threshold, it is judged whether the motherboard area temperature evaluation value is greater than the preset total temperature evaluation threshold.

[0149] In another embodiment, the dust accumulation detection auxiliary module includes a plurality of light auxiliary modules and brightness detection sensors, each of the light auxiliary modules is radially arranged in the mainboard area to be evaluated, and a brightness detection sensor is provided on the side of each light auxiliary module;

[0150] The mainboard dust accumulation detection data includes a plurality of single-point brightness detection data;

[0151] In step S300, the dust accumulation detection auxiliary module is controlled to perform dust accumulation detection on the to-be-evaluated mainboard area and obtain mainboard dust accumulation detection data, including:

[0152] Step S310: Control each lighting auxiliary module to light up in turn, and respectively obtain the single-point brightness detection data detected by the brightness detection sensor next to each lighting auxiliary module, wherein one lighting auxiliary module corresponds to one single-point brightness detection data, and the single-point brightness detection data are summarized to be the mainboard dust accumulation detection data.

[0153] In this embodiment, each of the lighting auxiliary modules generally adopts an LED lamp. Each of the lighting auxiliary modules is radially arranged in the area of ​​the mainboard to be evaluated. Specifically, each of the lighting auxiliary modules is respectively arranged on the four sides and the center of the area of ​​the mainboard to be evaluated. That is, the preferred solution is that the number of the lighting auxiliary modules is 5. Regarding the lighting auxiliary module, it can be pre-integrated on the PCB board in the area of ​​the mainboard to be evaluated. This method requires adding hardware to the main control board of the inverter, which increases the cost. It is also possible to use the indicator light inherent in the original PCB in the area of ​​the mainboard to be evaluated as the auxiliary detection. This method has a lower production cost.

[0154] Regarding the setting position of the brightness detection sensor, for the light auxiliary module and the brightness detection sensor at the center of the motherboard area to be evaluated, when the main control chip is set at the center of the motherboard area to be evaluated, the light auxiliary module and the brightness detection sensor are set beside the main control chip at the center of the motherboard area to be evaluated. Of course, when setting the brightness detection sensor, it is necessary to ensure that the brightness detection sensor is not blocked by other electronic components to ensure that the brightness data detected by the brightness detection sensor is accurate.

[0155] Furthermore, by first controlling each lighting auxiliary module to light up in sequence, and respectively acquiring the single-point brightness detection data detected by the brightness detection sensor, it is possible to achieve multi-angle acquisition of the brightness data in the mainboard area to be evaluated.

[0156] In addition, the brightness detection sensor on the mainboard area to be evaluated is also coated with glue, that is, before the main control board is installed in the inverter and the inverter is sealed, the outer surface of the brightness detection sensor is coated with glue to ensure better adhesion of dust to achieve the subsequent impact on brightness. In order to ensure that the brightness detection sensor is not blocked, the detection end of the brightness detection sensor is generally set higher than other electronic components. Therefore, when dust falls, there is a situation where it falls from the brightness detection sensor. At this time, there is no dust accumulation, which leads to inaccurate brightness data collected for calculating dust accumulation. Coating with glue can achieve adhesion of dust, thereby more accurately reflecting dust ingress and dust accumulation.

[0157] In another embodiment, step S400: generating a mainboard dust accumulation estimation value according to the mainboard dust accumulation detection data, and judging whether the mainboard area to be evaluated is in an abnormal dust accumulation state according to the mainboard dust accumulation estimation value, comprises:

[0158] Step S410: performing brightness collection according to the single-point brightness detection data in the mainboard dust accumulation detection data according to the preset data collection points and obtaining multiple single-point brightness values, wherein one single-point brightness detection data corresponds to M single-point brightness values;

[0159] Step S420: obtaining the number of electronic components around each of the light auxiliary modules, and generating a dust accumulation influence coefficient according to the number of electronic components, wherein one light auxiliary module corresponds to one dust accumulation influence coefficient, and the sum of the dust accumulation influence coefficients is 1;

[0160] Step S430: Generate an estimated value of dust accumulation on the mainboard based on the following formula:

[0161]

[0162] Wherein, Ctotal is the estimated value of dust accumulation on the mainboard, N is the number of single-point brightness detection data, wj is the dust accumulation influence coefficient corresponding to the j-th lighting auxiliary module, M is the number of single-point brightness values, Ijk is the k-th single-point brightness value in the j-th single-point brightness detection data, and Is is the reference brightness value;

[0163] Step S440: determining whether the mainboard dust accumulation estimated value is greater than or equal to the mainboard dust accumulation threshold;

[0164] Step S450: If the answer is yes, then it is determined that the mainboard area to be evaluated is in an abnormal dust accumulation state;

[0165] Step S460: If the judgment is no, it is determined that the mainboard area to be evaluated is not in an abnormal dust accumulation state.

[0166] In this embodiment, first, according to the single-point brightness detection data in the mainboard dust detection data, brightness is collected according to the preset data collection points and multiple single-point brightness values ​​are obtained. Then, in order to characterize the dust value of the entire mainboard area to be evaluated through the dust accumulation situation of each detection area, the number of electronic components around each lighting auxiliary module is obtained, and the dust accumulation influence coefficient is generated according to the number of electronic components, wherein one lighting auxiliary module corresponds to one dust accumulation influence coefficient, and the sum of each dust accumulation influence coefficient is 1. When obtaining the number of electronic components, statistics and calculations can be made in advance, or the density of the number of electronic components can also be calculated. Therefore, by associating the number of components on the mainboard area to be evaluated with the dust accumulation situation, the generated mainboard dust accumulation estimate can better reflect the dust accumulation situation on the mainboard area to be evaluated, thereby achieving a more accurate judgment on whether there is a risk of dust accumulation, and realizing refined judgment and data collection. Further, it is also judged whether the mainboard dust accumulation estimate is greater than or equal to the mainboard dust accumulation threshold; if it is judged to be yes, it is judged that the mainboard area to be evaluated is in an abnormal dust accumulation state; if it is judged to be no, it is judged that the mainboard area to be evaluated is not in an abnormal dust accumulation state.

[0167] In another embodiment, if Figure 2 As shown, a real-time operation data early warning processing system for a photovoltaic power station is also provided, the system comprising:

[0168] The abnormal cable screening module is used to obtain the temperature detection data of each connection cable group in the first operation monitoring area of ​​the inverter in the photovoltaic power station, and screen out the connection cable group with abnormal cable temperature according to each temperature detection data, and record it as an abnormal cable group;

[0169] A mainboard state judgment module is used to obtain the operating temperature detection data of the mainboard area to be evaluated corresponding to the abnormal cable group in the second operating monitoring area on the inverter, and judge whether the mainboard area to be evaluated is in an abnormal mainboard temperature state according to the operating temperature detection data;

[0170] A dust accumulation data detection module, which is used to control the dust accumulation detection auxiliary module to perform dust accumulation detection on the mainboard area to be evaluated and obtain mainboard dust accumulation detection data if the judgment is no, wherein the dust accumulation detection auxiliary module is pre-set in the mainboard area to be evaluated;

[0171] The risk warning generation module is used to generate a mainboard dust accumulation estimation value according to the mainboard dust accumulation detection data, and judge whether the mainboard area to be evaluated is in an abnormal dust accumulation state according to the mainboard dust accumulation estimation value. If it is judged to be so, a dust accumulation risk warning is generated.

[0172] In another embodiment, the abnormal cable screening module is further used for: after obtaining the temperature detection data of each connection cable group, if the temperature detection data of each connection cable group does not indicate abnormal cable temperature, no warning indication is given and continuous monitoring is performed.

[0173] In another embodiment, the mainboard status judgment module is also used to: if it is judged that the mainboard area to be evaluated is in an abnormal mainboard temperature state, generate a mainboard abnormality warning indication, and guide the photovoltaic power station maintenance personnel to repair the mainboard of the inverter according to the mainboard abnormality warning indication.

[0174] In another embodiment, the risk warning generation module is also used for: if it is determined that the mainboard area to be evaluated is not in an abnormal dust accumulation state, it means that there is no risk of dust accumulation at this time, and only the cable temperature is abnormal, so a cable inspection instruction is generated, and the photovoltaic power station maintenance personnel are guided to perform manual inspection according to the cable inspection instruction.

[0175] In another embodiment, the abnormal cable screening module is also used to: obtain the temperature detection data of each connection cable group in the first operation monitoring area of ​​the inverter in the photovoltaic power station and the corresponding inverter operation power data, and obtain the normal operation temperature range pre-stored in each connection cable group, wherein one connection cable group corresponds to a normal operation temperature range, and the normal operation temperature range corresponds to the normal operation power of the inverter; extract the real-time operation power matching the normal operation power from the inverter operation power data, and record the time period corresponding to the real-time operation power as the data collection time period; extract the temperature data to be analyzed from the temperature detection data according to the data collection time period, and generate a real-time operation power matching the normal operation power according to the temperature data to be analyzed. A real-time operating temperature range is formed; an abnormal temperature range in which the real-time operating temperature range exceeds the normal operating temperature range is calculated, and an operating temperature deviation ratio is generated according to the abnormal temperature range; it is determined whether the operating temperature deviation ratio is less than or equal to a preset standard temperature deviation ratio; if it is determined to be no, it is determined that the corresponding connection cable group has a cable temperature abnormality, and the corresponding connection cable group is set as an abnormal cable group; if it is determined to be yes, a pre-marked cable combination pre-marked in each of the connection cable groups is obtained, and the temperature data to be analyzed corresponding to the connection cable group in the pre-marked cable combination is obtained; according to the temperature data to be analyzed corresponding to the connection cable group in the pre-marked cable combination, a connection cable group with abnormal cable temperature is screened out, and recorded as an abnormal cable group.

[0176] In another embodiment, the pre-marked cable combination includes a first marked cable group and a second marked cable group, the temperature data to be analyzed corresponding to the first marked cable group is recorded as the first operating temperature data, and the temperature data to be analyzed corresponding to the second marked cable group is recorded as the second operating temperature data; the abnormal cable screening module is also used to: extract the temperature value of the first operating temperature data corresponding to the first marked cable group in the pre-marked cable combination according to the preset collection time point, and generate first temperature sequence data, wherein the first temperature sequence data includes multiple first temperature values; extract the temperature value of the second operating temperature data corresponding to the second marked cable group in the pre-marked cable combination according to the preset collection time point The invention relates to a method for extracting a value and generating a second temperature series data, wherein the second temperature series includes a plurality of second temperature values; calculating an operating temperature difference between a first temperature value and a second temperature value corresponding to each acquisition time point in the first temperature series data and the second temperature series data; generating a temperature difference change trend according to each of the operating temperature differences; judging whether the temperature difference change trend is a stable trend; if the temperature difference change trend is judged to be a stable trend, the corresponding first marked cable group and the second marked cable group are not set as the connection cable group with abnormal cable temperature; if the temperature difference change trend is judged not to be a stable trend, the corresponding first marked cable group and the second marked cable group are set as the connection cable group with abnormal cable temperature.

[0177] In another embodiment, each of the operating temperature differences constitutes a temperature difference sequence, and the temperature change trend includes a steady trend, an upward trend and a downward trend; the abnormal cable screening module is also used to: calculate the adjacent temperature difference between two adjacent operating temperature differences in the temperature difference sequence; sum each of the adjacent temperature differences and generate a total adjacent temperature difference value; determine whether the total adjacent temperature difference value belongs to a preset steady trend range value, wherein the steady trend range value includes a steady trend minimum value and a steady trend maximum value, the steady trend minimum value is less than 0, and the steady trend maximum value is greater than 0; if the judgment is yes, then the temperature difference change trend is judged to be a steady trend; when it is judged that the total adjacent temperature difference value is less than the steady trend minimum value, then the temperature difference change trend is judged to be a downward trend; if it is judged that the total adjacent temperature difference value is greater than the steady trend maximum value, then the temperature difference change trend is judged to be an upward trend.

[0178] In another embodiment, the motherboard status judgment module is also used to: obtain a pre-stored cable motherboard area association table, and determine the pre-stored monitoring motherboard area corresponding to the abnormal cable group according to the cable motherboard area association table, and record it as the motherboard area to be evaluated, wherein the cable motherboard area association table is provided with multiple pre-stored monitoring motherboard areas, and each of the pre-stored monitoring motherboard areas corresponds to a connecting cable group; obtain the operating temperature detection data collected by the first temperature detection sensor in the motherboard area to be evaluated, and obtain the adjacent motherboard area corresponding to the motherboard area to be evaluated, wherein the operating temperature detection data includes multiple actual operating temperatures; obtain the operating temperature detection data collected by the second temperature detection sensor in the adjacent motherboard area. Adjacent area temperature data, wherein the adjacent area temperature data includes multiple adjacent area temperatures; generating a first average temperature and a first temperature standard deviation according to each actual operating temperature in the operating temperature detection data; generating a second average temperature and a second temperature standard deviation according to each adjacent area temperature in the adjacent area temperature data; generating a mainboard area temperature evaluation value according to the first average temperature, the first temperature standard deviation, the second average temperature and the first temperature standard deviation; judging whether the mainboard area temperature evaluation value is greater than a preset temperature evaluation total threshold; if the judgment is yes, judging whether the mainboard area to be evaluated is in an abnormal mainboard temperature state; if the judgment is no, judging that the mainboard area to be evaluated is not in an abnormal mainboard temperature state.

[0179] In another embodiment, the mainboard state determination module is further used to generate a mainboard area temperature evaluation value based on the following formula:

[0180]

[0181] Among them, Stas is the temperature evaluation value of the mainboard area, μ1 is the temperature difference proportional coefficient, Tod is the temperature difference threshold, Tai is the i-th actual operating temperature in the operating temperature detection data, Tbi is the i-th adjacent area temperature in the adjacent area temperature data, μ2 is the temperature offset proportional coefficient, Tau is the first average temperature, Tbu is the second average temperature, σ1 is the first temperature standard deviation, and σ2 is the second temperature standard deviation.

[0182] In another embodiment, the dust accumulation detection auxiliary module includes multiple lighting auxiliary modules and brightness detection sensors, and each of the lighting auxiliary modules is radially arranged in the mainboard area to be evaluated, and a brightness detection sensor is provided on the side of each lighting auxiliary module; the mainboard dust accumulation detection data includes multiple single-point brightness detection data; the dust accumulation data detection module is also used to: control each lighting auxiliary module to light up in turn, and respectively obtain the single-point brightness detection data detected by the brightness detection sensor on the side of each lighting auxiliary module, wherein one lighting of the lighting auxiliary module corresponds to one single-point brightness detection data, and the single-point brightness detection data are summarized as the mainboard dust accumulation detection data.

[0183] In another embodiment, the risk warning generation module is further used to: perform brightness collection according to the single-point brightness detection data in the mainboard dust accumulation detection data according to the preset data collection points and obtain multiple single-point brightness values, wherein one single-point brightness detection data corresponds to M single-point brightness values; obtain the number of electronic components around each of the lighting auxiliary modules, and generate a dust accumulation influence coefficient according to the number of electronic components, wherein one lighting auxiliary module corresponds to one dust accumulation influence coefficient, and the sum of the dust accumulation influence coefficients is 1;

[0184] Generate an estimated value for motherboard dust accumulation based on the following formula:

[0185]

[0186] Wherein, Ctotal is the estimated value of dust accumulation on the mainboard, N is the number of single-point brightness detection data, wj is the dust accumulation influence coefficient corresponding to the j-th lighting auxiliary module, M is the number of single-point brightness values, Ijk is the k-th single-point brightness value in the j-th single-point brightness detection data, and Is is the reference brightness value;

[0187] Determine whether the mainboard dust accumulation estimated value is greater than or equal to the mainboard dust accumulation threshold; if so, determine that the mainboard area to be evaluated is in an abnormal dust accumulation state; if not, determine that the mainboard area to be evaluated is not in an abnormal dust accumulation state.

[0188] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps described in the above-mentioned method for processing real-time operation data early warning of a photovoltaic power station are implemented.

[0189] In one embodiment, a computer-readable storage medium is further provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for processing real-time operation data early warning of a photovoltaic power station are implemented.

[0190] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0191] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0192] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for early warning processing of real-time operation data of a photovoltaic power station, characterized in that: The method comprises: Acquire temperature detection data of each connection cable group in a first operation monitoring area on an inverter in a photovoltaic power station, filter out connection cable groups with abnormal cable temperatures according to the temperature detection data, and record them as abnormal cable groups; Acquire the operating temperature detection data of the mainboard area to be evaluated corresponding to the abnormal cable group in the second operating monitoring area on the inverter, and determine whether the mainboard area to be evaluated is in an abnormal mainboard temperature state according to the operating temperature detection data; If the judgment is no, then controlling the dust accumulation detection auxiliary module to perform dust accumulation detection on the to-be-evaluated mainboard area and obtaining mainboard dust accumulation detection data, wherein the dust accumulation detection auxiliary module is pre-set in the to-be-evaluated mainboard area; A mainboard dust accumulation estimated value is generated according to the mainboard dust accumulation detection data, and whether the mainboard area to be evaluated is in an abnormal dust accumulation state is determined according to the mainboard dust accumulation estimated value. If the determination is yes, a dust accumulation risk warning is generated.

2. The real-time operation data early warning processing method of a photovoltaic power station according to claim 1 is characterized in that: Acquiring temperature detection data of each connection cable group in the first operation monitoring area of ​​the inverter in the photovoltaic power station, screening out connection cable groups with abnormal cable temperatures according to each of the temperature detection data, and recording them as abnormal cable groups, including: Acquire each temperature detection data of each connection cable group in the first operation monitoring area of ​​the inverter in the photovoltaic power station and the corresponding inverter operation power data, and acquire the normal operating temperature range pre-stored in each of the connection cable groups, wherein one connection cable group corresponds to one normal operating temperature range, and the normal operating temperature range corresponds to the normal operating power of the inverter; Extracting the real-time operating power matching the normal operating power from the inverter operating power data, and recording the time period corresponding to the real-time operating power as the data collection time period; Extracting the temperature data to be analyzed from the temperature detection data according to the data collection time period, and generating a real-time operating temperature range according to the temperature data to be analyzed; Calculating an abnormal temperature range in which the real-time operating temperature range exceeds the normal operating temperature range, and generating an operating temperature deviation ratio according to the abnormal temperature range; Determining whether the operating temperature deviation ratio is less than or equal to a preset standard temperature deviation ratio; If the judgment is no, it is judged that the temperature of the corresponding connecting cable group is abnormal, and the corresponding connecting cable group is set as an abnormal cable group; If the judgment is yes, then obtaining a pre-marked cable combination pre-marked in each of the connection cable groups, and obtaining the temperature data to be analyzed corresponding to the connection cable group in the pre-marked cable combination; According to the to-be-analyzed temperature data corresponding to the connected cable groups in the pre-marked cable combination, the connected cable groups with abnormal cable temperatures are screened out and recorded as abnormal cable groups.

3. The real-time operation data early warning processing method of a photovoltaic power station according to claim 2 is characterized in that: The pre-marked cable combination includes a first marked cable group and a second marked cable group, the temperature data to be analyzed corresponding to the first marked cable group is recorded as the first operating temperature data, and the temperature data to be analyzed corresponding to the second marked cable group is recorded as the second operating temperature data; Screening out the connected cable groups with abnormal cable temperatures according to the to-be-analyzed temperature data corresponding to the connected cable groups in the pre-marked cable combination includes: Extracting temperature values ​​of first operating temperature data corresponding to a first marked cable group in the pre-marked cable combination according to a preset collection time point, and generating first temperature sequence data, wherein the first temperature sequence data includes a plurality of first temperature values; Extracting the temperature value of the second operating temperature data corresponding to the second marked cable group in the pre-marked cable combination according to the preset collection time point, and generating second temperature sequence data, wherein the second temperature sequence includes a plurality of second temperature values; Calculating an operating temperature difference between a first temperature value and a second temperature value corresponding to each acquisition time point in the first temperature series data and the second temperature series data; generating a temperature difference change trend according to each of the operating temperature differences; Determine whether the temperature difference change trend is a stable trend; If it is determined that the temperature difference change trend is a stable trend, the corresponding first marked cable group and the second marked cable group are not set as the connection cable group with abnormal cable temperature; If it is determined that the temperature difference variation trend is not a stable trend, the corresponding first marked cable group and the second marked cable group are set as connection cable groups with abnormal cable temperatures.

4. The real-time operation data early warning processing method of a photovoltaic power station according to claim 3 is characterized in that: Each of the operating temperature differences constitutes a temperature difference sequence, and the temperature change trend includes a stable trend, an upward trend and a downward trend; Generating a temperature difference change trend according to each of the operating temperature differences includes: Calculating the adjacent temperature difference between two adjacent operating temperature differences in the temperature difference sequence; Summing each of the adjacent temperature difference values ​​and generating an adjacent temperature difference total value; Determine whether the total value of the adjacent temperature difference belongs to a preset stable trend range value, wherein the stable trend range value includes a stable trend minimum value and a stable trend maximum value, the stable trend minimum value is less than 0, and the stable trend maximum value is greater than 0; If the judgment is yes, then the temperature difference change trend is judged to be a stable trend; When it is determined that the total value of the adjacent temperature differences is less than the minimum value of the stable trend, it is determined that the temperature difference change trend is a downward trend; If it is determined that the total value of the adjacent temperature differences is greater than the maximum value of the stable trend, then the temperature difference change trend is determined to be an upward trend.

5. The real-time operation data early warning processing method of a photovoltaic power station according to claim 1, characterized in that: Acquiring operating temperature detection data of the to-be-evaluated mainboard region corresponding to the abnormal cable group, and judging whether the to-be-evaluated mainboard region is in an abnormal mainboard temperature state according to the operating temperature detection data, including: Obtain a pre-stored cable motherboard area association table, and determine the pre-stored monitoring motherboard area corresponding to the abnormal cable group according to the cable motherboard area association table, and record it as the motherboard area to be evaluated, wherein the cable motherboard area association table is provided with a plurality of pre-stored monitoring motherboard areas, and each of the pre-stored monitoring motherboard areas corresponds to a connection cable group; Acquire operating temperature detection data collected by a first temperature detection sensor in the motherboard region to be evaluated, and acquire an adjacent motherboard region corresponding to the motherboard region to be evaluated, wherein the operating temperature detection data includes a plurality of actual operating temperatures; Acquire the adjacent area temperature data collected by the second temperature detection sensor in the adjacent mainboard area, wherein the adjacent area temperature data includes a plurality of adjacent area temperatures; generating a first average temperature and a first temperature standard deviation according to each actual operating temperature in the operating temperature detection data; Generate a second average temperature and a second temperature standard deviation according to the temperature of each adjacent area in the adjacent area temperature data; Generate a mainboard area temperature evaluation value according to the first average temperature, the first temperature standard deviation, the second average temperature, and the first temperature standard deviation; Determine whether the temperature evaluation value of the mainboard area is greater than a preset temperature evaluation total threshold; If the judgment is yes, then judging whether the motherboard area to be evaluated is in an abnormal motherboard temperature state; If the judgment is no, then it is determined that the to-be-evaluated mainboard area is not in an abnormal mainboard temperature state.

6. The real-time operation data early warning processing method of a photovoltaic power station according to claim 5, characterized in that: The dust accumulation detection auxiliary module includes a plurality of light auxiliary modules and brightness detection sensors, each of which is radially arranged in the mainboard area to be evaluated, and a brightness detection sensor is arranged beside each of the light auxiliary modules; The mainboard dust accumulation detection data includes a plurality of single-point brightness detection data; Controlling the dust accumulation detection auxiliary module to perform dust accumulation detection on the mainboard area to be evaluated and obtaining mainboard dust accumulation detection data, including: Control each lighting auxiliary module to light up in turn, and obtain the single-point brightness detection data detected by the brightness detection sensor next to each lighting auxiliary module respectively, wherein one lighting auxiliary module corresponds to one single-point brightness detection data, and the single-point brightness detection data are summarized to be the mainboard dust accumulation detection data.

7. The real-time operation data early warning processing method of a photovoltaic power station according to claim 6, characterized in that: Generating a mainboard dust accumulation estimation value according to the mainboard dust accumulation detection data, and judging whether the mainboard area to be evaluated is in an abnormal dust accumulation state according to the mainboard dust accumulation estimation value, including: According to the single-point brightness detection data in the mainboard dust accumulation detection data, brightness collection is performed at a preset data collection point and multiple single-point brightness values ​​are obtained, wherein one single-point brightness detection data corresponds to M single-point brightness values; Acquire the number of electronic components around each of the light auxiliary modules, and generate a dust accumulation influence coefficient according to the number of electronic components, wherein one light auxiliary module corresponds to one dust accumulation influence coefficient, and the sum of the dust accumulation influence coefficients is 1; Generate an estimated value for motherboard dust accumulation based on the following formula: Wherein, Ctotal is the estimated value of dust accumulation on the mainboard, N is the number of single-point brightness detection data, wj is the dust accumulation influence coefficient corresponding to the j-th lighting auxiliary module, M is the number of single-point brightness values, Ijk is the k-th single-point brightness value in the j-th single-point brightness detection data, and Is is the reference brightness value; Determining whether the mainboard dust accumulation estimated value is greater than or equal to a mainboard dust accumulation threshold value; If the answer is yes, then the to-be-evaluated mainboard area is judged to be in an abnormal dust accumulation state; If the judgment is no, it is determined that the mainboard area to be evaluated is not in an abnormal dust accumulation state.

8. A real-time operation data early warning processing system for a photovoltaic power station, characterized in that: The system comprises: The abnormal cable screening module is used to obtain the temperature detection data of each connection cable group in the first operation monitoring area of ​​the inverter in the photovoltaic power station, and screen out the connection cable group with abnormal cable temperature according to each temperature detection data, and record it as an abnormal cable group; A mainboard state judgment module is used to obtain the operating temperature detection data of the mainboard area to be evaluated corresponding to the abnormal cable group in the second operating monitoring area on the inverter, and judge whether the mainboard area to be evaluated is in an abnormal mainboard temperature state according to the operating temperature detection data; A dust accumulation data detection module, which is used to control the dust accumulation detection auxiliary module to perform dust accumulation detection on the mainboard area to be evaluated and obtain mainboard dust accumulation detection data if the judgment is no, wherein the dust accumulation detection auxiliary module is pre-set in the mainboard area to be evaluated; The risk warning generation module is used to generate a mainboard dust accumulation estimation value according to the mainboard dust accumulation detection data, and judge whether the mainboard area to be evaluated is in an abnormal dust accumulation state according to the mainboard dust accumulation estimation value. If it is judged to be so, a dust accumulation risk warning is generated.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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