Photovoltaic power generation area intelligent inspection monitoring method and system based on unmanned aerial vehicle remote sensing

Abstract

This invention discloses an intelligent inspection and monitoring method and system for photovoltaic power generation areas based on UAV remote sensing, relating to the field of photovoltaic power generation inspection technology. First, the photovoltaic power generation area is divided into sub-regions according to its photovoltaic electrical topology. Then, based on the grid connection requirements, peak-shaving parameters, and frequency regulation parameters of the power grid to which the photovoltaic power generation area is connected, it is determined whether the UAV should conduct an inspection. If so, the sub-regions requiring inspection are obtained based on the current environment of the photovoltaic power generation area, information from previous power grid adjustments, and power generation information of each sub-region. Finally, based on the power generation status and impact on the power grid of each inspected sub-region, the inspection priority of each sub-region is set, ensuring that photovoltaic electrical units can be fully inspected, reducing inspection costs, and guaranteeing the effectiveness and timeliness of the inspection.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic power generation inspection technology, specifically to a method and system for intelligent inspection and monitoring of photovoltaic power generation areas based on UAV remote sensing. Background Technology

[0002] Against the backdrop of dual-carbon goals and the construction of new power systems, photovoltaic power generation has become a core support for energy structure transformation due to its advantages such as being clean, renewable, and flexible in deployment. The installed capacity of photovoltaic power generation has experienced explosive growth, and intelligent inspection by drones has become a core line of defense for the industry's development.

[0003] Traditional intelligent inspection and monitoring methods and systems for photovoltaic (PV) power generation areas first divide the PV power generation area into grids to obtain sub-areas. Then, based on the fault and maintenance information of each sub-area, they set the inspection priority for each sub-area and perform a comprehensive inspection of the PV power generation area according to the inspection priority of each sub-area. Obviously, this kind of intelligent inspection and monitoring method and system for PV power generation areas has at least the following shortcomings: 1. Traditional intelligent inspection and monitoring methods and systems for PV power generation areas divide the PV power generation area equally, ignoring the distribution of PV electrical units within the PV power generation area. When dividing the PV power generation area equally, PV modules of the same PV electrical unit may be divided into different areas, which cannot ensure that PV electrical units are in the same sub-area. In the subsequent inspection process, it cannot be guaranteed that the PV electrical units that need to be inspected are completely inspected.

[0004] 2. Traditional intelligent inspection and monitoring methods and systems for photovoltaic power generation areas conduct comprehensive inspections of the photovoltaic power generation area, but cannot accurately locate the sub-areas that need to be inspected, resulting in a waste of inspection resources. At the same time, they ignore the impact of the power grid on the photovoltaic power generation area and cannot guarantee the effectiveness of the inspection.

[0005] 3. Different photovoltaic electrical units may have different impacts on the power grid. Traditional intelligent inspection and monitoring methods and systems for photovoltaic power generation areas set inspection priorities for each sub-area based on fault and maintenance information, ignoring the impact of photovoltaic electrical units on the power grid. Therefore, they cannot guarantee that photovoltaic electrical units with a high degree of impact on the power grid can be inspected in a timely manner, and thus cannot guarantee the timeliness of inspection. Summary of the Invention

[0006] To address the aforementioned technical shortcomings, the present invention aims to provide a method and system for intelligent inspection and monitoring of photovoltaic power generation areas based on unmanned aerial vehicle (UAV) remote sensing.

[0007] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: In a first aspect, the present invention provides an intelligent inspection and monitoring method for photovoltaic power generation areas based on UAV remote sensing, including: S1, area division: acquiring the electrical topology circuit of the photovoltaic power generation area, and dividing the photovoltaic power generation area into sub-areas according to the electrical topology circuit of the power generation area.

[0008] S2. Obtain the inspection area: Obtain the power grid to which the photovoltaic power generation area is connected, and refer to it as the marked power grid. Obtain the information of the marked power grid, and based on the information of the marked power grid, obtain the sub-areas that need to be inspected.

[0009] S3. Set inspection priority: Each sub-area that needs to be inspected is called an inspection sub-area. Obtain the power generation information of each inspection sub-area and set the inspection priority of each inspection sub-area based on the power generation information of each inspection sub-area.

[0010] S4. Photovoltaic power generation inspection: Obtain the inspection priority of each inspection sub-area and inspect each inspection sub-area in descending order of inspection priority.

[0011] Secondly, the present invention provides an intelligent inspection and monitoring system for photovoltaic power generation areas based on UAV remote sensing, comprising: an area division module for acquiring the electrical topology circuit of the photovoltaic power generation area, and dividing the photovoltaic power generation area into sub-areas according to the electrical topology circuit of the power generation area.

[0012] The inspection area acquisition module is used to acquire the power grid to which the photovoltaic power generation area is connected, and refers to it as the marked power grid. It acquires the information of the marked power grid and, based on the information of the marked power grid, acquires the sub-areas that need to be inspected.

[0013] The inspection priority setting module is used to refer to each sub-area that needs to be inspected as an inspection sub-area, obtain the power generation information of each inspection sub-area, and set the inspection priority of each inspection sub-area based on the power generation information of each inspection sub-area.

[0014] The photovoltaic power generation inspection module is used to obtain the inspection priority of each inspection sub-area and to inspect each inspection sub-area in descending order of inspection priority.

[0015] The database is used to store the photovoltaic electrical topology of the photovoltaic power generation area, the distribution of inverters, feeders and combiner boxes in the photovoltaic power generation area, as well as the grid connection requirements, real-time peak-shaving parameters, frequency regulation parameters and historical adjustment information of the power grid to which the photovoltaic power generation area is connected.

[0016] The beneficial effects of this invention are as follows: 1. This invention provides an intelligent inspection and monitoring method and system for photovoltaic power generation areas based on UAV remote sensing. First, the photovoltaic power generation area is divided into sub-areas according to the photovoltaic electrical topology. Then, based on the grid connection requirements, peak-shaving parameters, and frequency regulation parameters of the power grid to which the photovoltaic power generation area is connected, it is determined whether the UAV should conduct an inspection. If so, based on the current environment of the photovoltaic power generation area, information from previous power grid adjustments, and power generation information of each sub-area, the sub-areas that need to be inspected are obtained. Finally, based on the power generation status of each inspected sub-area and its impact on the power grid, the inspection priority of each inspected sub-area is set, ensuring that the photovoltaic electrical units can be fully inspected, reducing inspection costs, and ensuring the effectiveness and timeliness of the inspection.

[0017] 2. This invention obtains the photovoltaic electrical topology of a photovoltaic power generation area from a database. Based on this photovoltaic electrical topology, inverters, feeders, and combiner boxes belonging to the same photovoltaic electrical unit are grouped into a photovoltaic electrical group. This method is used to obtain each photovoltaic electrical group. The distribution of inverters, feeders, and combiner boxes in the photovoltaic power generation area is obtained from the database. Based on the distribution of inverters, feeders, and combiner boxes in the photovoltaic power generation area, the jurisdiction of each photovoltaic electrical group is obtained. Based on the jurisdiction of each photovoltaic electrical group, the photovoltaic area is divided into several sub-areas, ensuring that the photovoltaic electrical units can be fully inspected.

[0018] 3. This invention obtains the grid to which the photovoltaic power generation area is connected, and refers to it as the marked grid. It retrieves the grid connection demand of the marked grid from the database, and simultaneously obtains the peak-shaving parameters and frequency regulation parameters of the marked grid in real time. It determines whether the drone should enter the inspection task. When the drone is performing the inspection task, it determines whether the photovoltaic power generation of each sub-region meets the grid connection demand based on the grid connection demand of the marked grid. If the photovoltaic power generation of a certain sub-region does not meet the grid connection demand, it means that the sub-region needs to be inspected. If the photovoltaic power generation of a certain sub-region meets the grid connection demand, it retrieves the current peak-shaving parameters and frequency regulation parameters of the marked grid from the database, as well as the information of the marked grid during each historical adjustment, and monitors the current power generation information of the sub-region to analyze whether the sub-region needs to be inspected. This reduces the inspection cost and ensures the effectiveness of the inspection.

[0019] 4. This invention refers to each sub-region requiring inspection as an inspection sub-region, and the historical adjustments of each marker indicating good grid stability as a stable marker historical adjustment. It obtains the current power generation information of each inspection sub-region and the power generation information of each inspection sub-region during the historical adjustments of each stable marker, analyzes the power generation loss coefficient of each inspection sub-region, and builds a simulation platform. In this simulation platform, it analyzes the influence coefficient of each inspection sub-region on the marked grid. Based on the influence coefficient of each inspection sub-region on the marked grid and the power generation loss coefficient of each inspection sub-region, it determines the inspection priority of each inspection sub-region, ensuring the timeliness of inspection. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the implementation steps of the method of the present invention.

[0022] Figure 2 This is a schematic diagram of the system structure connection of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Please see Figure 1 As shown, the present invention provides an intelligent inspection and monitoring method for photovoltaic power generation areas based on UAV remote sensing, including: S1, area division: acquiring the electrical topology circuit of the photovoltaic power generation area, and dividing the photovoltaic power generation area into sub-areas according to the electrical topology circuit of the power generation area.

[0025] In a specific embodiment, the area division process is as follows: obtain the photovoltaic electrical topology of the photovoltaic power generation area from the database, and divide the inverters, feeders and combiner boxes belonging to the same photovoltaic electrical unit into a photovoltaic electrical group according to the photovoltaic electrical topology, and obtain each photovoltaic electrical group in this way.

[0026] The distribution of inverters, feeders, and combiner boxes in the photovoltaic power generation area is obtained from the database. Based on the distribution of inverters, feeders, and combiner boxes in the photovoltaic power generation area, the jurisdiction of each photovoltaic electrical group is obtained. Based on the jurisdiction of each photovoltaic electrical group, the photovoltaic area is divided into several sub-areas.

[0027] S2. Obtain the inspection area: Obtain the power grid to which the photovoltaic power generation area is connected, and refer to it as the marked power grid. Obtain the information of the marked power grid, and based on the information of the marked power grid, obtain the sub-areas that need to be inspected.

[0028] It should be noted that the information used to mark the power grid includes peak-shaving parameters, frequency regulation parameters, grid connection requirements, etc.

[0029] The peak-shaving parameters include the maximum peak-shaving amplitude, peak-shaving depth, and ramp rate, while the frequency regulation parameters include virtual inertia control parameters, damping ratio, and active power change rate limits. It's important to note that both peak-shaving and frequency regulation parameters are obtained from the local power grid system.

[0030] It should also be noted that the grid connection requirements of the marked grid are obtained from the "Technical Regulations for Photovoltaic Power Generation Systems Access to Distribution Networks".

[0031] It is important to know that the grid connection requirements of the grid include active power control requirements, reactive power and voltage control requirements, and power quality requirements.

[0032] In one specific embodiment, the process of obtaining the inspection area is as follows: obtain the grid connection requirements of the marked power grid from the database, and at the same time obtain the peak-shaving parameters and frequency regulation parameters of the marked power grid in real time to determine whether the UAV has entered the inspection task.

[0033] When the drone performs inspection tasks, it determines whether the photovoltaic power generation in each sub-region meets the grid connection requirements based on the grid connection requirements of the marked power grid. If the photovoltaic power generation in a certain sub-region does not meet the grid connection requirements, it means that the sub-region needs to be inspected. If the photovoltaic power generation in a certain sub-region meets the grid connection requirements, it retrieves the current peak-shaving parameters and frequency regulation parameters of the marked power grid from the database, as well as the information of each historical adjustment of the marked power grid. It also monitors the current power generation information of the sub-region and analyzes whether the sub-region needs to be inspected based on the current peak-shaving parameters, frequency regulation parameters, and information of each historical adjustment of the marked power grid, as well as the current power generation information of the sub-region. This method is used to determine whether each sub-region needs to be inspected and to obtain the sub-regions that need to be inspected.

[0034] It should be noted that the power factor and total harmonic distortion (THD) of each sub-region are monitored in real time and compared with the grid connection requirements for these data. When the power factor and THD of a sub-region meet the grid connection requirements, it means that the photovoltaic power generation in that sub-region meets the grid connection requirements; otherwise, it means that the photovoltaic power generation in that sub-region does not meet the grid connection requirements.

[0035] Among them, data such as power factor and total harmonic distortion rate of current are monitored by instruments such as multifunctional power meters and portable power quality analyzers.

[0036] It should also be noted that the information used to mark each historical adjustment of the power grid includes peak-shaving parameters, frequency regulation parameters, the environment of the photovoltaic power generation area, power generation information of each sub-region, and power generation information of each connected user.

[0037] It is important to know that the power generation information of the sub-region includes power factor, total harmonic distortion of current, active power, voltage and current, etc. The power generation information of the sub-region is monitored by instruments such as portable power quality analyzers, three-phase multi-function power meters and smart gate energy meters.

[0038] The specific process for determining whether the drone has entered the inspection mission is as follows: A11. Real-time collection of power generation information of each sub-region, and determination of the grid connection return value of each sub-region based on the power generation information of each sub-region and the grid connection requirements of the marked power grid.

[0039] It should be noted that when the power generation information of a certain sub-region meets the grid connection requirements of the marked grid, the grid connection return value of that sub-region is 1; otherwise, the grid connection return value of that sub-region is 0.

[0040] A12. Simultaneously obtain the peak-shaving parameters and frequency regulation parameters of the current marked power grid, as well as the peak-shaving parameters and frequency regulation parameters of the marked power grid at the previous moment, and determine the updated return value of the marked power grid.

[0041] It should be noted that if the peak-shaving and frequency regulation parameters of the current marked power grid are different from those of the marked power grid at the previous moment, the update return value of the marked power grid is 1; otherwise, the update return value of the marked power grid is 0.

[0042] A13. When there is a sub-region with a grid connection return value of 0 or the updated return value of the marked power grid is 1, the drone enters the inspection task. When the grid connection return value of each sub-region is 1 and the updated return value of the marked power grid is 0, the drone does not enter the inspection task.

[0043] The above-mentioned process for analyzing whether the sub-region needs to be inspected is as follows: obtain the current environment of the photovoltaic power generation area, and obtain the peak-shaving parameters, frequency regulation parameters, environment of the photovoltaic power generation area and power generation information of the sub-region from the database for each historical adjustment of the marked power grid. Based on the peak-shaving parameters, frequency regulation parameters and environment of the photovoltaic power generation area for each historical adjustment of the marked power grid, obtain the historical adjustments of the marked power grid.

[0044] It should be noted that the environment of the photovoltaic power generation area includes the temperature, humidity, and light intensity of the area. The environment of the photovoltaic power generation area is monitored by instruments such as fiber optic temperature sensors, humidity sensors, and irradiance meters.

[0045] It should also be noted that each historical adjustment that uses the same peak-shaving and frequency regulation parameters as the current marked grid, and where the environment of the photovoltaic power generation area is the same as that of the current photovoltaic power generation area, is referred to as the historical adjustment of each marked grid.

[0046] Each user connected to the marked grid is referred to as a marked user. The power supply information of each marked user during the historical adjustment of each mark is obtained from the database. Based on the power supply information of each marked user during the historical adjustment of each mark and the power generation information of the sub-region, the power generation level limit of the sub-region is determined.

[0047] It should be noted that the user's power supply information includes the number of power outages, voltage qualification rate, and frequency qualification rate.

[0048] Obtain the current power generation information of the sub-region, determine the current power generation level of the sub-region, and compare it with the power generation level limit of the sub-region. If the current power generation level of the sub-region is less than the power generation level limit of the sub-region, it means that the sub-region needs to be inspected; otherwise, it means that the sub-region does not need to be inspected.

[0049] It should be noted that the power generation information of this sub-region is normalized and the difference between it and the standard power generation information is calculated. This difference is then matched with a preset difference-power generation level table to obtain the power generation level of this sub-region.

[0050] Among them, the standard power generation information is set by staff based on the grid connection requirements, peak-shaving parameters and frequency regulation parameters of the marked power grid.

[0051] It is important to know that the difference-generation level table is used to store the range of differences between generation information and standard generation information under different generation levels, and it is set by the staff.

[0052] The specific process for determining the power generation level limit of the sub-region mentioned above is as follows: In a certain historical adjustment of the marker, based on the power supply information of each marked user at the time of the historical adjustment, the power supply return value of each marked user is analyzed. When there is a marked user with a power supply return value of 0, it indicates that the stability of the marked grid is poor at the time of the historical adjustment. When the power supply return value of each marked user is 1, it indicates that the stability of the marked grid is good at the time of the historical adjustment. The stability of the marked grid at each historical adjustment is judged by this method.

[0053] It should be noted that when a user's power supply information meets all power supply requirements, the user's power supply return value is 1; otherwise, the user's power supply return value is 1. These power supply requirements are set by staff and include parameters such as the maximum number of power outages, minimum voltage compliance rate, and minimum frequency compliance rate.

[0054] Each historical adjustment of the marker indicating poor grid stability is called a secondary marker historical adjustment. Based on the power generation information of the sub-region at the time of each secondary marker historical adjustment, the power generation level of the sub-region at the time of each secondary marker historical adjustment is calculated, and the highest power generation level is taken as the power generation level limit of the sub-region.

[0055] S3. Set inspection priority: Each sub-area that needs to be inspected is called an inspection sub-area. Obtain the power generation information of each inspection sub-area and set the inspection priority of each inspection sub-area based on the power generation information of each inspection sub-area.

[0056] In a specific embodiment, the process of setting the inspection priority is as follows: A21, each sub-region that needs to be inspected is called an inspection sub-region, each historical adjustment of the marker indicating good grid stability is called a stable historical adjustment, and the power generation information of each inspection sub-region at the current time and the power generation information of each inspection sub-region during the historical adjustment of each stable marker are obtained, and the power generation loss coefficient of each inspection sub-region is analyzed.

[0057] A22. Build a simulation platform and analyze the impact coefficients of each inspection sub-region on the marked power grid within the simulation platform.

[0058] It should be noted that the simulation platform is built using simulation software, and the selection of the simulation software is determined by the designers.

[0059] A23. Determine the inspection priority of each inspection sub-region based on the impact coefficient of each inspection sub-region on the marked power grid and the power generation loss coefficient of each inspection sub-region.

[0060] It should be noted that, in a certain inspection sub-region, the power generation loss coefficient of the inspection sub-region and the influence coefficient of the inspection sub-region on the marked power grid are normalized and multiplied together. The resulting value is used as the inspection priority of the sub-region. The inspection priority of each sub-region is determined by this method.

[0061] The specific process for analyzing the power generation loss coefficient of each inspection sub-region described above is as follows: In a certain inspection sub-region, based on the current power generation information of the inspection sub-region, the current power generation feature vector of the inspection sub-region is obtained and called the marked power generation feature vector of the inspection sub-region. At the same time, based on the power generation information of the inspection sub-region at the time of historical adjustment of each stable marker, the power generation feature vector of the inspection sub-region at the time of historical adjustment of each stable marker is obtained. Based on the power generation feature vector of the inspection sub-region at the time of historical adjustment of each stable marker, the average power generation feature vector of the inspection sub-region is calculated. The difference between the average power generation feature vector of the inspection sub-region and the marked power generation feature vector is used as the power generation loss coefficient of the inspection sub-region. The power generation loss coefficient of each inspection sub-region is analyzed by this method.

[0062] It should be noted that the power generation features are obtained through TCN, which is an existing technology. The specific process is as follows: power generation information is standardized and normalized, causal convolutional layers, dilated convolutional layers, 1×1 pointwise convolutional layers and residual blocks are built into the TCN, and the TCN is trained. After training, the processed power generation information is input into the TCN, and the power generation feature vector is output.

[0063] The above-mentioned analysis of the influence coefficient of each inspection sub-region on the marked power grid is carried out in the following specific process: In the simulation platform, the average power generation characteristic vector of each inspection sub-region is obtained. In a certain inspection sub-region, the average power generation characteristic vector of the inspection sub-region is subtracted from the unit vector to obtain the simulated power generation characteristic vector of the inspection sub-region. The simulated power generation characteristic vector of each inspection sub-region is obtained by this method.

[0064] It should be noted that the dimension of the unit vector is the same as the dimension of the average power generation characteristic vector.

[0065] In this simulation platform, the power generation of each inspection sub-region is simulated based on the average power generation characteristic vector and the simulated power generation characteristic vector of each inspection sub-region. The power generation of each inspection sub-region under its average power generation characteristic vector and the power generation of each inspection sub-region under its simulated power generation characteristic vector are obtained. The difference between the power generation of each inspection sub-region under its average power generation characteristic vector and the power generation under its simulated power generation characteristic vector is used as the influence coefficient of each inspection sub-region on the marked power grid.

[0066] It should be noted that power generation is monitored through online sensors.

[0067] S4. Photovoltaic power generation inspection: Obtain the inspection priority of each inspection sub-area and inspect each inspection sub-area in descending order of inspection priority.

[0068] Please see Figure 2 As shown, the present invention provides an intelligent inspection and monitoring system for photovoltaic power generation areas based on UAV remote sensing, including: an area division module for acquiring the electrical topology circuit of the photovoltaic power generation area, and dividing the photovoltaic power generation area into sub-areas according to the electrical topology circuit of the power generation area.

[0069] The inspection area acquisition module is used to acquire the power grid to which the photovoltaic power generation area is connected, and refers to it as the marked power grid. It acquires the information of the marked power grid and, based on the information of the marked power grid, acquires the sub-areas that need to be inspected.

[0070] The inspection priority setting module is used to refer to each sub-area that needs to be inspected as an inspection sub-area, obtain the power generation information of each inspection sub-area, and set the inspection priority of each inspection sub-area based on the power generation information of each inspection sub-area.

[0071] The photovoltaic power generation inspection module is used to obtain the inspection priority of each inspection sub-area and to inspect each inspection sub-area in descending order of inspection priority.

[0072] The database is used to store the photovoltaic electrical topology of the photovoltaic power generation area, the distribution of inverters, feeders and combiner boxes in the photovoltaic power generation area, as well as the grid connection requirements, real-time peak-shaving parameters, frequency regulation parameters and historical adjustment information of the power grid to which the photovoltaic power generation area is connected.

[0073] This invention first divides the photovoltaic power generation area into sub-regions based on the photovoltaic electrical topology. Then, based on the grid connection requirements, peak-shaving parameters, and frequency regulation parameters of the power grid to which the photovoltaic power generation area is connected, it determines whether the drone should conduct inspections. If so, it obtains the sub-regions that need to be inspected based on the current environment of the photovoltaic power generation area, information from previous power grid adjustments, and power generation information of each sub-region. Finally, based on the power generation status of each inspected sub-region and its impact on the power grid, it sets the inspection priority for each inspected sub-region, ensuring that the photovoltaic electrical units can be fully inspected, reducing inspection costs, and ensuring the effectiveness and timeliness of the inspections.

[0074] The examples described in this invention are not limited to the specific embodiments listed above. The examples are merely illustrative to facilitate understanding of the invention and do not constitute a limitation on the scope of protection of this invention. Any modifications, equivalent substitutions, etc., made within the spirit and principles of this invention should be included within the scope of protection.

[0075] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.

Claims

1. A method for intelligent inspection and monitoring of photovoltaic power generation area based on unmanned aerial vehicle remote sensing, characterized in that, Includes the following steps: S1. Region Division: Obtain the electrical topology of the photovoltaic power generation area and divide the photovoltaic power generation area into sub-regions based on the electrical topology of the power generation area; S2. Obtain the inspection area: Obtain the power grid to which the photovoltaic power generation area is connected, and refer to it as the marked power grid. Obtain the information of the marked power grid, and based on the information of the marked power grid, obtain the sub-areas that need to be inspected. S3. Set inspection priority: Each sub-area that needs to be inspected is called an inspection sub-area. Obtain the power generation information of each inspection sub-area and set the inspection priority of each inspection sub-area based on the power generation information of each inspection sub-area. S4. Photovoltaic power generation inspection: Obtain the inspection priority of each inspection sub-area and inspect each inspection sub-area in descending order of inspection priority. 2.The unmanned aerial vehicle remote sensing based photovoltaic power generation area intelligent patrol inspection and monitoring method according to claim 1, characterized in that, The specific process for dividing the region is as follows: The photovoltaic electrical topology of the photovoltaic power generation area is obtained from the database. Based on the photovoltaic electrical topology, inverters, feeders and combiner boxes belonging to the same photovoltaic electrical unit are divided into a photovoltaic electrical group. Each photovoltaic electrical group is obtained in this way. The distribution of inverters, feeders, and combiner boxes in the photovoltaic power generation area is obtained from the database. Based on the distribution of inverters, feeders, and combiner boxes in the photovoltaic power generation area, the jurisdiction of each photovoltaic electrical group is obtained. Based on the jurisdiction of each photovoltaic electrical group, the photovoltaic area is divided into several sub-areas. 3.The unmanned aerial vehicle remote sensing based photovoltaic power generation area intelligent patrol inspection and monitoring method according to claim 1, characterized in that, The specific process for obtaining the inspection area is as follows: The system retrieves the grid connection requirements of the marked power grid from the database, and simultaneously acquires the peak-shaving and frequency regulation parameters of the marked power grid in real time to determine whether the drone should enter the inspection mission. When the drone performs inspection tasks, it determines whether the photovoltaic power generation in each sub-region meets the grid connection requirements based on the grid connection requirements of the marked power grid. If the photovoltaic power generation in a certain sub-region does not meet the grid connection requirements, it means that the sub-region needs to be inspected. If the photovoltaic power generation in a certain sub-region meets the grid connection requirements, it retrieves the current peak-shaving parameters and frequency regulation parameters of the marked power grid from the database, as well as the information of each historical adjustment of the marked power grid. It also monitors the current power generation information of the sub-region and analyzes whether the sub-region needs to be inspected based on the current peak-shaving parameters, frequency regulation parameters, and information of each historical adjustment of the marked power grid, as well as the current power generation information of the sub-region. This method is used to determine whether each sub-region needs to be inspected and to obtain the sub-regions that need to be inspected.

4. The intelligent inspection and monitoring method for photovoltaic power generation areas based on UAV remote sensing according to claim 3, characterized in that, The specific process for determining whether a drone has entered an inspection mission is as follows: A11. Collect power generation information of each sub-region in real time, and determine the grid connection return value of each sub-region based on the power generation information of each sub-region and the grid connection demand of the marked power grid; A12. Simultaneously obtain the peak-shaving parameters and frequency regulation parameters of the current marked power grid, as well as the peak-shaving parameters and frequency regulation parameters of the marked power grid at the previous moment, and determine the updated return value of the marked power grid. A13. When there is a sub-region with a grid connection return value of 0 or the updated return value of the marked power grid is 1, the drone enters the inspection task. When the grid connection return value of each sub-region is 1 and the updated return value of the marked power grid is 0, the drone does not enter the inspection task. 5.The unmanned aerial vehicle remote sensing based photovoltaic power generation area intelligent patrol inspection and monitoring method according to claim 3, characterized in that, The specific process for analyzing whether this sub-region needs to be inspected is as follows: The system obtains the current environment of the photovoltaic power generation area and retrieves the peak-shaving parameters, frequency regulation parameters, environment of the photovoltaic power generation area, and power generation information of the sub-area from the database for each historical adjustment of the marked power grid. Based on the peak-shaving parameters, frequency regulation parameters, and environment of the photovoltaic power generation area for each historical adjustment of the marked power grid, the system obtains each historical adjustment of the marked power grid. Each user connected to the marked grid is called a marked user. The power supply information of each marked user during the historical adjustment of each mark is obtained from the database. Based on the power supply information of each marked user during the historical adjustment of each mark and the power generation information of the sub-region, the power generation level limit of the sub-region is determined. Obtain the current power generation information of the sub-region, determine the current power generation level of the sub-region, and compare it with the power generation level limit of the sub-region. If the current power generation level of the sub-region is less than the power generation level limit of the sub-region, it means that the sub-region needs to be inspected; otherwise, it means that the sub-region does not need to be inspected. 6.The unmanned aerial vehicle remote sensing based photovoltaic power generation area intelligent patrol inspection and monitoring method according to claim 5, characterized in that, The specific process for determining the power generation level limit for this sub-region is as follows: In a certain historical adjustment of the marker, based on the power supply information of each marked user at the time of the historical adjustment, the power supply return value of each marked user is analyzed. When there is a marked user with a power supply return value of 0, it means that the stability of the marked grid is poor at the time of the historical adjustment. When the power supply return value of each marked user is 1, it means that the stability of the marked grid is good at the time of the historical adjustment. The stability of the marked grid at each historical adjustment is judged by this method. Each historical adjustment of the marker indicating poor grid stability is called a secondary marker historical adjustment. Based on the power generation information of the sub-region at the time of each secondary marker historical adjustment, the power generation level of the sub-region at the time of each secondary marker historical adjustment is calculated, and the highest power generation level is taken as the power generation level limit of the sub-region. 7.The unmanned aerial vehicle remote sensing based photovoltaic power generation area intelligent patrol inspection and monitoring method according to claim 6, characterized in that, The specific process for setting inspection priorities is as follows: A21. Each sub-region that needs to be inspected is called an inspection sub-region. Each historical adjustment of the marker indicating good grid stability is called a stable marker historical adjustment. The power generation information of each inspection sub-region at present and the power generation information of each inspection sub-region during the historical adjustment of each stable marker are obtained. The power generation loss coefficient of each inspection sub-region is analyzed. A22. Build a simulation platform and analyze the impact coefficients of each inspection sub-region on the marked power grid within the simulation platform. A23. Determine the inspection priority of each inspection sub-region based on the impact coefficient of each inspection sub-region on the marked power grid and the power generation loss coefficient of each inspection sub-region. 8.The unmanned aerial vehicle remote sensing based photovoltaic power generation area intelligent patrol inspection and monitoring method according to claim 7, characterized in that, The specific process for analyzing the power generation loss coefficient of each inspection sub-region is as follows: In a specific inspection sub-region, based on the current power generation information of that sub-region, the power generation feature vector of that sub-region is obtained and referred to as the marked power generation feature vector of that sub-region. Simultaneously, based on the power generation information of that sub-region at the time of historical adjustment of each stable marker, the power generation feature vector of that sub-region at the time of historical adjustment of each stable marker is obtained. Based on the power generation feature vector of that sub-region at the time of historical adjustment of each stable marker, the average power generation feature vector of that sub-region is calculated. The difference between the average power generation feature vector of that sub-region and the marked power generation feature vector is used as the power generation loss coefficient of that sub-region. This method is used to analyze the power generation loss coefficient of each inspection sub-region.

9. The intelligent inspection and monitoring method for photovoltaic power generation areas based on UAV remote sensing according to claim 8, characterized in that, The specific process for analyzing the impact coefficients of each inspection sub-region on the marked power grid is as follows: In this simulation platform, the average power generation characteristic vector of each inspection sub-region is obtained. In a certain inspection sub-region, the average power generation characteristic vector of the inspection sub-region is subtracted from the unit vector to obtain the simulated power generation characteristic vector of the inspection sub-region. The simulated power generation characteristic vector of each inspection sub-region is obtained in this way. In this simulation platform, the power generation of each inspection sub-region is simulated based on the average power generation characteristic vector and the simulated power generation characteristic vector of each inspection sub-region. The power generation of each inspection sub-region under its average power generation characteristic vector and the power generation of each inspection sub-region under its simulated power generation characteristic vector are obtained. The difference between the power generation of each inspection sub-region under its average power generation characteristic vector and the power generation under its simulated power generation characteristic vector is used as the influence coefficient of each inspection sub-region on the marked power grid.

10. An inspection and monitoring system utilizing the intelligent inspection and monitoring method for photovoltaic power generation areas based on UAV remote sensing as described in any one of claims 1-9, characterized in that, include: The region division module is used to obtain the electrical topology circuit of the photovoltaic power generation region and divide the photovoltaic power generation region into sub-regions based on the electrical topology circuit of the power generation region; The inspection area acquisition module is used to acquire the power grid to which the photovoltaic power generation area is connected, and refers to it as the marked power grid. It acquires the information of the marked power grid and, based on the information of the marked power grid, acquires the sub-areas that need to be inspected. The inspection priority setting module is used to refer to each sub-area that needs to be inspected as an inspection sub-area, obtain the power generation information of each inspection sub-area, and set the inspection priority of each inspection sub-area based on the power generation information of each inspection sub-area. The photovoltaic power generation inspection module is used to obtain the inspection priority of each inspection sub-area and to inspect each inspection sub-area in descending order of inspection priority. The database is used to store the photovoltaic electrical topology of the photovoltaic power generation area, the distribution of inverters, feeders and combiner boxes in the photovoltaic power generation area, as well as the grid connection requirements, real-time peak-shaving parameters, frequency regulation parameters and historical adjustment information of the power grid to which the photovoltaic power generation area is connected.

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