Mountain photovoltaic power station monitoring importance grade evaluation method and related device
By constructing a three-dimensional digital model of a mountain photovoltaic power station and a multi-dimensional evaluation index system, the problem of unreasonable allocation of monitoring resources has been solved, scientific monitoring management has been achieved, and operation and maintenance efficiency and safety have been improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUANENG JIANGXI CLEAN ENERGY GENERATION CO LTD
- Filing Date
- 2026-01-05
- Publication Date
- 2026-04-21
AI Technical Summary
Current technology for monitoring mountain photovoltaic power plants lacks specificity, has unreasonable resource allocation, and lacks differentiation of importance levels, resulting in insufficient monitoring of key areas and potentially causing safety accidents.
A three-dimensional digital model of the target mountain photovoltaic power station is constructed, and the environmental and operational characteristics of equipment units and areas are extracted to form a power station feature library. A multi-dimensional monitoring importance evaluation index system is established, and the monitoring importance score is calculated through weight allocation to formulate differentiated monitoring strategies.
It enables scientific and precise allocation of monitoring resources, timely detection of potential safety hazards, reduction of accident probability, improvement of operation and maintenance efficiency, and reduction of management costs.
Smart Images
Figure CN121903451A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of photovoltaic power plant operation and maintenance technology, and relates to a method and related device for evaluating the importance level of monitoring of mountain photovoltaic power plants. Background Technology
[0002] With the increasing global demand for clean energy, solar energy, as an abundant and renewable energy source, has been widely applied and developed. Mountain photovoltaic power stations, with their advantages of not occupying arable land and making full use of mountain resources, are occupying an increasingly important position in the photovoltaic power generation field. In recent years, the construction scale of mountain photovoltaic power stations has continued to expand, and their installed capacity and power generation efficiency have also been continuously improving.
[0003] However, mountain photovoltaic power stations are located in complex environments with varied terrain and significant differences in sunlight conditions, climate, and equipment operation in different areas. This complexity presents a significant challenge to the monitoring and management of the power stations. On the one hand, traditional monitoring methods often employ uniform standards and models, making it difficult to conduct targeted monitoring based on the actual importance of each area. This leads to unreasonable resource allocation, where important areas may not receive sufficient attention, while relatively less important areas consume a large amount of monitoring resources. On the other hand, the lack of scientific methods for assessing the importance of monitoring makes it impossible to identify key areas and equipment units that have a significant impact on the safe and stable operation of the power station in advance. Once these parts malfunction or experience abnormalities, they may not be detected and dealt with in a timely manner, leading to serious safety accidents, causing huge economic losses and environmental pollution. For example, in some mountain photovoltaic power stations, the failure to accurately assess the monitoring importance of certain areas has resulted in insufficient monitoring of photovoltaic modules and supports located in landslide-prone areas on slopes during severe weather conditions such as heavy rain and strong winds. This has led to the failure to detect loosening or damage in a timely manner, ultimately causing accidents such as module detachment and support collapse, affecting the normal power generation of the power station, and even threatening the safety of the surrounding environment and personnel. Therefore, developing a scientific and reasonable method for evaluating the importance level of monitoring of mountain photovoltaic power stations is of great practical significance for improving the monitoring and management level of power stations and ensuring their safe and stable operation.
[0004] In conclusion, there is an urgent need for a monitoring importance level evaluation method applicable to mountain photovoltaic power stations to meet the market demand for scientific monitoring and management of mountain photovoltaic power stations, thereby improving operation and maintenance efficiency and reducing management costs. Summary of the Invention
[0005] The purpose of this invention is to provide a method and related apparatus for evaluating the importance level of monitoring mountain photovoltaic power stations, so as to solve the technical problems of lack of targeting, unreasonable resource allocation, and lack of importance level differentiation in the existing technology for monitoring mountain photovoltaic power stations.
[0006] To achieve the above objectives, the present invention employs the following technical solution: In a first aspect, the present invention provides a method for evaluating the importance level of monitoring a mountain photovoltaic power station, comprising the following steps: A three-dimensional digital model of the target mountain photovoltaic power station is constructed. The environmental and operational characteristics of each equipment unit and area within the power station are extracted from the three-dimensional digital model to form a power station feature library. Based on the power plant feature library, a multi-dimensional monitoring importance evaluation index system is constructed. Assign weights to each evaluation factor in the monitoring importance evaluation index system and calculate the monitoring importance score for each region.
[0007] Furthermore, the step of constructing a three-dimensional digital model of the target mountain photovoltaic power station, and extracting environmental and operational features of each equipment unit and area within the power station from the three-dimensional digital model to form a power station feature library, specifically includes: Geographic information data, 3D point cloud data, and equipment asset data of the target mountain photovoltaic power station are acquired, and a 3D digital model integrating terrain, landform, and equipment spatial location information is constructed. Based on the 3D digital model, environmental and operational characteristics of each equipment unit and area within the power station are identified and extracted to form a power station feature library. The environmental characteristics include at least altitude, slope and aspect, vegetation cover density, and access path complexity, and the operational characteristics include at least equipment type, installed capacity, historical failure rate, and power generation performance indicators.
[0008] Furthermore, the step of identifying and extracting the environmental and operational characteristics of each equipment unit and area within the power plant specifically includes: The three-dimensional digital model is analyzed using image recognition algorithms to identify the equipment locations and boundaries of photovoltaic strings, inverters, transformer substations, and combiner boxes; Based on digital elevation model analysis, the elevation, slope, and aspect of the equipment's location are calculated. By analyzing vegetation image data, the vegetation cover index within the area is calculated as the vegetation cover density. Based on the path planning algorithm, starting from the maintenance station, the shortest path distance and the difficulty coefficient of reaching each equipment point are calculated as quantitative indicators of the access path complexity.
[0009] Furthermore, the monitoring importance evaluation index system includes at least a safety risk dimension and an operational economic dimension; the evaluation factors of the safety risk dimension include the fire risk index, the probability of equipment failure triggering a chain of risks, and the personnel safety risks caused by terrain; the evaluation factors of the operational economic dimension include the theoretical power generation contribution of the equipment, the expected power generation loss caused by failure, and the comprehensive cost of maintenance and repair.
[0010] Furthermore, the step of assigning weights to each evaluation factor in the surveillance importance evaluation index system and calculating the surveillance importance score for each region specifically includes: For the smallest monitoring unit within the power plant, a weight allocation algorithm is used to assign weights to each evaluation factor in the monitoring importance evaluation index system. Based on the feature data in the power plant feature library, calculate the score of each smallest monitoring unit under each evaluation factor; The scores of each smallest monitoring unit under each evaluation factor are used to obtain the comprehensive monitoring importance score through weighted summation or fuzzy comprehensive evaluation algorithm. Based on the comprehensive monitoring importance score, different equipment and areas within the power plant are divided into multiple discrete monitoring importance levels.
[0011] Furthermore, the step of obtaining the comprehensive monitoring importance score through weighted summation or fuzzy comprehensive evaluation algorithm specifically includes: A judgment matrix is constructed, and the initial weights of each evaluation factor relative to the safety risk dimension and the operational economy dimension are determined by expert scoring. Then, the analytic hierarchy process is used to perform consistency checks and corrections to obtain the final weights. After normalizing the feature data in the power plant feature library, it is used as the input value for each evaluation factor for quantitative scoring. The quantitative score is weighted and summed with the corresponding final weight to obtain the comprehensive monitoring importance score.
[0012] Furthermore, it also includes: Based on the classification of surveillance importance levels, differentiated surveillance strategies are configured for different levels of equipment and areas to form the final surveillance layout scheme; among them, areas with higher surveillance importance levels are configured with higher density and frequency of surveillance resources, and more types of surveillance resources.
[0013] Secondly, the present invention provides a monitoring importance level evaluation system for mountain photovoltaic power stations, comprising: The feature library construction module is used to construct a three-dimensional digital model of the target mountain photovoltaic power station, and extract the environmental and operational features of each equipment unit and area within the power station from the three-dimensional digital model to form a power station feature library; The evaluation system construction module is used to construct a multi-dimensional monitoring importance evaluation index system based on the power plant feature library. The scoring calculation module is used to assign weights to each evaluation factor in the surveillance importance evaluation index system and calculate the surveillance importance score for each region.
[0014] Thirdly, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for evaluating the importance level of monitoring a mountain photovoltaic power station as described above.
[0015] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method for evaluating the importance level of monitoring a mountain photovoltaic power station as described above.
[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention discloses a method and related device for evaluating the monitoring importance level of a mountain photovoltaic power station. By constructing a three-dimensional digital model of the target mountain photovoltaic power station and extracting environmental and operational characteristics of each equipment unit and area within the station to form a power station feature library, it is possible to comprehensively and accurately grasp various key information of the power station. Based on this, a multi-dimensional monitoring importance evaluation index system is constructed, and the monitoring importance score of each area is calculated after reasonable weight allocation, providing a scientific and quantitative basis for the monitoring management of mountain photovoltaic power stations. This invention can accurately assess the monitoring importance of each area, allowing operation and maintenance personnel to rationally allocate monitoring resources based on the scoring results. More effort and resources can be invested in areas with high monitoring importance, enabling timely detection of potential safety hazards and operational anomalies, and early prevention and handling measures, effectively reducing the probability of accidents, ensuring the safe and stable operation of the mountain photovoltaic power station, and avoiding blind investment and waste of resources. This helps improve operation and maintenance efficiency, reduce the operating costs of the power station, and enhance the economic benefits of the power station. Attached Figure Description
[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a schematic diagram of the system of the present invention; Figure 3 This is a schematic diagram of the computer device structure of the present invention. Detailed Implementation
[0019] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.
[0020] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used in this invention is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.
[0021] See Figure 1 This invention discloses a method for evaluating the importance level of monitoring a mountain photovoltaic power station, comprising the following steps: S1. Construct a three-dimensional digital model of the target mountain photovoltaic power station, and extract the environmental and operational features of each equipment unit and area within the power station from the three-dimensional digital model to form a power station feature library. Geographic information data, 3D point cloud data, and equipment asset data of the target mountain photovoltaic power station are acquired, and a 3D digital model integrating terrain, landform, and equipment spatial location information is constructed. Based on the 3D digital model, environmental and operational characteristics of each equipment unit and area within the power station are identified and extracted to form a power station feature library. The environmental characteristics include at least altitude, slope and aspect, vegetation cover density, and access path complexity, and the operational characteristics include at least equipment type, installed capacity, historical failure rate, and power generation performance indicators.
[0022] Preferably, the "identification and extraction of environmental and operational characteristics of each equipment unit and area within the power plant" specifically includes: 1) The three-dimensional digital model is analyzed using an image recognition algorithm to automatically identify the equipment locations and boundaries of the photovoltaic strings, inverters, transformer substations, and combiner boxes; 2) Based on digital elevation model analysis, automatically calculate the altitude, slope, and aspect of the equipment's location; 3) By analyzing vegetation image data, the vegetation cover index in the area is calculated as the vegetation cover density; 4) Based on the path planning algorithm, starting from the maintenance station, calculate the shortest path distance and the difficulty coefficient of reaching each equipment point, which serve as a quantitative indicator of the access path complexity.
[0023] S2, Based on the power plant feature library, construct a multi-dimensional monitoring importance evaluation index system; Based on the power plant feature library, a multi-dimensional monitoring importance evaluation index system is constructed. The index system includes at least a safety risk dimension and an operational economic dimension. The evaluation factors of the safety risk dimension include the fire risk index, the probability of equipment failure triggering a chain of risks, and the personnel safety risks caused by terrain. The evaluation factors of the operational economic dimension include the theoretical power generation contribution of the equipment / area, the expected power generation loss caused by failure, and the comprehensive cost of maintenance and repair.
[0024] S3 assigns weights to each evaluation factor in the monitoring importance evaluation index system and calculates the monitoring importance score for each region.
[0025] For the smallest monitoring unit and / or geographical area within the power plant, a preset weight allocation algorithm is used to assign weights to each evaluation factor in the monitoring importance evaluation index system. Based on the feature data in the power plant feature library, the score of each smallest monitoring unit and / or geographical area under each evaluation factor is calculated, and its comprehensive monitoring importance score is obtained through weighted summation or fuzzy comprehensive evaluation algorithm. According to the level of the comprehensive monitoring importance score, different equipment and areas within the power plant are divided into multiple discrete monitoring importance levels.
[0026] Preferably, the weight allocation algorithm is the analytic hierarchy process (AHP) or the entropy weight method.
[0027] The step of obtaining the comprehensive monitoring importance score through weighted summation or fuzzy comprehensive evaluation algorithm is as follows: 1) Construct a judgment matrix, determine the initial weights of each evaluation factor relative to the safety risk dimension and the operational economic dimension through expert scoring, and then use the aforementioned analytic hierarchy process to perform consistency checks and corrections to obtain the final weights; 2) After normalizing the feature data in the power plant feature library, use it as the input value for each evaluation factor for quantitative scoring; 3) The quantitative score is weighted and summed with the corresponding final weight to obtain the comprehensive monitoring importance score.
[0028] In one feasible embodiment of the present invention, the method further includes: S4. Develop a differentiated surveillance layout plan: Based on the classified surveillance importance levels, configure differentiated surveillance strategies for equipment and areas of different levels to form the final surveillance layout plan; among them, high-density, high-frequency, and multi-type surveillance resources are configured for areas with high surveillance importance levels, while standard or low-density surveillance resources are configured for areas with low surveillance importance levels; the surveillance resources include, but are not limited to, the location and number of video surveillance points, the planning and frequency of UAV inspection routes, and the deployment density of ground sensor networks; The "high-density, high-frequency, and multi-type surveillance resources" specifically refer to: For areas with high monitoring importance, configure at least two of the following monitoring methods: a) Deploy high-definition video surveillance PTZ cameras with PTZ control function to achieve 24-hour uninterrupted monitoring and automatic patrol; b) Plan for drones to conduct automated, detailed inspections daily or weekly, with inspection routes covering all equipment in the area; c) Deploy special sensors such as temperature, smoke, and insulation partial discharge sensors for real-time status monitoring.
[0029] See Figure 2 This invention discloses a monitoring importance level evaluation system for mountain photovoltaic power stations, comprising a feature library construction module, an evaluation system construction module, and a scoring calculation module. The feature library construction module is used to construct a three-dimensional digital model of the target mountain photovoltaic power station, and extract environmental and operational features of each equipment unit and area within the power station from the three-dimensional digital model to form a power station feature library. The evaluation system construction module is used to construct a multi-dimensional monitoring importance evaluation index system based on the power station feature library. The scoring calculation module is used to assign weights to each evaluation factor in the monitoring importance evaluation index system and calculate the monitoring importance score for each area.
[0030] In one embodiment of the invention, see [link to embodiment]. Figure 3 A computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions from the computer storage medium to achieve a corresponding method flow or function. The processor described in this embodiment can be used in the operation of a method for evaluating the importance level of monitoring a mountain photovoltaic power station.
[0031] This invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the method for evaluating the importance level of monitoring a mountain photovoltaic power station in the above embodiments.
[0032] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0033] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0034] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.
[0035] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0036] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.
Claims
1. A method for evaluating the importance level of monitoring a mountain photovoltaic power station, characterized in that, Includes the following steps: A three-dimensional digital model of the target mountain photovoltaic power station is constructed. The environmental and operational characteristics of each equipment unit and area within the power station are extracted from the three-dimensional digital model to form a power station feature library. Based on the power plant feature library, a multi-dimensional monitoring importance evaluation index system is constructed. Assign weights to each evaluation factor in the monitoring importance evaluation index system and calculate the monitoring importance score for each region.
2. The method for evaluating the importance level of monitoring a mountain photovoltaic power station according to claim 1, characterized in that, The steps of constructing a three-dimensional digital model of the target mountain photovoltaic power station, and extracting environmental and operational features of each equipment unit and area within the power station from the three-dimensional digital model to form a power station feature library, specifically include: Geographic information data, 3D point cloud data, and equipment asset data of the target mountain photovoltaic power station are acquired, and a 3D digital model integrating terrain, landform, and equipment spatial location information is constructed. Based on the 3D digital model, environmental and operational characteristics of each equipment unit and area within the power station are identified and extracted to form a power station feature library. The environmental characteristics include at least altitude, slope and aspect, vegetation cover density, and access path complexity, and the operational characteristics include at least equipment type, installed capacity, historical failure rate, and power generation performance indicators.
3. The method for evaluating the importance level of monitoring a mountain photovoltaic power station according to claim 2, characterized in that, The steps for identifying and extracting the environmental and operational characteristics of each equipment unit and area within the power plant specifically include: The three-dimensional digital model is analyzed using image recognition algorithms to identify the equipment locations and boundaries of photovoltaic strings, inverters, transformer substations, and combiner boxes; Based on digital elevation model analysis, the elevation, slope, and aspect of the equipment's location are calculated. By analyzing vegetation image data, the vegetation cover index within the area is calculated as the vegetation cover density. Based on the path planning algorithm, starting from the maintenance station, the shortest path distance and the difficulty coefficient of reaching each equipment point are calculated as quantitative indicators of the access path complexity.
4. The method for evaluating the importance level of monitoring a mountain photovoltaic power station according to claim 1, characterized in that, The monitoring importance evaluation index system includes at least a safety risk dimension and an operational economic dimension; the evaluation factors of the safety risk dimension include the fire risk index, the probability of equipment failure triggering a chain of risks, and the personnel safety risks caused by terrain; the evaluation factors of the operational economic dimension include the theoretical power generation contribution of the equipment, the expected power generation loss caused by failure, and the comprehensive cost of maintenance and repair.
5. The method for evaluating the importance level of monitoring a mountain photovoltaic power station according to claim 1, characterized in that, The steps for assigning weights to each evaluation factor in the surveillance importance evaluation index system and calculating the surveillance importance score for each region specifically include: For the smallest monitoring unit within the power plant, a weight allocation algorithm is used to assign weights to each evaluation factor in the monitoring importance evaluation index system. Based on the feature data in the power plant feature library, calculate the score of each smallest monitoring unit under each evaluation factor; The scores of each smallest monitoring unit under each evaluation factor are used to obtain the comprehensive monitoring importance score through weighted summation or fuzzy comprehensive evaluation algorithm. Based on the comprehensive monitoring importance score, different equipment and areas within the power plant are divided into multiple discrete monitoring importance levels.
6. The method for evaluating the importance level of monitoring a mountain photovoltaic power station according to claim 5, characterized in that, The step of obtaining the comprehensive monitoring importance score through weighted summation or fuzzy comprehensive evaluation algorithm specifically includes: A judgment matrix is constructed, and the initial weights of each evaluation factor relative to the safety risk dimension and the operational economy dimension are determined by expert scoring. Then, the analytic hierarchy process is used to perform consistency checks and corrections to obtain the final weights. After normalizing the feature data in the power plant feature library, it is used as the input value for each evaluation factor for quantitative scoring. The quantitative score is weighted and summed with the corresponding final weight to obtain the comprehensive monitoring importance score.
7. The method for evaluating the importance level of monitoring a mountain photovoltaic power station according to claim 5, characterized in that, Also includes: Based on the classification of surveillance importance levels, differentiated surveillance strategies are configured for different levels of equipment and areas to form the final surveillance layout scheme; among them, areas with higher surveillance importance levels are configured with higher density and frequency of surveillance resources, and more types of surveillance resources.
8. A system for evaluating the importance level of monitoring a mountain photovoltaic power station, characterized in that, include: The feature library construction module is used to construct a three-dimensional digital model of the target mountain photovoltaic power station, and extract the environmental and operational features of each equipment unit and area within the power station from the three-dimensional digital model to form a power station feature library; The evaluation system construction module is used to construct a multi-dimensional monitoring importance evaluation index system based on the power plant feature library. The scoring calculation module is used to assign weights to each evaluation factor in the surveillance importance evaluation index system and calculate the surveillance importance score for each region.
9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for evaluating the importance level of monitoring of a mountain photovoltaic power station as described in any one of claims 1-7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for evaluating the importance level of monitoring of a mountain photovoltaic power station as described in any one of claims 1-7.