Online monitoring and operation and maintenance system for power distribution network equipment in high altitude area

Abstract

The invention relates to the technical field of power system operation and maintenance, and discloses a high-altitude area power distribution network equipment on-line monitoring and operation and maintenance system, which comprises a sensing layer for monitoring high-altitude environment parameters and the operation state of power distribution network equipment to obtain a data set; the network layer transmits the data set and transmits the data set from the sensing layer to the edge computing layer; the edge computing layer performs preprocessing and preliminary analysis on the data set to obtain a preprocessing result and an analysis result, and transmits the preprocessing result and the analysis result to the cloud platform layer; the cloud platform layer receives the preprocessing result and the analysis result, and processes the preprocessing result and the analysis result through a big data model to obtain a target result; based on the target result, the operation and maintenance execution layer executes the operation and maintenance strategy and remote operation, and the technical problems that power distribution network equipment monitoring in the high-altitude area is inaccurate, operation and maintenance response is not timely, and environmental adaptability is poor are solved.

Description

Technical Field

[0001] This invention relates to the technical field of power system operation and maintenance, and discloses an online monitoring and operation and maintenance system for power distribution network equipment in high-altitude areas. Background Technology

[0002] High-altitude areas (usually referring to areas above 1000 meters in altitude) have unique environmental characteristics such as low air pressure, strong ultraviolet radiation, large diurnal temperature range, and drastic fluctuations in air humidity. These environmental factors can have a significant negative impact on the operation of power distribution network equipment: low air pressure can lead to a decrease in the creepage performance of the equipment's external insulation and a reduction in heat dissipation efficiency; strong ultraviolet radiation can accelerate the aging of the equipment's insulation materials; and extreme temperature differences can easily cause deformation of equipment components or failure of seals.

[0003] Existing power distribution network equipment monitoring and maintenance systems are mostly designed for plains or low-altitude environments, which have the following shortcomings: they have not been specifically modified for high-altitude environmental parameters, resulting in large deviations in equipment performance evaluation; data transmission relies on a single communication method, which is difficult to adapt to the complex geographical environment of high-altitude areas. Summary of the Invention

[0004] The purpose of this invention is to solve the technical problems of inaccurate monitoring, untimely operation and maintenance response, and poor environmental adaptability of power distribution network equipment in high-altitude areas. Therefore, this invention provides an online monitoring and operation and maintenance system for power distribution network equipment in high-altitude areas. To achieve the above-mentioned technical effects, the technical solution adopted by this invention is: an online monitoring and operation and maintenance system for power distribution network equipment in high-altitude areas, comprising a sensing layer, a network layer, an edge computing layer, a cloud platform layer, and an operation and maintenance execution layer that are sequentially connected in communication, wherein: The sensing layer monitors the environmental parameters at high altitudes and the operating status of the power distribution network equipment to obtain data sets; The network layer transmits the data group from the perception layer to the edge computing layer; The edge computing layer preprocesses and performs preliminary analysis on the data set to obtain preprocessing results and analysis results, and then transmits the preprocessing results and analysis results to the cloud platform layer. The cloud platform layer receives the preprocessing results and analysis results, and processes the preprocessing results and analysis results through a big data model to obtain the target result; Based on the target result, the operation and maintenance execution layer executes operation and maintenance strategies and remote operations.

[0005] As a preferred embodiment, the cloud platform layer includes an environmental parameter correction module, which is used to correct the impact of high-altitude environments on the performance of power distribution network equipment. The environmental parameter correction module includes the following sub-modules: External insulation creepage distance correction submodule is used to correct the impact of low-pressure environment on insulation performance; The equipment heat dissipation coefficient correction submodule is used to correct the impact of high-altitude environments on the heat dissipation performance of equipment. The equipment current carrying capacity correction submodule is used to correct the impact of high-altitude environment on equipment current carrying capacity; The insulator disc count correction submodule is used to correct the impact of high-altitude environments on the insulator disc count.

[0006] As a preferred embodiment, the external insulation creepage distance correction submodule uses the following formula for correction: ; in, For the required creepage distance in high-altitude areas, H represents the standard creepage distance, m is the altitude correction factor with a value ranging from 0.3 to 0.65, and H is the actual altitude.

[0007] As a preferred embodiment, the equipment heat dissipation coefficient correction submodule uses the following formula for correction: ; in, For the thermal conductivity of gases in high-altitude areas, P represents the thermal conductivity of the gas under standard conditions, P represents the actual air pressure in high-altitude areas, P0 = 1 atm, and n is 1.1-1.5.

[0008] As a preferred embodiment, the device current carrying capacity correction submodule uses the following formula for correction: ; in, Rated current carrying capacity of power distribution equipment in high-altitude areas Rated current carrying capacity of distribution network equipment under standard conditions air density under standard conditions, Here, e represents the actual air density at high altitudes, and e is the flow form coefficient, which is 0.5 for natural convection and 0.8 for forced convection.

[0009] As a preferred embodiment, the insulator disc count correction submodule uses the following formula for correction: ; in, The total number of insulator discs required for high-altitude areas The number of insulator discs required at altitudes ≤1000 meters; m1 = 0.3~0.65, H is the actual altitude.

[0010] As a preferred embodiment, the sensing layer includes: An environmental monitoring module is used to monitor environmental parameters at high altitudes, including temperature, humidity, air pressure, and ultraviolet radiation. The equipment status monitoring module monitors the operating status of power distribution network equipment, including voltage, current, power, and temperature.

[0011] As a preferred embodiment, the network layer includes a hybrid communication module for transmitting the data group, wherein the transmission method includes one of the following: optical fiber, wireless private network, or 4G / 5G.

[0012] As a preferred embodiment, the edge computing layer includes: A data preprocessing unit is used to filter, denoise, and extract features from the data set. The on-site analysis and decision-making unit is used to run lightweight AI algorithm models to achieve real-time diagnosis and early warning of abnormal states.

[0013] Compared with existing technologies, the beneficial effects of this invention are as follows: The environmental parameter correction module accurately corrects the impact of factors such as high altitude, low air pressure, and strong ultraviolet radiation on equipment performance, improving monitoring and evaluation accuracy; the hybrid communication module supports multiple transmission methods, adapting to the complex geographical environment of high-altitude areas, ensuring data transmission without loss and with low latency; the edge computing layer enables on-site data preprocessing and real-time diagnosis, combined with in-depth cloud analysis, shortening anomaly warning and maintenance response time; based on accurate monitoring data and targeted maintenance strategies, it reduces blind inspections, lowers maintenance costs, and extends equipment lifespan. Attached Figure Description

[0014] Figure 1 This is the system architecture layer of the online monitoring and maintenance system for power distribution network equipment in high-altitude areas according to the present invention; Figure 2 This is a schematic diagram of the internal structure of the sensing layer of the present invention; Figure 3 This is a schematic diagram of the internal structure of the network layer of the present invention; Figure 4 This is a schematic diagram of the internal structure of the edge computing layer of the present invention; Figure 5 This is a schematic diagram of the internal structure of the cloud platform layer of the present invention; Figure label: 1. Sensing layer; 11. Environmental monitoring module; 12. Equipment status monitoring module; 2. Network layer; 21. Hybrid communication module; 3. Edge computing layer; 31. Data preprocessing unit; 32. In-situ analysis and decision-making unit; 4. Cloud Platform Layer; 41. Environmental Parameter Correction Module; 401. External Insulation Creepage Distance Correction Submodule; 402. Equipment Heat Dissipation Coefficient Correction Submodule; 403. Equipment Current Carrying Capacity Correction Submodule; 404. Insulator Disc Count Correction Submodule; 5. Operation and maintenance execution layer. Detailed Implementation

[0015] The present invention will now be described in further detail with reference to the embodiments and accompanying drawings. However, this should not be construed as limiting the scope of the above-described subject matter of the present invention to the following embodiments; all technologies implemented based on the content of the present invention fall within the scope of the present invention.

[0016] refer to Figures 1-5 Example 1: An online monitoring and operation and maintenance system for power distribution network equipment in high-altitude areas adopts a layered architecture, including a perception layer 1, a network layer 2, an edge computing layer 3, a cloud platform layer 4, and an operation and maintenance execution layer 5 that are connected in sequence. Each layer works together to realize equipment monitoring, data transmission, processing and analysis, and operation and maintenance execution functions.

[0017] ①Perception Layer 1 Sensing layer 1 is responsible for collecting high-altitude environmental parameters and power distribution network equipment operating status data, providing a basic data source for subsequent processing, specifically including: Environmental monitoring module 11: It adopts high-precision sensors to monitor environmental parameters such as temperature, humidity, air pressure, and ultraviolet radiation in real time. The sensors have the characteristics of resisting strong ultraviolet rays and resisting temperature differences, and are suitable for high-altitude environments. Equipment status monitoring module 12: Through monitoring units installed on power distribution network equipment, it collects operating status data such as voltage, current, power, and equipment body temperature, covering core equipment such as transformers, circuit breakers, and insulators.

[0018] ②Network Layer 2 Network layer 2 is responsible for data transmission, ensuring that the data collected by perception layer 1 is stably transmitted to edge computing layer 3. Its core is the hybrid communication module 21. It supports multiple transmission methods, including fiber optic, private wireless network, and 4G / 5G, and can be flexibly selected according to the geographical conditions and signal coverage of high-altitude areas. Fiber optic transmission is suitable for areas with relatively flat terrain and concentrated equipment, ensuring data transmission rate and stability. Private wireless network and 4G / 5G are suitable for areas with complex terrain and dispersed equipment, solving the data transmission problem in remote areas and ensuring coverage without dead zones.

[0019] ③ Edge computing layer 3 Edge computing layer 3 preprocesses and performs preliminary analysis on the collected data to reduce data transmission volume and improve response speed, including: Data preprocessing unit 31: Uses filtering and denoising algorithms to remove interference signals from the data, and uses feature extraction algorithms to filter key data and retain core information related to equipment operating status and environmental impact; On-site analysis and decision-making unit 32: Runs lightweight AI algorithm models (such as lightweight neural networks and decision tree models) to analyze preprocessed data, diagnose abnormal equipment status in real time and issue early warnings, without waiting for cloud processing, thus shortening the early warning delay.

[0020] ④ Cloud Platform Layer 4 The cloud platform layer 4 receives the preprocessing and analysis results transmitted from the edge computing layer 3, performs in-depth processing, and generates the target result. Its core components include a big data processing module and an environmental parameter correction module 41. Big data processing module: Based on big data models, it performs comprehensive analysis of received data, combines historical equipment operation data and similar equipment failure cases, to achieve equipment operation trend prediction and fault root cause location; Environmental parameter correction module 41: Addresses the impact of high-altitude environments on equipment performance through four sub-modules for specific corrections: The external insulation creepage distance correction submodule 401 uses the following formula for correction: ; in, For the required creepage distance in high-altitude areas, H represents the standard creepage distance, m is the altitude correction factor with a value ranging from 0.3 to 0.65, and H is the actual altitude.

[0021] The equipment heat dissipation coefficient correction submodule 402 uses the following formula for correction: ; in, For the thermal conductivity of gases in high-altitude areas, P represents the thermal conductivity of the gas under standard conditions, P represents the actual air pressure in high-altitude areas, P0 = 1 atm, and n is 1.1-1.5.

[0022] The equipment current carrying capacity correction submodule 403 uses the following formula for correction: ; in, Rated current carrying capacity of power distribution equipment in high-altitude areas Rated current carrying capacity of distribution network equipment under standard conditions air density under standard conditions, Here, e represents the actual air density at high altitudes, and e is the flow form coefficient, which is 0.5 for natural convection and 0.8 for forced convection.

[0023] The insulator disc count correction submodule 404 uses the following formula for correction: ; in, The total number of insulator discs required for high-altitude areas The number of insulator discs required at altitudes ≤1000 meters; m1 = 0.3~0.65, H is the actual altitude.

[0024] ⑤ Operation and Maintenance Execution Layer 5 Operations and maintenance execution layer 5 executes targeted operations and maintenance strategies and remote operations based on the target results output by cloud platform layer 4. It receives fault warning information and trend prediction results from the target results, and generates personalized operation and maintenance solutions, such as equipment inspection plans, component replacement suggestions, and parameter adjustment plans; it supports remote operation functions, and for equipment with remote control interfaces, it can directly perform operations such as parameter adjustment and fault isolation to improve operation and maintenance efficiency; it records the operation and maintenance process and results, and feeds them back to the cloud platform layer 4 to form an operation and maintenance closed loop.

[0025] When using, Data acquisition: Sensors in the perception layer 1 collect environmental parameters and equipment operating status data every 5 seconds, and transmit them to the edge computing layer 3 through the network layer 2; Data preprocessing and local diagnosis: Edge computing layer 3 filters, denoises and extracts features from the collected data. It diagnoses through a lightweight AI model. If an anomaly is found, such as transformer temperature exceeding 85°C or insulator leakage current exceeding 5mA, a local warning is immediately issued and the preprocessing results and anomaly information are transmitted to cloud platform layer 4. Deep cloud processing: After receiving data, the cloud platform layer 4 corrects the device performance parameters through the environmental parameter correction module 41, and analyzes the root cause of the anomaly by combining the big data model. For example, if the transformer temperature is too high, it may be caused by a decrease in the heat dissipation coefficient. The target result is generated, which includes the fault level, the handling solution, and whether remote operation is required. Operation and maintenance execution: The operation and maintenance execution layer 5 receives the target results. If it is a minor anomaly, it remotely adjusts the equipment parameters, such as reducing the transformer load. If it is a serious anomaly, it dispatches inspection tasks to the corresponding regional operation and maintenance personnel. After the operation and maintenance personnel arrive at the site, they troubleshoot the fault according to the handling solution provided by the platform. After the handling is completed, they report the results back to the platform, forming a closed loop.

[0026] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An online monitoring and maintenance system for power distribution network equipment in high-altitude areas, characterized in that, It includes a perception layer (1), a network layer (2), an edge computing layer (3), a cloud platform layer (4), and an operation and maintenance execution layer (5) that are connected in sequence, wherein: The sensing layer (1) monitors the environmental parameters at high altitudes and the operating status of the power distribution network equipment to obtain data sets; The network layer (2) transmits the data group from the perception layer (1) to the edge computing layer (3). The edge computing layer (3) preprocesses and performs preliminary analysis on the data group to obtain preprocessing results and analysis results, and transmits the preprocessing results and analysis results to the cloud platform layer (4). The cloud platform layer (4) receives the preprocessing results and analysis results, and processes the preprocessing results and analysis results through a big data model to obtain the target result; Based on the target result, the operation and maintenance execution layer (5) executes the operation and maintenance strategy and remote operation.

2. The online monitoring and maintenance system for power distribution network equipment in high-altitude areas according to claim 1, characterized in that, The cloud platform layer (4) includes an environmental parameter correction module (41), which is used to correct the impact of high-altitude environment on the performance of power distribution network equipment. The environmental parameter correction module (41) includes the following sub-modules: External insulation creepage distance correction submodule (401) is used to correct the impact of low-pressure environment on insulation performance; The equipment heat dissipation coefficient correction submodule (402) is used to correct the impact of high-altitude environment on the heat dissipation performance of the equipment. The equipment current carrying capacity correction submodule (403) is used to correct the impact of high-altitude environment on equipment current carrying capacity; The insulator disc count correction submodule (404) is used to correct the impact of high-altitude environment on the insulator disc count.

3. The online monitoring and maintenance system for power distribution network equipment in high-altitude areas according to claim 2, characterized in that, The external insulation creepage distance correction submodule (401) uses the following formula for correction: ； in, For the required creepage distance in high-altitude areas, H represents the standard creepage distance, m is the altitude correction factor with a value ranging from 0.3 to 0.65, and H is the actual altitude.

4. The online monitoring and maintenance system for power distribution network equipment in high-altitude areas according to claim 2, characterized in that, The device heat dissipation coefficient correction submodule (402) uses the following formula for correction: ； in, For the thermal conductivity of gases in high-altitude areas, P represents the thermal conductivity of the gas under standard conditions, P represents the actual air pressure in high-altitude areas, P0 = 1 atm, and n is 1.1-1.

5.

5. The online monitoring and maintenance system for power distribution network equipment in high-altitude areas according to claim 2, characterized in that, The device current carrying capacity correction submodule (403) uses the following formula for correction: ； in, Rated current carrying capacity of power distribution equipment in high-altitude areas Rated current carrying capacity of distribution network equipment under standard conditions air density under standard conditions, Here, e represents the actual air density at high altitudes, and e is the flow form coefficient, which is 0.5 for natural convection and 0.8 for forced convection.

6. The online monitoring and maintenance system for power distribution network equipment in high-altitude areas according to claim 2, characterized in that, The insulator disc count correction submodule (404) uses the following formula for correction: ； in, The total number of insulator discs required for high-altitude areas The number of insulator discs required at altitudes ≤1000 meters; m1 = 0.3~0.65, H is the actual altitude.

7. The online monitoring and maintenance system for power distribution network equipment in high-altitude areas according to claim 1, characterized in that, The perception layer (1) includes: The environmental monitoring module (11) is used to monitor environmental parameters at high altitudes, including temperature, humidity, air pressure and ultraviolet radiation. The equipment status monitoring module (12) monitors the operating status of the power distribution network equipment, including voltage, current, power and temperature.

8. The online monitoring and maintenance system for power distribution network equipment in high-altitude areas according to claim 1, characterized in that, The network layer (2) includes a hybrid communication module (21) for transmitting the data group, and the transmission method includes one of the following: optical fiber, wireless private network, and 4G / 5G.

9. The online monitoring and maintenance system for power distribution network equipment in high-altitude areas according to claim 1, characterized in that, The edge computing layer (3) includes: The data preprocessing unit (31) is used to filter, denoise and extract features from the data set; The on-site analysis and decision-making unit (32) is used to run a lightweight AI algorithm model to achieve real-time diagnosis and early warning of abnormal states.

Images