A Meteorological Risk Assessment Method for Power Lines Based on Gis and Multi-Sensor Integration

Abstract

ABSTRACT:Power lines, exposed in the natural environment, are vulnerable to various kinds of meteorological factors. Traditional research mainly deals with the influence of a single meteorological condition on the power line, which lacks of comprehensive effects evaluation and analysis of the multiple meteorological factors. In this paper, we use multiple meteorological monitoring data obtained by multi-sensors to implement the meteorological risk assessment and early warning of power lines. Firstly, we generate meteorological raster map from discrete meteorological monitoring data using spatial interpolation. Secondly, the expert scoring based analytic hierarchy process is used to compute the power line risk index of all kinds of meteorological conditions and establish the mathematical model of meteorological risk. By adopting this model in raster calculator of ArcGIS, we will have a raster map showing overall meteorological risks for power line. Finally, by overlaying the power line buffer layer to that raster map, we will get to know the exact risk index around a certain part of power line, which will provide significant guidance for power line risk management. In the experiment, based on five kinds of observation data gathered from meteorological stations in Guizhou Province of China, including wind, lightning, rain, ice, temperature, we carry on the meteorological risk analysis for the real power lines, and experimental results have proved the feasibility and validity of our proposed method.

Development of GIS-based Ground Flash Density and its Statistical Analysis for Lightning Performance Evaluation of Transmission Lines in Peninsular Malaysia

“…With GIS, users can better understand patterns, relationships, and the context of geographic information, leading to better communication and enhanced efficiency, management, and decision-making. It is also observed that there is a growing trend in the use of GIS within the electrical sector (ESRI, 2010;Husain et al, 2012;Kakumoto et al, 2016;Kezunovic et al, 2015;Korir & Ngigi, 2015;Leite et al, 2019;Li et al, 2014;Lin & Xu, 2016;Rahman et al, 2020;Yatim et al, 2019;Yan et al, 2016;Zheng et al, 2021).…”

Lightning Failure Risk Assessment of Overhead Transmission Lines Based on Modified Dempster–Shafer Theory

“…(1) Weather conditions: this was divided by region, and the confidence calculation results are shown in Table 2: (2) Altitude: this could be divided into four grades, and the confidence calculation results are shown in Table 3: (3) Topography: this could be divided into three grades, and the confidence calculation results are shown in Table 4: (4) Tower height: this could be divided into four grades, and the confidence calculation results are shown in Table 5: (5) Voltage grade: this could be divided into three grades, and the confidence calculation results are shown in Table 6: (6) Tower model: this could be divided into six grades, and the confidence calculation result is shown in Table 7: The total number of overhead transmission line towers in the data was 15,847, and the number of impact factors was six. The mass function value was calculated using the entropy method and gray correlation analysis, then the modified Mass function value of each influence factor was obtained using Equations ( 8)- (10), and finally, the trust degree function Bel(K i ) of 15,847 towers was calculated according to Equation (11).…”

“…In the literature [10], the analytic hierarchy process was improved, and a full level assessment system was established, which could comprehensively analyze various impact factors of lightning risk. In the literature [11], meteorological monitoring data were collected using multi-sensors, and a meteorological risk assessment model was established based on an analytic hierarchy process using expert scores.…”

“…With regard to the above literature, [8] performed a statistical analysis only, without considering the links between the data; [11] considered only the weather conditions around the lightning overhead transmission lines, without considering the effects of transmission line data, and expert experience evaluation has certain subjective factors that may adversely affect the accuracy of the results.…”