Automatic optimization model of transmission line based on GIS and genetic algorithm

IF 2.3 Q2 COMPUTER SCIENCE, THEORY & METHODS
Array Pub Date : 2023-03-01 DOI:10.1016/j.array.2022.100266
Yuancun Qin , Zhaozheng Li , Jieyu Ding , Fei Zhao , Ming Meng
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引用次数: 0

Abstract

At present, the planning of transmission lines mainly relies on human decision-making and lacks intelligence. This paper combines the advantages of GIS in processing spatial data with the advantages of genetic algorithm to explore the optimization method of transmission line planning. The combination of GIS and genetic algorithm can minimize the interference of human factors and quickly solve the path planning problem of transmission lines. According to the theoretical model of genetic algorithm, this study constructs the transmission line optimization model based on genetic algorithm, and realizes the Add-ins plug-in development of the transmission line planning model based on genetic algorithm with the help of C # language. Taking 500 kV overhead transmission line about 150 km from Jiantang Substation (starting point) in Shangri-La County to Tai’ an Substation (ending point) in Lijiang as an example, two groups of experiments are designed under the conditions of considering traffic single factor and comprehensive multi-factor respectively. It is obtained that the path optimization effect of genetic algorithm is the best under the condition of comprehensive multi-factor, which proves the rationality and superiority of the model constructed in this study.

基于GIS和遗传算法的输电线路自动优化模型
目前,输电线路的规划主要依靠人工决策,缺乏智慧。本文将GIS在处理空间数据方面的优势与遗传算法的优势相结合,探索输电线路规划的优化方法。GIS与遗传算法相结合,可以最大限度地减少人为因素的干扰,快速解决输电线路的路径规划问题。根据遗传算法的理论模型,构建了基于遗传算法的输电线路优化模型,并借助C#语言实现了基于遗传法的输电线路规划模型的插件开发。以香格里拉县建堂变电站(起点)至丽江泰安变电站(终点)约150km的500kV架空输电线路为例,分别在考虑交通单因素和综合多因素的条件下设计了两组试验。结果表明,在综合多因素条件下,遗传算法的路径优化效果最好,证明了本文构建的模型的合理性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Array
Array Computer Science-General Computer Science
CiteScore
4.40
自引率
0.00%
发文量
93
审稿时长
45 days
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