河北大学学报(自然科学版) ›› 2017, Vol. 37 ›› Issue (1): 92-100.DOI: 10.3969/j.issn.1000-1565.2017.01.014

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基于改进蚁群A*算法的输电线路路径搜索

苏海锋1,许道林2,李汶江2,黄昊2,郑炜3   

  • 收稿日期:2016-06-23 出版日期:2017-01-25 发布日期:2017-01-25
  • 通讯作者: 许道林(1966—),男,重庆人,国网重庆市电力公司工程师,主要从事电气自动化、输电线路规划研究. E-maill:17732663282@163.com
  • 作者简介:苏海锋(1977—),男,河北石家庄人,华北电力大学讲师,博士,主要从事电网规划及智能配电网方面的研究. E-mail:hfsups@163.com
  • 基金资助:
    中央高校基本科研业务项目(2015QN85)

Automatic search of the transmission line path based on the improved ant colony and A* algorithm

SU Haifeng1,XU Daolin2,LI Wenjiang2,HUANG Hao2,ZHENG Wei3   

  1. 1.Electrical Engineering Department, North China Electric Power University, Baoding 071003, China; 2.Infrastructure Department of State Grid, Chongqing Electric Power Company, Chongqing 400001, China; 3.Transmission Line Department, Chongqing Electric Power Design Institute, Chongqing 401120, China
  • Received:2016-06-23 Online:2017-01-25 Published:2017-01-25

摘要: 以GIS作为输电线路路径选择的地理信息采集和分析平台,综合考虑线路走廊区域地形、地貌、地物、环境等方面的影响因素,利用层次分析法得到线路走廊区域的线路综合成本量化值.结合高压输电线路路径选择特点,建立了基于改进蚁群算法的高压输电线路路径自动搜索模型,实现了输电路径的跨越式搜索和障碍的规避.模型引入路径局部成本控制启发策略及A*导向算法,提高了路径搜索效率.用C#2010和ArcGIS 10.0开发了输电线路路径自动选择程序,并采集无人机航拍的现场地理数据,验证了模型和方法的有效性.

关键词: 输电线路路径搜索, 地理信息系统, 层次分析法, 蚁群算法, A*算法

Abstract: GIS is used as a platform to collect and analyze the geographic information of the transmission line path selection,and use analytic hierarchy process to quantify and integrate complex geographic information in geographical units.In combination with the characteristics of the transmission line path selection,an improved model of ant colony algorithm search for the path is established.The model uses the heuristic search,integrate the local cost control and the A* algorithm,which makes the path search faster and more accurate.The geographic data is provided by the actual aerial,using the C#2010 and the ArgGis 10.0 to build a transmission line path automatic selection procedures,which verified the validity of the model and the method.

Key words: transmission line paths search, GIS, analytic hierarchy process, ant colony algorithm, A* algorithm

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