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Transmission Path Planning based on Improved Artificial Potential Field and Enhanced Ant Colony Algorithm

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DOI: 10.38007/Proceedings.0000720

Author(s)

Wenxuan Liu

Corresponding Author

Wenxuan Liu

Abstract

Using geographic information system (GIS) as the information platform, Based on the cost standard of typical transmission lines of 500kv power transmission and transformation project of State Grid Corporation of China, the clustering of environmental influencing factors was analyzed by principal component analysis. On this basis, the comprehensive cost of unit grid is evaluated by BP neural network, and the final comprehensive cost matrix of unit grid is obtained. Based on the principle of minimizing the cost of grid construction, the proposed grid region transmission path is searched by ant colony algorithm. Considering the environmental constraints of the search area, the corresponding cost compensation mechanism and avoidance crossing mechanism are set for regions with different degrees of constraint capacity to improve the environmental resultant force. An improved artificial potential field is introduced to estimate the starting direction of the path of the ant colony algorithm. The optimal corner processing mechanism is added to further reduce the comprehensive cost of transmission lines and improve the convergence speed of the algorithm

Keywords

Transmission Path Planning; Geographic Information Systems; Principal Component Analysis; BP Neural Network Algorithm; Artificial Potential Field; Ant Colony Algorithm