Optimal planning of a load transfer substation pair between two normally closed-loop feeders considering minimization of system power losses using a genetic algorithm

Wei-Tzer Huang, Kai-chao Yao, Shiuan Tai Chen, Hsiau Hsian Nien, Deng Chung Lin, Po Tung Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an effective approach for planning a load transfer substation pair(LTSP) between two normally closed-loop feeders considering minimization of system power losses. Firstly, the annual equivalent load of each load point is calculated. Then, a genetic algorithm-based (GA-Based) approach has been proposed to solve this optimization problem. The objective is minimization of the annual system power losses. Finally, the optimal LTSP was chosen considering minimizing annual system power losses and the maximum voltage drops at each bus as well as ampere capacities of each feeder segment. The method presents in this paper are valuable to distribution engineers for planning the LTSPs between normally closed-loop feeders.

Original languageEnglish
Title of host publicationProceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
Pages453-456
Number of pages4
DOIs
Publication statusPublished - 2010 Dec 1
Event4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 - Shenzhen, China
Duration: 2010 Dec 132010 Dec 15

Publication series

NameProceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010

Other

Other4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
CountryChina
CityShenzhen
Period10-12-1310-12-15

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Theoretical Computer Science

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    Huang, W-T., Yao, K., Chen, S. T., Nien, H. H., Lin, D. C., & Huang, P. T. (2010). Optimal planning of a load transfer substation pair between two normally closed-loop feeders considering minimization of system power losses using a genetic algorithm. In Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 (pp. 453-456). [5715467] (Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010). https://doi.org/10.1109/ICGEC.2010.119