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

Fingerprint

Power System
Closed-loop
Genetic algorithms
Planning
Genetic Algorithm
Annual
Engineers
Voltage
Optimization Problem
Voltage drop

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Theoretical Computer Science

Cite this

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
Huang, Wei-Tzer ; Yao, Kai-chao ; Chen, Shiuan Tai ; Nien, Hsiau Hsian ; Lin, Deng Chung ; Huang, Po Tung. / Optimal planning of a load transfer substation pair between two normally closed-loop feeders considering minimization of system power losses using a genetic algorithm. Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010. 2010. pp. 453-456 (Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010).
@inproceedings{4467b76090194e1e840856b537ac55e6,
title = "Optimal planning of a load transfer substation pair between two normally closed-loop feeders considering minimization of system power losses using a genetic algorithm",
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.",
author = "Wei-Tzer Huang and Kai-chao Yao and Chen, {Shiuan Tai} and Nien, {Hsiau Hsian} and Lin, {Deng Chung} and Huang, {Po Tung}",
year = "2010",
month = "12",
day = "1",
doi = "10.1109/ICGEC.2010.119",
language = "English",
isbn = "9780769542812",
series = "Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010",
pages = "453--456",
booktitle = "Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010",

}

Huang, W-T, Yao, K, Chen, ST, Nien, HH, Lin, DC & Huang, PT 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., 5715467, Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010, pp. 453-456, 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010, Shenzhen, China, 10-12-13. https://doi.org/10.1109/ICGEC.2010.119

Optimal planning of a load transfer substation pair between two normally closed-loop feeders considering minimization of system power losses using a genetic algorithm. / Huang, Wei-Tzer; Yao, Kai-chao; Chen, Shiuan Tai; Nien, Hsiau Hsian; Lin, Deng Chung; Huang, Po Tung.

Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010. 2010. p. 453-456 5715467 (Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010).

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

TY - GEN

T1 - Optimal planning of a load transfer substation pair between two normally closed-loop feeders considering minimization of system power losses using a genetic algorithm

AU - Huang, Wei-Tzer

AU - Yao, Kai-chao

AU - Chen, Shiuan Tai

AU - Nien, Hsiau Hsian

AU - Lin, Deng Chung

AU - Huang, Po Tung

PY - 2010/12/1

Y1 - 2010/12/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=79952546040&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79952546040&partnerID=8YFLogxK

U2 - 10.1109/ICGEC.2010.119

DO - 10.1109/ICGEC.2010.119

M3 - Conference contribution

AN - SCOPUS:79952546040

SN - 9780769542812

T3 - Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010

SP - 453

EP - 456

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

ER -

Huang W-T, Yao K, Chen ST, Nien HH, Lin DC, Huang PT. 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. 2010. p. 453-456. 5715467. (Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010). https://doi.org/10.1109/ICGEC.2010.119