Feeder reconfiguration for load factor improvement

Chang, Rung-Fang; Lu, Chan‐Nan

doi:10.1109/pesw.2002.985152

Cited by 46 publications

(30 citation statements)

References 7 publications

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“…To verify the performance of the proposed algorithm and compare with algorithms of typical BPSO (Eberhart & Kennedy, 1997) and modified BPSO (Chang & Lu, 2002) for feeder reconfiguration problem, a four-feeder distribution system is used. This distribution system is taken from Taoyuan division, Taiwan Power Company, Taiwan.…”

Section: Resultsmentioning

confidence: 99%

“…Randomly choosing the locations of these tie-switches will cause outages or non-radial structure in distribution systems. In (Chang & Lu, 2002), BPSO is used to solve the feeder reconfiguration problems and the method they proposed avoided the problem of unsuitable numbers of tie-switches. The concept of (Chang & Lu, 2002) is based on BPSO and the moving velocity of particle is defined in terms of probabilities.…”

mentioning

confidence: 99%

“…In (Chang & Lu, 2002), BPSO is used to solve the feeder reconfiguration problems and the method they proposed avoided the problem of unsuitable numbers of tie-switches. The concept of (Chang & Lu, 2002) is based on BPSO and the moving velocity of particle is defined in terms of probabilities. Instead of BPSO used in (Chang & Lu, 2002), this research tries to construct a more feasible discrete PSO scheme based on typical PSO for feeder reconfiguration.…”

mentioning

confidence: 99%

“…The concept of (Chang & Lu, 2002) is based on BPSO and the moving velocity of particle is defined in terms of probabilities. Instead of BPSO used in (Chang & Lu, 2002), this research tries to construct a more feasible discrete PSO scheme based on typical PSO for feeder reconfiguration. The method proposed in this research modifies the operators of PSO's formula based on the characteristics of both the status of switches and the shift operator to construct the binary coding particle swarm optimization for feeder reconfiguration.…”

mentioning

confidence: 99%

“…Minimizing total line losses and load balancing without violating operation constraints and maintaining radial structure are the two objective functions in this research. The simulations will be performed and the results are used to compare the proposed method, the method proposed in (Chang & Lu, 2002) and BPSO to verify the performance and effectiveness. A distribution system in Taiwan Power Company (TPC) is used in this study to verify the stability and usefulness of the proposed algorithm.…”

mentioning

confidence: 99%

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A Novel Binary Coding Particle Swarm Optimization for Feeder Reconfiguration

Tsai¹,

Wu²

2009

Particle Swarm Optimization

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Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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A Novel Binary Coding Particle Swarm Optimization for Feeder Reconfiguration

Tsai¹,

Wu²

2009

Particle Swarm Optimization

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A non-dominated sorting evolutionary programming algorithm for multi-objectives power distribution system feeder reconfiguration problems

Hsu

Tsai

2011

Int. Trans. Electr. Energ. Syst.

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SUMMARY Distribution system reconfiguration is performed during normal or emergency operations by changing the status of switches. System reconfiguration can be used for system loss reduction or voltage profile improvement during normal operations. For emergency operations, de‐energized loads can be transferred to adjacent energized feeders through system reconfiguration. Several objectives, for example, system real power loss reduction and transformer load balancing improvement, are considered simultaneously during system reconfiguration. In order to consider the objectives simultaneously, weighted sum method was commonly used. Only one solution may be obtained when weighted sum method was applied. However, several compromise solutions were preferred for the distribution system operators. Multi‐objective approach was one of the methods that can be used to provide multiple compromise solutions. In this paper, the fitness function in non‐dominated sorting genetic algorithm and the reproduction procedure in evolutionary programming were integrated. The proposed non‐dominated sorting evolutionary programming was applied to the multi‐objective problems in distribution systems in order to provide system operators with different compromise solutions. The results of this study indicated that the proposed non‐dominated sorting evolutionary programming was capable of identifying better solutions than that of non‐dominated sorting genetic algorithm for distribution system reconfiguration problems. Copyright © 2011 John Wiley & Sons, Ltd.

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