NDLI: Feeder reconfiguration for power quality requirement and feeder service quality matching

Content Provider	IEEE Xplore Digital Library
Author	Shen, C.C. Lu, C.N.
Copyright Year	2002
Description	Author affiliation: Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan (Shen, C.C.; Lu, C.N.)
Abstract	Electric power industry deregulation has forced utilities to face new challenges and to assess the cost-benefit implications of providing acceptable quality services for different customers. Distribution systems supply various types of customers that require different service quality. Through feeder reconfiguration, it is possible to coordinate these requirements with the reliability of network elements, and customers with special power quality requirements can be served by adequately reliable feeders. The coordination provides a guide for investing adequate PQ improvement equipment and locating these equipments. A method is proposed in this paper to assess the reliability indices of feeders and service quality requirements of different customer types. It finds a match between quality requirements of the loads and the feeder service performance by feeder reconfiguration. Fuzzy set theory and binary particle swarm optimization technique are used to find the optimal solution. Results based on a simple sample network are presented. The results can be used as a starting point for building Quality Control Centers (QCC) that provide difference classes of power service.
Starting Page	226
Ending Page	231
File Size	485431
Page Count	6
File Format	PDF
ISBN	0780375254
DOI	10.1109/TDC.2002.1178292
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-10-06
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Costs Power quality Quality control Production Power system harmonics Electricity supply industry Fuzzy set theory Electrical equipment industry Power system reliability Particle swarm optimization
Content Type	Text
Resource Type	Article

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