NDLI: Determination of Power Distribution Network Configuration Using Non-Revisiting Genetic Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Chun Wang Yuanhai Gao
Copyright Year	1969
Abstract	A non-revisiting genetic algorithm (NrGA) was used to determine distribution network configuration for loss reduction. By advocating binary space partitioning (BSP) to divide the search space and employing a novel BSP tree archive to store all the solutions that have been explored before, NrGA can quickly check for revisits by communicating with BSP tree archive when a new solution is generated by genetic algorithm (GA), and can mutate an alternative unvisited solution through a novel adaptive mutation mechanism that based on BSP tree while a revisit has occurred, which achieves no duplicates in the entire search. A method for getting independent loops of distribution network was realized using breadth-first search algorithm. Furthermore, the extended intermediate crossover mode, which requires no tuning parameter such as crossover rate and extends the crossover results, is employed for improving the performance of NrGA in solving distribution network configuration problem. The proposed approach has been successfully tested on three sample systems and three practical systems. Numerical studies have revealed its accuracy and efficient performance.
Sponsorship	IEEE Power Engineering Society
Starting Page	3638
Ending Page	3648
Page Count	11
File Size	1483405
File Format	PDF
ISSN	08858950
Volume Number	28
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic algorithms Power distribution Optimization non-revisit Adaptive mutation binary space partitioning distribution network configuration genetic algorithm
Content Type	Text
Resource Type	Article
Subject	Energy Engineering and Power Technology Electrical and Electronic Engineering

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