Abstract
Distributed feeder reconfiguration (DFR) is an operation problem, which entails altering the topological structure of the distribution feeders by rearranging the status of switches in order to obtain an optimal configuration. This paper proposes a new evolutionary algorithm (EA) for solving the multi-objective distribution feeder reconfiguration (MDFR) problem. The proposed algorithm is an efficient multi-objective modified shuffled frog leaping algorithm (MMSFLA) that has been used to solve MDFR problem. A new frog leaping rule is proposed to improve the local exploration of the SFLA, which in turn improves the overall performance of the MSLFA. The main focus of this study is to minimize the real power loss, deviation of the nodes' voltages, and the number of switching operations. In the proposed MMSFLA, an external repository is considered to save non-dominated solutions found during the search process. Since the objective functions are not the same, a fuzzy clustering technique is used to control the size of the repository within the limits. Three distribution test feeders are considered to evaluate the feasibility and effectiveness of the proposed approach. Copyright © 2010 John Wiley & Sons, Ltd.
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