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Reduced search space combined with particle swarm optimization for distribution system reconfiguration

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This paper presents a methodology based on a mesh analysis technique to reduce the search space of the distribution system reconfiguration problem. After reducing the search space, the metaheuristic particle… Click to show full abstract

This paper presents a methodology based on a mesh analysis technique to reduce the search space of the distribution system reconfiguration problem. After reducing the search space, the metaheuristic particle swarm optimization (PSO) was used to solve the problem, finding the best values presented in the literature. In the proposed methodology, the subsets of candidate switches were initially established through a two-stage heuristics. In the first stage, the number of open switches required to keep the radial configuration was calculated, which is the number of meshes on the system, and in the sequence the switches that make up each mesh were identified. In each subset, only one switch is opened, which makes the search process more efficient, compared to the analysis using all the switches. In the second stage of heuristic, the number of switches of the subsets was decreased with the help of an optimal power flow (OPF), which determines the switches from the subsets of first stage more propitious to be opened, this being the main contribution of the work. The PSO was developed for minimizing power losses in the distribution network lines subject to the following constraints: (a) minimum and maximum voltage limits; (b) radial network topology; and (c) balance of active and reactive power in the network buses. The algorithm was validated in four radial distribution systems: 5 nodes with 7 lines, 16 nodes with 21 lines, 33 nodes with 37 lines and 70 nodes with 74 lines.

Keywords: distribution system; methodology; search space; distribution

Journal Title: Electrical Engineering
Year Published: 2020

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