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Fuzzy Adaptive PSO Algorithm for Network Reconfiguration of Distribution Systems
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Abstract
This paper presents a Fuzzy based Adaptive Particle Swarm Optimization algorithm for minimization of losses. In this method a set of Fuzzy rules are incorporated for tuning the inertia weight and learning factors which are updated for each pbest and gbest position until a global gbest is found. In Conventional PSO the learning factors are generally treated as constants and the variations are not accounted. Due to this convergence of the solution is delayed. In the proposed algorithm the learning factors are tuned as per fuzzy rules which help in obtaining a solution which is near to the global best and thoroughly avoids the tendency of solution being stuck up in local pbest and gbest like in conventional PSO. This method thoroughly avoids premature convergence as well as convergence towards local optima. The effectiveness of the proposed method is demonstrated through IEEE 16 and 32 bus standard test systems
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