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Fuzzy Satisfied Multiobjective Distribution Network Reconfiguration: an Application of Adaptive Weighted Improved Discrete Particle Swarm Optimization


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DOI: https://doi.org/10.15866/iremos.v10i4.12267

Abstract


In this paper, a multiobjective framework for distribution network reconfiguration (DNR) is developed in the fuzzy domain to minimize power loss and improve load balancing. Since it is a nonlinear and combinatorial optimization problem a new fangled adaptive weighted improved discrete particle swarm optimization (AWIDPSO) algorithm is exercised. In this formulation each objective is normalized using fuzzy membership function, these are combined with the appropriate weight factor and maximized during the course of the iteration. In order to obtain high-quality solutions within lesser executing time, the constraint violations are handled perfectly so that intern produces a stable convergence characteristic. In this study, a 33-bus system is analyzed for optimum reconfiguration using the developed framework. Comparison of the simulated results with the results of well known prudent optimization technique confirms the applicability of the AWIDPSO algorithm for DNR problem.
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Keywords


Network Reconfiguration; Power Loss Reduction; Load Balancing; Fuzzified Multiobjective; Metaheuristic Algorithm

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References


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