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Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimisation algorithm and graph theory
Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimisation algorithm and graph theory
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Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimisation algorithm and graph theory
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Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimisation algorithm and graph theory
Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimisation algorithm and graph theory

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Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimisation algorithm and graph theory
Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimisation algorithm and graph theory
Journal Article

Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimisation algorithm and graph theory

2013
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Overview
This study proposes a Pareto-based multi-objective distribution network reconfiguration (DNRC) method using discrete particle swarm optimisation algorithm. The objectives are minimisation of power loss, the number of switching operations and deviations of bus voltages from their rated values subjected to system constraints. Probabilistic heuristics and graph theory techniques are employed to improve the stochastic random search of the algorithm self-adaptively during the optimisation process. An external archive is used to store non-dominated solutions. The archive is updated iteratively based on the Pareto-dominance concept to guide the search towards the Pareto optimal set. The method is implemented on the IEEE 33-bus and IEEE 70-bus radial distribution systems, simulations are carried out and results are compared with other available approaches in the literature. To assess the performance of the proposed method, a quantitative performance assessment is done using several performance metrics. The obtained results demonstrate the effectiveness of the proposed method in solving multi-objective DNRC problems by obtaining a Pareto front with great diversity, high quality and proper distribution of non-dominated solutions in the objective space.