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

• Published in: IET generation, transmission & distribution Vol. 7; no. 12; pp. 1367 - 1382
• Main Authors: Andervazh, Mohammad-Reza, Olamaei, Javad, Haghifam, Mahmoud-Reza
• Format: Journal Article
• Language: English
• Published: Stevenage The Institution of Engineering and Technology 01.12.2013; Institution of Engineering and Technology; The Institution of Engineering & Technology
• Subjects: adaptive multiobjective distribution network reconfiguration; Algorithms; Applied sciences; distribution networks; DNRC method; Electrical engineering. Electrical power engineering; Electrical power engineering; Exact sciences and technology; graph theory; graph theory technique; IEEE 33‐bus; IEEE 70‐bus radial distribution systems; IEEE standards; minimisation; Miscellaneous; multiobjective discrete particles swarm optimisation algorithm; Pareto optimal set; Pareto optimisation; Pareto‐based multi‐objective distribution network reconfiguration method; Pareto‐dominance concept; particle swarm optimisation; power loss minimisation; Power networks and lines; probabilistic heuristics; probability; quantitative performance assessment; stochastic random search; Theory. Simulation; IEEE 70-bus radial distribution systems; Pareto optimisation; DNRC method; distribution networks; particle swarm optimisation; graph theory; adaptive multiobjective distribution network reconfiguration; probability; quantitative performance assessment; graph theory technique; Pareto-based multi-objective distribution network reconfiguration method; IEEE 33-bus; multiobjective discrete particles swarm optimisation algorithm; Pareto-dominance concept; power loss minimisation; Pareto optimal set; IEEE standards; minimisation; probabilistic heuristics; stochastic random search; Radial distribution; Probabilistic approach; Pareto optimum; Multiobjective programming; Updating; Iterative method; Graph theory; Stochastic method; Adaptive method; Particle swarm optimization; Switching; Implementation; Search algorithm; Bus system; Electrical network; Power system simulation; Heuristic method; Power losses; Voltage; Reconfigurable architectures; Distribution network
• ISSN: 1751-8687; 1751-8695
• DOI: 10.1049/iet-gtd.2012.0712

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.