Reliability enhancement using optimal distribution feeder reconfiguration

• Published in: Neurocomputing (Amsterdam) Vol. 106; pp. 1 - 11
• Main Authors: Kavousi-Fard, Abdollah, Akbari-Zadeh, Mohammad-Reza
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 15.04.2013; Elsevier
• Subjects: Algorithmics. Computability. Computer arithmetics; Applied sciences; Computer science; control theory; systems; Data processing. List processing. Character string processing; Distribution feeder reconfiguration (DFR); Electrical engineering. Electrical power engineering; Electrical power engineering; Exact sciences and technology; Improved shuffled frog leaping algorithm (ISFLA); Memory organisation. Data processing; Multiobjective optimization; Operation. Load control. Reliability; Power networks and lines; Reliability enhancement; Software; Theoretical computing; SAIDI; DFR; Improved shuffled frog leaping algorithm (ISFLA); Reliability enhancement; Multiobjective optimization; MDFR; AENS; Distribution feeder reconfiguration (DFR); ISFLA; SAIFI; Cluster analysis; Costs; Multiobjective programming; Test standard; Leap frog configuration; Energy loss; Standard test; User service; Efficiency; Electric power; Voltage; Distribution network; Data analysis; Statistical analysis; Probabilistic approach; Pareto optimum; Rupture; Engineering design; Fuzzy logic; Electrical network; Optimal solution; Feasibility; External memory; Objective function; Power system reliability; Reconfiguration
• ISSN: 0925-2312; 1872-8286
• DOI: 10.1016/j.neucom.2012.08.033

Failure statistics show that distribution networks engage the most contribution to the customer unavailability services. Optimal reconfiguration of distribution systems has many advantages like total power losses reduction, voltage profile enhancement, reliability improvement and so on. Therefore, in this paper a new multiobjective improved shuffled frog leaping algorithm (ISFLA) is proposed to investigate the distribution feeder reconfiguration (DFR) problem from the reliability enhancement point of view. Nevertheless, since the total cost of MW loss is an important and attractive subject to the electric power utilities, the total active power losses is also considered as an objective function in the investigations. Therefore, the objective functions of the problem to be optimized are system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), average energy not supplied (AENS) and the total active power losses. During the optimization process, the proposed ISFLA finds a set of non-dominated optimal solutions referred to Pareto optimal solutions that are kept in an external memory called repository. As the result of the conflicting behavior of the objective functions investigated, a fuzzy clustering technique is employed to control the size of the repository in the predetermined limits. The feasibility and the efficiency of the proposed method are examined by a standard distribution test system.