A new hybrid HBMO-SFLA algorithm for multi-objective distribution feeder reconfiguration problem considering distributed generator units

Abstract

Distribution feeder reconfiguration (DFR) is one of the well-known and effective strategies adopted in distribution network. The goal of DFR problem is to obtain a new topological structure for distribution feeders by rearranging the status of switches such that an optimal configuration would be obtained. The existence of Distributed Generation (DG) can affect the entire power system and especially distribution networks. This paper presents an efficient approach for multi-objective DFR problem considering the simultaneous effect of DG units. The objective functions to be investigated are 1) power losses, 2) voltage deviation of buses, 3) emission produced by DG units and distribution companies and 4) the total cost of the active power generated by DG units and distribution companies. The new evolutionary method is based on an efficient multi-objective hybrid honey bee mating optimization (HBMO) and shuffled frog leaping algorithm (SFLA) called MHBMO-SFLA. The proposed hybrid algorithm integrates the outstanding characteristics of SFLA to improve the performance of HBMO algorithm sufficiently. In the proposed MHBMO-SFLA, an external repository is considered to save non-dominated solutions which are found during the search process. Also, since the objective functions are not the same, a fuzzy clustering technique is utilized to control the size of the repository within the limits. A distribution test feeder is considered to evaluate the feasibility and effectiveness of the proposed approach.