A modified KH algorithm to solve the optimal reconfiguration problem in the presence of distributed generations

This paper aims to propose an effective intelligent optimization method to solve the multi-objective distribution feeder reconfiguration (DFR) problem considering distributed generations (DGs). In this regard, we introduce a novel population based algorithm based on krill herd (KH) algorithm to solve the multi-objective distribution feeder reconfiguration problem considering DG units. In order to improve the search ability of the algorithm, a new modification process is proposed too. This modification enhances the overall outcome of the KH algorithm in both search and convergence area. During the search process of the proposed modified KH (MKH) algorithm, the achieved non-dominated solutions are stored in an external repository. Owing to distinctive objective functions, a fuzzy clustering technique is applied to control the size of the repository within the restrictions. The objective functions considered in this paper are power losses, voltage deviation of buses and total cost of the active power produced by DG units and distribution companies. In order to evaluate the feasibility and effectiveness of the method, the proposed approach is tested on a distribution test system.