Optimal Reconfiguration and Capacitor Allocation in Radial Distribution Systems Using the Hybrid Shuffled Frog Leaping Algorithm in the Fuzzy Framework

In distribution systems, network reconfiguration and capacitor placement are commonly used to diminish power losses and keep voltage profiles within acceptable limits. In this paper, the Hybrid Shuffled Frog Leaping Algorithm (HSFLA) has been used to optimize the balanced and unbalanced radial distribution systems using a network reconfiguration and capacitor placement. High accuracy and fast convergence are the major advantages of the proposed approach regarding the result of solving the multi-objective reconfiguration and capacitor placement in a fuzzy framework. These objectives are minimizing the total network real power losses and buses voltage violation, and balancing the load in the feeders. Each objective is transferred into fuzzy domain using its membership function and fuzzified separately. Then, the overall fuzzy satisfaction function is formed and considered as a fitness function. The value of this function has to be maximized to gain the optimal solution. In the literature review, several reconfiguration and capacitor placement methods which had already been implemented separately have been investigated, but there are few studies which simultaneously apply these two methods. The proposed algorithm has been implemented in three IEEE test systems (two balanced and one unbalanced systems).The numerical results obtained by the simulation carried out in this study show that the HSFLA algorithm improves the performance much more than other metaheuristic algorithms.