Optimal multi-objective reconfiguration and capacitor placement of distribution systems with the Hybrid Big Bang–Big Crunch algorithm in the fuzzy framework

Abstract

Network reconfiguration and capacitor placement are useful options applied to reduce power losses and to keep voltage profiles within permissible limits in distribution systems. This study presents an efficient algorithm for optimization of balanced and unbalanced radial distribution systems by a network reconfiguration and capacitor placement. An important property of the proposed approach is solving the multi-objective reconfiguration and capacitor placement in fuzzy framework and its high accuracy and fast convergence. The considered objectives are the minimization of total network real power losses, the minimization of buses voltage violation, and load balancing in the feeders. The proposed algorithm has been implemented in three IEEE test systems (two balanced and one unbalanced systems). Numerical results obtained by simulation show that the performance of the Hybrid Big Bang Big Crunch (HBB–BC) algorithm is slightly higher than or similar to other meta-heuristic algorithms.