Multi-objective Performance Management of the Capacitor Allocation Problem in Distributed System Based on Adaptive Modified Honey Bee Mating Optimization Evolutionary Algorithm

Abstract

Optimal capacitor placement as a precious and significant strategy to improve the performance of the power systems has attracted much attention in recent years. However, the non-linear and discrete nature of the optimal capacitor placement problem is a big barrier in front of the traditional optimization methods for global search. Therefore, this article proposes a powerful optimization technique based adaptive modified honey bee mating optimization algorithm to solve the optimal capacitor placement problem effectively. The proposed method consists of two sub-modification methods to let each solution choose the modification methods which best fit its situation. Also, in order to preserve the random search ability of the algorithm, the idea of the roulette wheel mechanism is employed in the selection process. The proposed algorithm can overcome the main shortcomings in the traditional honey bee mating optimization algorithm by using both local and global search schemes. Therefore, the problem investigated is formulated in a multi-objective framework optimizing the total power losses, voltage deviation, and cost of both power losses and capacitor investment simultaneously. As the result of the conflicting behavior of the objective functions, the idea of a non-dominated solution, called the Pareto solution, is employed to find the set of optimal solutions. During the optimization process, the set of Pareto solutions found is stored in an external memory called a repository. In order to avoid excessive growth of the repository, a fuzzy-based clustering technique is applied to the problem. The feasibility and superiority of the proposed method is tested through three standard test systems.