JCMPS

Enhanced Self Adaptive Bat Algorithm for Optimal Location of Unified Power Quality Conditioner

Abstract

Abstract: In the electrical, various researchers have worked on Unified Power Quality Conditioner (UPQC) is considered as an ultimate solution to enhance the power quality. Nevertheless, because of the maximum cost included; the position of UPQC in the Distributed System required to be determined with enormous concern and have to rather be resolved as the optimization issue. Moreover, the optimization of UPQC positioning issue in a competitive environment such as the reduction of Total Harmonic Distortion (THD), reduction of power losses, improvement of unbalance minimization and voltage profile in both voltage and normal sag circumstances. In this paper, a power quality enhancement method which is on the basis of a novel self-adaptive optimization method called enhanced Self-Adaptive Bat Algorithm. The proposed method discovers the optimal position for the UPQC device regarding the UPQC cost, power system losses, and Voltage Stability Index (VSI). The simulations are performed in IEEE 69 bus systems. The performance of the proposed technique is evaluated with the traditional methods such as Artificial Bee Colony (ABC), Firefly (FF), and Grey Wolf Optimization (GWO) to exhibit the advantage of the proposed algorithm.

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