Experimental Analysis on FireFly and Grey Wolf Optimization for Phasor Estimation in PMU

Abstract

Phasor Measurement Unit (PMU) determines the current/voltage signal in a power network. The PMU's functions are gathered by means of Phasor Estimation Method (PEM). Therefore, PEM has a lot of significance in modeling diverse security systems. This paper intends to develop a phasor estimation model in PMU exploiting two renowned meta-heuristic algorithms called FireFly (FF), and Grey Wolf Optimization (GWO). The optimization problem solving using these algorithms to estimate phasors of an Electric Power System (EPS) is depicted on concerning a sinusoidal model for the input voltage signal. The electrical signal can be investigated by considering a sliding window and objective is to lessen the error among the predicted and actual signal. Accordingly, the magnitude and phase of the signal are optimized by FF, and GWO algorithms in such a way that overall Total Vector Error (TVE) could be reduced. Here, the implemented model is carried out in IEEE 30 benchmark test bus systems, and the analysis is held by GWO and FF algorithms.