A Hybrid Improved Wolf Optimization with A Genetic Algorithm Developed for Analysis of the Optimal Location of UPFC to Optimize the Performance Improvement

In recent years, the reformation of the electricity industry has drawn significant interest on a global scale. The main goals are to raise customer attention, enhance power system achievement, and reduce cost income. There are many methods available today to give clients an effective and uninterrupted power supply. The power system managers and controllers use the crucial instrument known as Optimal Power Flow (OPF) to make decisions and manage the conventional power system. The OPF issue was a large-scale, nonlinear, non-convex, and complex optimization problem. As a result, alternatives are needed for the existing energy system's facilities to operate steadily &grow more fully. The Unified Power Flow Controller (UPFC) reliability enhancement was the focus to this article. A hybrid Improved Wolf Optimization based Genetic Algorithm (IWOG) proposed the best position for UPFC in selecting the Flexible AC Transmission System (FACTS) device and its location to carry out the needed operation. To develop UPFC of computing the instantaneous reactive and active power values, the hybrid IWOG approach and Local Random Search (LRS) method-based OPF methodology were described in this study. The proposed method is utilized to improve the flow of electricity while taking into account factors like generating limits, injected voltage, and angle. The results show that the compensating devices improve the power flow and voltage characteristics.