Hybrid Chaotic GWO and DA: Optimal Sizing and Positioning of D-STATCOM

Abstract

In this work, derivation of power quality technique for distribution system via nonlinear functions is determined. Therefore the requirement for power quality improvement can be accurately enumerated. As the technique is adjustable, it requires a novel optimization technique to estimate optimal position and D-STATCOM compensation. Therefore, this work adopts a hybrid optimization model on the basis of chaotic local search techniques. The adopted hybrid chaotic GWO, as well as DA, is exploited to determine optimal sizing and positioning of STATCOM by resolving the power quality technique. In order to address both the sizing as well as localizing issue, the solution is reactive power-encoded with two bound constraints. The hybrid method integrated with two excellent approaches can enhance the inadequacy of each approach by exploiting the chaotic local search as an enhancement, and improve the exploration and exploitation of the approach concurrently therefore the sizing as well as the position of D-STATCOM can be calculated accurately. The adopted Hybrid chaotic Grey Wolf Optimization (GWO) and Dragonfly Algorithm (DA) technique evaluates its performance with the existing techniques regarding the cost analysis, Total loss, as well as ascertains the efficiency of the adopted power quality model.