Metaheuristic nature-based algorithm for optimal reactive power planning

Abstract

An oppositional based Harris Hawks optimization technique enthralled is suggested and implemented to reactive power optimization planning in power systems in this research. As transmission loss minimization is a fundamental criterion for secured power system operation, Var planning has become increasingly important for improved coordination in modern power systems. The Oppositional based Harris Hawk Optimizer (OHHO) algorithm, which is implemented on the IEEE 57 bus system, is proposed in this paper as an enhanced meta-heuristic nature inspired approach. The suggested algorithm is based on the Harris Hawk Optimizer (HHO) algorithm, which is a speculative algorithm with no intrinsic dependent variables. To get improved estimation for the predominant approach, the search space is subsequently altered by combining HHO with the Oppositional Based Learning (OBL) technique. In the present study, the OHHO is proposed for reducing transmission losses, operating costs, and improving voltage profile at buses. The impact of the optimizers' update technique on the objective functions is examined. The research focuses on issues such as reactive power provided by generator buses, shunt capacitors, and transformer tap position changes. The simulation outcomes gained on typical test systems demonstrate that the proposed OHHO outperforms HHO, and other optimization techniques recently published in the state-of-the-art literature.