EXPLORING THE APPLICATION OF HYBRID METHODS FOR OPTIMAL LOCATION AND POWER SELECTION OF ENERGY STORAGE SYSTEMS IN POWER SYSTEMS

Abstract

Energy storage systems (ESS) within the transmission system have emerged as a critical area of research and application. This paper presents a novel hybrid

approach that offers a framework for determining optimal locations and power for deploying ESS. The primary objective is to enhance grid stability, minimize

disruptions and failures, bolster flexibility, and effectively meet the energy demands of consumers prior to the need for transmission expansion planning (TEP). The

proposed methodology combines the Min Cut (MC) algorithm with the genetic algorithm (GA). Initially, the MC algorithm is improved through the incorporation of a

penalty mechanism, aimed at reducing the search space for the optimization problem while preserving global optimality. Subsequently, the GA algorithm is employed

to solve the optimization problem within the constrained search space, thereby identifying the most suitable local and power for the ESS. The research findings are

evaluated on the IEEE 24-bus power system and demonstrate promising feasibility. Notably, the proposed approach significantly reduces computational complexity

when compared to previous separate methodologies, consequently diminishing computation time and facilitating timely and competitive investment decisions

pertaining to ESS systems.