Optimal sizing and placement of ESS in distribution system with renewable energy integration using multi-objective hybrid optimization technique

Abstract

In this paper presents a methodology for optimal placement and sizing of Energy Storage ESS in distribution system with renewable energy integration using Multi-objective Hybrid optimization technique (ESS-MHO). It combines improved ant colony optimization (IACO) and chaotic cuckoo search (CCS) algorithm. It will provide an optimal ESS placement, sizing, and operation. The optimal planning determines where ESS will be located and sized by renewable and schedules the battery charging and discharging, while reducing total energy losses that are subject to technical constraint. The deployment of ESSs is a large avenue for maximize the efficiency of energy in distribution system, The optimum operation, particular placement, and size of the overall systems performance can be enhanced. It can facilitate peak energy demand fulfillment, enhancing the benefits for integration of renewable and Distributed energy sources, it aid management of energy quality, and to reduce the expansion costs of the distribution network.The multi-objective will be considered for appropriate selection of ESS, smart charge and discharging of ESS, selection, placement and operation as well as problems of power quality.