Multi-objective Optimal Placement and Sizing of Battery Energy Storage System in Unbalanced Three-Phase Distribution Networks with High PV Penetration

Non-renewable energy resources cause high carbon emissions and Global Warming, threatening the environment. Due to these reasons, the Government of India has set a target of achieving 38000 MW of Roof Top Solar Plants by 31st December 2022. This will lead to remarkably high PV penetration at the distribution level. The generation through solar PV is not constant throughout the day due to the variable intensity of sunlight during the daytime and the absence of sunlight during the night. There are also seasonal variations. This results in degradation of voltage profile, increase in losses, increase in peak demand on the substation, and unbalances in the distribution system. Battery energy storage systems (BESS) play an important role in mitigating these worse impacts. However, because of the high cost of the battery storage system, its optimal sizing and placement is very important. Optimally placed BEES can make the distribution system more balanced, improve voltage profile, and reduce losses in the distributed network. In this paper, a new multi-objective technique using Particle Swarm optimization has been proposed for optimal placement and sizing of BESS. The proposed approach has been tested on a practical three-phase unbalanced 19-bus distribution feeder. The obtained results show that optimal placement of BESS using the proposed approach leads to reduced power losses, improved voltage profile and reduction in feeder load during peak-load hours.