Optimal Allocation of Battery Energy Storage Systems in Solar Integrated Distribution Networks Using Particle Swarm Optimization Technique

This study presents an efficient methodology for the optimal sizing and placement of Battery Energy Storage Systems (BESS) in distribution networks with pre-installed solar PV Distributed Generators (DGs). High solar photovoltaic (PV) penetration in distribution networks often leads to challenges such as voltage rise, reverse power flow, and increased daytime losses, thereby motivating the integration of BESS to effectively mitigate these issues. However, some of these issues can be exacerbated when the capacity and placement of BESS are not correctly optimized. The proposed approach employs Particle Swarm Optimization (PSO) to determine optimal BESS locations and capacities, aiming at minimizing energy losses while adhering to technical constraints such as feeder voltage and current limits, power balance, and BESS state of charge (SOC) boundaries. The methodology is validated through two case studies: a modified IEEE 33-bus network with integrated solar PV DGs and a practical feeder located in Kurunegala, Sri Lanka. The convergence statistics of this study confirm the effectiveness of the developed PSO algorithm in identifying optimal results, justifying its computational efficiency and robustness. Results of two case studies demonstrate that the optimal BESS placement significantly reduces daily energy losses while improving the voltage profile of the network. Therefore, the proposed framework provides a practical solution for improving reliability, energy efficiency, and solar PV hosting capacity in modern distribution networks through effective BESS integration while mitigating challenges associated with high solar PV penetration.