Optimization Sizing and Location of Battery Energy Storage Systems in Distribution Systems Connected with Distributed Generation Using Crayfish Optimization Algorithm
Abstract:
This research focuses on determining the optimal sizing and placement of multiple Battery Energy Storage Systems (BESSs) in distribution system connected with energy sources to enhance the performance of the distribution system in three key aspects: voltage stabilization, peak demand reduction, and power loss minimization. The study is divided into three scenarios: the installation of a single BESS, the installation of two BESSs, and the installation of three BESSs. The purpose is to compare the performance between a single BESS installation and multiple BESS installations. Crayfish Optimization Algorithm (COA) was employed in this research and compared with two widely used methods: Particle Swarm Optimization (PSO) and Salp Swarm Algorithm (SSA), to identify the most suitable algorithm for solving problems in the IEEE Standard Systems, specifically the IEEE 33-bus and IEEE 69-bus distribution systems. The findings from these standard systems were then applied to a practical distribution system of Provincial Electricity Authority (PEA), specifically the Hua Hin Substation No. 2, was connected to both solar and biomass energy sources. The optimal algorithm was identified by analyzing the objective function, which aims to minimize the overall system costs while maximizing efficiency in all three performance aspects. The simulation results of the BESS installations in all three scenarios demonstrated the ability to stabilize voltage levels, reduce power loss, and lower peak demand. Among the three methods, COA was found to be the most suitable algorithm for solving issues in various scenarios within the actual power distribution system.