Optimal Battery Energy Storage System Based on VAR Control Strategies Using Particle Swarm Optimization for Power Distribution System

We designed a battery energy storage system (BESS) based on the symmetrical concept where the required control is by the symmetrical technique known as volt/var control. The integration of BESS into the conventional distribution has significantly impacted energy consumption over the past year. Load demand probability was used to investigate optimal sizing and location of BESS in an electrical power system. The open electric power distribution system simulator (OpenDSS) was interfaced with MATLAB m-file scripts and presented by using time series analysis with load demand. The optimal BESS solution was adapted by using a genetic algorithm (GA) optimization technique and particle swarm optimization (PSO). The simulation results showed that the BESS was directly connected to the power grid with GA and PSO, and it was observed that BESS sizing also varied for these two values of 1539 kW and 1000 kW, respectively. The merit of those values is the power figure of the system, which is necessary for installation. Therefore, optimal sizing and location of the BESS are helpful to reduce the impact from the load demand to the total system loss and levelling of the energy demand from the power system network. The integration of the BESS can be applied to improve grid stability and store surplus energy very well. The grid increased the stability of the power system and reduced the impact from the large scale of BESS penetration.

Automated summary

The study designed a battery energy storage system based on symmetrical technique and integrated it into the conventional distribution system to reduce the impact from load demand and balance energy consumption. By applying genetic algorithm and particle swarm optimization, optimal sizing and location of the BESS were determined, improving grid stability.