Study of Optimal Alocation and Sizing of Battery Energy Storage Systems in Wind Turbine Integrated Power Generating Systems Using Metaheuristic AI

The output power of wind turbines varies periodically. Fluctuations in wind energy pose several challenges during operation. One of the best solutions to address this issue is by using a Battery Energy Storage System (BESS). The optimization method used is called Galactic Swarm Optimization (GSO), inspired by the movement of stars, galaxies, and galactic superclusters influenced by gravitational forces. GSO combines exploration and exploitation phases to achieve a balance between exploring new solutions and exploiting existing ones. This approach is applied to determine the optimal location and size of the battery energy storage system in the electrical system with the aim of minimizing total power losses. Simulations are conducted using MATLAB with a case study on the electrical system in the southern region of Sulawesi. Simulations are performed with two scenarios, the first scenario where the output power at PLTB Sidrap and Jeneponto is 100%, and the second scenario where the output power at PLTB Sidrap and Jeneponto is only 50%. In the first scenario, the power losses before battery installation are approximately 32.5280 MW and 112.9934 MVAR, while after battery installation, they become 32.5269 MW and 112.9618 MVAR. Meanwhile, in the second scenario, the power losses before battery installation are 32527.96778 kW and 112993.425327 kVAR, and after battery installation, they become 32527.96777 kW and 112993.4252830 kVAR. The simulation results indicate that with the installation of the battery energy storage system at optimal locations and sizes, power losses can be reduced by 0.0010 MW and 0.0316 MVAR in the first scenario, and 0.00001 kW and 0.000044 kVAR, in the second scenario. The percentage decrease in active power losses is 0.000031%, while for reactive power losses it is 0.00028%. The optimal size for battery energy storage system is 8.1810 MW.