TY  - JOUR
AU  - Diouf, Alioune
AU  - Noro, Yasuhiro
AU  - Goro, Fujita
PY  - 2025
DA  - 2025/10/24
TI  - BESS Sizing Optimization Combined with Optimal Scheduling Method Considering the Battery Degradation Using PSO
JO  - Journal of Energy and Power Technology
SP  - 015
VL  - 07
IS  - 04
AB  - Recently, renewable energy projects using storage systems have gained significant attention. This innovative technology requires a comprehensive investigation to overcome the technical and economic issues, which are related to optimal storage system capacity and operational requirements. In this study, an extensive battery energy storage system (BESS) sizing method was proposed considering four variables: charging and discharging scheduling, state of charge, BESS rate energy and power capacity, and degradation effect in the state of health. The problem was divided into two stages: BESS sizing optimization and operation schedule optimization. Both stages are solved using the particle swarm optimization algorithm. The initial BESS sizing is performed randomly and then iteratively adjusted after optimally dispatching the BESS output from the preceding size selection using the particle swarm algorithm, considering the minimum state of the health limit to enhance the BESS lifecycle. The adjustment is done interactively by maximizing the rate of return on investment using the particle swarm optimization to generate the optimal BESS size. Finally, different technologies were evaluated to determine the shortest payback period.
SN  - 2690-1692
UR  - https://doi.org/10.21926/jept.2504015
DO  - 10.21926/jept.2504015
ID  - Diouf2025
ER  -