Optimal Battery Storage Sizing and Strategic Operation in Renewable Energy Integrated Grid using Roulette Chaotic Pelican Optimisation Algorithm

Abstract

The incorporation of Renewable Energy Sources (RESs) into the power grids poses a considerable challenge due to the intermittent nature of their production. Battery Energy Storage Systems (BESS) eliminate such problems by absorbing excess generation during peaks and providing stored charge at troughs. This leads to the fact that identifying a suitable BESS size is important to ensure a trade-off between cost-efficiency and grid stability, as inappropriately sized systems would lead to inefficiency, high capital and operating costs, and reduced reliability. This study uses the Roulette Chaotic Pelican Optimisation Algorithm (RCPOA) to optimise BESS sizing in RES-integrated grids. RCPOA outperforms at least five out of seven algorithms across 23 classical benchmarks. It excels in the CEC 2019 benchmarks, ranking first in the Friedman rank test, demonstrating its robustness compared to other state-of-the-art algorithms. Its success extends to the 'tension spring design' constraint problem, underscoring its versatility in different optimisation contexts. Simulations validate RCPOA's capability to determine optimal BESS sizes, enhancing grid performance and cost efficiency. Furthermore, sensitivity analyses show that changes in State of Charge (SOC) minimum limits, battery efficiency, and range of capacities all affect the optimal battery capacity greatly. By comparison, minimum capital costs are relatively stable and are only highly sensitive to the costs of operations and maintenance, a shortfall in demand, and the cost of grid energy. These results confirm the usefulness of RCPOA to optimise BESS setup in renewable energy solutions, indicating potential to promote economic and operational goals in current power systems.