OPTIMAL SIZING AND TECHNO-ECONOMIC ANALYSIS OF A BATTERY ENERGY STORAGE SYSTEM FOR AN 11 kV RURAL DISTRIBUTION NETWORK

Abstract

Distribution grids are currently facing operational stress due to peak load demands and voltage regulation problems, necessitating cost-effective grid modernization solutions. This study formulated an optimization framework benchmarking three metaheuristic algorithms: Particle Swarm Optimization (PSO), Boda-Boda Optimization algorithm (BBOA) and Adaptive Boda-Boda Optimization Algorithm with Fuzzy Logic (ABBOA-Fuzzy). The framework was employed to determine the optimal capacity and siting of a Battery Energy Storage System (BESS) for a real-world 11 kV rural feeder in Kenya comprising 158 buses. Baseline analysis of the feeder indicated a peak demand of 2.809 MW, loading the substation transformer to 99.6% and a voltage drop to 0.936 p.u. at the furthest buses. The optimization algorithms were implemented in a Python-based environment, where the ABBOA Fuzzy algorithm demonstrated clear superiority by identifying a near-optimal solution from the first iteration and reaching full stability by iteration 7. The optimal solution was determined to be a 392.59 kW/1177.76 kWh BESS at Bus 117. Based on this, a commercially available 400 kW / 1200 kWh BESS was selected for validation. This configuration reduced peak demand by 15.5% and raised the minimum bus voltage to 0.952 p.u. A 15-year techno-economic simulation confirmed that the project is economically viable, yielding a positive NPV of $43,643 and an IRR of 15.54%. Thus, this study recommended the adoption of the proposed framework as a planning tool by utilities in BESS projects. Future research could further enhance this framework by incorporating ‘value stacking’ of auxiliary services, such as energy arbitrage and frequency regulation, to potentially maximize the project’s net present value.