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In rural areas of developing countries, microgrids paired with energy storage offer a reliable, decentralized solution to electrification, enabling the continuous supply of power and the integration of renewable energy sources despite fluctuations in generation during peak demand. The present work proposes a novel, real-life measurement-based, holistic methodology to support multipurpose battery sizing in grid-connected microgrids, including adequacy and stability considerations within a single sizing process. In terms of energy, a numerical sizing procedure is applied to a yearly, hourly discretized load demand profile for primary energy. Subsequently, the system’s dynamic response characterization relies on a multi-offspring genetic algorithm to tune a high-fidelity governor. A transient stability analysis is performed to determine the additional power required to ensure stable service provision. The proposed procedure is applied to the microgrid of St. Mary’s Hospital Lacor in Uganda, addressing the challenges of grid instability and the need for curtailment in PV-based systems in a real-life scenario. The final sizing analysis showed that a limited size battery is effective in reducing yearly curtailment by 42.9%, limiting frequency peak-to-peak fluctuations by 64.1%. • Integrating adequacy and stability for BESS sizing in MGs of developing countries. • Iterative GA tunes governor parameters to address data scarcity issues. • Python–PowerFactory tool simulates MG transient behavior. • Approach balances cost-effectiveness with system reliability in dynamics.
Caminiti et al. (Wed,) studied this question.