Optimization of a grid-connected hybrid energy system with battery storage for hydrogen production in South Africa

This paper presents an optimization study for a grid-connected hybrid energy system combining wind, solar PV, and a battery energy storage system (BESS) for hydrogen production. To address the intermittency of wind and solar resources, the grid compensates for insufficient energy to meet the electrolyzer load demand, while excess or curtailed energy is stored in the BESS to enhance reliability. The study employs a constrained multi-objective non-dominated genetic algorithm within the Python-based Pymoo framework. The optimization identifies an ideal grid-connected hybrid energy system with minimized electricity costs and maximized efficiency at high reliability. Subsequently, the BESS is optimized to reduce storage and electricity costs while maintaining reliability. The optimized BESS is successfully integrated into the hybrid system. Cost of electricity and reliability are assessed based on time-of-use tariffs and loss of power supply probability, respectively. Using a 2 MW proton exchange membrane electrolyzer, the study achieves a highly efficient hybrid system with the BESS applied to six Renewable Energy Development Zones in South Africa. Including the BESS reduces electricity costs, improves reliability, and lowers curtailment ratios by 40–66%.