Optimized hybrid storage standalone microgrid with electrical, heat, and hydrogen loads based on stochastic photovoltaic modelling

The challenges posed by the intermittency of renewable energy generation and the mismatch between energy supply and demand have been addressed through hybrid energy storage solution for standalone microgrids. It is hypothesized that a combination of battery, thermal, and hydrogen storage systems can cost-effectively fulfill electrical, thermal, and hydrogen demands. An optimization framework was developed and implemented using the Gurobi solver to determine the optimal sizing of two microgrid configurations. Stochastic hourly solar irradiance data from Abu Dhabi, UAE, were utilized in the analysis. In the proposed configuration, thermal energy storage (TES) was integrated with a Stirling engine (SE), alongside battery and hydrogen storage components. Through optimization, a 59% reduction in battery capacity was achieved compared to the baseline configuration. Additionally, the levelized cost of energy was reduced from 0.252 to 0.178 USD/kWh. It was found that the cost reduction was primarily driven by decreased capacities of batteries and electrolyzers, while fuel cells remained economically unviable under current pricing. A sensitivity analysis was conducted, which highlighted the greater impact of capital cost reductions compared to operational costs. The impact of solar tracking was also evaluated, revealing that single-axis systems reduce PV area by 16% with only a moderate LCOE increase. Based on these findings, the adoption of hybrid energy storage systems, specifically incorporating TES and SE, is recommended to enhance the cost-effectiveness and reliability of renewable-powered standalone microgrids.