Optimizing integrated hydrogen technologies and demand response for sustainable multi-energy microgrids

Abstract

In response to the imperative of achieving net-zero emissions, Multi-Energy Microgrids (MEMGs) have emerged as pivotal infrastructures. This study advocates for precise scheduling of integrated energy resources within MEMGs, incorporating energy conversion facilities and optimizing a hybrid Demand Response (DR) scheme. The integration of hydrogen-based technologies, such as hydrogen power transmission units, hydrogen storage systems (HSSs), fuel cells, and battery electric vehicles (BEVs), offers unprecedented opportunities to mitigate carbon emissions effectively. The approach leverages a novel multi-objective optimization method, the Horse Herd Optimization Algorithm (HOA), complemented by fuzzy sampling and Pareto criteria, to address complex objectives including minimizing operational costs and emissions. The developed energy management model facilitates continuous control mechanisms for MEMG operators, accommodating both flexible and inflexible energy demands. Importantly, the study navigates uncertainties in electricity market prices, energy demand, and renewable power generation through robust stochastic modeling and multiple probabilistic scenarios. This study achieves a significant 18% reduction in operational costs and a remarkable 25% decrease in greenhouse gas emissions, leveraging advanced technologies like HSSs, fuel cells, and BEVs within MEMGs. The integration of these technologies also enables up to 15% improvement in energy efficiency and a 12% increase in revenue generation through optimized energy trading strategies.