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Abstract
This study developed a multi-objective optimization framework for configuring independent multi-energy hubs (MEHs) that integrate electricity, heat, and hydrogen systems. The model addressed uncertainties in renewable energy sources, including wind and solar, using a hybrid particle swarm optimization (PSO) and grasshopper optimization algorithm (GOA) to achieve high levels of reliability, economic efficiency, and renewable energy utilization (REU). A robust capacity configuration strategy was designed to focus on balancing economic and environmental goals while enhancing system reliability. The integration of hydrogen storage and methanation systems minimized the curtailment of renewable energy and improved energy flexibility. The proposed approach employed stochastic optimization techniques with scenario generation and reduction to model uncertainties effectively. Advanced coordination between renewable energy sources, combined heat and power (CHP) units, and energy storage systems ensures efficient dispatch of electrical, thermal, and hydrogen energy under dynamic operating ...
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