A holistic risk-aware coordinated framework for coupled hydrogen transport, LOHC storage, and rich renewable grid optimization

The transition to sustainable energy systems is essential for achieving net-zero emissions and addressing climate change. While renewable energy sources (RES) are critical for this transition, their high penetration often leads to significant curtailment and grid stability challenges. Hydrogen energy systems (HES) offer a promising solution by providing grid flexibility and efficiently utilizing excess renewable energy. Although prior studies have explored HES components such as electrolyzers, hydrogen storage, and fuel cells, they often lack the level of detail and computational efficiency required for integration into large-scale optimization models. This paper addresses these gaps by proposing a novel, holistic framework that integrates highly detailed yet computationally efficient models of key HES components, such as proton exchange membrane fuel cells (PEMFCs), alkaline water electrolysis (AWE), and hydrogen transportation systems (HTS) leveraging liquid organic hydrogen carriers (LOHC), with advanced optimization techniques and risk-based demand response (DR) strategies. Advanced linearization techniques are developed for the AWE and PEMFC models to ensure computational efficiency without sacrificing accuracy, enabling scalable optimization of large-scale systems. The framework incorporates a two-stage stochastic programming model enhanced by a hidden Markov process (HMP) to address uncertainties in RES generation and electricity demand. By integrating HTS into the framework, this study highlights the logistical constraints of hydrogen delivery, ensuring a comprehensive approach to system optimization. Validated on the IEEE 24-bus reliability test system (RTS), the proposed framework demonstrates significant improvements in grid performance. Under deterministic conditions, it reduces RES curtailment by 99 %, lowers system costs by 11.2 %, and decreases emissions by 26.44 %. In stochastic settings, the risk-based DR strategy mitigates the impact of uncertainties on hydrogen production and grid operations, enhancing resilience and cost-effectiveness. Comparing coordinated and non-coordinated HES operations reveals the superiority of coordinated models in achieving better performance outcomes. By integrating HES components, HTS, DR strategies, and advanced optimization techniques, this paper provides a robust methodology for optimizing renewable-rich power systems. The findings highlight the transformative potential of HES in reducing curtailment, enhancing flexibility, supporting the supply chain, and facilitating sustainable and resilient energy systems.