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<p>This study presents a novel approach to modeling hydrogen production, demand, and storage in a Power-to-Hydrogen (PtH) system, leveraging a Weibull cumulative distribution function (CDF) framework to capture renewable energy variability. The model integrates stochastic elements directly into the hydrogen production and storage processes, effectively addressing the uncertainties inherent in renewable energy inputs. By employing a hybrid Weibull-Gamma demand model and incorporating probabilistic constraints, the proposed approach enables dynamic adjustment of hydrogen production and storage, optimizing both reliability and cost. Comparative analysis shows that this model offers significant advantages over conventional deterministic methods, providing a resilient and cost-effective solution for renewable-driven hydrogen systems under varying conditions.</p>

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Power-to-Hydrogen Systems: Stochastic Optimization for Renewable Energy Integration

  • 期刊论文

  • 发表日期：

    2026年1月13日

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  • Neeraj Dhanraj Bokde

摘要

This study presents a novel approach to modeling hydrogen production, demand, and storage in a Power-to-Hydrogen (PtH) system, leveraging a Weibull cumulative distribution function (CDF) framework to capture renewable energy variability. The model integrates stochastic elements directly into the hydrogen production and storage processes, effectively addressing the uncertainties inherent in renewable energy inputs. By employing a hybrid Weibull-Gamma demand model and incorporating probabilistic constraints, the proposed approach enables dynamic adjustment of hydrogen production and storage, optimizing both reliability and cost. Comparative analysis shows that this model offers significant advantages over conventional deterministic methods, providing a resilient and cost-effective solution for renewable-driven hydrogen systems under varying conditions.