Optimal operation management of distributed and centralized electrolysis-based hydrogen generation and storage systems

The interest in producing hydrogen from electricity has been recently identified as a potential means for large-scale energy storage, proliferation of hydrogen mobility, and decarbonization of several processes that require hydrogen. Such interest is growing due to the increase of the renewable energy penetration levels and the significant drop in their costs. The rollout of hydrogen-based applications increases the global demand for hydrogen and thus necessitates the deployment of reliable and cost-effective hydrogen infrastructure, i.e., generation, storage, and delivery. Based on its application, hydrogen fuel could be generated and stored in either distributed onsite or centralized offsite compositions. Yet, the operation of both distributed and centralized electrolysis-based hydrogen generation and storage systems (eHGSS) needs to be optimally managed not only to supply the hydrogen demand but also to provide appropriate services to improve the flexibility of power grids. To that end, this paper aims to develop a unified formulation for the optimal operation management of distributed and centralized eHGSS. The objective of the developed formulation is to maximize the net revenue of eHGSS via sale of the produced hydrogen and participation in the provision of multiple grid's ancillary services. The developed optimization model is utilized to conduct qualitative techno-economic analysis for the two composition forms of eHGSS, i.e., centralized and distributed. The applications of the two arrangements under various operating scenarios including sole services to the hydrogen market and concurrent ancillary services provision to an electricity market are numerically investigated. These studies are significantly valuable to private investors and grid operators that would like to assess the techno-economic variability of distributed and centralized eHGSS. The superiority of the proposed operation management model has been substantiated with numerical investigation, discussions, and analysis.