Electrolysis plant size optimization and benefit analysis of a far offshore wind-hydrogen system based on information gap decision theory and chance constraints programming. (29th January 2022)

• Record Type: Journal Article
• Authors: Jiang, Yuewen; Huang, Weijie; Yang, Guoming
• Is Part Of: International journal of hydrogen energy. Volume 47:Number 9(2022)
• Page Start: 5720
• Page End: 5732
• Publication Date: 2022-01-29
• Subjects: Far offshore wind-hydrogen project -- Dynamic efficiency of electrolyzer -- IGDT-CCP -- Electrolysis plant size optimization -- Economic viability; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2021.11.211
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: In order to explore far offshore wind resource, it is an eloquent pathway to develop a far offshore wind-hydrogen project. The size optimization of electrolysis plant is beneficial and conducive to upgrade wind-hydrogen projects' cost-effectiveness. This paper aims to perform size optimization as well as a techno-economic assessment to contribute to investors' decision-making. Firstly, the efficiency methodology of Proton Exchange Membrane (PEM) electrolyzer is deduced in the presence of aging and changing operation powers since it directly impacts on the productivity of hydrogen. Secondly, a chance constrained programming (CCP) model of size optimization is established to reach a benchmark maximum net present value (NPV) for the wind-hydrogen project, taking into account random fluctuations of offshore wind power output and replacement price of electrolyzer which is the key device of the hydrogen system, and the aging of electrolyzer. Further, for the pursuit of evaluating the influence of hydrogen sale price's irregular fluctuations on the economic feasibility, information gap decision theory (IGDT) is exerted to assess acceptable hydrogen price ranges from investors' point based on acceptable NPVs, taking maximum hydrogen price uncertainty as the upper layer objective and minimum acceptable NPV as the lower layer objective, and the delicate IGDT-CCP prototype is evolved with CCP constraint conditions. The particle swarm optimization of stochastic simulation is adopted to solve both CCP and IGDT-CCP models. Finally, detailed results are demonstrated and compared through a study case, including optimum size in view of multi scenarios, economic viability and the acceptable hydrogen prices. Highlights: Size optimization for a far offshore wind-hydrogen system is developed by IGDT-CCP. Dynamic efficiency of electrolyzer considering the aging factors is derived. Fluctuations of hydrogen sale price based on expected NPVs are quantified by IGDT. Probabilistic wind power output and eletrolyzer replacement costs are considered. Compare the differences of two efficiency features of electrolyzer on NPVs.