Is One Year Enough? The Impact of Availability of Wind Data on Optimal Wind-to-hydrogen System Design

Decreasing prices of renewable energy sources (RES), like wind and solar, in recent years have led to numerous studies on the optimal design of RES for hydrogen production in an off-grid system. RES are intermittent and vary from year to year. Yet, most of the studies still consider only a random single weather year for system design, often ignoring the impact of input weather data on system design and its performance. This study evaluates, for a gaseous hydrogen system, the impact of input weather data on optimal system design, system reliability and system costs. Random single-year, averaged, and multiple years of weather data from 1994 to 2021 are considered. Further, multiple years of weather data are considered using a novel method of near-optimal solutions and a maximum of near-optimal solutions. The results show that using the maximum of near-optimal solutions method improves system reliability by as much as 96 % when used in other weather years. The system costs are reduced to 0.1 €/kgH2 in other weather years at the expense of an oversized system design. Meanwhile, a wind-to-hydrogen system (WHS) designed using randomly selected single-year weather data results in a significantly undersized system with lower reliability (3.5 %) and higher cost variability (up to 4.7 €/kgH2) in other weather years. On the other hand, averaging the weather data smoothens the weather fluctuations and always results in a WHS design with lower reliability and higher cost variability than a WHS designed using multi-year weather data values. The results reveal that the size of input weather dataset significantly impacts the system design and its performance. The maximum of near-optimal solutions method proposed in this study provided significantly lower computational time with improved system performance (reliability and cost variability) in comparison to solving the WHS using multiple years of weather data outright.