Vargas-Ferrer, Pedro; Sauma, Enzo; Jalil-Vega, Francisca; (2026) Incorporating intra-hour renewable variability into the design of stand-alone electrolytic hydrogen production systems. Applied Energy , 404 , Article 126982. 10.1016/j.apenergy.2025.126982.

Text Jalil-Vega_Electrolyzers_selection.pdf - Accepted Version Access restricted to UCL open access staff until 25 November 2026. Download (2MB)

Abstract

The integration of variable renewable energy sources (VRE) and electrolytic hydrogen production is a key factor in the cost-effective production of hydrogen. The challenge lies in designing systems where electrolyzers can flexibly adapt to the inherent temporal variability of VRE sources. This relationship is difficult to model, as it involves phenomena across a wide range of timescales, from sub-hourly fluctuations to long-term operational dynamics. In this work, we propose a mathematical model to represent the behavior of a renewable hydrogen production system over its lifetime, incorporating sub-hourly information on the balance between renewable generation and the flexibility of the electrolysis stage. Our approach is unique because it takes detailed sub-hourly behavior and efficiently embeds it into a standard hourly framework. It allows to realistically model the complex interplay between VRE generation and electrolyzer flexibility over a system’s entire lifespan. The model is evaluated at four locations in Chile – two wind-based and two solar PV-based – and a variety of scenarios are constructed considering factors such as the temporal hydrogen dispatch profile, the flexibility of the alkaline electrolysis stage, and the electrolysis technology mix. Based on projected costs for the year 2030, the main results show that the levelized cost of hydrogen across the four sites ranges from $2.96 to $7.59/kgH2, although these values can be significantly affected by the temporal profiles of hydrogen dispatch. It was found that modeling intra-hourly characteristics can alter levelized cost predictions by up to 10%. We also found that the optimal technology mix is influenced by the renewable resource. Specifically, wind-based sites need more flexible proton exchange membrane electrolysis capacity to handle their high sub-hour variability, whereas sites with less variable photovoltaic sources can rely more on alkaline technology.

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