Optimizing electrolyzer investments for green hydrogen production under market and technology uncertainties

Abstract

Motivated by increasing curtailment of renewable energy, negative electricity prices, and growing importance of green hydrogen, many renewable energy producers are considering investing in electrolyzers to produce and sell green hydrogen. However, electrolyzers are still expensive technologies and their profitability is affected by uncertainties in electricity and hydrogen prices, investment cost, and curtailment levels, all of which fluctuate over time. In this paper, we study optimal electrolyzer investments as a real option problem where a renewable energy producer can decide over a planning horizon whether investing in an electrolyzer, its capacity, and whether to couple it with a storage system. Since the resulting dynamic stochastic optimization problem is intractable to solve to optimality, we leverage state-of-the-art approximate dynamic programming (ADP) methods to compute near-optimal investment policies and dual bounds. A computational study is conducted, offering insights into the investment option value under traditional and new ADP policies, and optimal investment decisions in relation to the evolution of the uncertainties, including the expected time to invest, asset size, and optimal electrolyzer utilization. The findings can be valuable for renewable energy producers interested in green hydrogen but lacking tools and insights to assess investment decisions in a complex and evolving energy landscape.