Hedging Hydrogen: Planning and Contracting Under Uncertainty for a Green Hydrogen Producer
Owen Palmer, Hugo Radet, Simon Camal, Jalal Kazempour, Robin Girard
TL;DR
This paper tackles the financial risk inherent in green hydrogen production under uncertain demand, renewable output, and energy prices by proposing a market-focused 2-stage stochastic model that co-optimises electrolyser sizing and energy hedging under Hydrogen Purchase Agreements (HPAs). It introduces a set of Planning Policies, including deterministic, risk-neutral, and risk-averse stochastic variants, and evaluates them using a rigorous in-sample/out-of-sample framework with CVaR-based risk measures. Key findings show that deterministic planning can incur up to ~30% higher production costs under stress tests, while stochastic risk-averse planning improves both mean and worst-case LCOH; subsidies and contract structure further influence hedging and storage needs. The work also cautions against no-resale formulations which bias hedging choices, and demonstrates how hedging strategies and capacity choices should be jointly optimised to maintain competitive LCOH in a developing green hydrogen market, with practical implications for project finance and contract design. All mathematical expressions are presented with proper notation, including $J^d$, $J^o_s$, and CVaR$_{\alpha}$ with $\alpha=0.99$, to ensure precise formulation of the optimisation framework.
Abstract
Green hydrogen production by water electrolysis using renewable electricity is considered essential for decarbonisation of certain sectors of the global economy, however development of the industry is lagging behind expectations due to the perceived financial risk for individual projects. This risk stems from a number of uncertainties, including future hydrogen demand, variable renewable energy sources, and volatile energy market prices. The interaction of these uncertainties is complex, yet the analysis of hydrogen projects is often carried out using simplified modelling that often omits uncertainty and/or energy hedging practices which are typical for intensive power consumers. In this study, we define a set of planning methods (planning policies) in order to compare the effectiveness of different modelling approaches. We propose a 2-stage market-focused stochastic program to represent a hydrogen producer supplying an industrial customer through a hydrogen offtake contract (a Hydrogen Purchase Agreement, or HPA). The model can be used to obtain equipment sizing decisions, as well as energy hedging decisions using Power Purchase Agreements (PPA's) and power futures. We find that for some HPA contract types, failure to use stochastic modelling can lead to planning decisions that result in 30% higher production costs during scenario stress-testing for the same project. This could lead to some projects being discarded by developers, incorrectly deemed to be unviable due to cost projections being too high. The results also show the importance of HPA contract volumetric obligations in limiting demand uncertainty.