Green hydrogen projects face significant market risk from volatile electricity costs, uncertain renewable supply, and unstable hydrogen and ammonia prices. We present a two-stage stochastic optimization framework that integrates long-term financial contracts into the joint design and operation of an integrated hydrogen–ammonia plant. The model endogenizes Hydrogen Purchase Agreements (HPAs) and Contracts-for-Difference (CfDs) as first-stage decisions together with capacities of electrolysis, Haber–Bosch synthesis, air separation, storage, and grid connection. Second-stage decisions represent hourly dispatch with detailed material and power balances under scenario-based uncertainty in renewable availability and commodity prices. The objective maximizes expected net present value penalized by Conditional Value at Risk (CVaR) to reflect downside protection and bankability.
The problem is formulated as a mixed-integer linear program. We solve the extensive form via sample average approximation (SAA) and implement an integer L-shaped method with multi-cuts. The master problem includes capacity and contract variables and a linear CVaR reformulation, while scenario subproblems are linear operational models that generate feasibility and optimality cuts. Warm starts from a risk-neutral solution and contract screening are used to improve convergence. Computational experiments report solution quality and convergence behavior as functions of scenario count and risk aversion and evaluate outcomes using expected NPV, CVaR, and probability of loss, including out-of-sample performance assessment.
A case study motivated by export-oriented projects in Chile evaluates contractual portfolios by comparing no contracts, HPA-only, CfD-only, and joint portfolios against risk-neutral and risk-averse baselines. The analysis characterizes how contracting interacts with optimal sizing and operations across regimes and discusses implications for policy programs offering bankable offtake or price-stabilization instruments in green hydrogen–ammonia value chains.
