Renewable-Colocated Green Hydrogen Production: Optimality, Profitability, and Policy Impacts

TL;DR

This paper develops a closed-form, threshold-based framework for optimizing online production and market participation of a Renewable-Colocated Hydrogen Producer (RCHP) that leverages onsite renewable energy for hydrogen production and wholesale grid services. It introduces four market models (M0,M1-p,M1-c,M2) and derives a linear, piecewise optimal production policy characterized by LMP thresholds $\underline{\pi}^{\sf LMP}$ and $\overline{\pi}^{\sf LMP}$ and a capacity-matching ratio $\kappa=Q_H/Q_R$, yielding $Q^*_H=\kappa Q_R$ under profitability. The paper provides a stochastic profitability analysis over $n$ periods, linking expected operating profit to nameplate capacities under a budget constraint, with proofs that colocation yields a profit advantage. Empirical studies across NYISO, CAISO, and MISO show that the prosumer model (M2) generally maximizes profitability, with profitability sensitive to hydrogen price, subsidies, resource mix (wind vs solar), and regional market characteristics, underscoring policy and design implications for scalable green hydrogen deployment.

Abstract

We study the optimal green hydrogen production and energy market participation of a renewable-colocated hydrogen producer (RCHP) that utilizes onsite renewable generation for both hydrogen production and grid services. Under deterministic and stochastic profit-maximization frameworks, we analyze RCHP's multiple market participation models and derive closed-form optimal scheduling policies that dynamically allocate renewable energy to hydrogen production and electricity export to the wholesale market. Analytical characterizations of the RCHP's operating profit and the optimal sizing of renewable and electrolyzer capacities are obtained. We use real-time renewable production and electricity price data from three independent system operators to assess impacts from market prices and environmental policies of renewable energy and green hydrogen subsidies on RCHP's profitability.

Figures (12)

• Figure 1: Schematic of a flexible RCHP.
• Figure 2: (a) Optimal hydrogen production policy for flexible RCHP (M2). (b) Operating profit heatmap as the function of the electrolyzer and renewable nameplate capacities.
• Figure 3: Optimal production plans of RCHP under different models when $Q_{\hbox{\tiny\sf H}}<Q_{\hbox{\tiny\sf R}}$. See Sec. \ref{['sec:Appendix_OptimalPlan']} for the $Q_{\hbox{\tiny\sf H}}>Q_{\hbox{\tiny\sf R}}$ case.
• Figure 4: Annual operating profit in 2022 as a function of solar generation nameplate capacity (x-axis) and electrolyzer nameplate capacity (y-axis). Solid black: Break-even line. Green dashed: Optimal electrolyzer nameplate capacity as a function of solar generation nameplate capacity. (Top: hydrogen price of $1/kg; bottom: $4/kg.)
• Figure 5: Mean annual operating profit of the RCHP under varying hydrogen prices (2012-2022), with error bars indicating inter-annual variability. (Left: (45 MW, 20 MW) wind-colocated hydrogen producer; right: (45 MW, 20 MW) solar-colocated hydrogen producer.)

Theorems & Definitions (9)

• Theorem 1
• Proposition 1: Expected Operating Profit
• Proposition 2: Colocation Profit Advantage
• Theorem 2: Profitability Characterization
• Theorem 3: Optimal Nameplate Capacity
• proof : Proof of Theorem \ref{['Thm:solution']}
• proof : Proof of Proposition \ref{['Prop:linear']}
• proof : Proof of Theorem \ref{['Thm:profitability']}
• proof