Emissions and cost tradeoffs of time-matched clean electricity procurement under inter-annual weather variability -- case study of hydrogen production
Michael Giovanniello, Dharik S. Mallapragada

TL;DR
This study evaluates how inter-annual weather variability impacts the cost and emissions of time-matched clean electricity procurement for hydrogen production, highlighting the effects of demand flexibility and policy interactions.
Contribution
It introduces a stochastic capacity expansion model to analyze the cost and emissions tradeoffs of hourly versus annual time-matching requirements under weather variability.
Findings
Hourly TMR incurs higher costs than annual TMR under weather variability.
Demand flexibility reduces the cost premium of hourly TMR.
Integrating H2 demand into RPS constraints lowers costs and emissions.
Abstract
Regulators and voluntary corporate sustainability efforts are increasingly adopting time-matching requirements (TMRs) for clean electricity procurement for large loads, such as data centers, and electricity-intensive fuel production, such as hydrogen. We use a stochastic capacity expansion model (CEM) framework to assess how inter-annual weather variability affects the cost, composition, and emissions of procurement-driven infrastructure to meet annual and hourly TMRs using the case study of a grid-connected hydrogen producer in Texas. Our approach, which relies on co-optimizing investments and hourly operations over nine weather scenarios, reveals that hourly TMR comes at a higher cost premium compared to annual TMR than previously estimated by single-scenario deterministic modeling, while emissions outcomes remain directionally consistent. Demand flexibility and partial hourly TMR…
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Taxonomy
TopicsIntegrated Energy Systems Optimization · Electric Power System Optimization · Smart Grid Energy Management
