525. Risk-constrained two-stage demand response scheduling for green hydrogen production
Invited abstract in session WB-12: Chemical and Energy Systems Optimization, stream Applications: AI, uncertainty management and sustainability.
Wednesday, 10:30-12:30Room: B100/8009
Authors (first author is the speaker)
| 1. | Gabriel Patron
|
| Imperial College London |
Abstract
Hydrogen is increasingly being incorporated into global net zero plans with a
particular emphasis on electrolysis-based “green” hydrogen. When integrated with
the power grid, the demand response scheduling of a hydrogen production plant
can be posed as a cost minimization problem that relies on having predicted
electricity price signals as inputs. In reality, these price signals are often
subject to considerable uncertainty and, especially when participating in
several power markets (e.g., day-ahead, intraday), the performance of a
deterministic scheduling solution can be significantly suboptimal. In this
presentation, we propose a stochastic risk-aware formulation to determine the
optimal hydrogen production schedule in a multi-market context with uncertain
price signals. A multi-stage formulation allows for recourse actions upon price
perturbations and prediction errors, while risk-aware objective functions such
as conditional value-at-risk (CVaR) can minimize shortfall. Further, the
proposed approach determines the proportion of participation in each power
market.
Keywords
- Stochastic optimization
- Optimization under uncertainty
- Linear and nonlinear optimization
Status: accepted
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