Exploiting Electrolyzer Flexibility via Multiscale Model Predictive Control Cross Heterogeneous Energy Markets
Zhichao Chen (1), Hongyuan Sheng (2), Hao Wang (3), Jiaze Ma (1),((1) Department of Systems Engineering, City University of Hong Kong, (2) Department of Chemistry, Fudan University, (3) Department of Automation, Zhejiang University)

TL;DR
This paper presents a multiscale model predictive control strategy enabling electrolyzers to actively participate in both day-ahead and real-time electricity markets, significantly reducing costs and potentially generating profit for green hydrogen production.
Contribution
It introduces a dynamic, multi-scale market participation framework for electrolyzers, leveraging market arbitrage to lower costs and increase profitability in green hydrogen production.
Findings
Near-zero or negative net electricity costs achieved.
Electrolyzers can profitably buy low in RTM and sell high back to the grid.
Significant cost reductions demonstrated in realistic scenarios.
Abstract
Green hydrogen production via electrolysis is crucial for decarbonization but faces significant economic hurdles primarily due to the high cost of the electricity. However, current electrolyzer-based hydrogen production processes predominantly rely on the single-scale Day-Ahead Market (DAM) for electricity procurement, failing to fully exploit the economic benefits offered by multi-scale electricity market that integrates both the DAM and the Real-Time Market (RTM), thereby eliminating the opportunity to reduce the overall cost. To mitigate this technical gap, this research investigates a dynamic operational strategy enabling electrolyzers to strategically navigate between the DAM and RTM to minimize net operation costs. Using a rolling horizon optimization framework to coordinate bidding and operation, we demonstrate a strategy where electrolyzers secure primary energy via exclusive…
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