Peak shaving with hydrogen energy storage: From stochastic control to experiments on a 4 MWh facility

Marta Fochesato, Christian Peter, Lisa Morandi and John Lygeros

Applied Energy, 2024, vol. 376, issue PA, No S0306261924013485

Abstract: The formation of power peaks caused by the stochastic nature of the electric vehicles (EVs) charging process is raising concerns related to the stability of the power grid. In this work, we consider an EV charging station equipped with a hydrogen-based energy storage system (HESS) and on-site renewable power generation, and we offer an experimental demonstration of its potential in reducing the power peak of the EV charging station, despite uncertainty in the demand. Our contributions are as follows: (1) we derive a complete system description of a real 4 MWh HESS, and (2) we develop a stochastic model-based receding horizon controller that jointly schedules the charging process and the HESS operation to minimize the power peak. The proposed approach is validated both in simulation and via experiments that demonstrate (i) excellent performance, with an average daily peak reduction of 49.2% with respect to the benchmark, and (ii) scalable run times, making it amenable to real-time operations even in the large EV penetration regime.

Keywords: Peak shaving; Electric vehicles; Hydrogen energy storage systems; Stochastic predictive control (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123965

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