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Temporal-Aware Deep Reinforcement Learning for Energy Storage Bidding in Energy and Contingency Reserve Markets
March 1, 2024, 5:43 a.m. | Jinhao Li, Changlong Wang, Yanru Zhang, Hao Wang
cs.LG updates on arXiv.org arxiv.org
Abstract: The battery energy storage system (BESS) has immense potential for enhancing grid reliability and security through its participation in the electricity market. BESS often seeks various revenue streams by taking part in multiple markets to unlock its full potential, but effective algorithms for joint-market participation under price uncertainties are insufficiently explored in the existing research. To bridge this gap, we develop a novel BESS joint bidding strategy that utilizes deep reinforcement learning (DRL) to bid …
abstract arxiv battery bidding cs.lg cs.sy eess.sy electricity energy energy storage grid market markets math.oc multiple part reinforcement reinforcement learning reliability revenue security storage temporal through type
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