Reinforcement Learning-Enhanced Adaptive Scheduling of Battery Energy Storage Systems in Energy Markets

Reinforcement Learning-Enhanced Adaptive Scheduling of Battery Energy Storage Systems in Energy Markets

Battery Energy Storage Systems (BESSs) play a vital role in modern power grids by optimally dispatching energy according to the price signal. This paper proposes a reinforcement learning-based model that optimizes BESS scheduling with the proposed Q-learning algorithm combined with an epsilon-greedy...

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Bibliographic Details
Main Authors: Yang Liu, Qiuyu Lu, Zhenfan Yu, Yue Chen, Yinguo Yang
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Energies
Subjects:
battery energy storage system
optimal scheduling
reinforcement learning
epsilon-greedy strategy
economic operation
Online Access:https://www.mdpi.com/1996-1073/17/21/5425
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