Applications of Reinforcement Learning in Deregulated Power Market: A Comprehensive Review. (arXiv:2205.08369v2 [cs.LG] UPDATED)

The increasing penetration of renewable generations, along with the
deregulation and marketization of power industry, promotes the transformation
of power market operation paradigms. The optimal bidding strategy and
dispatching methodology under these new paradigms are prioritized concerns for
both market participants and power system operators, with obstacles of
uncertain characteristics, computational efficiency, as well as requirements of
hyperopic decision-making. To tackle these problems, the Reinforcement Learning
(RL), as an emerging machine learning technique with advantages compared with
conventional optimization tools, …

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