Contextual Reinforcement Learning for Offshore Wind Farm Bidding (Papers Track) Spotlight
David Cole (University of Wisconsin-Madison); Himanshu Sharma (Pacific Northwest National Laboratory); Wei Wang (Pacific Northwest National Laboratory)
Abstract
We propose a framework for applying reinforcement learning to contextual two-stage stochastic optimization and apply this framework to the problem of energy market bidding of an off-shore wind farm. Reinforcement learning could potentially be used to learn close to optimal solutions for first stage variables of a two-stage stochastic program under different contexts. Under the proposed framework, these solutions would be learned without having to solve the full two-stage stochastic program. We present initial results of training using the DDPG algorithm and present intended future steps to improve performance.