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Energy Storage Price Arbitrage via Opportunity Value Function Prediction. (arXiv:2211.07797v1 [eess.SY])
cs.LG updates on arXiv.org arxiv.org
This paper proposes a novel energy storage price arbitrage algorithm
combining supervised learning with dynamic programming. The proposed approach
uses a neural network to directly predicts the opportunity cost at different
energy storage state-of-charge levels, and then input the predicted opportunity
cost into a model-based arbitrage control algorithm for optimal decisions. We
generate the historical optimal opportunity value function using price data and
a dynamic programming algorithm, then use it as the ground truth and historical
price as predictors to …
arxiv energy energy storage function prediction price storage value