Optimal Storage Control for Dynamic Pricing

Renewable energy brings huge uncertainties to the power system, which challenges the traditional power system operation with limited flexible resources. One promising solution is to introduce dynamic pricing to more consumers, which, if designed properly, could enable an active demand side. To further exploit flexibility, in this work, we seek to advise the consumers of an optimal online control policy to utilize their storage devices facing dynamic pricing. We prove that using the one-shot load decomposition technique, a simple threshold policy is enough to achieve the online optimality. Towards designing a more adaptive control policy, we devise a data-driven approach to estimating the price distribution.