Optimal Storage Control for Dynamic Pricing

TL;DR

This paper proposes an optimal online storage control policy for consumers facing dynamic electricity prices, using a data-driven approach to estimate price distributions, enhancing demand-side flexibility in power systems with renewable energy.

Contribution

It introduces a novel data-driven method for adaptive storage control under dynamic pricing, improving demand response strategies in renewable-rich power systems.

Findings

Simulation results confirm the optimality of the proposed control schemes.

The data-driven approach effectively estimates price distributions for better decision-making.

The method enhances flexibility and efficiency in power system operation.

Abstract

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 advice the consumers an optimal online control policy to utilize their storage devices facing dynamic pricing. Towards designing a more adaptive control policy, we devise a data-driven approach to estimating the price distribution. Simulation studies verify the optimality of our proposed schemes.