Data Center Demand Response Pricing Using Inverse Optimization

In Demand Response (DR), consumers regulate their power based on requests from an energy supplier. Data Centers (DC) are among the promising candidates to perform DR to help stabilize the power grid due to their flexibility and controllability. In this work, we present a novel framework for offering incentives to DCs so they can dynamically adjust their electricity consumption and provide DR to the grid. Coordination between an Independent System Operator (ISO) and DCs is done through pricing where the ISO computes optimal prices which elicit desired responses from the DCs. We model DCs using realistic cost functions based on Quality of Service (QoS) requirements of the DC workloads and present an inverse optimization approach to cost function parameter estimation for precise and efficient pricing along with simulation results that highlight the strength of our approach.