Data Center Control Strategy for Participation in Demand Response Programs

Abstract

This paper presents a framework for the optimal operation of data centers, leveraging their heating, ventilation, and air conditioning unit, delay-tolerant information technology workload and battery storage system for participating in demand response programs. In this context, an model predictive control based control framework has been developed that guarantees the reliable operation of the data centers core activities. We derive a modeling approach to represent the dynamics of the data centers subsystems and validate it for a data center test bed via practical experiments. Hereby, the thermal subsystem leads to deviations of less than 0.60 K in the modeled outlet temperature. The validated model is used for incremental prototyping of the proposed control via simulations under uncertainties. The results demonstrate a mean absolute error of the relative deviations between the data center consumption and the target load profile of 2.71% for an incentive-based scenario and a cost reduction of 3.86% for a price-based scenario.