An optimization framework for data centers to minimize electric bill under day-ahead dynamic energy prices while providing regulation services

Considering the growing number of Internet and cloud computing data centers in operation today and the high, yet flexible· data center electric load, data centers can be good candidates to offer ancillary services and respond to regulation signals in a smart grid This paper considers a problem whereby the smart grid employs both day-ahead dynamic energy prices and regulation signals to incentivize (cloud) data centers to simultaneously reduce their energy consumptions and participate in an ancillary service market A data center controller schedules task dispatch and performs resource allocation in order to minimize the overall cost, which is the total electricity cost based on time-of-use energy prices minus any monetary compensations that data center may receive due to offering ancillary services. Moreover, the data center must satisfy average latency requirements in processing requests as specified in service-level agreements with clients. A two-tier hierarchical solution is presented for the data center controller, which achieves optimality in minimizing the overall cost with polynomial time complexity. Experimental results on Google trace demonstrate the effectiveness of the proposed solution in minimizing the overall cost in the data center.

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