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The smart power grid aims at harnessing information and communicationtechnologies to enhance reliability and enforce sensible use of energy. Itsrealization is geared by the fundamental goal of effective management of demandload. In this work, we envision a scenario with real-time communication betweenthe operator and consumers. The grid operator controller receives requests forpower demands from consumers, with different power requirement, duration, and adeadline by which it is to be completed. The objective is to devise a powerdemand task scheduling policy that minimizes the grid operational cost over atime horizon. The operational cost is a convex function of instantaneous powerconsumption and reflects the fact that each additional unit of power needed toserve demands is more expensive as demand load increases.First, we study theoff-line demand scheduling problem, where parameters are fixed and known. Next,we devise a stochastic model for the case when demands are generatedcontinually and scheduling decisions are taken online and focus on long-termaverage cost. We present two instances of power consumption control based onobserving current consumption. First, the controller may choose to serve a newdemand request upon arrival or to postpone it to the end of its deadline.Second, the additional option exists to activate one of the postponed demandswhen an active demand terminates. For both instances, the optimal policies arethreshold based. We derive a lower performance bound over all policies, whichis asymptotically tight as deadlines increase. We propose the ControlledRelease threshold policy and prove it is asymptotically optimal. The policyactivates a new demand request if the current power consumption is less than athreshold, otherwise it is queued. Queued demands are scheduled when theirdeadline expires or when the consumption drops below the threshold.

Control and Optimization Meet the Smart Power Grid - Scheduling of Power Demands for Optimal Energy Management