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The smart power grid harnesses information and communication technologies to enhance reliability and enforce sensible use of energy through effective management of demand load. We envision a scenario with real-time communication between the grid operator and the consumers. The operator controller receives consumer power demand requests with different power requirements, durations, and deadlines by which they are to be activated. The objective of the operator is to devise a power demand task scheduling policy that minimizes the grid operational cost over a time horizon. The cost is a convex function of total instantaneous power consumption and reflects the fact that each additional unit of power needed to serve demands is more expensive as the demand load increases. First, we study the off-line demand scheduling problem, where parameters are known a priori. If demands can be scheduled preemptively, the problem is a load balancing one, and we present an iterative algorithm that optimally solves it. If demands need to be scheduled non-preemptively, the problem is a bin packing one.
Koutsopoulos et al. (Tue,) studied this question.