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This paper presents a design and evaluates the performance of a power consumption scheduler in smart grid homes or buildings, aiming at reducing the peak load in them as well as in the system-wide power transmission network. Following the task model consist of actuation time, operation length, deadline, and a consumption profile, the scheduler linearly copies the profile entry or maps a combinatory vector to the allocation table one by one according to the task type, which can be either preemptive or nonpreemptive. The proposed scheme expands the search space recursively to traverse all the feasible allocations for a task set. A pilot implementation of this scheduling method reduces the peak load by up to 23.1 % for the given task set. The execution time, basically approximated by O(M^NNP(3^M/2)^NP), where M, N_NP, and NP are the number of time slots, nonpreemptive tasks, and preemptive tasks, respectively, is reduced almost to 2% taking advantage of an efficient constraint processing mechanism which prunes a search branch when the partial peak value already exceeds the current best. In addition, local peak reduction brings global peak reduction by up to 16% for the home-scale scheduling units without any global coordination, avoiding uncontrollable peak resonance.

Keywords: smart grid, demand-side management, energy consumption scheduler, peak load reduction, execution time

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Received May 31, 2011; accepted March 31, 2012.
Communicated by Jiman Hong, Junyoung Heo and Tei-Wei Kuo.
^* This research was supported by the MKE (The Ministry of Knowledge Economy), Republic of Korea, under IT/SW Creative research program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2012-(H0502-12-1002)).