Power consumption scheduling for peak load reduction in smart grid homes

Abstract

This paper presents a design and evaluates the performance of a power consumption scheduler in smart grid homes, aiming at reducing the peak load in individual homes 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 copies or maps the profile 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 greatly depends on the search space of a preemptive task, as its time complexity is estimated to be O (MNnp · (MM/2)Np), where M, Nnp, and Np are the number of time slots, preemptive tasks, and nonpreemptive tasks, respectively. However, it can not only be reduced almost to 2% but also made stable with a basic constraint processing mechanism which prunes a search branch when the partial peak value already exceeds the current best.