Smart grid technology has the opportunity to revolutionize our control over power consumption. Currently power-requesting jobs are scheduled in an on-demand fashion; power draw begins when the consumer requests power (turns on an appliance) and ends when the job is complete (appliance is turned off). Often such jobs may have some flexibility in their starting times (e.g. a dishwasher or electric vehicle charger). We consider the problem scheduling power jobs so as to minimize peak demand. We first consider a general version of the problem in which the job intervals can be staggered. While the problem is known to be NP-hard (we show it is even NP-hard to approximate), we provide an effective new heuristic algorithm. For several important special cases, we provide new constant-factor approximation algorithms that improve on previous results. Simulation results using real power job data show that our algorithms improve on existing methods.
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Yaw et al. (2014) studied this question.