When to reap and when to sow - lowering peak usage with realistic batteries

Authors:
Amotz Bar-Noy;Yi Feng;Matthew P. Johnson;Ou Liu
Affiliations:
Department of Computer Science, The Graduate Center of the City University of New York;Department of Computer Science, The Graduate Center of the City University of New York;Department of Computer Science, The Graduate Center of the City University of New York;Department of Computer Science, The Graduate Center of the City University of New York
Venue:
WEA'08 Proceedings of the 7th international conference on Experimental algorithms
Year:
2008

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Abstract

In some energy markets, large clients are charged for both total energy usage and peak energy usage, which is based on the maximum single energy request over the billing period. The problem of minimizing peak charges was recently introduced as an online problem in [4], which gave optimally competitive algorithms. In this problem, a battery (previously assumed to be perfectly efficient) is used to store energy for later use. In this paper, we extend the problem to the more realistic setting of lossy batteries, which lose to conversion inefficiency a constant fraction of any amount charged (e.g. 33%). For this setting, we provide efficient and optimal offline algorithms as well as possibly competitive online algorithms. Second, we give factor-revealing LPs, which provide some quasi-empirical evidence for competitiveness. Finally, we evaluate these and other, heuristic algorithms on real and synthetic data.