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Title: Online EV Scheduling Algorithms for Adaptive Charging Networks with Global Peak Constraints
Electricity bill constitutes a significant portion of operational costs for large scale data centers. Empowering data centers with on-site storages can reduce the electricity bill by shaping the energy procurement from deregulated electricity markets with real-time price fluctuations. This work focuses on designing energy procurement and storage management strategies to minimize the electricity bill of storage-assisted data centers. Designing such strategies is challenging since the net energy demand of the data center and electricity market prices are not known in advance, and the underlying problem is coupled over time due to evolution of the storage level. Using competitive ratio as the performance measure, we propose an online algorithm that determines the energy procurement and storage management strategies using a threshold based policy. Our algorithm achieves the optimal competitive ratio of as a function of the price fluctuation ratio. We validate the algorithm using data traces from electricity markets and data-center energy demands. The results show that our algorithm achieves close to the offline optimal performance and outperforms existing alternatives.%  more » « less
Award ID(s):
1752362 1736448 1711188
NSF-PAR ID:
10132913
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
IEEE Transactions on Sustainable Computing
ISSN:
2377-3790
Page Range / eLocation ID:
1 to 1
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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