Publication Type

Journal Article

Version

submittedVersion

Publication Date

7-2013

Abstract

This paper presents transformative energy-saving schedule-leveraging agent (TESLA), an agent for optimizing energy usage in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. This paper provides four key contributions: (i) online scheduling algorithms, which are at the heart of TESLA, to solve a stochastic mixed integer linear program for energy-efficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; (iii) an extensive analysis on energy savings achieved by TESLA; and (iv) surveys of real users which indicate that TESLA’s assumptions of user flexibility hold in practice. TESLA was evaluated on data gathered from over 110,000 meetings held at nine campus buildings during an 8-month period in 2011–2012 at the University of Southern California and Singapore Management University. These results and analysis show that, compared to the current systems, TESLA can substantially reduce overall energy consumption.

Keywords

Energy, Sustainable multiagent systems, Energy-oriented scheduling, Scheduling flexibility

Discipline

Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering

Research Areas

Intelligent Systems and Optimization

Publication

Autonomous Agents and Multi-Agent Systems

Volume

28

Issue

4

First Page

605

Last Page

636

ISSN

1387-2532

Identifier

10.1007/s10458-013-9234-0

Publisher

Springer Verlag

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1007/s10458-013-9234-0

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