TESLA: An extended study of an energy-saving agent that leverages schedule flexibility

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 contributio...

Full description

Saved in:
Bibliographic Details
Main Authors: KWAK, Jun Young, VARAKANTHAM, Pradeep, Maheswaran, Rajiv, Tambe, Milind, Becerik-Gerber, Burcin
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2013
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/1931
https://ink.library.smu.edu.sg/context/sis_research/article/2930/viewcontent/TESLA_JAAMAS_R1_20_1_.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English
id sg-smu-ink.sis_research-2930
record_format dspace
spelling sg-smu-ink.sis_research-29302019-07-23T00:48:11Z TESLA: An extended study of an energy-saving agent that leverages schedule flexibility KWAK, Jun Young VARAKANTHAM, Pradeep Maheswaran, Rajiv Tambe, Milind Becerik-Gerber, Burcin 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. 2013-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1931 info:doi/10.1007/s10458-013-9234-0 https://ink.library.smu.edu.sg/context/sis_research/article/2930/viewcontent/TESLA_JAAMAS_R1_20_1_.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Energy Sustainable multiagent systems Energy-oriented scheduling Scheduling flexibility Artificial Intelligence and Robotics Operations Research, Systems Engineering and Industrial Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Energy
Sustainable multiagent systems
Energy-oriented scheduling
Scheduling flexibility
Artificial Intelligence and Robotics
Operations Research, Systems Engineering and Industrial Engineering
spellingShingle Energy
Sustainable multiagent systems
Energy-oriented scheduling
Scheduling flexibility
Artificial Intelligence and Robotics
Operations Research, Systems Engineering and Industrial Engineering
KWAK, Jun Young
VARAKANTHAM, Pradeep
Maheswaran, Rajiv
Tambe, Milind
Becerik-Gerber, Burcin
TESLA: An extended study of an energy-saving agent that leverages schedule flexibility
description 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.
format text
author KWAK, Jun Young
VARAKANTHAM, Pradeep
Maheswaran, Rajiv
Tambe, Milind
Becerik-Gerber, Burcin
author_facet KWAK, Jun Young
VARAKANTHAM, Pradeep
Maheswaran, Rajiv
Tambe, Milind
Becerik-Gerber, Burcin
author_sort KWAK, Jun Young
title TESLA: An extended study of an energy-saving agent that leverages schedule flexibility
title_short TESLA: An extended study of an energy-saving agent that leverages schedule flexibility
title_full TESLA: An extended study of an energy-saving agent that leverages schedule flexibility
title_fullStr TESLA: An extended study of an energy-saving agent that leverages schedule flexibility
title_full_unstemmed TESLA: An extended study of an energy-saving agent that leverages schedule flexibility
title_sort tesla: an extended study of an energy-saving agent that leverages schedule flexibility
publisher Institutional Knowledge at Singapore Management University
publishDate 2013
url https://ink.library.smu.edu.sg/sis_research/1931
https://ink.library.smu.edu.sg/context/sis_research/article/2930/viewcontent/TESLA_JAAMAS_R1_20_1_.pdf
_version_ 1770571687972044800