Why TESLA Works: Innovative Agent-based Application Leveraging Schedule Flexibility for Conserving Energy

Citation:

Jun-young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Yu-Han Chang, Milind Tambe, Burcin Becerik-Gerber, and Wendy Wood. 2013. “Why TESLA Works: Innovative Agent-based Application Leveraging Schedule Flexibility for Conserving Energy .” In Workshop on Multiagent-based Societal Systems (MASS) at AAMAS.

Abstract:

This paper presents TESLA, an agent-based application for optimizing the energy use in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. TESLA provides two key contributions: (i) three online scheduling algorithms that consider flexibility of people’s preferences for energy-efficient scheduling of incrementally/dynamically arriving meetings and events; and (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility. TESLA was evaluated on data of over 110,000 meetings held at nine campus buildings during eight months in 2011–2012 at the University of Southern California (USC) and the Singapore Management University (SMU), and it indicated that TESLA’s assumptions exist in practice. This paper also provides an extensive analysis on energy savings achieved by TESLA. These results and analysis show that, compared to the current systems, TESLA can substantially reduce overall energy consumption.
See also: 2013