Sustainable Multiagent Application to Conserve Energy

Citation:

Jun-young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe, Farrokh Jazizadeh, Geoffrey Kavulya, Laura Klein, Burcin Becerik-Gerber, Timothy Hayes, and Wendy Wood. 2012. “Sustainable Multiagent Application to Conserve Energy .” In International Conference on Autonomous Agents and Multiagent Systems (AAMAS) Demonstration Track .

Abstract:

Limited availability of energy resources has motivated the need for developing efficient measures of conserving energy. Conserving energy in commercial buildings is an important goal since these buildings consume significant amount of energy, e.g., 46.2% of all building energy and 18.4% of total energy consumption in the US [1]. This demonstration focuses on a novel application to be deployed at Ralph & Goldy Lewis Hall (RGL) at the University of Southern California as a practical research testbed to optimize multiple competing objectives: i) energy use in the building; ii) occupants’ comfort level; and iii) practical usage considerations. This demonstration complements our paper in the AAMAS innovative applications track [4], presenting a novel multiagent building application for sustainability called SAVES (Sustainable multiAgent systems for optimizing Variable objectives including Energy and Satisfaction). This writeup will provide a high-level overview of SAVES and focus more on the proposed demonstration, but readers are referred to [4] for a more technical description. SAVES provides three key contributions: (i) jointly performed with the university facility management team, our research is based on actual building and occupant data as well as real sensors and devices, etc.; (ii) it focuses on non-residential buildings, where human occupants do not have a direct financial incentive in saving energy; and (iii) SAVES uses a novel algorithm for generating optimal BM-MDP (Bounded parameter Multi-objective MDP) policies. We demonstrate SAVES to show how to achieve significant energy savings and comparable average satisfaction level of occupants while emphasizing the interactive aspects of our application.
See also: 2012