Demand-Driven Power Saving by Multiagent Negotiation for HVAC Control
Journal
IJCAI Workshop on AI Problems and Approaches for Intelligent Environments
Date Issued
2013
Author(s)
Tsao, Yi-ting
Abstract
Buildings account for roughly 40% of all U.S. energy use, and HVAC systems are a major culprit. The goal of this research is to reduce power consumption without sacrificing human comfort. This paper presents a cooling demand estimation from heat generation to assess the quantity of cooling supply, which helps diagnose potential problems in the HVAC system. A negotiation-based approach is proposed to balance power consumption, cooling for human comfort, and smooth operation for equipment health. Experiments were conducted with the NTU CSIE July 2012 dataset [6] as well as online live experiments in the computer science building on campus. The experiments demonstrated that the proposed method reduced 3.81% to 5.96% of power consumption with consideration of smoothness. © 2013 ACM.
Other Subjects
Demand estimation; Demand-driven; Human comforts; HVAC control; HVAC system; Multiagent negotiation; Potential problems; Power savings; Cooling; Experiments; Intelligent agents; Multi agent systems; Semantics; Climate control
Type
conference paper