@inproceedings{d10ac74b7c0b4fd2ba0495898568d4e4,
title = "Demand-driven power saving by multiagent negotiation for HVAC control",
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.",
keywords = "HVAC system, multi-agent system, power saving",
author = "Tsao, {Yi Ting} and Hsu, {Jane Yung Jen}",
year = "2013",
doi = "10.1145/2516911.2516918",
language = "英语",
isbn = "9781450323468",
series = "ACM International Conference Proceeding Series",
pages = "9--14",
booktitle = "Joint Proc. of the Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd IJCAI 2013",
note = "Joint Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd Int. Joint Conf. on Artificial Intelligence, IJCAI 2013 ; Conference date: 04-08-2013 Through 05-08-2013",
}
