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.
Cite
Text
Tsao and Hsu. "Demand-Driven Power Saving by Multiagent Negotiation for HVAC Control." International Joint Conference on Artificial Intelligence, 2013. doi:10.1145/2516911.2516918Markdown
[Tsao and Hsu. "Demand-Driven Power Saving by Multiagent Negotiation for HVAC Control." International Joint Conference on Artificial Intelligence, 2013.](https://mlanthology.org/ijcai/2013/tsao2013ijcai-demand/) doi:10.1145/2516911.2516918BibTeX
@inproceedings{tsao2013ijcai-demand,
title = {{Demand-Driven Power Saving by Multiagent Negotiation for HVAC Control}},
author = {Tsao, Yi-Ting and Hsu, Jane Yung-jen},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2013},
pages = {9-14},
doi = {10.1145/2516911.2516918},
url = {https://mlanthology.org/ijcai/2013/tsao2013ijcai-demand/}
}