Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88310
Title: Energy efficiency improvement with k-means approach to thermal comfort for ACMV systems of smart buildings
Authors: Zhai, Deqing
Chaudhuri, Tanaya
Soh, Yeng Chai
Keywords: Energy Efficiency
Thermal Comfort
Issue Date: 2017
Source: Zhai, D., Chaudhuri, T., & Soh, Y. C. (2017). Energy efficiency improvement with k-means approach to thermal comfort for ACMV systems of smart buildings. 2017 Asian Conference on Energy, Power and Transportation Electrification (ACEPT), 17415930-.
Abstract: This paper proposes a novel methodology to predict thermal comfort states of occupants with k-means approach. The approach is embedded into an optimization problem, which is used to locate optimal operating conditions via Augmented Firefly Algorithm (AFA), for improving energy efficiency of buildings and maintaining satisfactory indoor thermal comfort states in the meantime. The neural networks models of energy, air temperature, skin temperature and skin temperature gradient have been implemented and verified. The prediction of thermal comfort states via k-means approach has been implemented and it is based on features of skin temperature and skin temperature gradient. The problem is formulated directly from the developed thermal comfort model and energy model. The formulated problem has been followed by optimizations of AFA approach, and the experimental results show that the energy efficiency can be improved by at least 21% while maintaining the indoor thermal comfort satisfaction of occupants, thus conforming to the objectives of a smart building.
URI: https://hdl.handle.net/10356/88310
http://hdl.handle.net/10220/44836
DOI: 10.1109/ACEPT.2017.8168568
Rights: © 2017 IEEE.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles
ERI@N Conference Papers
IGS Journal Articles

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