Energy efficiency improvement with k-means approach to thermal comfort for ACMV systems of smart buildings

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 building...

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Main Authors: Zhai, Deqing, Chaudhuri, Tanaya, Soh, Yeng Chai
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2018
Subjects:
Online Access:https://hdl.handle.net/10356/88310
http://hdl.handle.net/10220/44836
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-883102021-01-08T07:03:41Z Energy efficiency improvement with k-means approach to thermal comfort for ACMV systems of smart buildings Zhai, Deqing Chaudhuri, Tanaya Soh, Yeng Chai School of Electrical and Electronic Engineering Interdisciplinary Graduate School (IGS) 2017 Asian Conference on Energy, Power and Transportation Electrification (ACEPT) Energy Research Institute @ NTU (ERI@N) Energy Efficiency Thermal Comfort 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. NRF (Natl Research Foundation, S’pore) 2018-05-18T06:36:46Z 2019-12-06T17:00:26Z 2018-05-18T06:36:46Z 2019-12-06T17:00:26Z 2017 Conference Paper 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-. https://hdl.handle.net/10356/88310 http://hdl.handle.net/10220/44836 10.1109/ACEPT.2017.8168568 en © 2017 IEEE.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Energy Efficiency
Thermal Comfort
spellingShingle Energy Efficiency
Thermal Comfort
Zhai, Deqing
Chaudhuri, Tanaya
Soh, Yeng Chai
Energy efficiency improvement with k-means approach to thermal comfort for ACMV systems of smart buildings
description 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.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Zhai, Deqing
Chaudhuri, Tanaya
Soh, Yeng Chai
format Conference or Workshop Item
author Zhai, Deqing
Chaudhuri, Tanaya
Soh, Yeng Chai
author_sort Zhai, Deqing
title Energy efficiency improvement with k-means approach to thermal comfort for ACMV systems of smart buildings
title_short Energy efficiency improvement with k-means approach to thermal comfort for ACMV systems of smart buildings
title_full Energy efficiency improvement with k-means approach to thermal comfort for ACMV systems of smart buildings
title_fullStr Energy efficiency improvement with k-means approach to thermal comfort for ACMV systems of smart buildings
title_full_unstemmed Energy efficiency improvement with k-means approach to thermal comfort for ACMV systems of smart buildings
title_sort energy efficiency improvement with k-means approach to thermal comfort for acmv systems of smart buildings
publishDate 2018
url https://hdl.handle.net/10356/88310
http://hdl.handle.net/10220/44836
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