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...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2018
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| Online Access: | https://hdl.handle.net/10356/88310 http://hdl.handle.net/10220/44836 |
| _version_ | 1826119323894153216 |
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| author | Zhai, Deqing Chaudhuri, Tanaya Soh, Yeng Chai |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Zhai, Deqing Chaudhuri, Tanaya Soh, Yeng Chai |
| author_sort | Zhai, Deqing |
| collection | NTU |
| 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. |
| first_indexed | 2024-10-01T04:58:03Z |
| format | Conference Paper |
| id | ntu-10356/88310 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:58:03Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | ntu-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. |
| 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 |
| title | 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_short | 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 |
| topic | Energy Efficiency Thermal Comfort |
| url | https://hdl.handle.net/10356/88310 http://hdl.handle.net/10220/44836 |
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