Investigation on demand-based chiller optimization
Buildings in Singapore are one of the major contributor of carbon footprint. This sector in particular consumes large amount of electricity. Most of these electricity consumption are by air conditioning equipment which is essential in providing thermal comfort in the hot and humid climate region. As...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
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2014
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| Online Access: | http://hdl.handle.net/10356/60987 |
| _version_ | 1826127310727675904 |
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| author | Ler, Han Qiang |
| author2 | Wong Yew Wah |
| author_facet | Wong Yew Wah Ler, Han Qiang |
| author_sort | Ler, Han Qiang |
| collection | NTU |
| description | Buildings in Singapore are one of the major contributor of carbon footprint. This sector in particular consumes large amount of electricity. Most of these electricity consumption are by air conditioning equipment which is essential in providing thermal comfort in the hot and humid climate region. As Singapore progressively pushes itself to decrease the nation’s carbon footprint, studies looking into reducing the main electricity consumers are necessary. Simulation tools such as TRNSYS are able to model after real buildings, Singapore’s weather and cooling equipment based on past data and mathematical models in the software. In this study, a typical 20-storey office building with a constant mixed air distribution water-cooled chilled water chiller plant is modelled. A parametric study of the chiller plant is then performed. Based on the simulations, savings of up to 19% is demonstrated as compared to conventional constant mixed air distribution water-cooled chilled water chiller plant system. |
| first_indexed | 2024-10-01T07:06:28Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/60987 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:06:28Z |
| publishDate | 2014 |
| record_format | dspace |
| spelling | ntu-10356/609872023-03-04T18:32:46Z Investigation on demand-based chiller optimization Ler, Han Qiang Wong Yew Wah School of Mechanical and Aerospace Engineering DRNTU::Engineering::Mechanical engineering::Energy conservation Buildings in Singapore are one of the major contributor of carbon footprint. This sector in particular consumes large amount of electricity. Most of these electricity consumption are by air conditioning equipment which is essential in providing thermal comfort in the hot and humid climate region. As Singapore progressively pushes itself to decrease the nation’s carbon footprint, studies looking into reducing the main electricity consumers are necessary. Simulation tools such as TRNSYS are able to model after real buildings, Singapore’s weather and cooling equipment based on past data and mathematical models in the software. In this study, a typical 20-storey office building with a constant mixed air distribution water-cooled chilled water chiller plant is modelled. A parametric study of the chiller plant is then performed. Based on the simulations, savings of up to 19% is demonstrated as compared to conventional constant mixed air distribution water-cooled chilled water chiller plant system. Bachelor of Engineering (Mechanical Engineering) 2014-06-04T01:29:22Z 2014-06-04T01:29:22Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/60987 en Nanyang Technological University 70 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Mechanical engineering::Energy conservation Ler, Han Qiang Investigation on demand-based chiller optimization |
| title | Investigation on demand-based chiller optimization |
| title_full | Investigation on demand-based chiller optimization |
| title_fullStr | Investigation on demand-based chiller optimization |
| title_full_unstemmed | Investigation on demand-based chiller optimization |
| title_short | Investigation on demand-based chiller optimization |
| title_sort | investigation on demand based chiller optimization |
| topic | DRNTU::Engineering::Mechanical engineering::Energy conservation |
| url | http://hdl.handle.net/10356/60987 |
| work_keys_str_mv | AT lerhanqiang investigationondemandbasedchilleroptimization |