Energy Star based benchmarking model for Malaysian Government hospitals - A qualitative and quantitative approach to assess energy performances
The hospital building's operation can be symbolised as high energy usage with different services provision and facilities. The energy performances for hospital buildings in Malaysia are often quantified using a simple Building Energy Intensity (BEI) as the indicator. However, this method has le...
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2022
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2-s2.0-85118479581 Dahlan N.Y.; Mohamed H.; Kamaluddin K.A.; Abd Rahman N.M.; Reimann G.; Chia J.; Ilham N.I. Energy Star based benchmarking model for Malaysian Government hospitals - A qualitative and quantitative approach to assess energy performances 2022 Journal of Building Engineering 45 10.1016/j.jobe.2021.103460 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118479581&doi=10.1016%2fj.jobe.2021.103460&partnerID=40&md5=055c781e2d11aa051e98dcc760f874c4 The hospital building's operation can be symbolised as high energy usage with different services provision and facilities. The energy performances for hospital buildings in Malaysia are often quantified using a simple Building Energy Intensity (BEI) as the indicator. However, this method has less accuracy on the building's performance due to complex energy systems and different sizes for hospital-built environments. Hereof, this study aims to establish an energy benchmarking indicator for government hospitals in Malaysia using the Energy Star score method. The actual large dataset of hospitals samples has been quantified, scrutinised and optimised using the multiple linear regression (MLR) analysis to identify specific parameters affecting the energy use. The proposed model found that the final output result had shown a good fit for all hospital datasets. Further classifications were conducted on hospitals according to their energy score and air-conditioned area (ACA) for ranking comparison and assessment. Subsequently, from the same benchmarking model, an energy benchmarking calculator was developed in order to assist hospitals in automatically assessing their energy performance and labelling. Therefore, better energy management practices and decisions may be suggested for the Malaysian hospital buildings' continuous improvement. The novelties for this study are the formulated benchmarking models by optimising significant parameters from the actual large dataset of Malaysian hospitals and the developed benchmarking calculator for the regulator and hospital use. © 2021 Elsevier Ltd Elsevier Ltd 23527102 English Article |
author |
Dahlan N.Y.; Mohamed H.; Kamaluddin K.A.; Abd Rahman N.M.; Reimann G.; Chia J.; Ilham N.I. |
spellingShingle |
Dahlan N.Y.; Mohamed H.; Kamaluddin K.A.; Abd Rahman N.M.; Reimann G.; Chia J.; Ilham N.I. Energy Star based benchmarking model for Malaysian Government hospitals - A qualitative and quantitative approach to assess energy performances |
author_facet |
Dahlan N.Y.; Mohamed H.; Kamaluddin K.A.; Abd Rahman N.M.; Reimann G.; Chia J.; Ilham N.I. |
author_sort |
Dahlan N.Y.; Mohamed H.; Kamaluddin K.A.; Abd Rahman N.M.; Reimann G.; Chia J.; Ilham N.I. |
title |
Energy Star based benchmarking model for Malaysian Government hospitals - A qualitative and quantitative approach to assess energy performances |
title_short |
Energy Star based benchmarking model for Malaysian Government hospitals - A qualitative and quantitative approach to assess energy performances |
title_full |
Energy Star based benchmarking model for Malaysian Government hospitals - A qualitative and quantitative approach to assess energy performances |
title_fullStr |
Energy Star based benchmarking model for Malaysian Government hospitals - A qualitative and quantitative approach to assess energy performances |
title_full_unstemmed |
Energy Star based benchmarking model for Malaysian Government hospitals - A qualitative and quantitative approach to assess energy performances |
title_sort |
Energy Star based benchmarking model for Malaysian Government hospitals - A qualitative and quantitative approach to assess energy performances |
publishDate |
2022 |
container_title |
Journal of Building Engineering |
container_volume |
45 |
container_issue |
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doi_str_mv |
10.1016/j.jobe.2021.103460 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118479581&doi=10.1016%2fj.jobe.2021.103460&partnerID=40&md5=055c781e2d11aa051e98dcc760f874c4 |
description |
The hospital building's operation can be symbolised as high energy usage with different services provision and facilities. The energy performances for hospital buildings in Malaysia are often quantified using a simple Building Energy Intensity (BEI) as the indicator. However, this method has less accuracy on the building's performance due to complex energy systems and different sizes for hospital-built environments. Hereof, this study aims to establish an energy benchmarking indicator for government hospitals in Malaysia using the Energy Star score method. The actual large dataset of hospitals samples has been quantified, scrutinised and optimised using the multiple linear regression (MLR) analysis to identify specific parameters affecting the energy use. The proposed model found that the final output result had shown a good fit for all hospital datasets. Further classifications were conducted on hospitals according to their energy score and air-conditioned area (ACA) for ranking comparison and assessment. Subsequently, from the same benchmarking model, an energy benchmarking calculator was developed in order to assist hospitals in automatically assessing their energy performance and labelling. Therefore, better energy management practices and decisions may be suggested for the Malaysian hospital buildings' continuous improvement. The novelties for this study are the formulated benchmarking models by optimising significant parameters from the actual large dataset of Malaysian hospitals and the developed benchmarking calculator for the regulator and hospital use. © 2021 Elsevier Ltd |
publisher |
Elsevier Ltd |
issn |
23527102 |
language |
English |
format |
Article |
accesstype |
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record_format |
scopus |
collection |
Scopus |
_version_ |
1814778505447079936 |