Energy Analysis and Forecast of a Major Modern Hospital
Auteur(s): |
Aaron Liu
Yunlong Ma Wendy Miller Bo Xia Sherif Zedan Bruce Bonney |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Buildings, 31 juillet 2022, n. 8, v. 12 |
Page(s): | 1116 |
DOI: | 10.3390/buildings12081116 |
Abstrait: |
Healthcare buildings often have high energy use intensity, which is potentially influenced by a few factors, such as occupancy and climate. A suite of data analysis methods, including principal component analysis and regressions, is applied to analyse monthly electricity data of a modern major hospital in subtropical Australia. The analysis shows that occupancy is not highly correlated with the hospital’s electricity use, nor is it important for building energy modelling. However, outdoor environment temperature is highly correlated with the hospital’s electricity use. Then, the hospital’s electricity uses in 2030 to 2090 scenarios are forecast with future climate files. The impacts are analysed in terms of bill increases and renewable capacity needed to offset the increased electricity use. This study has established a process to predict future hospital energy use using data-driven energy modelling. This succinct article provides vital evidence to support the healthcare sector to continuously improve energy efficiency for health buildings, which is a major asset to adapt to the changing climate. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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10688684 - Publié(e) le:
13.08.2022 - Modifié(e) le:
10.11.2022