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An analysis of climatic influences on chiller plant electricity consumption

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  • Lam, Joseph C.
  • Wan, Kevin K.W.
  • Cheung, K.L.

Abstract

Principal component analysis of dry-bulb temperature, wet-bulb temperature, global solar radiation, clearness index and wind speed was conducted, and a two-component solution obtained which could explain 80% of the variance in the original weather data. Clustering analysis of these two principal components resulted in a total of 18 typical day types being identified. A year long monitoring of the daily chiller plant electricity consumption in a fully air-conditioned office building was conducted. It was found that the typical day types exhibited daily and seasonal variations similar to the daily and monthly electricity consumption recorded. Three regression models were developed to correlate the daily chiller plant electricity consumption and the corresponding day types. The coefficient of determination (R2) was 0.86-0.99 showing strong correlation. It is proposed that the day type approach can be used as a tool for weather normalisation and inter-year comparisons in the analysis of energy savings due to building retrofits. It was also found that the typical day types identified appeared to show a slight increasing trend during the 28-year period (1979-2006) indicating a subtle, but gradual change of climatic conditions that might affect chiller plant electricity consumption in future years.

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  • Lam, Joseph C. & Wan, Kevin K.W. & Cheung, K.L., 2009. "An analysis of climatic influences on chiller plant electricity consumption," Applied Energy, Elsevier, vol. 86(6), pages 933-940, June.
    • Handle: RePEc:eee:appene:v:86:y:2009:i:6:p:933-940
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    1. Lam, Joseph C. & Tang, H.L. & Li, Danny H.W., 2008. "Seasonal variations in residential and commercial sector electricity consumption in Hong Kong," Energy, Elsevier, vol. 33(3), pages 513-523.
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    2. Chong, Daokun & Zhu, Neng & Luo, Wei & Zhang, Zhiyu, 2019. "Broadening human thermal comfort range based on short-term heat acclimation," Energy, Elsevier, vol. 176(C), pages 418-428.
    3. Yu, F.W. & Chan, K.T., 2012. "Improved energy management of chiller systems by multivariate and data envelopment analyses," Applied Energy, Elsevier, vol. 92(C), pages 168-174.
    4. Yu, Xinqiao & Yan, Da & Sun, Kaiyu & Hong, Tianzhen & Zhu, Dandan, 2016. "Comparative study of the cooling energy performance of variable refrigerant flow systems and variable air volume systems in office buildings," Applied Energy, Elsevier, vol. 183(C), pages 725-736.
    5. Yu, F.W. & Chan, K.T., 2010. "Simulation and electricity savings estimation of air-cooled centrifugal chiller system with mist pre-cooling," Applied Energy, Elsevier, vol. 87(4), pages 1198-1206, April.
    6. Moral-Carcedo, Julián & Pérez-García, Julián, 2015. "Temperature effects on firms’ electricity demand: An analysis of sectorial differences in Spain," Applied Energy, Elsevier, vol. 142(C), pages 407-425.
    7. Hsu, David, 2015. "Comparison of integrated clustering methods for accurate and stable prediction of building energy consumption data," Applied Energy, Elsevier, vol. 160(C), pages 153-163.
    8. Chammy Lau & Irini Lai Fun Tang & Wilco Chan, 2021. "Waterfront Hotels’ Chillers: Energy Benchmarking and ESG Reporting," Sustainability, MDPI, vol. 13(11), pages 1-15, June.
    9. Lam, Tony N.T. & Wan, Kevin K.W. & Wong, S.L. & Lam, Joseph C., 2010. "Impact of climate change on commercial sector air conditioning energy consumption in subtropical Hong Kong," Applied Energy, Elsevier, vol. 87(7), pages 2321-2327, July.
    10. Zhu, Dan & Tao, Shu & Wang, Rong & Shen, Huizhong & Huang, Ye & Shen, Guofeng & Wang, Bin & Li, Wei & Zhang, Yanyan & Chen, Han & Chen, Yuanchen & Liu, Junfeng & Li, Bengang & Wang, Xilong & Liu, Wenx, 2013. "Temporal and spatial trends of residential energy consumption and air pollutant emissions in China," Applied Energy, Elsevier, vol. 106(C), pages 17-24.
    11. Wan, Kevin K.W. & Li, Danny H.W. & Pan, Wenyan & Lam, Joseph C., 2012. "Impact of climate change on building energy use in different climate zones and mitigation and adaptation implications," Applied Energy, Elsevier, vol. 97(C), pages 274-282.
    12. Lam, Joseph C. & Wan, Kevin K.W. & Wong, S.L. & Lam, Tony N.T., 2010. "Long-term trends of heat stress and energy use implications in subtropical climates," Applied Energy, Elsevier, vol. 87(2), pages 608-612, February.
    13. Lam, Joseph C. & Wan, Kevin K.W. & Lam, Tony N.T. & Wong, S.L., 2010. "An analysis of future building energy use in subtropical Hong Kong," Energy, Elsevier, vol. 35(3), pages 1482-1490.
    14. Tarek Rakha & Rawad El Kontar, 2019. "Community energy by design: A simulation-based design workflow using measured data clustering to calibrate Urban Building Energy Models (UBEMs)," Environment and Planning B, , vol. 46(8), pages 1517-1533, October.
    15. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    16. Elnazeer Ali Hamid Abdalla & Perumal Nallagownden & Nursyarizal Bin Mohd Nor & Mohd Fakhizan Romlie & Sabo Miya Hassan, 2018. "An Application of a Novel Technique for Assessing the Operating Performance of Existing Cooling Systems on a University Campus," Energies, MDPI, vol. 11(4), pages 1-24, March.
    17. Abou-Ziyan, Hosny Z. & Alajmi, Ali F., 2014. "Effect of load-sharing operation strategy on the aggregate performance of existed multiple-chiller systems," Applied Energy, Elsevier, vol. 135(C), pages 329-338.
    18. Lai, Sau Man & Hui, Chi Wai, 2010. "Integration of trigeneration system and thermal storage under demand uncertainties," Applied Energy, Elsevier, vol. 87(9), pages 2868-2880, September.

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