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Improved energy management of chiller systems by multivariate and data envelopment analyses

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  • Yu, F.W.
  • Chan, K.T.

Abstract

The operation of chiller systems accounts for the major proportion of electricity consumption in commercial buildings. This paper considers using multivariate and data envelopment analyses to facilitate the energy management of chiller systems. The system studied contains five sets of chillers, pumps and cooling waters and it operates for an institutional building. Based on a huge set of operating data, multiple linear regression was used to correlate the system coefficient of performance (COP) with a set of climatic and operating variables. Data envelopment analysis was then employed to calculate the scale, technical and overall efficiencies. These three efficiencies were further examined to ascertain which controllable variables caused a decrease of system COP. The results show that the existing energy management gives a technical efficiency of 0.76 and fine-tuning the controllable variables could achieve an electricity saving of 5.34% in relation to the existing operation. The significance of this study is to demonstrate a systematic approach to examine which operating variable should be fine-tuned to improve system performance with higher technical efficiency.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:92:y:2012:i:c:p:168-174
    DOI: 10.1016/j.apenergy.2011.11.016
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    1. Fong, K.F. & Yuen, S.Y. & Chow, C.K. & Leung, S.W., 2010. "Energy management and design of centralized air-conditioning systems through the non-revisiting strategy for heuristic optimization methods," Applied Energy, Elsevier, vol. 87(11), pages 3494-3506, November.
    2. Ma, Zhenjun & Wang, Shengwei, 2011. "Supervisory and optimal control of central chiller plants using simplified adaptive models and genetic algorithm," Applied Energy, Elsevier, vol. 88(1), pages 198-211, January.
    3. Torrella, E. & Sánchez, D. & Cabello, R. & Larumbe, J.A. & Llopis, R., 2009. "On-site real-time evaluation of an air-conditioning direct-fired double-effect absorption chiller," Applied Energy, Elsevier, vol. 86(6), pages 968-975, June.
    4. Chung, William, 2011. "Review of building energy-use performance benchmarking methodologies," Applied Energy, Elsevier, vol. 88(5), pages 1470-1479, May.
    5. Chan, K.T. & Yu, F.W., 2006. "Thermodynamic-behaviour model for air-cooled screw chillers with a variable set-point condensing temperature," Applied Energy, Elsevier, vol. 83(3), pages 265-279, March.
    6. Lee, Tzong-Shing & Lu, Wan-Chen, 2010. "An evaluation of empirically-based models for predicting energy performance of vapor-compression water chillers," Applied Energy, Elsevier, vol. 87(11), pages 3486-3493, November.
    7. 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.
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    11. Chen, Qun & Wang, Yi-Fei & Xu, Yun-Chao, 2015. "A thermal resistance-based method for the optimal design of central variable water/air volume chiller systems," Applied Energy, Elsevier, vol. 139(C), pages 119-130.
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    15. Tirmizi, Syed A. & Gandhidasan, P. & Zubair, Syed M., 2012. "Performance analysis of a chilled water system with various pumping schemes," Applied Energy, Elsevier, vol. 100(C), pages 238-248.
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    19. Xuefeng, Liu & Jinping, Liu & Zhitao, Lu & Kongzu, Xing & Yuebang, Mai, 2015. "Diversity of energy-saving control strategy for a parallel chilled water pump based on variable differential pressure control in an air-conditioning system," Energy, Elsevier, vol. 88(C), pages 718-733.
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    21. Afroz, Zakia & Shafiullah, GM & Urmee, Tania & Higgins, Gary, 2018. "Modeling techniques used in building HVAC control systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 83(C), pages 64-84.

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