Subzone control optimization of air distribution for thermal comfort and energy efficiency under cooling load uncertainty

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

2 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Article number113378
Journal / PublicationApplied Energy
Volume251
Online published22 May 2019
Publication statusPublished - 1 Oct 2019

Abstract

The previous subzone control method of air distribution divides the occupied zone into subzones and controls the thermal conditions of the subzones to satisfy the respective thermal preferences. The previous method improves thermal comfort efficiently by considering the non-uniform thermal environment and differentiated thermal preferences of the occupants. However, firstly it is unable to account energy efficiency; and secondly, it fails to treat cooling load uncertainty. Cooling load uncertainty exists prevailingly in practice and could significantly deteriorate the performance of air distribution. This study proposes a subzone control optimization to simultaneously improve thermal comfort and energy efficiency under cooling load uncertainty. Using Monte Carlo simulations, the thermal deviation of the thermal conditions of the subzones from the respective thermal preferences and energy efficiency indicated by heat removal efficiencies of the subzones are quantified with a confidence level of 0.95 under cooling load uncertainty. Overall performance is maximized by making a trade-off between minimizing the thermal deviation for thermal comfort and maximizing the energy efficiency using the multi-criteria decision-making technique. Results of case studies based on experiments of stratum ventilation show that increasing the uncertainty level in cooling load deteriorates thermal comfort and energy efficiency. The thermal comfort is more sensitive to the cooling load uncertainty than energy efficiency. Under thirty-six scenarios with different uncertainty levels of cooling load, thermal preferences of the subzones and weighting factors of thermal comfort and energy efficiency, the new method improves the overall performance by 75% on average compared with the previous method.

Research Area(s)

  • Air distribution, Control optimization, Cooling load uncertainty, Energy efficiency, Subzones of occupied zone, Thermal preferences