A study of energy consumption of secondary school buildings in Hong Kong

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

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Detail(s)

Original languageEnglish
Article number110388
Journal / PublicationEnergy and Buildings
Volume226
Online published10 Aug 2020
Publication statusPublished - 1 Nov 2020

Abstract

Junior and senior secondary classes in Hong Kong are conducted in the same secondary school premise, which consists of a multistorey main (interlocking) building and an assembly hall. According to our survey, the building complex does not use a central cooling or heating system. Instead, air-conditioning is commonly provided using a mix of split- and window-type air conditioners and ceiling fans. Lighting services are provided using fluorescent lamps (T5 and T8), and light-emitting diode (LED) systems are rarely used. The school buildings have no dormitory or canteen; thus, electricity constitute the primary energy consumption. The average energy consumption and energy use intensity per school are 529,925 kWh and 105.61 kWh/m2/year, respectively. 
On the basis of the characteristics of the management practices of school building, regression analyses involving energy performance factors (independent variables) that can be managed by the school management are conducted. In the perspective of the school management, a regression model with manageable energy performance factors is desirable. We conducted a backward stepwise (BS) regression analysis to achieve this objective. However, because the resulting BS regression model does not provide a satisfactory goodness of fit and only one manageable factor, we performed convex non-parametric least squares (CNLS) to obtain a non-parametric regression model with improved variables and goodness of fit. The obtained CNLS regression model can be used to forecast energy consumption, as confirmed by an illustrative application.

Research Area(s)

  • Energy consumption, Forecasting models, Questionnaire survey, Regression analyses, School buildings