Lecture and non-lecture week baseline energy model development and energy prediction in Malaysia educational building

The development of baseline energy models and prediction of energy consumption in educational buildings especially universities are heavily depending on its operation period. The main operation period can be divided into two period i.e. lecture week and non-lecture week. Possible independent variabl...

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Bibliographic Details
Published in:Journal of Physics: Conference Series
Main Author: Mustapa R.F.; Dahlan N.Y.; Yassin A.I.M.; Nordin A.H.M.
Format: Conference paper
Language:English
Published: Institute of Physics Publishing 2020
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079086556&doi=10.1088%2f1742-6596%2f1432%2f1%2f012001&partnerID=40&md5=cc32e504507368807000045bb17e040b
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Summary:The development of baseline energy models and prediction of energy consumption in educational buildings especially universities are heavily depending on its operation period. The main operation period can be divided into two period i.e. lecture week and non-lecture week. Possible independent variable candidates that may have an effect towards energy consumption during this two period differ with each other. In addition, spaces that occupies the educational building such as classrooms, laboratories and office rooms within the same building operates differently depending on its operation period. In order to achieve accurate baseline energy models in educational buildings, the operation period have to be considered based on the independent variables that will have an effect towards the energy consumption. Thus, the twofold objectives of this paper are to develop a baseline energy model for two operation period in educational buildings and predicting the energy consumption using multiple linear regression model. One building in a university compound was selected as a case study for modelling and prediction purposes. Independent variables were selected based on the two-period mentioned and from the modelling and prediction results, the independent variables that were selected gives a high coefficient of correlation (R2) value which suggest that the independent variables effect the educational building's energy consumption. © Published under licence by IOP Publishing Ltd.
ISSN:17426588
DOI:10.1088/1742-6596/1432/1/012001