Predicting Building Energy Consumption using Engineering and Data Driven Approaches: A Review

Aulon Shabani and Orion Zavalani
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Aulon Shabani: PhD student, Polytechnic University of Tirana, Faculty of electrical Engineering
Orion Zavalani: Department of Automation, Faculty of Electrical Engineering, Polytechnic University of Tirana

European Journal of Engineering and Technology Research, 2017, vol. 2, issue 5, 44-49

Abstract: Rapid growth of world population has higher impact on increasing buildings energy consumption. Therefore, improving energy consumption is an important concern for building engineers and operators. Energy management through forecasting approaches as one of most effective methods is in focus of this paper. Review of most elaborated methods is in our focus, where we investigate two main directions of energy prediction approaches. First category of approaches focuses on engineering methods mainly very reliable on building early operation stages and design phase, meanwhile second category go through data driven methods. Existing research works focused on these two models are introduced emphasizing advantages and relevant applications of methods.

Keywords: Artificial Intelligence; Building; Energy Consumption; Engineering Methods; Prediction (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:2:y:2017:i:5:id:60352

DOI: 10.24018/ejeng.2017.2.5.352

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