
Predicting Building Energy Consumption using Engineering and Data Driven Approaches: A Review
Author(s) -
Aulon Shabani,
Orion Zavalani
Publication year - 2017
Publication title -
european journal of engineering research and science
Language(s) - English
Resource type - Journals
ISSN - 2506-8016
DOI - 10.24018/ejers.2017.2.5.352
Subject(s) - energy consumption , consumption (sociology) , focus (optics) , computer science , energy (signal processing) , population , energy management , risk analysis (engineering) , systems engineering , management science , industrial engineering , engineering , business , mathematics , social science , statistics , physics , demography , optics , sociology , electrical engineering
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.