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Data-driven modeling of smart builiding energy management
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Buildings consume approximately 40% of energy in total, which contributes negatively to the environment. Building Energy Management Systems(BEMS) have been used to monitor energy consumption and increase usage efficiency. In this study, the components and importance of BEMS are emphasized. The data from the management systemoftheChamchuri5building in Chula long korn University, Thailand, were used as a template for data-driven modeling for energy usage in smart buildings to analyze the patterns of energy consumption. Using multilevel modeling on theChamchuri5 building ,the main factors that consume energy on a macro and micro level are analyzed .Energy variation between zones and floors was spotted.
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Machine learning Business and data analytics Energy efficiency Energy management Smart buildings