Data-driven modeling of smart builiding energy management

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...

Full description

Bibliographic Details
Main Author: Salama, Raghda Ahmed Abdelkerim (author)
Format: masterThesis
Language:eng
Published: 2022
Subjects:
Machine learning
Business and data analytics
Energy efficiency
Energy management
Smart buildings
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
Online Access:http://hdl.handle.net/10362/132389
Country:Portugal
Oai:oai:run.unl.pt:10362/132389
Description
Summary: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.

Similar Items