Effective Energy Consumption Parameters in Residential Buildings Using Building Information Modeling
Creators: name: REZASOROUSH, ABDULAMIR
name: Amani, Nima
Publisher: name: figshare
Year: 2024
Subjects: classificationCode: 400501
subject: Architectural engineering
classificationCode: 400504
subject: Construction engineering
classificationCode: 400505
subject: Construction materials
classificationCode: 400808
subject: Photovoltaic power systems
classificationCode: 401102
subject: Environmentally sustainable engineering
classificationCode: 401105
subject: Life cycle assessment and industrial ecology
classificationCode: 401703
subject: Energy generation, conversion and storage (excl. chemical and electrical)
classificationCode: 330102
subject: Architectural design
classificationCode: 330110
subject: Sustainable architecture
classificationCode: 330201
subject: Automation and technology in building and construction
classificationCode: 330202
subject: Building construction management and project planning
classificationCode: 330204
subject: Building information modelling and management
classificationCode: 330206
subject: Building science, technologies and systems
classificationCode: 330301
subject: Data visualisation and computational (incl. parametric and generative) design
classificationCode: 330305
subject: Design management
classificationCode: 330311
subject: Models and simulations of design
classificationCode: 330314
subject: Sustainable design
classificationCode: 330101
subject: Architectural computing and visualisation methods
classificationCode: 330203
subject: Building industry studies
classificationCode: 330306
subject: Design practice and methods

description: Building information modeling can help in predicting energy efficiency in the future based on dynamic patterns obtained by visualization of data. This study aimed to investigate the effective parameters of energy consumption using BIM technology which can evaluate the building’s energy performance. First, three forms of general states in the building were modeled to evaluate the proposed designs in Autodesk Revit Software. Then, the main building form for energy modeling and analysis was selected. Autodesk Revit 2020 software was also used to obtain the results of climate data analysis and building energy consumption index. Finally, the optimal mode was selected by examining different energy consumption modes. The results showed that the use of building information modeling technology in adjusting the parameters affecting energy consumption can save energy costs up to 58.23% in block D. Energy cost savings for block C and the western lobby were obtained as 51.03% and 43.05%, respectively. Based on energy use intensity, energy cost savings for blocks C, D, and the western lobby were estimated as 16.67%, 16.30%, and 11%, respectively. The results of parametric studies on alternative energy use intensity optimization schemes showed that 16.30% savings could be achieved by the base building model in a 30-year time horizon. Therefore, it was concluded that optimizing energy consumption would reduce environmental pollutant emissions and contribute to the preservation and sustainability of the environment.