Applications of Digital Twins in Optimizing Building Energy Consumption

Buildings significantly contribute to global energy consumption and greenhouse gas emissions, exacerbating the energy crisis and highlighting the urgent need for innovative solutions to enhance sustainability and efficiency. Digital twins, virtual models that integrate real-time data with physical assets, emerge as a transformative technology for optimizing building energy management. This study employs a systematic literature review and theoretical analysis to investigate the potential of digital twins in building energy optimization. The findings reveal that digital twins enable substantial energy savings through applications such as real-time monitoring, design simulation, automated control systems, and predictive maintenance, particularly in commercial buildings. However, challenges including complex data integration, high implementation costs, and the need for specialized expertise limit their widespread adoption. By synthesizing these applications and barriers, this paper offers valuable insights for architects, engineers, and policymakers to advance sustainable building practices.

کلیدواژه ها:

digital twins ، building energy efficiency ، IoT ، Real-Time Monitoring ، Sustainability ، Predictive Maintenance