A Review on Energy Analysis of Building Using Building Information Modelling

Abstract

Building Information Modeling (BIM) has emerged as a crucial tool for energy analysis in building design, enabling precise simulations and predictive analytics to optimize energy efficiency throughout a structure\'s lifecycle. This literature review explores the importance of energy efficiency in buildings and the role of BIM in modern architecture. It discusses theoretical frameworks for energy analysis, including an overview of techniques and the integration of BIM with energy simulation tools. The review also examines methodological approaches in the literature, such as case studies and comparative analyses of different BIM tools for energy analysis. Recent advances in energy analysis of buildings are highlighted, including innovations in BIM technology and advances in energy simulation algorithms. The review identifies challenges and limitations, such as technical barriers in BIM adoption for energy analysis and gaps in current research and practice. Future directions in energy analysis using BIM are discussed, including emerging trends and technologies, as well as recommendations for future research. The review concludes by emphasizing the importance of integrating BIM with energy-efficient retrofitting strategies, community engagement, and smart energy management systems to drive the transition towards net-zero energy buildings that align with ecological imperatives and social values.

Introduction

I. Introduction

Energy analysis in building design aims to improve energy efficiency and sustainability throughout a building's lifecycle. The integration of Building Information Modelling (BIM) is crucial as it allows for accurate energy simulations, data sharing, and real-time collaboration among stakeholders. These tools help detect inefficiencies before construction, thus supporting environmentally responsible decision-making.

II. Importance of Energy Efficiency

With rising climate concerns, AI-powered predictive analytics are increasingly used to improve sustainability in building design. Historical data enables the creation of smarter, more energy-efficient buildings. For example, companies like Unilever demonstrate how AI and consumer insights can drive eco-friendly innovations—a concept adaptable to architecture. The combination of BIM and AI supports energy optimization across a building's lifecycle.

III. Role of BIM in Modern Architecture

BIM enhances the design and performance of buildings by:

• Facilitating real-time energy simulations

• Supporting sustainability-focused design decisions

• Allowing early identification of energy inefficiencies

• Encouraging smarter urban planning that aligns with climate resilience goals

Projects like the Masdar Headquarters highlight the real-world success of integrating BIM with AI to achieve significant energy savings.

IV. Theoretical Frameworks & Techniques

1. Energy Analysis Techniques:

   • Use AI and BIM for proactive, sustainable design

   • Enable multi-disciplinary collaboration for efficiency

2. Integration with Simulation Tools:

   • Tools help optimize orientation, materials, and systems

   • Enhance energy performance and reduce carbon emissions

V. Literature Review Highlights

• BIM differs from 3D CAD by embedding semantic and operational data into models

• BIM is crucial in prefabrication and modular construction, improving quality, speed, and sustainability

• Modular projects face challenges like seismic resilience, cost overruns, and coordination risks, but BIM helps mitigate these through enhanced modeling and planning

VI. Methodology

• Research Type: Descriptive and comparative

• Data Collection:

  • Primary: Surveys, expert interviews, BIM modeling using Revit and Navisworks

  • Secondary: Literature and historical project data

• Sampling: Stratified random sample of 100–150 professionals, focusing on BIM-experienced stakeholders

VII. Case Study: Pride Purple Square, Pune

A premium commercial project in Pune showcasing real-world application of modern building design practices. Integrates community living with sustainable development features.

VIII. Experimental Analysis

Tools Used:

• Revit: Architectural modeling

• Navisworks: 5D modeling, clash detection, and project simulation

• Energy Simulation: Comparison of modular vs. conventional construction

Key Metrics:

• Energy Consumption:

  • Modular: 90 kWh/m²/year

  • Conventional: 120 kWh/m²/year

• Embodied Energy:

  • Modular: 500 kWh/m²

  • Conventional: 700 kWh/m²

• Cost Efficiency: Modular construction demonstrates lower energy use and lifecycle costs

Lighting & Solar Parameters:

• Window-to-wall ratio: 30%

• Indoor temp: 22°C; Outdoor: 35°C

• Solar radiation: 800 W/m²

IX. Cost Comparison: Green vs. Conventional Construction

Despite higher upfront costs, green buildings offer long-term energy savings, durability, and environmental benefits.

Conclusion

As the integration of community engagement and sustainable practices evolves, it is crucial to consider the role of technological advancements such as Smart Energy Management Systems (SEMS) in facilitating these efforts. By employing SEMS alongside Building Information Modeling (BIM), stakeholders can harness real-time data analytics not only to improve energy efficiency but also to involve communities in monitoring their environmental impact actively. For instance, when residents have access to energy consumption data through user-friendly interfaces, they are more likely to engage in energy-saving behaviors, thereby fostering a culture of sustainability at the grassroots level. This collaborative approach, which combines technology with local insights, can lead to innovative solutions tailored to specific community needs while ensuring compliance with increasingly stringent regulations aimed at reducing overall carbon footprints in urban settings. Ultimately, this synergy between advanced technologies and community involvement will be pivotal in driving the transition towards net-zero energy buildings that resonate with both ecological imperatives and social values.

References

[1] D. Dahiya and B. Laishram, “Life cycle energy analysis of buildings: A systematic review,” Building and Environment, Jan. 2024, doi: 10.1016/j.buildenv.2024.111160. [2] J. E. Anderson, G. Wulfhorst, and W. Lang, “Energy analysis of the built environment—A review and outlook,” Renewable & Sustainable Energy Reviews, Apr. 2015, doi: 10.1016/J.RSER.2014.12.027. [3] “1.Transformative_Potential_of_Artificial_Intelligence_In_Green_Marketing.pdf”. [4] E. I. Samuel and E. Joseph-Akwara, “Responding To Building Energy Analysis and Performance With Building Information Model (BIM),” Jan. 2015. [5] A. Alothman, S. Ashour, and L. Krishnaraj, “Energy Performance Analysis of Building for Sustainable Design Using Bim: A Case Study on Institute Building,” International Journal of Renewable Energy Research, Jun. 2021. [6] S. I. Egwunatum, E. Joseph-Akwara, and R. Akaigwe, “Optimizing Energy Consumption in Building Designs Using Building Information Model (BIM),” Slovak Journal of Civil Engineering, Sep. 2016, doi: 10.1515/SJCE-2016-0013. [7] “IRJAEH-02-11-352-2410002-2566-2568.pdf”. [8] “2025-03-19 ManasiBobade Air and Noise (2) e2[1].pdf”. [9] T. B. Kurniawan, D. A. Dewi, F. Usman, and F. Fadly, “Towards Energy Analysis and Efficiency for Sustainable Buildings,” Emerging science journal, Dec. 2023, doi: 10.28991/esj-2023-07-06-022 [10] F. Jalaei and A. Jrade, “Integrating Building Information Modeling (BIM) and Energy Analysis Tools with Green Building Certification System to Conceptually Design Sustainable Buildings,” Journal of Information Technology in Construction, Nov. 2014.

Copyright

Copyright © 2025 Mr. Rahul D. Shinde, Mrs. Snehalata Sharma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.