VIJ Digital library
Articles

Revolutionizing Energy Efficiency in Commercial and Institutional Buildings: A Complete Analysis

Bengold Anarene
Western Sydney University (South Parramatta Campus) Sydney,

Published 2024-09-19

Keywords

  • Revolutionizing Energy Efficiency ,
  • Commercial and Institutional Buildings

Abstract

Heating, ventilation, and air conditioning (HVAC) systems of commercial and institutional buildings consume a large proportion of the energy used worldwide and, as a result, are a major contributor to greenhouse gas emissions and operational expenses. According to Wang et al. (2021), HVAC systems in commercial buildings account for approximately 40% of total energy consumption, making them a key focus in efforts to reduce energy use and emissions. As climate change and energy resource depletion intensify, increasing the energy efficiency of these buildings is viewed as a sustainable development solution. Improving building energy efficiency is considered one of the most effective strategies to mitigate global energy consumption and carbon footprints (Pérez-Lombard et al., 2008).

This critical review re-anchors the current research, strategies, and case studies toward improving energy efficiency in existing commercial and institutional buildings, providing insights on which approaches work best, the challenges of implementation, and ways forward to guide future research and practice. The paper starts by outlining an overall view of the use of energy in commercial and institutional buildings and identifies the key energy-using systems, which include HVAC, lighting, and the building envelope (Mendell et al., 2017).

Technological enhancements scientifically proven to reduce energy consumption include efficient HVAC systems, lighting systems, and advancements in insulation and window technologies (Kim et al., 2019). In addition, the utilization of renewable energy within existing building structures—such as solar and wind energy—is explored as a complementary option for reducing reliance on non-renewable energy sources (Hossain et al., 2020).

Beyond technological improvements, behavioral change and policy measures play a critical role in improving energy efficiency. Studies have shown that occupant behavior significantly affects energy consumption, and energy management practices, coupled with incentives, can lead to measurable efficiency gains (Delzendeh et al., 2017). Energy performance standards and governmental incentives are essential in fostering greater efficiency in building systems (Ürge-Vorsatz et al., 2012).

The review also addresses the challenges of retrofitting, particularly the high initial costs, operational disruptions, and legal constraints involved in upgrading existing buildings. These barriers, particularly in terms of cost and logistics, are critical to overcome if retrofitting is to be widely adopted (Ma et al., 2012). Case studies such as the Empire State Building's retrofitting project, which resulted in a projected 38% energy savings, and Harvard University's energy efficiency initiatives, demonstrate the real-world feasibility of significant energy reductions (Guldmann et al., 2020).

It is particularly relevant to stress here that more innovation is required in the sphere of energy-efficient technologies, backed by stronger policy support, education, and collaboration among stakeholders. As noted by Sartori et al. (2012), the collaboration between governments, industry, and academia is essential to address the global challenge of increasing the energy efficiency of buildings and reducing energy consumption in response to climate change.

 

References

  1. Ruparathna, R., Hewage, K., & Sadiq, R. (2016). Improving the energy efficiency of the existing building stock: A critical review of commercial and institutional buildings. Renewable and sustainable energy reviews, 53, 1032-1045.
  2. Sheikh, N., Laverge, J., & Delghust, M. (2024). A Critical Analysis of Institutional and Regulatory Framework for Building Stock Energy Efficiency and Transition in Pakistan. Environmental Science & Sustainable Development, 32-41.
  3. Shaikh, P. H., Shaikh, F., Sahito, A. A., Uqaili, M. A., & Umrani, Z. (2017). An overview of the challenges for cost-effective and energy-efficient retrofits of the existing building stock. Cost-effective energy efficient building retrofitting, 257-278.
  4. Marquez, L., McGregor, J., & Syme, M. (2012). Barriers to the adoption of energy efficiency measures for existing commercial buildings. Victoria: CSIRO Mathematics, Informatics and Statistics.
  5. Bedoya, M. V. (2024). Different perspectives on Latin American identity. Valley International Journal Digital Library, 1908-1915.
  6. Carlson, K., & Pressnail, K. D. (2018). Value impacts of energy efficiency retrofits on commercial office buildings in Toronto, Canada. Energy and Buildings, 162, 154-162.
  7. Kumar, S., Yadav, N., Singh, M., & Kachhawa, S. (2019). Estimating India’s commercial building stock to address the energy data challenge. Building Research & Information, 47(1), 24-37.
  8. Arefin, S. (2024). IDMap: Leveraging AI and Data Technologies for Early Cancer Detection. Valley International Journal Digital Library, 1138-1145.
  9. Parejo-Navajas, T. (2015). A Legal Approach to the Improvement of Energy Efficency Measures for the Existing Building Stock in the United States Based on the European Experience. Seattle Journal of Environmental Law, 5(1), 14.
  10. Mukhtar, M., Ameyaw, B., Yimen, N., Zhang, Q., Bamisile, O., Adun, H., & Dagbasi, M. (2021). Building retrofit and energy conservation/efficiency review: A techno-environ-economic assessment of heat pump system retrofit in housing stock. Sustainability, 13(2), 983.
  11. Kim, J. T., & Yu, C. W. F. (2018). Sustainable development and requirements for energy efficiency in buildings–the Korean perspectives. Indoor and Built Environment, 27(6), 734-751.
  12. Anarene, B. (2024). Advanced Decision-Making Framework for Sustainable Energy Retrofit of Existing Commercial Office Buildings. Valley International Journal Digital Library, 7269-7297.
  13. Benson, A., Vargas, E., Bunts, J., Ong, J., Hammond, K., Reeves, L., ... & Duan, P. (2011). Retrofitting commercial real estate: current trends and challenges in increasing building energy efficiency. UCLA Institute of the Environment and Sustainability.
  14. Liu, Z., Wu, H., Wang, P., & Li, Y. (2024). Reliability-Based Design Optimization of Additive Manufacturing for Lithium Battery Silicon Anode. ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg, 10(3).
  15. Mir, A. A. (2024). Adaptive Fraud Detection Systems: Real-Time Learning from Credit Card Transaction Data. Advances in Computer Sciences, 7(1).
  16. Wu, H. (2022). Probabilistic Design and Reliability Analysis with Kriging and Envelope Methods (Doctoral dissertation, Purdue University).
  17. Mir, A. A. (2024). Optimizing Mobile Cloud Computing Architectures for Real-Time Big Data Analytics in Healthcare Applications: Enhancing Patient Outcomes through Scalable and Efficient Processing Models. Integrated Journal of Science and Technology, 1(7).
  18. Wu, H., & Du, X. (2022, August). Envelope Method for Time-and Space-Dependent Reliability-Based Design. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (Vol. 86236, p. V03BT03A002). American Society of Mechanical Engineers.
  19. Mir, A. A. (2024). Transparency in AI Supply Chains: Addressing Ethical Dilemmas in Data Collection and Usage. MZ Journal of Artificial Intelligence, 1(2).
  20. Wu, H., Bansal, P., Liu, Z., Li, Y., & Wang, P. (2023, August). Uncertainty Quantification on Mechanical Behavior of Corroded Plate With Statistical Shape Modeling. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (Vol. 87318, p. V03BT03A051). American Society of Mechanical Engineers.
  21. Mir, A. A. (2024). Sentiment Analysis of Social Media during Coronavirus and Its Correlation with Indian Stock Market Movements. Integrated Journal of Science and Technology, 1(8).
  22. Yu, H., Khan, M., Wu, H., Du, X., Chen, R., Rollins, D. M., ... & Sawchuk, A. P. (2022). A new noninvasive and patient‐specific hemodynamic index for the severity of renal stenosis and outcome of interventional treatment. International Journal for Numerical Methods in Biomedical Engineering, 38(7), e3611.
  23. Liu, Z., Xu, Y., Wu, H., Wang, P., & Li, Y. (2023, August). Data-Driven Control Co-Design for Indirect Liquid Cooling Plate With Microchannels for Battery Thermal Management. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (Vol. 87301, p. V03AT03A048). American Society of Mechanical Engineers.