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Retrofitting Existing Buildings to Improve Energy Performance

Author

Listed:
  • Sunil Kumar Sharma

    (School of Engineering & Applied Science, National Rail and Transportation Institute, Vadodara 390004, Gujarat, India)

  • Swati Mohapatra

    (School of Science, Gujarat State Fertilizers and Chemicals University, Vadodara 391750, Gujarat, India)

  • Rakesh Chandmal Sharma

    (Mechanical Engineering Department, Maharishi Markandeshwar, Mullana 133207, Haryana, India)

  • Sinem Alturjman

    (Artificial Intelligence Engineering Department, Research Center for AI and IoT, AI and Robotics Institute, Near East University, Mersin 10-99138, Turkey)

  • Chadi Altrjman

    (Artificial Intelligence Engineering Department, Research Center for AI and IoT, AI and Robotics Institute, Near East University, Mersin 10-99138, Turkey)

  • Leonardo Mostarda

    (Computer Science Division, Camerino University, 62032 Camerino, Italy)

  • Thompson Stephan

    (Department of Computer Science and Engineering, M. S. Ramaiah University of Applied Sciences, Bengaluru 560054, Karnataka, India)

Abstract

Energy-efficient retrofits embrace enhancement of the building envelope through climate control strategies, employment of building-integrated renewable energy technologies, and insulation for a sustainable city. Building envelope improvements with insulation is a common approach, yet decision-making plays an important role in determining the most appropriate envelope retrofit strategy. In this paper, the main objective is to evaluate different retrofit strategies (RS) through a calibrated simulation approach. Based on an energy performance audit and monitoring, an existing building is evaluated on performance levels and improvement potentials with basic energy conservation measures. The considered building is experimentally monitored for a full year, and monitoring data are used in calibrating the simulation model. The validation of the base model is done by comparing the simulation analysis with the experimental investigation, and good agreement is found. Three different retrofit strategies based on Intervention of minor (RS1), Moderate (RS2), and Major (RS3) are analyzed and juxtaposed with the base model to identify the optimal strategy of minimizing energy consumption. The result shows that total energy intensity in terms of the percentage reduction index is about 16.7% for RS1, 19.87 for RS2, and 24.12% for RS3. Hence, RS3 is considered the optimal retrofit strategy and is further simulated for a reduction in carbon dioxide (CO 2 ) emissions and payback investigation. It was found that the annual reduction in CO 2 emissions of the building was 18.56%, and the payback period for the investment was 10.6 years.

Suggested Citation

  • Sunil Kumar Sharma & Swati Mohapatra & Rakesh Chandmal Sharma & Sinem Alturjman & Chadi Altrjman & Leonardo Mostarda & Thompson Stephan, 2022. "Retrofitting Existing Buildings to Improve Energy Performance," Sustainability, MDPI, vol. 14(2), pages 1-14, January.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:2:p:666-:d:720056
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    Citations

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    Cited by:

    1. Piotr Michalak & Krzysztof Szczotka & Jakub Szymiczek, 2023. "Audit-Based Energy Performance Analysis of Multifamily Buildings in South-East Poland," Energies, MDPI, vol. 16(12), pages 1-21, June.
    2. Ashraf Ud Din & Heesup Han & Antonio Ariza-Montes & Alejandro Vega-Muñoz & António Raposo & Shruti Mohapatra, 2022. "The Impact of COVID-19 on the Food Supply Chain and the Role of E-Commerce for Food Purchasing," Sustainability, MDPI, vol. 14(5), pages 1-14, March.
    3. Małgorzata Szulgowska-Zgrzywa & Ewelina Stefanowicz & Agnieszka Chmielewska & Krzysztof Piechurski, 2023. "Detailed Analysis of the Causes of the Energy Performance Gap Using the Example of Apartments in Historical Buildings in Wroclaw (Poland)," Energies, MDPI, vol. 16(4), pages 1-19, February.

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