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doi:10.3808/jei.202000448
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Evaluating Building Systems Energy Performance Superiority and Inferiority Ranking

M. Marzouk1 *, I. Abdelbasset2, and K. Al-Gahtani2

  1. Structural Engineering Department, Faculty of Engineering, Cairo University, Giza 12613, Egypt
  2. Civil Engineering Department, College of Engineering, King Saud University, Riyadh 11362, Kingdom of Saudi Arabia

*Corresponding author. Tel.: +(202) 35678425; fax: +(202) 35723486. E-mail address: mmarzouk@cu.edu.eg (M. Marzouk).

Abstract


Nowadays, the demand for sustainable buildings is increasing. The main purpose of buildings is to provide a comfort- able living environment for their occupants, considering different aspects including thermal, visual, and acoustic comfort as well as In- door Air Quality. Decreasing carbon footprint and energy consumption rates while increasing comfort level can help to achieve better living and working environment for building users. This research proposes a framework that aims at improving building system energy performance using building information modeling (BIM) during buildings’ design stage by evaluating different alternatives for install- ed building systems. According to experts’ opinions, evaluating buildings’ energy performance by analyzing the energy consumption rates alone without including economic and environmental factors is insufficient. Therefore, in this paper, building systems are evalu- ated using four main criteria; operating cost savings, total energy consumption per year, Lifecycle cost savings, and carbon emissions. A Multiple Criteria Decision-making (MCDM) technique is applied using Superiority and Inferiority Ranking (SIR) to study the behav- ior of different alternatives. Sensitivity analysis is performed to detect the criticality and effectiveness of the different defined criteria that influence environmental concerns and building system energy performance. A case study is presented to demonstrate the use of the proposed framework on an academic building by considering four criteria which are Operating Costs, Life Cycle Cost, Energy Con- sumption, and Carbon Emissions. Sensitivity analysis is performed on the weights of the criteria to determine how critical each crite- rion is and how they affect the ranking of the alternatives. A total of 36 combinations are simulated, considering changing the weights and procedure (SAW vs. TOPSIS). The rank that has the top repetitive percentage is considered to identify the most dominating alternative.

Keywords: sustainability, building systems energy performance, multiple criteria decision-making, building information modeling, sensitivity analysis, superiority and inferiority ranking


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