Energy-efficient envelope design for residential buildings: A case study in Oman

Abstract

This study summarizes the results from a simulation study for a typical villa in Muscat, a hot humid city in Oman. A housing model was generated in the DesignBuilder software. The model was compared against real utility readings before it was further taken for the energy calculations. Different thermal characteristics of building envelope including the heat transmission, thermal mass, solar heat gain through windows and air infiltration were evaluated. Many energy-efficient envelope design options were generated. Sensitivity analysis was then performed to narrow down the design parameters to the most significant parameters. From the sensitivity analysis, it was found that no significant energy savings are achieved beyond 15 cm of thermal insulation for both walls and roof. The solar heat gain coefficient (SHGC) was found more significant than the U-values of the glazing. It was also found that the house should be air tight as the air infiltration was significant. External shading was advantageous too in hot climates. A brute force optimization approach was then carried out using unsubsidized and subsidized energy cost scenarios. A maximum energy savings of 26.7% and a minimum energy savings of 18.4% were achieved for both energy cost scenarios. For maximum energy savings, 15 cm insulation for walls and roof, a double low-e selective tinted glazing, 100 cm of overhang shading were found to be the optimal design. The optimal designs for minimum life cycle cost were, however, different for the two energy cost scenarios. For unsubsidized energy cost, 10 cm insulation for walls and roof, a single green tinted glazing, and 100 cm of overhang shading were found to be the optimal design. For subsidized energy cost, a 7.5 cm for wall and roof are the optimal while other parameters are similar to the unsubsidized case. The results from the study will help both the policy makers, designers, and owners to select their optimal designs based on different cost functions.