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Modelling Framework for Reducing Energy Loads to Achieve Net-Zero Energy Building in Semi-Arid Climate: A Case Study

Buildings consume a significant 40% of global energy, where, reducing the building energy consumption to a minimum, virtually zero, has become a thriving research area. Accordingly, this research aimed to determine and portray the huge potential of energy conservation in existing structures by making a retrofit at relatively low costs in finance strained economies. A walk-through of the survey of energy consuming appliances determined the energy consumption based on the power rating; the appliances were then virtually replaced and the reduced energy consumption was determined in terms of the cooling loads. Modelling these intervention using the hourly analysis program (HAP) showed significantly positive results. The pre- and post-retrofit model analysis of an institutional building in Pakistan exhibited significant potential for reducing the cooling load of 767 kW (218 TON) to 408 kW (116 TON) with an investment payback period of 2.5 years. The additional benefit is the reduced greenhouse gas (GHG) emissions which reduce the overall energy requirements. The study continues with the design of a solar energy source using the system advisor model (SAM) for the reduced energy demand of a retrofitted building. It is then concluded that using the available area, a solar energy source with a capital payback period of 5.7 years would bring an institutional building within its own energy footprint making it a net-zero building, since it will not be consuming energy from any other source outside of its own covered area. The study has the limitation to exposure and climate related conditions. In addition, the decline in heating and cooling loads represents model values which may vary when calculated after an actual retrofit for the same structure due to any site related issues.

Publication date: 26/10/2023

Author: Umair Azam

Reference: doi: 10.3390/buildings13112695

MDPI (buildings)


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870292.