Currently, commercial buildings consume almost 18% of the total primary energy in the US and this is bound to increase with time due to population and economic growth. Small commercial buildings are those with less than 50,000 ft2 of conditioned area and represent 94% of total commercial buildings in the U.S. Since windows are responsible for 34% of commercial space conditioning energy use, windows in small commercial buildings should be given considerable attention. Besides the window material, selecting an optimum window dimension and location has played an important role in building energy performance. Since different weather conditions and sun angles impact on determining the optimum window dimensions and location, the goal of this study is to identify the optimum window design parameters in seven US climate zones in order to minimize building energy use. In this study, an optimization model using a genetic algorithm is developed and coupled with EnergyPlus software to identify the optimum window design parameters including a window to wall ratio, aspect ratio, and fenestration location. A double-story commercial building model, as a case study, is designed using DesignBuilder software to illustrate the application of the model. Identifying the optimum window dimensions and location in different locations would help engineers and designers to reduce building energy consumption in the early stages of the design. The results show that selecting optimum window dimensions and locations can reduce the total building energy consumption by 2 and 15% in cold and hot climate zones respectively.
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment
- Environmental Science(all)
- Strategy and Management
- Industrial and Manufacturing Engineering