The average commercial building wastes 30% of the energy it consumes. Reducing the energy consumed remains high-priority policy in efforts to combat energy wastage and lessen carbon footprint. For instance, in the United States alone, commercial buildings which total to about 5.6 million, consume 18% of the total primary energy. This is predicted to increase by 1.2% per year from 2006 to 2030 due to population and economic growth. Therefore, improving commercial building energy performance would increase building energy efficiency and subsequently reduce the environmental effects. Ideally, since the building enclosure separates the outdoor and indoor environment, most of the energy gain and loss occur through this specific section of the building. Windows are fundamental to a façade as they provide light, views, and air ventilation. However, reports previously showed that windows in commercial buildings are responsible for approximately 34% of commercial space conditioning energy use and 1.5% of total energy use in the United States. In essence, controlling the heat gain and loss from windows in commercial buildings would save a significant amount of energy and subsequently reduce the carbon footprint. As the main function of shading is to moderate light rays, whether intercepting or allowing them to enter, having well-designed shading can improve building energy performance. Shading should be designed carefully since decreasing the cooling load may result in increased heating load and vice versa. In addition, in designing window shading, achieving a balance between energy load reduction and light energy consumption is always challenging.
At present, although several studies have been conducted to determine the optimum value of each window design parameter few have focused on a multiparameter solution. Simulation-based optimization is a widely used method of identifying the mutual effect of multiple design parameters. In this process, an optimization code is developed and coupled with simulation software to identify the optimum solutions. With the goal being to resolve the outlined energy challenges associated with windows, Professor Reza Foroughi at the Appalachian State University, in collaboration with Professor Somayeh Asadi at the Pennsylvania State University and Dr. Soha Khazaeli from Raleigh Technology Center developed a novel approach for designing kinetic exterior window shading for small commercial buildings, which changes the geometrical parameters of the exposed glazing area (EGA) of existing windows. Their work is currently published in the Journal of Architectural Engineering.
To achieve this, first, an optimization code was developed based on the hill climbing algorithm to identify the optimum glazing geometrical parameter. The research team then coupled the optimization code with EnergyPlus software to identify the optimum EGA: its optimum area, aspect ratio, and location on the window surface. Finally, a building model was designed and presented in DesignBuilder (a graphical interface for EnergyPlus) to illustrate application of the proposed shading. The energy consumption of the proposed shading model was compared with the Venetian blind and baseline models.
The authors reported that the largest EGA occurred on the east side window with an aspect ratio of 3.31, while the smallest EGA was on the north and south sides of the building with aspect ratios of 1.5. More so, the simulation results showed significant energy reduction of around 34% and 14% in comparison with the baseline and traditional shading models respectively.
In summary, the study introduced a novel approach for designing kinetic exterior window shading that changes the geometrical parameters of the exposed glazing area (EGA) of an existing window in order to increase building energy efficiency. The proposed shading model utilized simulation-based optimization using the hill climbing algorithm to identify optimum EGA on the window shading. In a statement to Advances in Engineering, the authors explained their study showed that significant amount of energy could be saved by applying the proposed shading.
Reza Foroughi, Somayeh Asadi, Soha Khazaeli. New Approach in Designing a Kinetic Window Shading Using Optimization Methods. Journal of Architectural Engineering; Volume 26 Issue 3.