Abstract
Windows are among the most important building systems as they provide lights and outside views for occupants, and they are considered to be the key element that needs to be correctly designed to save energy. As windows are made of transparent surfaces and are exposed to different climatic conditions, most of the heat gain and loss of a building occurs through this part of the building. Windows are responsible for 28% of cooling and 35% of heating loads in commercial buildings which is equal to almost 6% of total primary energy use in the United States. Using a window shading system is one of the most effective design strategies to control daylighting and energy load. The biggest challenge in designing a window shading is striking a balance between heating and cooling loads and lighting energy consumption since decreased cooling loads may result in increased heating loads and vice versa. To achieve this goal, an intelligent and adaptable solar shade is designed and constructed to investigate the trade-off between heating and cooling loads and lighting energy use, and to minimize the energy consumption of the buildings. To design the proposed adaptable window shades, an optimization model is developed using the Hill-Climbing (HC) algorithm coupled with EnergyPlus software. The DesignBuilder software (a graphical interface of EnergyPlus) is also used to design the model’s geometry. The developed model is capable of identifying the optimum configurations of adaptable solar shades and consequently minimizing the building energy consumption.
Presenters
Reza ForoughiAssociate Professor, Sustainable Technology/Building Sciences, Appalachian State University, North Carolina, United States
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
Adaptable Solar Shades, Energy Optimization, Intelligent Window Shading System
