Volume 21: Sustainable Energy Solutions for a Post-COVID Recovery towards a Better Future: Part IV

Daylight optimization and energy retrofit by using proportionate automated louvers in home-based offices (case study: a house in Tehran, Iran) Omid Veisi, Nastaran Fadaee, Morteza Rahbar, Hadi Ebadi

Abstract

Many businesses ceased working physically during the current pandemic and started working remotely. Therefore, launching home-based offices has now become popular among people ever before. One type of place where people are currently working is home-based offices. However, these residential places are not as standard as they are supposed to be. While working at their homes, workers consume more artificial lighting than natural lighting compared to normal conditions (their workplace). Thus, his research aims to study daylight and energy optimization used in home-based offices to achieve maximum natural light during working hours. This optimization works based on auto-extract-window-to-wall and automatic louvers for windows. The suggested research method for this study is the “Genetic Algorithm” to optimize the proportion, which can be achieved by using a special parametric algorithm in Grasshopper. The paper concludes that optimization can be conceived as a creative modeling method for increasing natural light and reducing energy consumption in home-based offices. The results of this study validate that with the use of optimization used for louvers, shelves, and other mentioned elements, spatial daylight autonomy have the potential to be increased up to 25%. The annual sunlight exposure can also be reduced up to 10%. This will lead to a reduction in artificial lighting consumption. This type of optimization develops the agenda of optimizing “daylight and energy retrofit.”

Keywords Daylight, Retrofit, Genetic Algorithm, Home-based Office, Automated Louvers, Optimization,