Impact of Building Design Parameters on Daylighting Metrics Using an Analysis, Prediction, and Optimization Approach Based on Statistical Learning Technique

Jaewook Lee,Mohamed Boubekri,Feng Liang

doi:10.3390/su11051474

Abstract

Daylighting metrics are used to predict the daylight availability within a building and assess the performance of a fenestration solution. In this process, building design parameters are inseparable from these metrics; therefore, we need to know which parameters are truly important and how they impact performance. The purpose of this study is to explore the relationship between building design attributes and existing daylighting metrics based on a new methodology we are proposing. This methodology involves statistical learning. It is an emerging methodology that helps us to analyze a large quantity of output data and the impact of a large number of design variables. In particular, we can use these statistical methodologies to analyze which features are important, which ones are not, and the type of relationships they have. Using these techniques, statistical models may be created to predict daylighting metric values for different building types and design solutions. In this article we will outline how this methodology works, and analyze the building design features that have the strongest impact on daylighting performance.

Highlights

The benefits of daylight extend beyond building energy savings, and the importance of daylight has attracted the attention of building designers as well as researchers [1]
Our analyses indicate that the daylighting metrics that are more reliable at predicting performance include Spatial Daylight Autonomy (sDA), A.Mean Hourly Illuminance (MHI), and Annual Sunlight Exposure (aSE)
The relationship between building design parameters and daylighting metrics was compared through database creation

Summary

Introduction

The benefits of daylight extend beyond building energy savings, and the importance of daylight has attracted the attention of building designers as well as researchers [1]. This leads us to the question of what constitutes good building design or a good daylighting performance. With the development of computer simulation protocols, analyzing how much daylight enters a building has become a sophisticated process Computer programs such as Radiance and others can analyze how much daylight enters a building with an error rate significantly similar to that of measurements taken by a hand-held light meter [10]. Performance-driven computer simulation approaches have often been used to estimate the impact of one or a few design variables

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