Multivariable Coupling Influence on Energy-Efficient Skylight Design

Despite the great achievements made in energy-efficient architectural design over the past decade, the majority of studies have used single-variable or bivariate-orthogonal methods, which treat the variables separately. Thus, the existing literature largely neglects multivariable interactions, which are often encountered in design practice. To address this insufficiency, the response surface method is introduced and applied to a roof glazing system (skylights with exterior shades) of an office atrium in Nanjing, China. The method is used to analyze multivariable interactions and optimization processes where architectural features are parameterized and formulated in mathematical models. Model generation, effect visualization, and optimization all contribute to general conclusions and design strategies for architects. The study reveals several findings, including that up to 72% of total energy demand could be reduced by changing the value of design factors. As for energy-saving design strategies, in regions like Nanjing that have hot summer–cold winter climates, small slats are recommended. The window-to-floor ratio, the number of strips, blind reflectance, and the U-value of the skylights are suggested to reach their minimum, while glazing transmittance should be at its maximum. In addition, substitute relations of factors are proposed, indicating that architects have more choices to reach similarly low levels of total energy demand when multivariable interactions are considered.