Multi-parameter sensitivity analysis: A design methodology applied to energy efficiency in temperate climate houses

• Published in: Energy and buildings 2012-12, Vol.55, p.668-673
• Main Authors: Smith, G.B., Aguilar, J.L.C., Gentle, A.R., Chen, D.
• Format: Article
• Language: English
• Subjects: Air exchange rate; Applied sciences; Building technical equipments; Buildings; Buildings. Public works; Cool roof; Cost benefits; Design sensitivity; Energy efficiency; Energy management and energy conservation in building; Environmental engineering; Exact sciences and technology; Residential building; Temperate climate; Types of buildings
• ISSN: 0378-7788
• DOI: 10.1016/j.enbuild.2012.09.007

► A new methodology for choosing building parameters for energy efficiency is presented. ► Variations in seasonal loads as parameters shift in temperate climates are exploited. ► Changes in sensitivity to each design variable when another changes are important. ► Interdependence of the impacts of roof albedo, air exchange rate, sub-roof R value are quantified. ► The sub-roof R-value impact is secondary to optima in ACH and roof albedo for large annual savings. Quantified sensitivities of heating and cooling loads to different variables that influence heat gain and loss in a building provides a valuable basis for energy efficient design, especially in temperate climate zones where particular parameter settings could be beneficial in one season while reducing performance or neutral in the other. In doing so it is important in this multi-parameter design space to consider impact of changes in each parameter when other variables also change. Such 2-variable up to n-variable correlation is called factorial analysis. The methodology is introduced using three variables (roof solar absorptance, air exchange rates, and sub-roof R-value) in a simple structure with all other parameters fixed. Sensitivity is via impact of changes on each of heating load, cooling load and annual total. Knowledge of factorial effects is shown to be important and lead to simple strategies that provide large benefits in both seasons. They also show that some standard approaches to saving energy (e.g. raising R significantly), while useful are often unnecessary, unless poor settings are made in other parameters.