Open AccessTowards a universal ranking system for design parameters’ impact on buildings’ lifecycle energy
Author(s) -
Rafaela Orenga Panizza,
Mazdak Nik-Bakht
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/609/7/072039
Subject(s) - ranking (information retrieval) , sensitivity (control systems) , energy consumption , scope (computer science) , energy (signal processing) , computer science , window (computing) , environmental science , orientation (vector space) , simulation , mathematics , statistics , engineering , artificial intelligence , geometry , electrical engineering , electronic engineering , programming language , operating system
The energy consumption of buildings depends on numerous factors that can be categorized in four major categories: geometry parameters; location; attributes of electric and mechanical systems; and behaviour of users. Most of the existing publications on ‘energy-consumption influencing parameters’ test the sensitivity of energy consumption to these inputs in a single building; not making it possible to correlate different projects. The purpose of this study is to evaluate the impact caused by the model when evaluating parameters. In this paper we have studied a series of nine real-world design projects in cold climate (Québec, Canada) to analyse the behaviour of thirteen design parameters. Among the four major categories mentioned above, our scope is limited to geometry parameters (variation in climate, mechanical systems and occupants is excluded). The parameters include building orientation; window-to-wall ratio; overhang size; insulation; and Solar Heat Gain Coefficient (SHGC) for windows. All parameters are analysed using the Morris method for sensitivity analysis and are ranked based on the simulation results. According to the results, window-to-wall ratio and orientation show lower variation among different models while insulation, overhangs and SHGC appear to be more sensitive. The developed analysis is the starting point to what can be a shortcut for designers to control energy consumptions efficiently in new designs.