Quantifying energy poverty vulnerability with minimal data – A building energy simulation approach

Abstract

Energy poverty is a pressing issue that many countries currently face. The income per household and energy use data per household are variables used in widely known methodologies on the topic of energy poverty. However, due to different reasons, this data isn’t made available in many locations of interest, which prevents them from quantifying energy poverty. To overcome this problem, this study introduces a not yet explored asset-based workflow that makes use of income distributions and building energy modelling to quantify a household’s energy poverty vulnerability. This study defines a novel energy poverty vulnerability index (EVI) that makes use of the widely known ten-percent rule’s fundamental concepts but avoids the latter’s main critics through two major improvements; a varying threshold is introduced with a linear function and distortion is prevented using a weighted average. The methodology has been applied to more than 85,000 low-rise apartment buildings in Montreal, Canada to quantify their energy poverty vulnerability, a feat that wasn’t possible using typical methodologies. The case study results have shown that Montreal’s buildings’ energy poverty vulnerability is highly dependent on the household’s income, but also on the insulation level and floor area. A sensitivity analysis has been conducted to determine the EVI’s requirements and limitations. From this analysis, the EVI is most sensitive to variables related to the building’s energy consumption and is least sensitive to income.