Multivariate Statistical Analysis for the Assessment of Potential Energy Savings in Low-Density Urban Building Stocks in the City of Mendoza, Argentina

The present study’s goal is to contribute knowledge and methodology to the assessment of the potential energy recovery for space heating, retrofitting existing building stocks in low-density urban environments of Mendoza’s Metropolitan Area. The morphological features of the built environment, urban and architectural, combined with the technological alternatives of the existing buildings, were analyzed for the reference situation (present without changes) and for a theoretical improved condition, massively implementing increased conservation measures and additional passive solar gain. Three indicators were selected to assess the significance of the solar contribution: 1. the masking of potential collectors by neighbouring obstructions, 2. the useful fraction of the total energy received on a given urban area and 3. the potential savings obtainable by the massive recycling of the buildings. In a first stage, the solar contribution was determined by the use of a graphic-computational model and, in a second stage, given the complexity and interrelationships of morphological variables, the results were analyzed through the use of a statistical multiple linear regression model, which yielded two useful results per indicator (response variables): 1. a simple calculation tool (equation) to infer values for each of the three indicators (response variables) and 2. a hierarchical order of the most significant, morphological explanatory variables in their possible combinations to assess the three selected response variables. The methodology allows estimating the potential energy savings for space heating in urban buildings as a function of their morphologic features and provides a technical basis for the development of a normative aimed at contributing to a greater share of energy and environmental sustainability in the near future.