Improvement of energy performance metrics for the retrofit of the built environment. Adaptation to climate change and mitigation of energy poverty

摘要

Energy retrofit of existing buildings was highlighted as an efficient massive action to decrease energy consumption and emissions of greenhouse gases. But, detecting the optimal retrofit strategies for groups of buildings is nowadays a highly complex problem. Their energy consumptions are influenced by building related factors (climate, building envelope, building services and systems) and by user-related ones (building operation and maintenance, occupant behavior, and indoor environmental quality). Detecting the contributions of each factor and grouping buildings with similarities-in order to establish similar retrofit strategies - are the main issues that can be faced by statistical multivariate methods. In this paper, we present a new and broader view to propose retrofit strategies adapted to a climate change scenario and analyzed from the economic and energy-poverty points of view, by using multivariate and clustering techniques that include building-related and user-related metrics influencing the energy consumption of groups of buildings. A group of 10 single-family houses in Argentina were selected as a case-study. The contributions of eleven building-related driving metrics and four user-related ones to the energy consumption were analyzed. Then, the more representative house of the cluster was selected for a retrofit analysis for current weather conditions and for future weather under a climate change scenario. The analysis also included an economic assessment in relation to the energy poverty. The higher CV values found in the user-related metrics highlight the influence of occupants in the energy consumption that can result in huge gaps between real and predicted energy performance of buildings. This holistic study contributes to reveal the internal structure of energy consumption and to generate useful knowledge about energy retrofit of the built environment in cities, particularly for those householders which are more susceptible to suffer the adverse effects of energy poverty and climate change. (C) 2018 Elsevier B.V. All rights reserved.