Multidimensional analyses tools for energy efficiency in large building stocks

Energy Indices and Targets for large building stocks are a still complex field of debate. While various indices have been suggested, for instance based on Heating Degree Days or energy consumption per square meter / user, there is no generally recognized index for large building stocks, because of several factors which complicate their analysis. The heterogeneity in building functions and structures, number of users and opening hours, for instance, directly affects the energy consumption. Our approach is based on multidimensional analysis of various Energy Efficiency Indices (EEI), as energy consumption per square meter or the day / night energy efficiency index, computed from simple data available for any building: monthly energy consumptions, total area, and building functions. Starting from available data for the University of Turin, composed by over than 46 buildings, and thanks to Data Visualization Javascript libraries, an interactive web application has been developed. In this paper, four different types of multidimensional plots, based on the scatter method and the parallel coordinates method, will be discussed. These approaches can be employed to form clusters of buildings and to identify specific thresholds for indices with respect to the functions of the buildings or other factors. Where the most common and simplest indices actually fail, the setting of alert thresholds for the energy consumption of buildings with different functions can support the Energy Management in meeting efficiency targets. Results obtained for specific building types have been reported.