Analysis of electricity consumption profiles in public buildings with dimensionality reduction techniques

The analysis of the daily electricity consumption profile of a building and its correlation with environmental factors makes it possible to examine and estimate its electricity demand. As an alternative to the traditional correlation analysis, a new approach is proposed to provide a detailed and visual analysis of the correlations between consumption and environmental variables. Since consumption profiles can be characterized by many components, the input space is high dimensional. For that reason, it is necessary to apply dimensionality reduction techniques that enable a projection of these data onto an easily interpretable 2D space. In this paper, several dimensionality reduction techniques are tested in order to determine the most appropriate one for the stated purpose. Later, the proposed approach uses the chosen algorithm to analyze the influence of the environmental variables on the electricity consumption in public buildings located at the University of Leَn. Finally, electricity profiles from all buildings are compared with regard to two aspects, the magnitude and dynamics of the consumption.