Grade analysis for energy usage patterns segmentation based on smart meter data

The Grade Correspondence Analysis (GCA) with posterior clustering and visualization is introduced and applied to smart meter data on individual household level. The main task of this analysis is to reveal the latent structure of electricity usage patterns and to propose a two dimensional segmentation taking into account the usage of selected home appliances and time of their usage. This provides the solutions applicable in smart metering systems that can support usage forecasting and contribute to higher energy awareness.