Application of cluster analysis for enhancing power consumption awareness in smart grids

Abstract The conceptualization of computing paradigms aimed at converting the power demand data into actionable information, allowing the prosumer to have a full understanding of the available information, represents a timely and relevant issue to address in the context of future smart grids. In the light of this need, this chapter outlines the potential role of self-organizing models based on clustering analysis for classifying the load profiles, correlating them with the endogenous measured variables, and identifying irregularities in energy consumption. The benefits deriving from the application of the proposed framework on complex load patterns have been assessed by detailed experimental results obtained on a real case study.