Smart home heating system malfunction and bad behavior diagnosis by Multi-Scale PCA under indoor temperature feedback control

The household sector is one of the biggest aggregate consumers and this is the reason why increasingly policies have been considering it. One of the key factors in curbing energy consumption in this sector is widely recognized to be due to erroneous behaviors and systems malfunctioning. In this context, energy management in homes is playing, and will play even more in future, a key role in increasing the final consumer awareness towards its own energy consumption and consequently in bursting its active role in smart grids. This paper highlights the economic benefits of low cost intelligent control domestic devices and identifies energy behavior, system malfunctions and improves energy efficiency. The scope is to detect and isolate different types of malfunctions and bad behaviors under an ambient temperature feedback control. The paper presents an application of Multi-Scale Principal Component Analysis to diagnose inefficient occupant behavior and systems malfunctioning and suggest good practices of energy conservation.