A Non-Intrusive Load Disaggregation Tool based on Smart Meter Data for Residential Buildings

In the last years there has been a growing spread of smart meters that measure and communicate residential electricity consumption, allowing the development of new energy efficiency services. An interesting application involves the disaggregation of the main home appliances from the aggregated consumption signal. This is essential, in order to make predictions and optimizations for the implementation of Demand Side Management (DSM) strategies, also applicable to Energy Communities perspective. In this paper an infrastructure and a set of algorithms to collect data from Italian second-generation smart meters and break down the total power measured by them into those used by main individual appliances are presented. By using Non-Intrusive Load Monitoring (NILM) techniques, the proposed methodology can identify when a specific appliance is operating and then, through unsupervised clustering algorithms applied to the detected devices, create an appliance's properties database. The system is also tested using data collected from three households in Italy and results are reported in the paper.