A subspace signature based approach for residential appliances identification using less informative and low resolution smart meter data

This paper presents a subspace signature based approach for the identification of turned on appliances at a given observation time using one single-function smart meter. The novelty of the proposed approach compared to existing method is its capability for proper identification while relying on a significantly lower amount of measurement data. Unlike existing techniques which rely on multiple measurements at high sampling rate, the proposed method uses only the active power consumption of a grid sampled at second level sampling intervals. This is enabled by constructing signatures for each appliance based on a subspace analysis which incorporates amplitude and frequency information based on active power data. The identification is performed using a Maximum a Posteriori (MAP) criteria using the subspace database that was constructed. This accurately predicts which appliances are turned at any given observation time window. A performance validation is performed for various scenarios to highlight the methods superior accuracy while operating on minimal data at large sampling interval.