With the large-scale deployment of smart meters

data analysis based on low frequency signals collected by electric meter has become a research hotspot. Therefore

a low-rate power signal disaggregation algorithm based on graph signal processing(GSP)is studied in the background of non-intrusive load monitoring. Firstly

the power signal disaggregation problem is defined as a minimization problem

the total graph variation based on graph shift matrix is introduced as a regularization term. Then

the optimization problem is solved in two steps

which are minimizing the regularization term to find the approximate solution with minimum variation

using SA algorithm to minimize the objective function and constraint interactively based on the approximate solution. Finally

the open-access REDD dataset is used to demonstrate the advantage of the proposed algorithm in classification accuracy

especially for low power and multi-state load. Compared with other algorithms

the proposed algorithm is less dependent on training data.