A Step-by-Step Identification Method for Non-intrusive Loads based on Fused Features and Inception-TOPSIS

It fails to correctly identify loads with similar voltage-current trajectories within the non-intrusive load recognition method, besides the training parameters of the recognition model are too many by using a conventional deep learning algorithm, and it also uses up more computer resources. Therefore, the use of fused features and a step-by-step identification algorithm are provided for non-intrusive loads combining the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) algorithm and the Inception network in this paper. Firstly, the Inception network is applied to recognize the loads with voltage-current trajectories in the first step; then the loads that are not successfully identified in the first step can be identified using fused numerical features in the second step based on the TOPSIS algorithm to achieve fast and fine recognition. The proposed method reduces the computational cost and enhances the performance of load recognition, according to the validation and comparative analysis with other algorithms on the Plug-Load Appliance Identification Data set (PLAID).