Residential Electricity Consumption Behavior Analysis and Energy Management Based on NILM

Non-intrusive load monitoring (NILM) technology can obtain detailed residential electricity load data and provide data support for smart home energy management. Based on the non-intrusive load data set, this paper performs analysis on the electricity consumption data of all electrical equipment, calculates residents' electrical appliance usage duration, usage frequency, and electricity consumption proportion, and analyzes the electricity consumption behavior patterns of residential users. Furthermore, based on the analysis of electricity consumption behavior, this paper establishes the models of interruptible load, shiftable load and non-shiftable load for residential electricity consumption. Then an optimization model is established with the goals of economic optimization and user comfort, and an improved genetic algorithm is used to solve this problem. Experimental results show that the proposed method can effectively optimize energy usage plans and guide users to use energy properly.