The Pattern Recognition of Residential Power Consumption Based on HMM

The residential power consumption pattern includes user electricity activity and electric power utility, and the accurate identification of residential power consumption pattern is beneficial to the energy saving and management of power demand side. Based on the analysis of the user’s electric activity, this paper realizes the automatic classification of electric utility of home devices. Based on commercial office buildings, schools, hospitals, residential buildings and other places, through intelligent plugs, sensors, intelligent terminals, such as collection of information related to user activity data, this paper expounds the concept of power use pattern recognition analysis. The main process of power using pattern recognition is introduced, this paper discusses the different scenarios of power use the Hidden Markov Model (HMM) modeling method of pattern recognition, from single-user single-appliance, single-user multi-appliances, multi-users multi-appliances gradually in-depth analysis. Secondly, the main algorithms of learning and decoding are introduced, and the concept of association probability matrix is introduced. Finally, an example is given based on the actual scenario.