Stochastic modeling and disaggregation of energy-consumption behavior

This paper focuses on stochastic modeling and energy disaggregation based on conditional random fields (CRFs) using real-world energy consumption data. Firstly, energy-consumption activities modeling aims at understanding and identifying energy-consumption activities using behavior models based on observed energy signals. Our ultimate goal is to suggest ways to modify human behavior activities in order to conserve energy by optimizing the use of energy. Preliminary analysis of energy consumption data clearly shows the potential effectiveness of activity behavior changes on the changing energy consumption behavior. Secondly energy disaggregation aims at breaking up the total energy signal into its component appliances. This is very useful since it can provide home owners with feedback about the way they use electrical energy, and can also motivate users to conserve significant amounts of energy. In the current study, we focus on activity/event disaggregation using the total energy-consumption signal.