Home Energy Simulation for Non-Intrusive Load Monitoring Applications

Abstract

Home Energy Management (HEM) is a vital component of smart grid, which can be considered as a distributed cyber physical system. HEM involves appropriate management of home appliance usage through deliberate efforts from the end-user. This can enable a stable operation of the grid as well as reduce energy usage and bills for the end-user. The installation of smart meter has led to a number of analytics and applications developed on top of its data. However, the algorithms are evaluated over a very small subset of experimental or open dataset. To mitigate this problem, a bottom-up data generation approach is proposed in this paper. The appliances are considered as combination of fundamental electrical components. The appliance characteristics and operations are modeled through stochastic parameters, which are available as prior information or through learning from existing meter data. Preliminary results of generating data for the application of Non-Intrusive Load Monitoring is presented.