Simulation of a Smart Home Energy Management System with Dynamic Price Response - Jason Y Chan; Qinran Hu (Pursuit - The Journal of Undergraduate Research at the University of Tennessee, 2014)
With the continuing development of the smart grid combined with the fluctuating nature of the electricity market, the development of demand-side management with controllable loads have been greatly driven. With the amount of household loads in the residential sector, managing their energy usage has received lots of interest. This paper presents a simulation of a previously proposed hardware design of a smart home energy management system (SHEMS), focusing on the data collection and processing functions of the proposed design while implementing them onto standard household loads like an electric water heater and an electric vehicle charging station. It was found that the simulation of the loads save consumers money by a significant amount when an SHEMS is implemented when compared to without implementation of an SHEMS.
Keywords: simulation; SHEMS; Smart Home; Energy; Dynamic Pricing; Real Time Pricing; Machine Learning Algorithms