Optimization of Smart Home Appliances with Energy Management System

Development of smart grid has given the opportu-nity for the residential consumers to lower their electricity cost by planning their power usage. Accordingly the system operators have the opportunity to include the renewable Energy sources penetration thereby allowing grids dependability by demand side adaptability and load control. Thus, in this work the main goal is to give customers direct access to smart controller to reduce the energy usage depending on their preferences and degree of comfort. In order to optimally schedule different household appliances in a smart home, a unique architecture of home energy management system (HEMS) and an automated Demand response (DR) framework is proposed in this research. Additionally the paper proposes particle swarm optimization to tackle this optimization problem with integration of rooftop solar and wind energies. The proposed method is validated for different case studies of scheduling both in weekdays and weekdays and was found to be very effective in reducing the energy cost of the residential consumers.