Robust scheduling of smart home with heating load and storage with plug-in electric vehicle battery energy storage and photovoltaic array

Due to the growing prevalence of electric vehicles and photovoltaic arrays, as well as the need to reduce electricity consumption during peak load periods, energy management systems (EMS) are becoming increasingly crucial in smart homes. By determining when and how electric vehicles are charged or discharged, as well as when electricity is used for other residential activities, EMS can significantly reduce peak energy consumption. In order to accomplish this, a heating and storage model has been developed that incorporates PV cells with uncertain power output, electric vehicles in smart parking lots that can charge or discharge energy from the grid, an air conditioning system that controls the temperature of the smart home with input and output temperature constraints, and deferrable loads that can be shifted to times when electricity prices are lower. GAMS simulation software is used to optimize this model using the CPLEX solver. The model was solved without taking time-of-use (TOU) uncertainty and dynamic load pricing into account. Using EMS in smart homes is an excellent method to promote energy efficiency and sustainability. By incorporating uncertainty and dynamic pricing into the optimization procedure, the model can be enhanced and the decision-making process made more transparent.

Keywords:

Smart home , Electric vehicle , Photovoltaic , Energy management system , Robust