Developing a novel model for a smart home energy management system considering grid-connected renewable photovoltaic cell energy

A smart home is equipped with an energy management system aiming to optimize energy consumption. Depending on the residents' needs and preferences, it can adjust the heating and cooling systems to the desired temperature. Furthermore, it intelligently shifts the scheduling of specific high-consumption electrical appliances from the high-price peak power load to the low-price base load. Most previous studies on scheduling home appliances in smart homes have overlooked the potential of harnessing energy from renewable sources. In addition, the mathematical modeling of the optimization problem has commonly resulted in non-linear programming models. This work introduces a new linear mixed-integer programming model for energy management in a smart home, integrating grid-connected renewable photovoltaic cell energy. The energy from the power grid is priced using a real-time pricing policy throughout the day. The objective is to establish an optimal schedule for home appliances, minimizing the overall power consumption cost, and analyzing the economic justification for utilizing solar cells. The proposed model is applied in various scenarios, and the obtained results are compared.