The theoretical potential for renewable energy resources (RES) to meet the global demands of energy is generally high and the ambitions for introducing RES into energy systems are growing worldwide, which also can contribute to global climate change mitigation if it is produced in a sustainable manner. To address these issues, more and more governments are implementing various programs and energy policies to accelerate the deployment of RES. The aforementioned two reasons lead to an urgent need to add new generating capacity or reduce consumption during peak periods, or both. The first option for power generation is to use RES which can inject electric energy to the grid while avoiding greenhouse gas emissions. However, the capacities of RES are not enough to supply all the required power from the side of the load. Facts that are leading to the proposal of original ways to reduce the use of energy in many sectors, namely in commercial, residential, and industrial sectors, in order to reduce the total energy costs of the consumer, to reduce the energy demand specially during on-peak hours and the greenhouse gas emissions while safeguarding end-user preferences. The aim of this paper is to determine the impact of model predictive control (MPC) on energy savings of residential households. Furthermore, the value and impact of generated power by local power sources, such as roof-top-solar, will be determined during off-peak, mid-peak, and on-peak, providing simulations during 24 hours in a house.