A novel economic structure to improve the energy label in smart residential buildings under energy efficiency programs

Energy label could be a powerful tool to save energy and reduce energy costs in the residential sector. This paper proposes a novel economic structure between the residential consumers and the International Energy Agency (IEA) to determine the energy label of the smart residential buildings within the framework of the energy efficiency policies. The proposed structure is a developed model of the existing national certificates, such as Energy Star. In the proposed method, the concept of the energy labeling was improved based on the optimization problem by considering the hourly injected energy from the utility to buildings and annual energy consumption. In addition, an incentive mechanism was designed to encourage volunteer customers to change their consumption patterns based on the presented energy labeling structure. The incentive mechanism is flexible and can be changed by the system operator considering the energy label variation. Different practical methods, which included the economic heat and electrical demands model, building-integrated photovoltaic (BIPV), and building integrated plug-in hybrid electric vehicle (PHEV), were evaluated to promote the energy label of the residential building. For practical implementation, the proposed structure was applied to a sample smart residential building in East-Azerbaijan of Iran, and it was solved using GAMS software. The numerical results based on realistic data validated the effectiveness of the presented practical methods within the framework of the introduced energy labeling structure. According to the obtained results, the energy label index of the selected test system was promoted from F to E in the presence of the economic demand model and PHEV and promoted to D by using the economic demand model and BIPV system. In addition, the amount of energy injected into the building was decreased by up to 2.52% through the economic demand and PHEV schemes and up to 17.22% in the presence of the BIPV system. (C) 2020 Elsevier Ltd. All rights reserved.