<p>This paper presents an innovative strategy for the management of smart homes integrated within a residential microgrid. The objective is to enhance the efficiency of energy consumption and production within the smart microgrid in order to reduce the reliance of smart homes on external energy sources. Specifically, the study investigates zero-energy buildings by taking into account local renewable energy resources and electric vehicles. The primary goal of the energy management program is to increase the zero-energy rate of smart buildings in a residential microgrid by decreasing the energy dependence of homes on the microgrid’s energy. To fulfill this goal, the multi-objective optimization program focuses on minimizing network peak demand and lowering customers' electricity costs as its key objectives. The simulation of the actual operational condition of the microgrid is enhanced by taking into account the stochastic behavior exhibited by photovoltaic panels, wind turbines, and electric vehicles. Furthermore, household appliances are divided into non-shiftable and shiftable groups. The dragonfly algorithm, integrated with the fuzzy setting approach, is employed to address the specified multi-objective challenge. To assess the efficacy of the intelligent approach, a residential microgrid comprising fifty smart homes is considered. The numerical results indicate that the proposed method successfully determines the optimal operational schedule for smart homes, leading to a reduction in economic and environmental indices by approximately 48.44 and 45.69%, respectively, compared to the initial conditions. Consequently, this approach contributes to an increase in the zero-energy rate of residential buildings.</p>