عنوان مقاله [English]
Using the capabilities of smart meters and smart grid technologies, a new DR participant with considerable load flexibility is created from the residential side called the intelligent residential community. In this paper, smart residential loads are divided into three categories of shiftable, interruptible, and controllable loads and a new method based on binary particle swarm algorithm (BPSO) to solve the DR problem is presented. The type of load shedding is determined for different loads. Then, by solving the continuous variables of the problem, the amount of load shedding at different loads is determined. The proposed system uses distributed generation sources, battery storage, and electric vehicles. Also, in real-world problems, changing one of the data may violate a large number of constraints and make the answer non-optimal or even impossible. As a result, we need a model that is resistant to this data uncertainty. This type of optimization is called robust optimization (RO). Therefore, a variety of real-time pricing (RTP), time-of-use (TOU), and critical peak pricing (CPP) schemes have been used in a robust design. To validate of the proposed method, the simulation is performed on a test system. The results show the efficiency of the proposed method in planning and reducing users' consumption costs. Also, the proposed method is able to provide solutions that are resistant to various conditions due to uncertainty.