Introducing a New Scheme for Demand Response of a Smart Residential Community with a Variety of Demand Response Models

Using the capabilities of smart meters and smart grid technologies, a new demand response (DR) participant with considerable load flexibility was created from the residential side called the intelligent residential community. In this paper, smart residential loads were 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 was determined for different loads. Then, by solving the continuous variables of the problem, the amount of load shedding at different loads was determined. The proposed system uses distributed generation sources, battery storage, and electric vehicles. Furthermore, in the proposed model, a robust optimization method for dealing with uncertainties is presented using a variety of real-time pricing (RTP), time-of-use (TOU), and critical peak pricing (CPP) schemes in a robust design. A comparison of the different types of demand response schemes was made and the best design for optimal demand response was selected. To validate the proposed method, a simulation was performed on a test system and the results indicated the efficiency of the proposed method in planning and reducing users' consumption costs.