Optimal scheduling of flexible residential loads under demand response programs considering user comfort

This study proposes a new model to optimize the costs and benefits of residential customers participating in an incentive-based demand response program with the consideration of customers' comfort level. In this respect, a model is proposed for minimizing an objective function including the cost of electricity purchased from the grid and the financial rewards that a customer receives from participating in an incentive-based demand response program. The proposed model takes advantage of a new multilevel reward function while also accounting for consumers' comfort level. The model is formulated as a mixed-integer linear programming (MILP) optimization problem. Implementation of the proposed model for a residential consumer reveals the significant potential of heating, ventilation, and air-conditioning (HVAC), electric water heater (EWH), and electric vehicle (EV) with the capability of power injection to the grid for consumption reduction during a target period. It is shown that the incentive-based DR has a higher impact compared to the price-based DR.