A distributed game-theoretic demand response with multi-class appliance control in smart grid

We propose an event-triggered game-theoretic strategy for managing the power grids demand side, capable of responding to changes in consumer preferences or the price parameters coming from the wholesale market. The relationship between the retailer and the residential consumers is modeled as one-leader, N-follower Stackelberg game. We provide a detailed characterization of the household appliances to reflect the reality and improve the efficiency of the demand response (DR). Moreover, to consider all the appliances’ essentials, the consumer's objective function is formulated as a mixed integer non-linear program (MINLP), which, unlike conventional procedures, is solved via an integrated method. The proposed method consists of a day-ahead stage, in which the DR problem is solved for the next scheduling horizon, and a real-time stage which runs repeatedly to tackle the change in the parameters and adapt to the new condition. For any change in the grid, the consumers use the estimated optimal parameters (given by the original objective function) and develop another Stackelberg game based solution to maximize the satisfaction level. Given the appliances of multi-class nature, the proposed method is shown to be very tractable for ancillary services and reducing the mismatch between the renewable power generation and the load demand