An autonomous demand-side management based on adaptive diffusion strategy

This work presents a novel fully distributed and cooperative demand-side management framework based on the adaptive diffusion strategy, wherein, each customer autonomously and without any need to the global information, minimizes his incommodity function. Our framework has ability to track drifts resulting from the changes in the customer preferences and conditions or rapidly updated price parameter coming from the wholesale market. In the considered scenario, the customers aim at maximizing their individual utility functions, while the utility company aims at minimizing the smart grid total payment (i.e., maximization of the social welfare). We show that there is no need for the utility company to participate in the scheduling program for maximizing the social welfare, and this measurement is maximized automatically while the customers minimizing their incommodity. Numerical results show that the proposed framework works well, is scale free, and can achieve lower peak-to-average ratio of the total energy demand compared with game theoretical methods.