Real-time deferrable load control

Real-time demand response is potential to handle the uncertainties of renewable generation. It is expected that a large number of deferrable loads, including electric vehicles and smart appliances, will participate in demand response in the future. In this paper, we propose a decentralized algorithm that reduces the tracking error between demand and generation, by shifting the power consumption of deferrable loads to match the generation in real-time. At each time step within the control window, the algorithm minimizes the expected tracking error to go with updated predictions on demand and generation. It is proved that the root mean square tracking error vanishes as control window expands, even in the presence of prediction errors.