A Data-Driven Dispatching Approach for Sustainable Exploitation of Demand Response Resources

Under the smart-grid environment, demand response (DR) provides an equivalent reserve resource to mitigate operational uncertainties, in addition to the supply-side solutions. Thus, identifying the effect of DR to service reliability turns to be essential for strategic planning decisions. In this paper, a novel data-driven dispatching approach for sustainable exploitation of DR capabilities in future smart-grids is proposed. Differing to existing studies, the user willingness factor attended with DR is especially focused in this work. To achieve this, we develop a two-term DR model, wherein the compliance of customers is characterized as a dynamic self-optimizing process that specified by the regret measure regarding historical payoffs. On this basis, a data-driven-based DR scheduling model is formulated from the grid’s point of view. It could permit desired tradeoffs between the system reliability target and sustainability of DR provision. To verify the effectiveness of the proposed approach, a hybrid algorithm embedded with sequential Monte-Carlo simulations is developed. Numerical experiments are conducted to illustrate the performance of the proposed method based on a real-world distribution network.