Day-ahead optimal scheduling of power systems considering extreme unanticipated timing scenarios

With the large-scale grid connection of new energy and global warming, the probability of unanticipated extreme scenarios in the power system increases. Aiming at the problem that the existing optimal scheduling methods cannot satisfy the feasibility of unanticipated full scenarios, we propose a day-ahead optimal scheduling method considering the extreme unanticipated timing scenarios, and construct an optimal scheduling model containing scheduling plans and scheduling preliminaries. The application cases in real power grids show that the day-ahead scheduling optimization method proposed in this paper can not only take into account the robustness and economy of the scheduling decision, but also fully exploit the role of peak shaving and valley filling of flexible loads under extreme scenarios.