Multistage Scheduling of Regional Power Grids Against Sequential Outage and Power Uncertainties

Abstract

Aiming at the scheduling problem for regional power grids under both outage and power uncertainties, this paper puts forward a multistage robust optimization (RO) method that ensures the reliable power supply in system operations. Firstly, a multistage RO model is proposed according to the practical scheduling request of the regional power grid. The startup and shutdown of slow-acting generators are optimized in the first stage. The optimal topology is then determined in the second stage in preparation to the outage uncertainty of grid-connected lines. In the third to 2+ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${T}$ </tex-math></inline-formula> stages, the scheduling plans of generation units in each time period are further formulated regarding the sequential realizations of renewable-load power uncertainties, which ensures the nonanticipativity of the obtained robust schedules. Secondly, a tailored and efficient transformation-decomposition algorithm is exploited for the solution of multistage RO problem. Based on the affine control function, the nested max-min optimization of the third to 2+ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${T}$ </tex-math></inline-formula> stages is explicitly transformed to a single-stage max-min model via the multi-to-one strategy. A column and constraint generation (C&CG) algorithm with looped alternative optimization procedure (AOP) handles the equivalent three-stage RO problem with binary recourses, thus avoiding numerous forward and backward iterations as well as speeding up the modeling solution. Numerical experiments of real-world regional power grids verify the effectiveness, superiorities and scalability of the proposed multistage RO scheduling method, which indicates great guidance for engineering applications.