Estimating lower probability bound of power system's capability to fully accommodate variable wind generation

• Main Authors: Bin Liu, Bingxu Zhai, Mengchen Liu, Feng Liu, Haibo Lan
• Format: Article
• Language: English
• Published: Wiley 2019-04-01
• Series: The Journal of Engineering
• Subjects: probability; wind power plants; integer programming; linear programming; variable wind generation; wind generation increases; power system operation; lower probability bound estmation; immune operation strategies; power system capability; polyhedron; three-level optimisation problem; max-min problem; mixed-integer linear program; MILP; bisection algorithm; modified IEEE systems
• Online Access: https://digital-library.theiet.org/content/journals/10.1049/joe.2018.8603

As the penetration of wind generation increases, the uncertainty it brings has imposed great challenges to power system operation. To cope with the challenges, tremendous research work has been conducted, among which two aspects are of most importance, that is, making immune operation strategies and accessing the power system's capability to accommodate the variable energy. Driven and inspired by the latter problem, this paper will discuss the power system's capability to accommodate variable wind generation in a probability sense. Wind generation, along with its uncertainty is illustrated by a polyhedron, which contains prediction, risk, and uncertainty information. Then, a three-level optimisation problem is presented to estimate the lower probability bound of power system's capability to fully accommodate wind generation. After reformulating the inner max-min problem, or feasibility check problem, into its equivalent mixed-integer linear program (MILP) form, the bisection algorithm is presented to solve this challenging problem. Modified IEEE systems are adopted to show the effectiveness of the proposed method.