Open AccessEstimating lower probability bound of power system's capability to fully accommodate variable wind generation
Author(s) -
Liu Bin,
Zhai Bingxu,
Liu Mengchen,
Liu Feng,
Lan Haibo
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.8603
Subject(s) - wind power , mathematical optimization , computer science , variable (mathematics) , electric power system , bisection method , upper and lower bounds , random variable , integer programming , linear programming , electricity generation , power (physics) , mathematics , engineering , electrical engineering , mathematical analysis , statistics , physics , quantum mechanics
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.