Contingency analysis (CA) plays a critical role to guarantee operation security in the modern power systems. With the high penetration of renewable energy, a real-time and comprehensive N-1 CA is needed as a power system analysis tool to ensure system security. In this paper, a graph-based preconditioning conjugate gradient (GPCG) approach is proposed for the nodal parallel computing in N-1 CA. To pursue a higher performance in the practical application, the coefficient matrix of the base case is used as the incomplete LU (ILU) preconditioner for each N-1 scenario. Additionally, the re-dispatch strategy is employed to handle the islanding issues in CA. Finally, computation performance of the proposed GPCG approach is tested on a real provincial system in China.
@article{arxiv.1803.03290,
title = {Graph-based Preconditioning Conjugate Gradient Algorithm for N-1 Contingency Analysis},
author = {Yiting Zhao and Chen Yuan and Guangyi Liu and Ilya Grinberg},
journal= {arXiv preprint arXiv:1803.03290},
year = {2018}
}
Comments
5 pages, 8 figures, Proc. of 2018 IEEE Power and Energy Society General Meeting