Graph-based Preconditioning Conjugate Gradient Algorithm for "N-1" Contingency Analysis

descriptionPublicationkeyboard_double_arrow_right Article , Preprint 01 Aug 2018Embargo end date: 01 Jan 2018Publisher:IEEEJournal:2018 IEEE Power & Energy Society General Meeting (PESGM)

Authors: Zhao, Yiting; Yuan, Chen; Liu, Guangyi; Grinberg, Ilya;

doi: 10.1109/pesgm.2018.8586214 , 10.48550/arxiv.1803.03290

arXiv: 1803.03290

Graph-based Preconditioning Conjugate Gradient Algorithm for "N-1" Contingency Analysis

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Abstract

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.

5 pages, 8 figures, Proc. of 2018 IEEE Power and Energy Society General Meeting

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Keywords

FOS: Computer and information sciences, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Data Structures and Algorithms, FOS: Mathematics, Data Structures and Algorithms (cs.DS), Mathematics - Numerical Analysis, Distributed, Parallel, and Cluster Computing (cs.DC), Numerical Analysis (math.NA)

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