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

Yiting Zhao; Chen Yuan; Guangyi Liu; Ilya Grinberg

doi:10.1109/pesgm.2018.8586214

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

Yiting Zhao, Chen Yuan, Guangyi Liu, Ilya Grinberg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

25 Scopus citations

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.

Original language	English
Title of host publication	2018 IEEE Power and Energy Society General Meeting, PESGM 2018
Publisher	IEEE Computer Society
ISBN (Electronic)	9781538677032
DOIs	https://doi.org/10.1109/pesgm.2018.8586214
State	Published - 21 Dec 2018
Externally published	Yes
Event	2018 IEEE Power and Energy Society General Meeting, PESGM 2018 - Portland, United States Duration: 5 Aug 2018 → 10 Aug 2018

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2018-August
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2018 IEEE Power and Energy Society General Meeting, PESGM 2018
Country/Territory	United States
City	Portland
Period	5/08/18 → 10/08/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

"N-1" contingency analysis
Graph theory
ILU preconditioner
Nodal parallel computing
Preconditioning conjugate gradient algorithm

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/pesgm.2018.8586214

Cite this

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title = "Graph-based Preconditioning Conjugate Gradient Algorithm for {"}n-1{"} Contingency Analysis",

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.",

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Zhao, Y, Yuan, C, Liu, G & Grinberg, I 2018, Graph-based Preconditioning Conjugate Gradient Algorithm for "n-1" Contingency Analysis. in 2018 IEEE Power and Energy Society General Meeting, PESGM 2018., 8586214, IEEE Power and Energy Society General Meeting, vol. 2018-August, IEEE Computer Society, 2018 IEEE Power and Energy Society General Meeting, PESGM 2018, Portland, United States, 5/08/18. https://doi.org/10.1109/pesgm.2018.8586214

Graph-based Preconditioning Conjugate Gradient Algorithm for "n-1" Contingency Analysis. / Zhao, Yiting; Yuan, Chen; Liu, Guangyi et al.
2018 IEEE Power and Energy Society General Meeting, PESGM 2018. IEEE Computer Society, 2018. 8586214 (IEEE Power and Energy Society General Meeting; Vol. 2018-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Graph-based Preconditioning Conjugate Gradient Algorithm for "n-1" Contingency Analysis

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AU - Yuan, Chen

AU - Liu, Guangyi

AU - Grinberg, Ilya

PY - 2018/12/21

Y1 - 2018/12/21

N2 - 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.

AB - 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.

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KW - Nodal parallel computing

KW - Preconditioning conjugate gradient algorithm

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

Abstract

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Bibliographical note

Keywords

UN SDGs

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