Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

Abhyankar, Shrirang; Constantinescu, Emil M.; Smith, Barry F.; Flueck, Alexander J.; Maldonado, Daniel A.

doi:10.1109/TSG.2016.2610863

Title: Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

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Abstract

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including a real utility network, show good scalability on different computing architectures.

Authors:

Abhyankar, Shrirang ^[1]; Constantinescu, Emil M. ^[1]; Smith, Barry F. ^[1]; Flueck, Alexander J. ^[2]; Maldonado, Daniel A. ^[2]

Argonne National Lab. (ANL), Argonne, IL (United States)
Illinois Institute of Technology, Chicago, IL (United States)

Publication Date:: Mon Nov 07 00:00:00 EST 2016

Research Org.:: Argonne National Lab. (ANL), Argonne, IL (United States)

Sponsoring Org.:: USDOE Office of Electricity Delivery and Energy Reliability

OSTI Identifier:: 1374603

Grant/Contract Number:: AC02-06CH11357

Resource Type:: Accepted Manuscript

Journal Name:: IEEE Transactions on Smart Grid

Additional Journal Information:: Journal Volume: 8; Journal Issue: 3; Journal ID: ISSN 1949-3053

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 24 POWER TRANSMISSION AND DISTRIBUTION; 97 MATHEMATICS AND COMPUTING; parallel processing; iterative linear solution; dynamics simulation; GMRES; Krylov subspace; power system dynamics; Schwarz preconditioning; transient stability

Citation Formats


                    Abhyankar, Shrirang, Constantinescu, Emil M., Smith, Barry F., Flueck, Alexander J., and Maldonado, Daniel A. Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme.  United States: N. p., 2016. 
Web.  doi:10.1109/TSG.2016.2610863.

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                    Abhyankar, Shrirang, Constantinescu, Emil M., Smith, Barry F., Flueck, Alexander J., & Maldonado, Daniel A. Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme.  United States.  https://doi.org/10.1109/TSG.2016.2610863

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                    Abhyankar, Shrirang, Constantinescu, Emil M., Smith, Barry F., Flueck, Alexander J., and Maldonado, Daniel A. Mon .  
"Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme".  United States.  https://doi.org/10.1109/TSG.2016.2610863.  https://www.osti.gov/servlets/purl/1374603.

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@article{osti_1374603,

  title        = {Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme},

  author       = {Abhyankar, Shrirang and Constantinescu, Emil M. and Smith, Barry F. and Flueck, Alexander J. and Maldonado, Daniel A.},

  abstractNote = {Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including a real utility network, show good scalability on different computing architectures.},

  doi          = {10.1109/TSG.2016.2610863},

  journal      = {IEEE Transactions on Smart Grid},

  number       = 3,

  volume       = 8,

  place        = {United States},

  year         = {Mon Nov 07 00:00:00 EST 2016},

  month        = {Mon Nov 07 00:00:00 EST 2016}

}

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