A highly parallel method for transient stability analysis

Scala, Massimo La; Bose, Anjan; Tylavsky, Daniel; Chai, J.S.

doi:10.1109/pica.1989.39020

Cited by 21 publications

(9 citation statements)

References 11 publications

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“…Later methods, like waveform relaxation [17] and parallel-in-time [18], introduced the idea of exploiting parallelization in time to increase the granularity of the parallel tasks. Following, several methods were proposed inspired by different hardware platforms, memory models and partitioning schemes [2], [19], [20], [21].…”

Section: B3 Coarse-grained Parallel Methodsmentioning

confidence: 99%

Dynamic Simulation of Large-Scale Power Systems Using a Parallel Schur-Complement-Based Decomposition Method

Aristidou

Fabozzi

Cutsem

2014

IEEE Trans. Parallel Distrib. Syst.

116

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Article:Aristidou, P orcid.org/0000-0003- 4429-0225, Fabozzi, D and Van Cutsem, T (2014) Dynamic simulation of large-scale power systems using a parallel schur-complement-based decomposition method. IEEE Transactions on Parallel and Distributed Systems, 25 (10). pp. 2561 -2570 . ISSN 1045 https://doi.org/10.1109/TPDS.2013.252 © 2013 IEEE. This is an author produced version of a paper published in IEEE Transactions on Parallel and Distributed Systems. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy.eprints@whiterose.ac.uk https://eprints.whiterose.ac.uk/ Reuse Unless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. APPENDIX A DOMAIN DECOMPOSITION METHODSDDMs were originally used due to the lack of memory in computing systems: data needed for smaller portions of a problem could fit entirely to the memory while for the whole problem they could not. They lost their appeal as larger and cheaper memory became available, only to resurface in the era of parallel computing. These methods are inherently suited for execution on parallel architectures and many parallel implementations have been presented on multi-core computers, clusters and lately Graphics Processing Units (GPUs) [1], [2]. They are mainly distinguished by three features: subdomain partitioning, problem solution over sub-domains and sub-domain interface variable processing [3]. A.1 Sub-domain PartitioningSub-domain partitioning has to be chosen based on the desired sub-domain characteristics for the given problem. This includes choosing the number of sub-domains, the type of partitioning, and the level of overlap between the sub-domains. Each of these choices depend on a variety of factors such as size, type, and geometry of the problem domain, the number of parallel processors, communication cost, and the actual system being solved.When considering spatial domain problems, such as PDEs, the decomposition is usually g...

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Section: B3 Coarse-grained Parallel Methodsmentioning

confidence: 99%

Dynamic Simulation of Large-Scale Power Systems Using a Parallel Schur-Complement-Based Decomposition Method

Aristidou

Fabozzi

Cutsem

2014

IEEE Trans. Parallel Distrib. Syst.

116

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“…Para estes casos, métodos iterativos pré-condicionados baseados no subespaço Krylov surgiram como boas alternativas e passaram a ser explorados em diversas áreas da engenharia (Dong & Li, 2007;Lee et al, 2004;Polydorides et al, 2002;Saitoh & Kamitani, 2004). Uma das vantagens desses métodos é o alto desempenho e relativa simplicidade de implementação em ambientes computacionais paralelos, fato não observado para os métodos diretos (Alvarado, 1979;La Scala et al, 1989;Chai & Bose 1993).…”

Section: Ax = Bunclassified

Investigação crítica do desempenho do GMRES pré-condicionado via fatoração incompleta LU em estudos de fluxo de carga

Pessanha¹,

Portugal

Saavedra³

2009

Sba Controle & Automação

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Este artigo investiga causas associadas ao baixo desempenho de um pré-condicionador ILU e propõe uma metodologia para melhorar a sua qualidade e a taxa de convergência do método iterativo GMRES. O objetivo é solucionar o subproblema linear do fluxo de carga, com destaque para condições de carga pesada e de difícil convergência. A metodologia está baseada em duas etapas. Na primeira, um pré-condicionador é construído a partir da matriz Jacobiana da primeira iteração Newton-Raphson reordenada. A segunda etapa só é considerada se o GMRES falhar no início do processo de solução devido à baixa qualidade do pré-condicionamento. Nela, o processo é reiniciado e um pré-condicionador de melhor qualidade é construído a partir da matriz Jacobiana pré-processada via escalonamento e permutações não-simétricas e simétricas (reordenamento). A fim de amenizar o custo computacional associado a sua construção, uma estratégia para manter o pré-condicionador fixo sempre que possível é incluída. Experimentos numéricos corroboram a robustez numérica e a eficiência computacional da metodologia proposta.

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“…Parallelization in time allows computing in parallel the evolution of sub-systems over windows of time. Parallelization in space and in time have been exploited to various degrees in the waveform relaxation method [5], in the methods described in [6,7], and in the multi-rate method [8]. All these approaches involve some form of relaxation which, on one hand, allows full parallelization but, on the other hand, may require to perform several iterations over the same window of time, until convergence of solution is reached.…”

Section: Introductionmentioning

confidence: 99%

Localization and latency concepts applied to time simulation of large power systems

Fabozzi

Cutsem

2010

2010 IREP Symposium Bulk Power System Dynamics and Control - VIII (IREP)

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This paper reports on investigations to speed up timedomain simulations of large electric power systems. First, a decomposed scheme is considered which exploits the bordered block diagonal structure of the original Jacobian involved in the Newton iterations, and keeps the resulting "local" Jacobians constant over multiple iterations. Next, a localization technique is considered, allowing to perform less iterations on the system components with lower activity. Finally, a third scheme consists of visiting only a subset of components, identified as active, and skipping the other ones, identified as latent. The first two techniques solve the whole set of equations with the required accuracy, while the third one involves an adjustable degree of approximation. The methods are illustrated on a small system, while preliminary checks of computational savings from a large test system are reported. Additional results deal with the application of the localization and latency techniques to simplified simulation of the detailed model.

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A highly parallel method for transient stability analysis

Cited by 21 publications

References 11 publications

Dynamic Simulation of Large-Scale Power Systems Using a Parallel Schur-Complement-Based Decomposition Method

Dynamic Simulation of Large-Scale Power Systems Using a Parallel Schur-Complement-Based Decomposition Method

Investigação crítica do desempenho do GMRES pré-condicionado via fatoração incompleta LU em estudos de fluxo de carga

Localization and latency concepts applied to time simulation of large power systems

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