Parallel Newton type methods for power system stability analysis using local and shared memory multiprocessors

Chai, J.S.; Zhu, Ning; Bose, Anjan; Tylavsky, Daniel

doi:10.1109/59.117001

Cited by 78 publications

(33 citation statements)

References 9 publications

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“…It could be seen that from Table 4 the new parallel algorithm has higher parallel efficiency than that of parallel-in-space algorithm. 4, it is indicated that the performance of the new algorithm for the test system case is decreased greatly when the CPU number reaches 6, although the simulation run-time is shortened a little, the parallel efficiency is reduced sharply, about 21.8% decreased compared with that of 4 CPUs, the speedup only increases a little too and nearly arrives the saturation ( the limit). The main reason of that situation is the communication bottleneck between the subsystems.…”

Section: A the Speedup Of The Tested Casementioning

confidence: 92%

“…The main idea of the parallel-in-space is to solve the linear equations in parallel and is suitable for parallelizing the serial program [2][3][4][5][6]. Actually it has not fully taken use of the inherent parallel characteristic of power system, for an example: the operation and management of power system is always divided by sub-areas and layers (voltage levels) and exist much parallel behavior among them.…”

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confidence: 99%

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Parallel simulation for the transient stability of power system

Lin

Tong

Wang

et al. 2008

2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies

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Parallel time domain simulation is one of the reliable and potential methods that might realize the real-time online transient stability analysis of power system. In the paper, a new parallel calculation method, based on waveform relaxation method, is proposed for power system transient stability analysis. In the method, the entire transmission network is first divided into several subsystems by the geographical location; for each subsystem, its neighboring systems are represented as equivalent voltage sources at the boundary buses; the tie line flows are considered as the communication waveform among the subsystems; then, time domain simulation for each subsystem is performed in parallel. The test result of the practical system indicates that the new parallel algorithm completely achieves the on-line real-time or even over-real-time calculation speed and could be applied to the on-line transient stability analysis of practical system.

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Section: A the Speedup Of The Tested Casementioning

confidence: 92%

mentioning

confidence: 99%

Parallel simulation for the transient stability of power system

Lin

Tong

Wang

et al. 2008

2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies

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“…This saves a lot of efforts to make the estimator fast. If the Jacobian is fixed for a very long time, it is also referred as the very dishonest Newton (VDHN) method [6]. It is mainly applied in the stability analysis.…”

Section: Performance Of Dishonest Gauss Newton Methodsmentioning

confidence: 99%

Dishonest Gauss Newton method based power system state estimation on a GPU

Rahman

Venayagamoorthy

2016

2016 Clemson University Power Systems Conference (PSC)

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To control a fast changing power system in real time, it is important to accelerate the computation processes related to it. Being one of the most time-consuming processes, state estimation needs to be made fast and scalable. Different methods were introduced in the literature over time to serve the purpose. It is high time to make the best out of them to find the fastest estimator with current parallel computation technology. In this study, the dishonest Gauss Newton method is implemented in a Graphics Processing Unit (GPU). As the method is not well explored in the literature, the performance of it is investigated first. Then different aspects of the parallel implementation is explained. It runs in hundreds of microseconds for IEEE 118-bus systems which is the fastest according to the authors findings. For very large systems, the required configuration of a GPU and the corresponding time are also estimated.Index Terms: Dishonest Gauss-Newton method, nonlinear power flow, parallel programming, scalability, and weighted least square estimator.

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“…Some methods, like parallel VDHN [12], Newton W-matrix [13] and parallel LU [14], divide the independent vector and matrix operations involved in the linear system solution over the available computing units. Other methods, like parallel successive over relaxed Newton [15] and MaclaurinNewton [12], use an approximate (relaxed) Jacobian matrix with more convenient structure for parallelization.…”

Section: B2 Fine-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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Parallel Newton type methods for power system stability analysis using local and shared memory multiprocessors

Cited by 78 publications

References 9 publications

Parallel simulation for the transient stability of power system

Parallel simulation for the transient stability of power system

Dishonest Gauss Newton method based power system state estimation on a GPU

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

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