A distributed computing approach for real-time transient stability analysis

Power system online dynamic security assessment (DSA) is a challenging computing problem. A key problem in DSA is the analysis of a large number of dynamic stability contingencies every 10-20 minutes using online data. In order to speed up the transient stability analysis, parallel processing has be...

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Veröffentlicht in:IEEE transactions on power systems Jg. 12; H. 2; S. 981 - 987
Hauptverfasser: Aloisio, G., Bochicchio, M.A., La Scala, M., Sbrizzai, R.
Format: Journal Article Tagungsbericht
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.05.1997
Institute of Electrical and Electronics Engineers
Schlagworte:
Applied sciences
Clustering algorithms
Data security
Distributed computing
Electrical engineering. Electrical power engineering
Electrical power engineering
Exact sciences and technology
Power networks and lines
Power system analysis computing
Power system dynamics
Power system security
Power system stability
Power system transients
Stability analysis
Theory. Simulation
Transient analysis
Workstation
Distributed processing
Synchronous machine
Multimachine power system
Electrical network
Virtual machine
Parallel processing
Software
Transient stability
Real time
System analysis
ISSN:0885-8950
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Abstract Power system online dynamic security assessment (DSA) is a challenging computing problem. A key problem in DSA is the analysis of a large number of dynamic stability contingencies every 10-20 minutes using online data. In order to speed up the transient stability analysis, parallel processing has been applied and several results can be found in the literature. In this paper, the authors present a distributed approach for real-time transient stability analysis. Distributed computing is economically attractive providing the processing power of supercomputing at a lower cost. Several distributed software environments like the parallel virtual machine (PVM) allow an effective use of heterogeneous clusters of workstations. Both functional and domain decomposition of the transient stability problem were tested under PVM on a homogeneous cluster of eight DEC ALPHA and on an IBM SP2 machine. Functional decomposition has been obtained by the Shifted-Picard algorithm, whereas domain decomposition has been obtained concurrently running different contingencies on different nodes of the cluster, using the very dishonest Newton algorithm. In order to assess the performance of these approaches, time domain simulations, adopting detailed modeling for synchronous machines, have been carried out on a realistic-sized power network comprising 2583 buses and 511 generators.
AbstractList Power system online dynamic security assessment (DSA) is a challenging computing problem. A key problem in DSA is the analysis of a large number of dynamic stability contingencies every 10-20 minutes using online data. In order to speed up the transient stability analysis, parallel processing has been applied and several results can be found in the literature. In this paper, the authors present a distributed approach for real-time transient stability analysis. Distributed computing is economically attractive providing the processing power of supercomputing at a lower cost. Several distributed software environments like the parallel virtual machine (PVM) allow an effective use of heterogeneous clusters of workstations. Both functional and domain decomposition of the transient stability problem were tested under PVM on a homogeneous cluster of eight DEC ALPHA and on an IBM SP2 machine. Functional decomposition has been obtained by the Shifted-Picard algorithm, whereas domain decomposition has been obtained concurrently running different contingencies on different nodes of the cluster, using the very dishonest Newton algorithm. In order to assess the performance of these approaches, time domain simulations, adopting detailed modeling for synchronous machines, have been carried out on a realistic-sized power network comprising 2583 buses and 511 generators
Power system online dynamic security assessment (DSA) is a challenging computing problem. A key problem in DSA is the analysis of a large number of dynamic stability contingencies every 10-20 minutes using online data. In order to speed up the transient stability analysis, parallel processing has been applied and several results can be found in the literature. In this paper, the authors present a distributed approach for real-time transient stability analysis. Distributed computing is economically attractive providing the processing power of supercomputing at a lower cost. Several distributed software environments like the parallel virtual machine (PVM) allow an effective use of heterogeneous clusters of workstations. Both functional and domain decomposition of the transient stability problem were tested under PVM on a homogeneous cluster of eight DEC ALPHA and on an IBM SP2 machine. Functional decomposition has been obtained by the Shifted-Picard algorithm, whereas domain decomposition has been obtained concurrently running different contingencies on different nodes of the cluster, using the very dishonest Newton algorithm. In order to assess the performance of these approaches, time domain simulations, adopting detailed modeling for synchronous machines, have been carried out on a realistic-sized power network comprising 2583 buses and 511 generators.
Author Aloisio, G.
La Scala, M.
Sbrizzai, R.
Bochicchio, M.A.
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Keywords Workstation
Distributed processing
Synchronous machine
Multimachine power system
Electrical network
Virtual machine
Parallel processing
Software
Transient stability
Real time
System analysis
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SubjectTerms Applied sciences
Clustering algorithms
Data security
Distributed computing
Electrical engineering. Electrical power engineering
Electrical power engineering
Exact sciences and technology
Power networks and lines
Power system analysis computing
Power system dynamics
Power system security
Power system stability
Power system transients
Stability analysis
Theory. Simulation
Transient analysis
Title A distributed computing approach for real-time transient stability analysis
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