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

Power system dynamic simulations are crucial for the operation of electric power systems as they provide important information on the dynamic evolution of the system after an occurring disturbance. This paper proposes a robust, accurate and efficient parallel algorithm based on the Schur complement...

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Vydáno v:	IEEE transactions on parallel and distributed systems Ročník 25; číslo 10; s. 2561 - 2570
Hlavní autoři:	Aristidou, Petros, Fabozzi, Davide, Van Cutsem, Thierry
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.10.2014 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers
Témata:	Acceleration Algorithms Complement Computational modeling Computer simulation Domain decomposition methods Dynamical systems Dynamics Electric power generation Electrical & electronics engineering Engineering, computing & technology Equations Heuristic algorithms Ingénierie électrique & électronique Ingénierie, informatique & technologie Mathematical model Mathematical models OpenMP ower system dynamic simulation Parallel algorithms power system dynamic simulation Power system dynamics Schur complement shared-memory
ISSN:	1045-9219, 1558-2183, 1558-2183
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Abstract	Power system dynamic simulations are crucial for the operation of electric power systems as they provide important information on the dynamic evolution of the system after an occurring disturbance. This paper proposes a robust, accurate and efficient parallel algorithm based on the Schur complement domain decomposition method. The algorithm provides numerical and computational acceleration of the procedure. Based on the shared-memory parallel programming model, a parallel implementation of the proposed algorithm is presented. The implementation is general, portable and scalable on inexpensive, shared-memory, multi-core machines. Two realistic test systems, a medium-scale and a large-scale, are used for performance evaluation of the proposed method.
AbstractList	Power system dynamic simulations are crucial for the operation of electric power systems as they provide important information on the dynamic evolution of the system after an occurring disturbance. This paper proposes a robust, accurate and efficient parallel algorithm based on the Schur complement domain decomposition method. The algorithm provides numerical and computational acceleration of the procedure. Based on the shared-memory parallel programming model, a parallel implementation of the proposed algorithm is presented. The implementation is general, portable and scalable on inexpensive, shared-memory, multi-core machines. Two realistic test systems, a medium-scale and a large-scale, are used for performance evaluation of the proposed method.
Author	Van Cutsem, Thierry Aristidou, Petros Fabozzi, Davide
Author_xml	– sequence: 1 givenname: Petros surname: Aristidou fullname: Aristidou, Petros email: p.aristidou@ieee.org organization: Dept. of Electr. Eng. & Comput. Sci., Univ. of Liege, Liege, Belgium – sequence: 2 givenname: Davide surname: Fabozzi fullname: Fabozzi, Davide organization: Dept. of Electr. Eng. & Comput. Sci., Univ. of Liege, Liege, Belgium – sequence: 3 givenname: Thierry surname: Van Cutsem fullname: Van Cutsem, Thierry email: t.vancutsem@ulg.ac.be organization: Dept. of Electr. Eng. & Comput. Sci., Univ. of Liege, Liege, Belgium
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SubjectTerms	Acceleration Algorithms Complement Computational modeling Computer simulation Domain decomposition methods Dynamical systems Dynamics Electric power generation Electrical & electronics engineering Engineering, computing & technology Equations Heuristic algorithms Ingénierie électrique & électronique Ingénierie, informatique & technologie Mathematical model Mathematical models OpenMP ower system dynamic simulation Parallel algorithms power system dynamic simulation Power system dynamics Schur complement shared-memory
Title	Dynamic Simulation of Large-Scale Power Systems Using a Parallel Schur-Complement-Based Decomposition Method
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