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  • http://hdl.handle.net/10402/era.27826
  • Acceleration of Transient Stability Simulation for Large-Scale Power Systems on Parallel and Distributed Hardware
  • Jalili-Marandi, Vahid
  • English
  • Transient Stability Simulation
    Parallel Processing
    Instantaneous Relaxation
    Real-time Simulation
    Graphics Processing Units
  • Aug 12, 2010 8:56 PM
  • Thesis
  • English
  • Adobe PDF
  • 2549896 bytes
  • Transient stability analysis is necessary for the planning, operation, and control of power systems. However, its mathematical modeling and time-domain solution is computationally onerous and has attracted the attention of power systems experts and simulation specialists for decades. The ultimate promised goal has been always to perform this simulation as fast as real-time for realistic-sized systems. In this thesis, methods to speedup transient stability simulation for large-scale power systems are investigated. The research reported in this thesis can be divided into two parts. First, real-time simulation on a general-purpose simulator composed of CPU-based computational nodes is considered. A novel approach called Instantaneous Relaxation (IR) is proposed for the real-time transient stability simulation on such a simulator. The motivation of proposing this technique comes from the inherent parallelism that exists in the transient stability problem that allows to have a coarse grain decomposition of resulting system equations. Comparison of the real-time results with the off-line results shows both the accuracy and efficiency of the proposed method. In the second part of this thesis, Graphics Processing Units (GPUs) are used for the first time for the transient stability simulation of power systems. Data-parallel programming techniques are used on the single-instruction multiple-date (SIMD) architecture of the GPU to implement the transient stability simulations. Several test cases of varying sizes are used to investigate the GPU-based simulation. The simulation results reveal the obvious advantage of using GPUs instead of CPUs for large-scale problems. In the continuation of part two of this thesis the application of multiple GPUs running in parallel is investigated. Two different parallel processing based techniques are implemented: the IR method, and the incomplete LU factorization based approach. Practical information is provided on how to use multi-threaded programming to manage multiple GPUs running simultaneously for the implementation of the transient stability simulation. The implementation of the IR method on multiple GPUs is the intersection of data parallelism and program-level parallelism, which makes possible the simulation of very large-scale systems with 7020 buses and 1800 synchronous generators.
  • Doctoral
  • Doctor of Philosophy
  • Department of Electrical and Computer Engineering
  • Fall 2010
  • Dinavahi, Venkata (Electrical and Computer Engineering)
  • Salmon, John (Electrical and Computer Engineering)
    Nowrouzian, Behrouz (Electrical and Computer Engineering)
    Moussa, Walid (Mechanical Engineering)
    Rosehart, William (Electrical and Computer Engineering, University of Calgary)