This paper presents a single-instruction-multiple-data (SIMD) based implementation of the transient stability simulation on the Graphics Processing Unit (GPU). Two programming models to implement the standard method of the transient stability simulation are proposed and implemented on a single GPU. In the first model the CPU is responsible for part of the simulation, while the onerous computations were offloaded to the GPU, creating a hybrid GPU-CPU simulator. In the second model, the GPU performs all the computations, while the CPU simply monitors the flow of the simulation. The accuracy of the proposed methods are validated using the PSS/E software for several large test systems. A substantial increase in speed was observed for the GPU-based simulations.
This paper proposes large-scale transient stability simulation based on the massively parallel architecture of multiple graphics processing units (GPUs). A robust and efficient instantaneous relaxation based parallel processing technique which features implicit integration, full Newton iteration, and sparse LU based linear solver is used to run the multiple GPUs simultaneously. This implementation highlights the combination of coarse-grained algorithm-level parallelism with fine-grained data-parallelism of the GPUs to accelerate large-scale transient stability simulation. Multi-threaded parallel programming makes the entire implementation highly transparent, scalable and efficient. Several large test systems are used for the simulation with a maximum size of 9984 buses and 2560 synchronous generators all modeled in detail resulting in matrices that are larger than 20000×20000.Index Terms-Graphics processors, instantaneous relaxation, large-scale systems, multiple GPUs, newton-raphson method, parallel multi-threaded programming, power system simulation, power system transient stability, sparse direct solvers.
Real-time transient stability simulation is of paramount importance for system security assessment and to initiate preventive control actions before catastrophic events such as blackouts happen. Transient stability simulation of realistic power systems involves the solution of a large set of nonlinear differential-algebraic equations in the time-domain which requires significant computational resources. Exploitation of parallel processing techniques can provide an efficient and cost-effective solution to this problem. This paper proposes a fully parallel method known as instantaneous relaxation (IR) for real-time transient stability simulation. To validate the proposed method, two test systems have been implemented on an advanced PC-cluster-based real-time simulator. A comparison of the captured real-time results with those from the PSS/E software shows high accuracy.
This paper proposes large-scale transient stability simulation based on the massively parallel architecture of multiple graphics processing units (GPUs). A robust and efficient instantaneous relaxation (IR)-based parallel processing technique which features implicit integration, full Newton iteration, and sparse LU-based linear solver is used to run the multiple GPUs simultaneously. This implementation highlights the combination of coarse-grained algorithm-level parallelism with fine-grained data-parallelism of the GPUs to accelerate large-scale transient stability simulation. Multithreaded parallel programming makes the entire implementation highly transparent, scalable, and efficient. Several large test systems are used for the simulation with a maximum size of 9,984 buses and 2,560 synchronous generators all modeled in detail resulting in matrices that are larger than 20,000 Â 20,000.
The electromagnetic transient (EMT) simulation of a power system interconnected with wind farms involves such intensive computations that fully digital real-time simulators are among the effective tools for performing such simulations. To practically exploit real-time simulators for the simulation of wind farms with numerous wind turbines, the application of aggregation techniques is inevitable. In this paper, a detailed EMT model of a grid-connected wind farm with ten doubly-fed-inductiongenerator-based General Electric 1.5-MW wind turbines has been implemented on an advanced PC-Cluster-based real-time simulator. Three levels of physical aggregation methods are presented to reduce the computational efforts of the real-time simulation while maintaining adequate accuracy. A combination of these aggregation methods with parallel processing allowed the real-time simulation to be carried out with a fixed time step of 50 μs and high accuracy. Various fault transient results are provided for all the aggregation levels and compared against results from the detailed wind farm model. The validity of the proposed methods and real-time simulation results has also been confirmed by comparing with offline simulation results in MATLAB/SIMULINK.
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