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GPU-based power converter transient simulation with matrix exponential integration and memory management

机译:基于GPU的功率转换器瞬态模拟矩阵指数集成和内存管理

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摘要

With the extensive application of power electronic equipment in power systems, electromagnetic transient (EMT) simulation involving power converters becomes more challenging. Due to its multithreads and high throughput architecture, the graphics processing unit (GPU) can be used to accelerate those EMT simulations. A GPU-based matrix exponential method and its memory management for power converter transient simulation are proposed in this paper. A parallel exponential integration algorithm is established from two aspects to fully utilize the GPU multithreads capability. The matrix exponentials which are recomputed with the on/off state changes of power electronic switches are cached in GPU memory. The simulation efficiency is improved by reusing the cached data and reducing heterogeneous data transmission between CPU and GPU. Several strategies are experimented to manage the cache memory considering the EMT simulation workflow. The proposed memory management expands the simulation capability by substantially reducing the memory requirement and maintains the speed advantage of the GPU-based simulator. The proposed method is tested on wind power plants of different scales with power electronic interfaced wind generators. Simulation results indicate that the proposed method and its memory management expand the simulation capability and achieve speedups.
机译:随着电力电子设备的广泛应用,电磁瞬态(EMT)仿真涉及电源转换器变得更具挑战性。由于其多线程和高吞吐量架构,图形处理单元(GPU)可用于加速这些EMT模拟。本文提出了一种基于GPU的矩阵指数方法及电力转换器瞬态仿真的存储器管理。从两个方面建立并行指数集成算法以充分利用GPU多线程能力。用电力电子开关的ON / OFF状态变化重新计算的矩阵指数在GPU存储器中缓存。通过重用缓存的数据并减少CPU和GPU之间的异构数据传输来提高模拟效率。考虑EMT模拟工作流程,实验了几种策略来管理高速缓冲存储器。所提出的存储器管理通过大大降低内存要求并维持基于GPU的模拟器的速度优势来扩展模拟能力。该方法在具有电力电子接口风力发电机的不同尺度的风电厂测试。仿真结果表明,所提出的方法及其内存管理扩展了模拟能力并实现了加速度。

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