Detailed high-order models of the insulated-gate bipolar transistor (IGBT) and the diode are rarely included in power converters for large-scale system-level electromagnetic transient (EMT) simulation on the CPU, due to the nonlinear characteristics albeit they are more accurate. The massively parallel architecture of the graphics processing unit (GPU) enables a lower computational burden by avoiding the computation of complex devices repetitively in a sequential manner and thus is utilized in this paper to simulate the wind farm-integrated multiterminal dc (MTdc) grid based on the modular multilevel converter (MMC). Fine-grained circuit partitioning is proposed so that the nonlinear switching elements are physically separated with the smallest circuit unit. By implementing these subsystems with the same attributes as a GPU program and computing it in a massively parallel manner, it is demonstrated that the GPU is able to achieve a significant speedup over multicore CPUs and its computation time incremental is much smaller when the MMC level scales up. The improved insight and accuracy of the proposed modeling methodology and the designed GPU program are validated at the system- and device-level by off-line commercial simulation tools.

中文翻译：

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用于 MTDC 电网与风电场交互的细粒度并行 EMT 仿真的精确非线性微建模


由于非线性特性，绝缘栅双极晶体管 (IGBT) 和二极管的详细高阶模型很少包含在用于 CPU 上大规模系统级电磁瞬态 (EMT) 仿真的电源转换器中，尽管它们更具有非线性特性。准确的。图形处理单元（GPU）的大规模并行架构避免了复杂设备按顺序重复计算，从而降低了计算负担，因此本文利用该架构来模拟基于电网的风电场集成多端直流（MTdc）模块化多电平转换器（MMC）。提出了细粒度电路划分，使得非线性开关元件以最小的电路单元在物理上分离。通过实现与 GPU 程序具有相同属性的这些子系统并以大规模并行方式计算，结果表明 GPU 能够比多核 CPU 实现显着的加速，并且当 MMC 级别扩展时，其计算时间增量要小得多向上。所提出的建模方法和设计的 GPU 程序的洞察力和准确性得到了提高，并通过离线商业仿真工具在系统和设备级别进行了验证。