大型多端直流电网并行高保真电磁瞬变仿真

Ning Lin, V. Dinavahi
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引用次数: 4

摘要

在CPU上进行的电力电子电磁瞬变(EMT)仿真随着系统规模的扩大而减慢。因此,利用图形处理单元(GPU)的大规模并行性来加速多终端直流(MTDC)网格的仿真,其中采用半导体开关的详细模型来提供全面的设备级信息。由于节点多导致直流电网求解效率低,因此采用了三种层次的电路划分,即基于传输线的换流站自然分离、站内设备的分割和电压电流耦合源的细粒度划分。相似属性的组件被编写成一个CUDA C函数,并通过单指令多线程进行大规模并行计算。GPU作为大型MTDC网格分析的新型EMT仿真平台的潜力得到了证明,对于更大的CIGRÉ直流网格,时间步长为50 ns和$1~\mu \text{s}$进行设备级和系统级仿真,CPU实现的加速高达270倍。最后,通过商用工具SaberRD和PSCAD/EMTDC验证了GPU仿真的准确性。
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Parallel High-Fidelity Electromagnetic Transient Simulation of Large-Scale Multi-Terminal DC Grids
Electromagnetic transient (EMT) simulation of power electronics conducted on the CPU slows down as the system scales up. Thus, the massively parallelism of the graphics processing unit (GPU) is utilized to expedite the simulation of the multi-terminal DC (MTDC) grid, where detailed models of the semiconductor switches are adopted to provide comprehensive device-level information. As the large number of nodes leads to an inefficient solution of the DC grid, three levels of circuit partitioning are applied, i.e., the transmission line-based natural separation of converter stations, splitting of the apparatus inside the station, and the coupled voltage-current sources for fine-grained partitioning. Components of similar attributes are written as one CUDA C function and computed in massive parallelism by means of single-instruction multi-threading. The GPU’s potential as a new EMT simulation platform for the analysis of large-scale MTDC grids is demonstrated by a remarkable speedup of up to 270 times for the Greater CIGRÉ DC grid with time-steps of 50 ns and $1~\mu \text{s}$ for device-level and system-level simulation over the CPU implementation. Finally, the accuracy of GPU simulation is validated by the commercial tools SaberRD and PSCAD/EMTDC.
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