Two-Stage Parallel Waveform Relaxation Method for Large-Scale Power System Transient Stability Simulation
Two-Stage Parallel Waveform Relaxation Method for Large-Scale Power System Transient Stability Simulation
复制标题
大规模电力系统暂态稳定仿真的两级并行波形弛豫方法
DOI：
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发表时间：
2016
影响因子：
6.6
通讯作者：
Q. Jiang
中科院分区：
文献类型：
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作者：
Yunfei Liu;Q. Jiang
这项工作提出了一种基于大规模电力系统波形松弛的并行暂态稳定性仿真。通过基于 epsilon 分解的划分算法，将大规模微分代数方程 (DAE) 描述的电力系统分解为多个子系统。该方法采用预处理和波形预测来加速系统的收敛。此外，基于OpenMP的两阶段并行策略进一步提高了并行效率。在通过隐式梯形规则对状态变量进行离散化后，所有子系统均采用非常不诚实的牛顿（VDHN）方法结合基于 Adomian 分解的迭代方法独立求解。最后，两个具有详细动态模型的大规模测试用例验证了所提出的算法。计算结果表明，所提出的波形松弛方法具有较高的并行效率。
This work presents a parallel transient stability simulation based on waveform relaxation for large-scale power systems. A power system described by large-scale differential-algebraic equations (DAE) is decomposed into several subsystems by a partitioning algorithm based on epsilon decomposition. The method adopts preconditioning and waveform prediction to accelerate convergence of the system. Moreover, a two-stage parallel strategy based on OpenMP further improves parallel efficiency. All subsystems are solved using a very dishonest Newton (VDHN) method combined with an iteration method based on Adomian decomposition independently after the state variables are discretized by implicit-trapezoidal rule. Finally, two large-scale test cases with detailed dynamic models verify the proposed algorithm. The computational results show that the proposed waveform relaxation method achieves high parallel efficiency.