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Parallel Simulation of Power Systems Transient Stability Based on Implicit Runge-Kutta Methods and W-transformation

机译:基于隐式Runge-Kutta方法和W变换的电力系统暂态稳定并行仿真

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摘要

This paper presents a novel parallel algorithm for power systems transient stability simulation based on fully implicit Runge-Kutta (IRK) method. The s-stage IRK method is used to convert the differential-algebraic system simultaneously at s different time points into a set of non-linear algebraic equations, and the algebraic system is then solved by Newton's method. By the use of the matrix factorization technique, the solution of the linear equations involved in Newton's process is divided into two parts: the first part is decoupled at s different time points, thus it is fully parallelizable in time, and the second part is solved by preconditioned generalized minimal residual method (GMRES) method, while a new preconditioning method has been proposed by using the W-transformation and double-parameters method. For test, the proposed algorithm is implemented on multiple-graphics processing units (GPUs) computing platform. The results show that the proposed algorithm is accurate and has good convergence. Moreover, the parallel algorithm implemented on multiple-GPUs computing platform achieves high parallel efficiency.
机译:本文提出了一种基于完全隐式Runge-Kutta(IRK)方法的电力系统暂态稳定仿真并行算法。 s-stage IRK方法用于将微分代数系统同时在s个不同的时间点转换为一组非线性代数方程,然后通过牛顿法求解代数系统。通过矩阵分解技术,将牛顿过程中涉及的线性方程组的解分为两部分:第一部分在不同的时间点解耦,因此可以在时间上完全并行化,第二部分得到解决通过预处理的广义最小残差法(GMRES)进行处理,而使用W变换和双参数方法提出了一种新的预处理方法。为了进行测试,该算法在多图形处理单元(GPU)计算平台上实现。结果表明,该算法准确,收敛性好。此外,在多GPU计算平台上实现的并行算法实现了很高的并行效率。

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