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首页> 外文期刊>International Journal of Electrical Power & Energy Systems >Accurate tracking of harmonic signals in VSC-HVDC systems using PSO based unscented transformation
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Accurate tracking of harmonic signals in VSC-HVDC systems using PSO based unscented transformation

机译：使用基于PSO的无味变换来准确跟踪VSC-HVDC系统中的谐波信号

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摘要

This paper presents the estimation of harmonics in a voltage source converter based HVDC (VSC-HVDC) system for designing AC side filters. The extended Kalman filter (EKF) is well known for estimating amplitude, phase, frequency, and harmonic content of a signal corrupted with noise. However, the EKF algorithm suffers from instability due to linearization and costly calculation of jacobian matrices, and its performance deteriorates when the signal model is highly nonlinear. This paper, therefore, proposes an unscented Kalman filter (UKF) to overcome these difficulties of linearization and derivative calculations for robust tracking of harmonics in VSC-HVDC system. The model and measurement error covariance matrices Qand R along with the UKF parameters are selected using a modified particle swarm optimization (PSO) algorithm. To circumvent the problem of premature convergence and local minima, a dynamically varying inertia weight based on the variance of the population fitness is used. This results in a better local and global searching ability of the particles, which improves the convergence of the velocity and better accuracy of the UKF parameters. Various simulation results for harmonic signals corrupted with noise obtained from VSC-HVDC system reveal significant improvement in noise rejection and speed of convergence and accuracy.
机译：本文介绍了在基于电压源转换器的HVDC（VSC-HVDC）系统中用于设计交流侧滤波器的谐波估计。扩展卡尔曼滤波器（EKF）众所周知，它可以估算出被噪声破坏的信号的幅度，相位，频率和谐波含量。但是，EKF算法由于线性化和雅各比矩阵的计算成本高而遭受不稳定，当信号模型为高度非线性时，其性能会下降。因此，本文提出了一种无味卡尔曼滤波器（UKF），以克服线性化和VSC-HVDC系统中谐波稳健跟踪的导数计算难题。使用改进的粒子群优化（PSO）算法选择模型和测量误差协方差矩阵Q和R以及UKF参数。为了避免过早收敛和局部极小值的问题，使用了基于总体适应度方差的动态变化的惯性权重。这导致更好的局部和全局粒子搜索能力，从而提高了速度的收敛性和UKF参数的准确性。对从VSC-HVDC系统获得的被噪声破坏的谐波信号进行的各种仿真结果表明，噪声抑制以及收敛速度和精度均得到了显着改善。

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