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首页> 外文期刊>IEEE Transactions on Power Delivery >Two-Stage Improved Recursive Newton-Type Algorithm for Power-Quality Indices Estimation
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Two-Stage Improved Recursive Newton-Type Algorithm for Power-Quality Indices Estimation

机译:电能质量指标的两阶段改进递归牛顿型算法

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摘要

In the paper, a new improved recursive Newton-type algorithm (IRNTA) suitable for various measurement applications in the electric power systems is presented. Here, it is applied for power-quality (PQ) indices estimation according to the IEEE Standard 1459–2000. Basically, the algorithm is a recursive nonlinear estimator, improved with a strategy of sequentially tuning the forgetting factor. This approach generally improves the algorithm performance: immunity to random noise, accuracy, and the speed of convergence. The IRNTA considers the power frequency as an unknown model parameter and takes into account distortion of voltages and currents. Therefore, it is suitable for the real-time PQ monitoring. The algorithm has two stages. In the first stage, the input signal spectra and fundamental frequency are estimated, whereas in the second stage, the unknown PQ indices are calculated. To demonstrate the efficiency of the proposed algorithm, the results of computer simulations and laboratory testing are presented.
机译:在本文中,提出了一种新的改进的递归牛顿型算法(IRNTA),适用于电力系统中的各种测量应用。在这里,它根据IEEE标准1459-2000用于功率质量(PQ)指数估计。基本上,该算法是递归非线性估计器,通过顺序调整遗忘因子的策略进行了改进。这种方法通常可以提高算法性能:对随机噪声的免疫力,准确性和收敛速度。 IRNTA将电源频率视为未知的模型参数,并考虑了电压和电流的失真。因此,它适用于实时PQ监视。该算法分为两个阶段。在第一阶段,估计输入信号频谱和基频,而在第二阶段,计算未知的PQ指数。为了证明该算法的有效性,给出了计算机仿真和实验室测试的结果。

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