Spectral analysis techniques with Kalman filtering for estimating power quality indices

R. Zolfaghari, Y. Shrivastava, V. Agelidis, G. M. Chu
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引用次数: 3

Abstract

This paper presents the theory, design and implementation of two real time virtual instruments to measure the power quality indices such as current harmonic distortion, voltage harmonic distortion and power factor as given by the IEEE standard. Different windowing techniques are explored in the estimation of the spectra. Cross spectral analysis is used for the measurement of phase angles in voltage and current signal. The virtual instrument integrates digital signal processing (DSP) methods such as windowing techniques and Cross-spectral density estimation with Welch spectral estimation to calculate voltage and current phasors. Moreover a tunable Kalman filter with a forgetting factor is applied to further enhance the results due to noise in the measurement. Simulations followed by a real time experiment using a rectified AC waveform applied across an RL circuit is followed to support the theoretical claims and further to show the robustness of the virtual instruments. Finally the two instruments are compared with each other in terms of performance and speed.
用卡尔曼滤波估计电能质量指标的频谱分析技术
本文介绍了两种实时虚拟仪器的原理、设计和实现,用于测量IEEE标准中规定的电流谐波失真、电压谐波失真和功率因数等电能质量指标。在光谱估计中探讨了不同的加窗技术。交叉谱分析用于测量电压和电流信号中的相角。该虚拟仪器集成了数字信号处理(DSP)方法,如加窗技术、交叉谱密度估计和韦尔奇谱估计来计算电压和电流相量。此外,还采用了带遗忘因子的可调谐卡尔曼滤波器,进一步增强了测量噪声对测量结果的影响。仿真之后,通过RL电路应用整流交流波形进行实时实验,以支持理论主张,并进一步显示虚拟仪器的鲁棒性。最后对两种仪器的性能和速度进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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