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首页> 外文期刊>Electric power systems research >Harmonic Estimation In A Power System Using A Novel Hybrid Least Squares-adaline Algorithm
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Harmonic Estimation In A Power System Using A Novel Hybrid Least Squares-adaline Algorithm

机译：新型混合最小二乘-ADALINE算法的电力系统谐波估计

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摘要

Nowadays many algorithms have been proposed for harmonic estimation in a power system. Most of them deal with this estimation as a totally nonlinear problem. Consequently, these methods either converge slowly, like GA algorithm [U. Qidwai, M. Bettayeb, GA based nonlinear harmonic estimation, IEEE Trans. Power Delivery (December) 1998], or need accurate parameter adjustment to track dynamic and abrupt changes of harmonics amplitudes, like adaptive Kalman filter (KF) [Steven Liu, An adaptive Kalman filter for dynamic estimation of harmonic signals, in: 8th International Conference On Harmonics and Quality of Power, ICHQP'98, Athens, Greece, October 14-16,1998]. In this paper a novel hybrid approach, based on the decomposition of the problem into a linear and a nonlinear problem, is proposed. A linear estimator, i.e., Least Squares (LS), which is simple, fast and does not need any parameter tuning to follow harmonics amplitude changes, is used for amplitude estimation and an adaptive linear combiner called 'Adaline'. which is very fast and very simple is used to estimate phases of harmonics. An improvement in convergence and processing time is achieved using this algorithm. Moreover, better performance in online tracking of dynamic and abrupt changes of signals is the result of applying this method.
机译：如今，已经提出了许多用于电力系统谐波估计的算法。他们中的大多数人将此估计视为完全非线性的问题。因此，这些方法要么收敛缓慢，要么像GA算法[U. Qidwai，M。Bettayeb，基于GA的非线性谐波估计，IEEE Trans。 Power Delivery（1998年12月），或需要精确的参数调整以跟踪谐波幅度的动态和突变，例如自适应Kalman滤波器（KF）[Steven Liu，用于动态估算谐波信号的自适应Kalman滤波器，在：第八届国际会议上关于谐波和功率质量，ICHQP'98，希腊雅典，1998年10月14日至16日]。本文提出了一种基于问题分解为线性和非线性问题的新型混合方法。线性估计器，即最小二乘（LS），它简单，快速并且不需要任何参数调整即可跟随谐波幅度变化，用于幅度估计，并使用自适应线性组合器“ Adaline”。它非常快速，非常简单，用于估计谐波相位。使用该算法可以提高收敛性和处理时间。此外，应用此方法的结果是在线动态跟踪信号的突然变化时具有更好的性能。

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