Recognising nonlinear interactions in power systems

S. Chakravarthy
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引用次数: 0

Abstract

The availability of high speed data acquisition systems (DAS) allows voltage and current waveforms to be captured on-line as a time series. The voltage and current oscillations, of varying periodicity, arise out of nonlinear interactions in power systems. Conventional spectral analysis is based on the assumption that the time-series data is Gaussian. This assumption, as will be shown, cannot be universally applied. Higher-order spectral (HOS) analysis, on the other hand, offers a method to recognise these interactions in a power system when the waveforms are non-Gaussian. The time series data, to be analysed in this paper, in particular, is taken from a system of well known dynamical equations in the power system. We demonstrate, by using HOS, the extent of joint dependence of the spectral components.
识别电力系统中的非线性相互作用
高速数据采集系统(DAS)的可用性允许电压和电流波形作为时间序列在线捕获。电力系统中的非线性相互作用产生了不同周期的电压和电流振荡。传统的谱分析是基于时间序列数据是高斯分布的假设。下面将说明,这种假设不能普遍适用。另一方面,高阶频谱(HOS)分析提供了一种方法来识别非高斯波形时电力系统中的这些相互作用。本文特别要分析的时间序列数据取自电力系统中一个众所周知的动力学方程系统。我们用HOS证明了谱分量的联合依赖程度。
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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