Detection of Nonlinear Behavior in Voltage Source Converter Control in Wind Farms Based on Higher-Order Spectral Analysis
Zetian Zheng, Chen Shen

TL;DR
This paper presents a higher-order spectral analysis method to detect nonlinear behavior in voltage source converter control systems in wind farms, aiding in understanding and diagnosing sub-synchronous oscillation issues.
Contribution
It extends traditional describing functions and applies bispectrum and trispectrum analysis to identify nonlinear saturation effects in VSC control systems.
Findings
HOS effectively detects nonlinear saturation in VSC controls
Bispectrum and trispectrum distinguish bilateral and unilateral saturation effects
Simulation confirms the method's accuracy and robustness
Abstract
In recent years, the sub-synchronous oscillation (SSO) accidents caused by wind power have received extensive attention. A method is needed to distinguish if nonlinear behavior exists in the recorded equal-amplitude accident waveforms, so that different methods can be adopted to analyze the mechanism of the oscillation. The theory of higher-order statistics (HOS) has become a powerful tool for detection of nonlinear behavior (DNB) in production quality control since 1960s. However, HOS analysis has been applied in mechanical condition monitoring and fault diagnosis, even after being introduced into the power system and wind farms. This paper focuses on the voltage source converter (VSC) control systems in wind farms and tries to detect the nonlinear behavior caused by the bilateral or unilateral saturation hard limits based on HOS analysis. First, the traditional describing function is…
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Taxonomy
TopicsMachine Fault Diagnosis Techniques · Fault Detection and Control Systems · Advanced Algorithms and Applications
