A novel flicker detection method for vertical axis wind turbine using two‐dimensional discrete wavelet transform

Abstract

Background Pattern recognition applications have increased dramatically over the past four decades. In power system, pattern recognition can be used in fields such as power quality. One of the important power quality aspects is flicker, which is caused by torque fluctuations in wind turbines. Aims In this paper, the various mechanical faults including single and double faults that cause flicker in vertical axis wind turbines (VAWTs) are modeled; then flicker caused by single and double faults are analyzed. Then, a novel method for pattern recognition is presented which results in more accuracy in flicker detection. Materials and Methods In this paper, features of voltage and current signals are extracted by the 2D‐DWT. The 2D‐DWT is capable of producing valuable features than the discrete wavelet transform (DWT) at a lower level of decomposition. The 2D‐DWT is even capable of compressing data that can be suitable for smart grids, which high volume data is one of their problems. In order to reduce the redundant data, dimension of features vector, and computational burden, a new method is presented for feature selection. The backbone of the presented feature selector is the used classifier in the corresponding pattern system; so it is compatible with the classifier. Results Results show the high accuracy of the proposed method in identifying the factors that cause flicker in VAWTs. Conclusion In this paper, it was shown that the features extracted from the current and voltage signal by the 2D‐DWT were superior to the features extracted from the only voltage signal by the DWT. Also, the advantage of the proposed feature selection over the Relieff method was shown.

Identification of Combined Power Quality Disturbances in the Presence of Distributed Generations using Variational Mode Decomposition and K-nearest Neighbors Classifier

“…Other scenarios such as LLG fault and switching a large capacitor are added to the mentioned harmonic sources. It is notable that wind turbines alone can be the cause of generating flicker and harmonic [34,40]. Combined PQDs were introduced in classes 11 to 15.…”

“…In the modern power systems, some events in diesel-engine driven generators such as misfiring in cylinders, and gearbox tooth crashing lead to generate flicker [33]. Also, some events in wind turbines such as tower shadow, wind shear, turbine blade break down, and blade pitching errors lead to generate flicker in the modern power systems [34]. To identify different combined PQDs in the modern power systems, a new method is presented in this paper.…”

A new approach for the simultaneous identification of the location and individual contribution of multiple flicker sources using the least number of monitoring points

“…There have been several studies on flicker source tracing, but they are not based on IEC 61000‐4‐15 23‐28 . Axelberg et al 29,30 proposed an analytical theory to detect the direction of the flicker source (FS) with respect to the monitoring points based on IEC 61000‐4‐15.…”