Abstract

In a microgrid, the distributed generators (DG) can power the user loads directly. As a result, power quality (PQ) events are more likely to affect the users. This paper proposes a Multiresolution Generalized S-transform (MGST) approach to improve the ability of analyzing and monitoring the power quality in a microgrid. Firstly, the time-frequency distribution characteristics of different types of disturbances are analyzed. Based on the characteristics, the frequency domain is segmented into three frequency areas. After that, the width factor of the window function in the S-transform is set in different frequency areas. MGST has different time-frequency resolution in each frequency area to satisfy the recognition requirements of different disturbances in each frequency area. Then, a rule-based decision tree classifier is designed. In addition, particle swarm optimization (PSO) is applied to extract the applicable features. Finally, the proposed method is compared with some others. The simulation experiments show that the new approach has better accuracy and noise immunity.

Highlights

  • The fast growing microgrid technology provides a good solution to solve the problem of large scale distributed generator coupling

  • Power quality disturbance classification is a basis of analysis and control of power quality, which plays an important role in transient analysis and monitoring of power electronic devices

  • There exist many problems to solve in Hilbert-Huang Transform (HHT), some progresses have been reached in power quality disturbance classification

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Summary

Introduction

The fast growing microgrid technology provides a good solution to solve the problem of large scale distributed generator coupling. The capability of microgrids is relatively small and there exist high proportions of nonlinear and unbalanced loads, so microgrids are more likely to be troubled by PQ (power quality) events, such as harmonics, transient disturbances and so on [2]. That is what we call a complex disturbance This results in a higher need for signal processing. There exist many problems to solve in HHT, some progresses have been reached in power quality disturbance classification. Analysis methods and methods of exhaustion are not suitable here because the calculation process is complicated, PSO can effectively decrease the computation time, and achieve a solution with a high fitness value

Generalized S-Transform
Multiresolution Generalized S-Transform
The Setting of the Width Factor in the High Frequency Area
PQ Disturbance Classifier Based on Decision Tree
The Analysis of Disturbance Signal via MGST
The Structure of DT
Background
The Search of Optimized Threshold via Modified PSO
Basic Fundamentals of PSO
The Improvement of PSO
Simulation and Experiment
Conclusions
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