Wind turbine power conversion topology with machine side fault detection and classification method

Unal Yilmaz

Energy, 2025, vol. 335, issue C

Abstract: In grid-tied wind turbine power conversion systems, accurate detection and classification of inter-phase and ground faults on the generator side enable proactive mitigation of adverse effects such as DC-link voltage instability, increased electrical stress on power electronic components, and the injection of high-order harmonic currents into the utility grid, thereby enhancing overall system reliability and power quality. In this study, a power system structure that includes permanent magnet synchronous generator (PMSG) and LCL filter connection for single phase grid-tied wind turbine and also enables injecting current to grid with low harmonic distortion and high power factor with synchronous performance of phase locked loop (PLL) and proportional resonance (PR) controllers is proposed. In addition, fault detection and classification processes are provided by Gaussian Process (GPR) and Support Vector Machine (SVM), respectively.The study was tested on a prototype with a nominal power of 3 kW under 8 different conditions, including fault-free and 7 different faults. Additionally, to verify the reliability of the system, even at suddenly changing wind speeds (12 m/s to 16 m/s) under fault-free condition, grid-side power factor was >0.98 and grid current THD was <5 %. Also, in case of fault, detection and classification were realized with >99 % accuracy.

Keywords: Wind turbine; Power conversion; Fault detection; Classification (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544225035455
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:335:y:2025:i:c:s0360544225035455

DOI: 10.1016/j.energy.2025.137903

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().