Fuzzy-logic-controlled DVR for enhancing the fault resilience of wind energy conversion systems

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Authors: Ahmed Muthanna Nori, Ali Kadhim Abdulabbas, Hassan Zuhair Al Garni, Wulfran Fendzi Mbasso, Mohammed Alruwaili, Ali M. Elrashidi
Cited by: 1
References: 30

Abstract

As wind energy becomes more common in modern power networks, it is becoming more important to keep turbines running smoothly even when the grid is having major problems. This study examines the utilization of a Dynamic Voltage Restorer (DVR) within a Permanent Magnet Synchronous Generator (PMSG)-based grid-connected Wind Energy System (WES) to improve Low Voltage Ride-Through (LVRT) performance. The DVR reduces the consequences of grid faults by adding the right series compensation voltage, which brings the Point of Common Coupling (PCC) voltage back to its rated value. A significant contribution to this study is the creation of a cost-effective DVR configuration powered by the existing DC-link of the back-to-back converter (BTBC). This allows the DVR to draw the necessary active power during disturbances without needing an external Battery Energy Storage System (BESS). To improve dynamic responsiveness, a fuzzy logic controller is employed with the DVR feedforward control approach. This makes it better at rejecting disturbances. To keep the DC-link voltage stable during fault events, a brake chopper (BC) is also added. We use comprehensive simulations in MATLAB/Simulink R2024a to test the proposed system. The results show that the fuzzy-controlled DVR can quickly, smoothly, and reliably restore voltage in a variety of faulty conditions. This greatly improves the LVRT performance of PMSG-based WES. A comparative examination shows that the fuzzy-controlled DVR is better than the standard PI-based DVR when it comes to transient behavior, voltage regulation accuracy, and post-fault recovery. This makes the grid code more compliant, and the overall reliability of the system improved.

Fields of Study & Subjects

Wind Turbine Control Systems Power Systems Fault Detection Islanding Detection in Power Systems

Publication details

Journal / source
Scientific Reports
Publisher
Springer Science and Business Media LLC
Volume
16
Issue
1
Publication date
3 March 2026
Language
EN