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Related Concept Videos

Wind Turbine Machine Models01:24

Wind Turbine Machine Models

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In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
545
Generator Voltage Control01:21

Generator Voltage Control

601
Generator voltage control is crucial for maintaining the stable operation of synchronous generators and wind turbines. In older models, a DC generator driven by the rotor delivers DC power to the rotor's field winding, and the power is transferred through slip rings and brushes. In the latest models, static or brushless exciters are used. Static exciters rectify AC power from the generator terminals and then transfer the DC power directly to the rotor. Brushless exciters, on the other hand, use...
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Turbine-Governor Control01:17

Turbine-Governor Control

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Turbine-governor control is crucial for maintaining power system stability by balancing turbine mechanical power output with electrical load demand. This mechanism ensures that generator frequency and rotor speed are within acceptable limits during load variations. Turbine-generator units store kinetic energy due to their rotating masses; this energy is released to meet the load requirement when the load increases. The electrical torque of turbines rises to meet the demand, whereas the...
897
Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

719
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
719
Control of Power Flow01:30

Control of Power Flow

650
There are several methods to control power flow in power systems:
650
Load-frequency control01:28

Load-frequency control

584
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
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Adaptive vector oriented control of doubly fed induction generator wind turbines using M5P model tree for robust

Koudri Benyoucef1, Moualidia Abdelhafidh1, Boudana Djamel2

  • 1Department of Electrical Engineering, Laboratory of Research in Electrical and Automatic (LREA), University of Medea, Medea, Algeria.

Scientific Reports
|December 22, 2025
PubMed
Summary

This study introduces an M5-Pruned model tree (M5P) controller for wind energy systems, improving dynamic performance and power quality. The M5P approach offers enhanced accuracy and robustness over traditional methods for doubly fed induction generators.

Keywords:
Doubly fed induction generator (DFIG)Fuzzy logic controller (FLC)M5P algorithmVector oriented control (VOC)Wind energy conversion system (WECS)

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Area of Science:

  • Electrical Engineering
  • Renewable Energy Systems
  • Control Theory

Background:

  • Doubly fed induction generators (DFIGs) are crucial for wind energy conversion.
  • Conventional vector-oriented control (VOC) using PI controllers faces challenges with nonlinearities and wind fluctuations.
  • Degraded dynamic performance and power quality are common issues in existing systems.

Purpose of the Study:

  • To propose an intelligent VOC strategy for DFIG-based wind turbines.
  • To enhance the dynamic performance and power quality of wind energy systems.
  • To compare the proposed M5P controller with fuzzy logic controllers (FLC) and traditional PI controllers.

Main Methods:

  • Development of an M5-Pruned model tree (M5P) based intelligent VOC controller.
  • Comparative analysis with fuzzy logic controllers (FLC).
  • Simulation using MATLAB/Simulink for a grid-connected DFIG wind turbine under varying wind profiles.

Main Results:

  • The M5P strategy significantly reduces overshoot and settling time.
  • Improved active and reactive power regulation is achieved.
  • Enhanced overall system stability and robustness under variable wind conditions.

Conclusions:

  • Machine learning-based control, specifically the M5P algorithm, offers a superior alternative to conventional VOC techniques.
  • The M5P controller demonstrates significant advantages in accuracy, robustness, and dynamic performance for DFIG wind energy systems.
  • This approach addresses limitations of traditional PI and FLC methods, paving the way for more reliable renewable energy integration.