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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...
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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Adaptive Observer Based Fault Tolerant Control for Sensor and Actuator Faults in Wind Turbines.

Jing Teng1, Changling Li1, Yizhan Feng1

  • 1School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China.

Sensors (Basel, Switzerland)
|December 28, 2021
PubMed
Summary

This study introduces an adaptive observer-based fault tolerant control for wind turbines to handle sensor and actuator issues. The proposed method effectively stabilizes the system and compensates for faults, improving operational reliability in harsh environments.

Keywords:
adaptive observerfast adaptive fault estimation (FAFE) algorithmfault tolerant controlwind turbines

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Area of Science:

  • Engineering
  • Control Systems
  • Renewable Energy

Background:

  • Global wind energy capacity is rapidly expanding.
  • Wind turbines often operate in harsh environments, necessitating robust control.
  • Sensor and actuator faults are common in wind turbine subsystems.

Purpose of the Study:

  • To propose an adaptive observer-based fault tolerant control (FTC) scheme.
  • To address sensor and actuator faults in wind turbines.
  • To ensure reliable operation of wind turbines.

Main Methods:

  • Utilized adaptive observers with the fast adaptive fault estimation (FAFE) algorithm for fault detection.
  • Designed state feedback fault tolerant controllers.
  • Employed pole placement method for controller gain calculation.

Main Results:

  • The FAFE algorithm accurately and rapidly located faults.
  • The proposed FTC scheme effectively stabilized the wind turbine system under fault conditions.
  • Simulation results demonstrated superior performance compared to baseline methods.

Conclusions:

  • The adaptive observer-based FTC scheme with FAFE is effective for wind turbines.
  • This approach enhances system stability and fault compensation.
  • It offers improved reliability for wind energy generation.