Integrated optimal active and reactive power control scheme for grid connected permanent magnet synchronous generator wind turbines

Integrated optimal active and reactive power control scheme for grid connected permanent magnet synchronous generator wind turbines

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This research presents a novel approach for optimal active and reactive power control using permanent magnet synchronous generator with fully rated converter (PMSG-FRC). The power output variations and wind energy intermittent performance create significant challenges for power system integration, operation, and control. A fast and reliable sensorless optimal wind speed (WS) control system-based extreme learning machines and complete ensemble empirical mode decomposition with adaptive noise is developed. Also, an approximate entropy-based complexity measure is used for online WS estimation. The fuzzy controller system is used for calculating the optimal wind turbine (WT) speed, power, and torque, and then adjusts WT by the optimal speed value. Moreover, the wind farm (WF) active and reactive power controller is utilised for obtaining the active and reactive power reference values for every region/feeder. The system is applied and integrated to power system grid by using IEEE standard models, and the speed of WT is adjusted by the required active power level and the estimated WS value to increase the maximum power capture from WF. The simulations results using different cases studies and power system voltage levels have confirmed the validity and accuracy of the proposed control algorithms for practical applications and demonstrated excellent performance for power system integration.

Inspec keywords: synchronous generators; wind power plants; entropy; IEEE standards; reactive power control; permanent magnet generators; learning (artificial intelligence); Hilbert transforms; angular velocity control; power generation control; maximum power point trackers; fuzzy control; approximation theory; control engineering computing; sensorless machine control; power grids; optimal control; wind turbines

Other keywords: WS control system-based extreme learning machines; entropy-based complexity measure approximation; power system integration; fuzzy controller system; wind farm reactive power control scheme; MATLAB platforms; grid connected permanent magnet synchronous generator wind turbine; power system control; IEEE standard models; optimal WT power calculation; wind farm active power control scheme; FRC; wind energy intermittent performance; power system voltage levels; sensorless optimal wind speed control system-based extreme learning machines; power system operation; adaptive noise; integrated optimal active and reactive power control scheme; real WS data; Australia; hybrid maximum power tracking system; power system grid; optimal WT torque calculation; optimal wind turbine speed calculation; WF; intelligent DIgSILENT platforms; fully rated converter; complete ensemble empirical mode decomposition; online WS estimation

Subjects: Velocity, acceleration and rotation control; Wind power plants; Interpolation and function approximation (numerical analysis); Synchronous machines; Power and energy control; Knowledge engineering techniques; Fuzzy control; Integral transforms in numerical analysis; Interpolation and function approximation (numerical analysis); Integral transforms in numerical analysis; Optimal control; Control of electric power systems; Control engineering computing


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