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Wind energy conversion system using perturb & observe-based maximum power point approach interfaced with T-type three-level inverter connected to grid

S Pranupa, A. T. Sriram, S. Nagaraja Rao

2022Clean Energy23 citationsDOIOpen Access PDF

Abstract

Abstract In this paper, the performance of a permanent magnet synchronous generator (PMSG)-based wind energy conversion system (WECS) supplied to an uncontrolled rectifier-fed boost converter (BC) interfaced with a three-phase T-type three-level inverter (TLI) has been analysed. The proposed WECS involves three converters, namely an uncontrolled rectifier that is used for conversion from AC to DC; a BC supplied by a PMSG-fed rectifier used to enhance the voltage gain; and a grid-connected three-phase T-type TLI is proposed to eliminate power-quality issues with synchronization of grid voltage and current. The main goal of this research is to model and control the grid-connected T-type TLI using a d–q synchronous frame for wind energy for regulating the DC-link voltage and transferring the generated wind power from the BC to the grid. Furthermore, the perturb & observe (P&O)-based maximum power point (MPP) approach is recommended to keep track of the MPP for a BC that is supplied from a PMSG-based WECS under constant and variable wind speeds. The proposed PMSG-based WECS interfaced with grid-connected T-type TLI using d–q control has been computationally modelled, simulated and validated with constant and variable speeds using MATLAB® and Simulink®. It is confirmed that the P&O-based MPP approach ensures maximum power for varying wind speeds, and the total harmonic distortion of the T-type TLI grid current value is 3.18%, which is within IEEE-519 limits. Furthermore, with grid synchronization, the power factor of the T-type TLI is maintained at unity to avoid power-quality issues.

Topics & Concepts

Control theory (sociology)Rectifier (neural networks)Maximum power point trackingPermanent magnet synchronous generatorTotal harmonic distortionMaximum power principleWind powerInverterVoltagePower (physics)Computer scienceEngineeringElectrical engineeringPhysicsControl (management)Stochastic neural networkArtificial neural networkMachine learningArtificial intelligenceRecurrent neural networkQuantum mechanicsMultilevel Inverters and ConvertersMicrogrid Control and OptimizationWind Turbine Control Systems