SMALL WIND TURBINE PMSG GENERATION SYSTEM

1. SMALL WIND TURBINE PMSG GENERATION SYSTEM Gene Z. Guo May 19, 2006 Sustainable Power Research Group University of New Brunswick

2. Introduction • R&D of distributed power generation (DG) systems is becoming more and more popular nowadays because of • 1.     Increasing demand of electric generation • 2.     Various advantages of DG system, such as • environmental-friend, short construct period, etc. • 3.     and the development of related theory and technology. • Wind power generation systems are one of the most important R&D and application of the DG systems. • Direct-drive, variable frequency PMSG grid-connected wind generation system is playing an important role in the small wind power applications.

3. A 3kW wind power generation system is presented, the system includes • Whisper 175 wind turbine from Southwest windpower •  3kW DSP-controlled single phase grid-connected IGBT inverter Three key issues are studied to improve the performance •    Inverter current THD reduction Improved predictive current control algorithm is presented •     Inverter Noise reduction Improved PWM strategy is applied •      Maximum wind power extraction of the inverter Fuzzy-logic-based MPPT strategy is employed

4. Rotor Diameter: 15 ft. (4.5m) Weight: 155 lbs (70kg) Mount: 5” schedule 40 (12.7cm) Start-up wind speed: 7.5 mph (3.4m/s) Voltage: 0~440Vac Rated Power: 3000 watts at 24mph (10.5m/s) Peak Power: 3200 watts at 27mph (12m/s) Turbine Controller: EZ-Wire Wind & Solar Hybrid Blades (three): Carbon reinforced fiberglass Kilowatt hours per month: 538 kWh/mo @12mph (5.4m/s) Warranty: 2 Year Limited Warranty or 5 year Extended Warranty Option Whisper 175 Wing Turbine Specifications Southwest Windpower

5. PMSG Power Converter Grid Single-phase Inverter Current Controller VSWT Block diagram of VSWT generation system Improved predictive current controler Features of inverter: • 3-phase input • single-phase output, • grid-connected, • DSP controlled • Voltage Source The key to reduce current THD is to slect suitable current controller

6. Generally, the inverter current controllers can be classified as: • Hysteresis Current Controller • Simple and robust • Switching frequency depends on the load parameters • Current THD is high • Ramp Comparison Current Controller • Switching frequency is limited to that of the triangular waveform • Produced current harmonics are defined at a fixed frequency • Inherent phase and amplitude errors arise, even in the steady state • Predictive Current Controllers. • Offers potential for achieving more precise current control with minimum distortion and harmonic noise • Increase the computation effort and parameters dependency

7. Standard Predictive Control Algorithm Single-Phase Grid-Connected Inverter Topology Govern Eq.: Discrete form:

8. Control target: =Iload[n+1] Therefore: After formule manipulation

9. Improved Predictive Current Algorithm Standard predictive current algorithm is of poor robustness TD:Total delay The sampling point is moved as shown above Govern Eq.:

10. An Improved PWM Strategy for Inverter Noise Reduction Inverter noise mainly comes from AC filter inductor, depends on the harmonic current frequency passing the inductor, furthermore, PWM carrier frequency Noise can be reduced through control the current harmonic frequency of inductor, higher or lower than the hearable spectrum Limited to present IGBT technology and considering of the losses and temperature rise, the switching frequency of IGBT is set as 10kHz in this project

11. Conventional PWM Strategy Switching PWM Scheme

12. Improved PWM Strategy Improved PWM Strategy PWM Scheme Generation in DSP Compared with the conventional one, the current harmonics of the new is doubled to 20kHz, prevent the hearable noise

13. TEST RESULTS By splitting the pulse width in a PWM period, the switching frequency keep same: 10kHz,but the noise and current THD is significantly improved

14. MPPT Based on Fuzzy-logic Algorithm • In order to extract maximum power from the wind turbine, the Maximum Power Point Tracking (MPPT) method should be employed. In this project, a fuzzy-logic-based MPPT algorithm is presented and applied. • In this method, the dc-link voltage and current, Vdc and Idc, are sampled as the power feedback for the inverter controller, and the Vdc reference signal is updated in real time using a hill-climbing searching (HCS) method so as to lead the system to its optimal operation point. • The FLC is robust and the searching for optimal Vdc is fast and accurate.

15. Diode Rectifier IGBT Inverter Bridge L DB T1 T3 From Generator 240V 60Hz Grid C Cdc V T4 T2 Idc Vdc MPPT 4 PWM Vdc* Idm IL FLC HCS CC Power circuit of single-phase grid-connected inverter and its control block diagram

16. Simulation model of VSWT generation system in Matlab

17. Simulation results with step change in wind speed Simulation results with random wind speed

18. Inverter Construction & Test Results Power circuit schematic diagram

19. Start PWM Underflow ISR Serve Timers Synchronization System Initialization Input & Output Control Start/Stop P/B LCD Display Main Loop Module Relays Control O/P Power Control System Protection Zero-crossing Detection CAP3 ISR Interrupt Serving Module ADC ISR PWM Control PWM Underflow ISR Serve Timers Synchronization Software block diagram of the inverter

28. ACKNOWLEDGEMENT • The research group wish to thank the Atlantic Innovation Fund (AIF) for its support to this research project