Wind Speed And Rotor Position Sensorless Control For Direct-Drive PMG Wind Turbines

ABSTRACT:

Wind turbine generators (WTGs) are usually equipped with mechanical sensors to measure wind speed and rotor position for system control, monitoring, and protection.The use of mechanical sensors increases the cost and hardware complexity and reduces the reliability of the WTG system. This paper proposes a wind speed and rotor position sensorless control for wind turbines directly driving permanent magnetic generators (PMGs). A sliding mode observer is designed to estimate the rotor position of the PMG, which is then used to calculate the shaft rotating speed. Based on the measured output electrical power and estimated rotor speed of the PMG, the mechanical power of the turbine is estimated by taking account into the power losses of the WTG system. A back propagation artificial neural network (BPANN) is then designed to estimate the wind speed in real time by using the estimated turbine shaft speed and mechanical power. The estimated wind speed is used to determine the optimal shaft speed or power reference for the PMG control system. Finally, a sensorless control is developed for the PMG wind turbines to continuously generate the maximum electrical power without using any wind speed or rotor position sensors. The validity of the proposed estimation and control algorithms are shown by simulation studies on a 3- kW PMG wind turbine and are further demonstrated by experimental results on a 300-W practical PMG wind turbine.

KEYWORDS:

  1. Artificial neural network (ANN)
  2. Direct-drive PMG wind turbine
  3. Sensorless control
  4. Sliding mode observer

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

                Fig. 1. Configuration of a direct-drive PMG wind turbine connected to a power grid.

EXPECTED SIMULATION RESULTS:

 

Fig. 2. Rotor position estimation results.

Fig. 3. Shaft speed estimation results.

Fig. 4. Shaft mechanical power estimation results.

Fig. 5. Wind speed estimation results.

Fig. 6. Shaft speed tracking results.

Fig. 7. Actual and optimal tip speed ratios.

CONCLUSION:

This paper has proposed a novel mechanical sensorless control algorithm for maximum wind power generation using direct-drive PMG wind turbines. The values of wind speed, rotor position, and turbine shaft speed have been estimated from the measured stator voltages and currents of the PMG in real time. These estimated variables were then used for optimal control of the power electronic converters and the PMG. Therefore, the commonly used mechanical sensors in WTG systems, i.e., the wind speed sensors and rotor position sensors, are not needed. The effectiveness of the proposed estimation methods and sensorless control algorithm have been demonstrated by simulation results of a 3-kW PMG wind turbine. Experimental studies have been carried out on a 300-W practical PMG wind turbine system to further validate the proposed speed estimation algorithms.

REFERENCES:

[1] J. Ribrant and L. M. Bertling, “Survey of failures in wind power systems with focus on Swedish wind power plants during 1997-2005,” IEEE Trans. Energy Conversion, vol. 22, no. 1, pp. 167-173, Mar. 2007.

[2] W. Qiao, W. Zhou, J. M. Aller, and R. G. Harley, “Wind speed estimation based sensorless output maximization control for a wind turbine driving a DFIG,” IEEE Trans. Power Electronics, vol. 23, no. 3, pp. 1156-1169, May 2008.

[3] B. Boukhezzar and H. Siguerdidjane, “Nonlinear control of variable speed wind turbines without wind speed measurement,” in Proc. 44th IEEE Conference on Decision and Control, Seville, Spain, Dec. 12-15, 2005, pp. 3456-3461.

[4] T. Tanaka and T. Toumiya, “Output control by Hill-Climbing method for a small wind power generating system,” Renewable Energy, vol. 12, no. 4, pp. 387-400, 1997.

[5] M. G. Simoes, B. K. Bose, and R. J. Spiegel, “Fuzzy logic based intelligent control of a variable speed cage machine wind generation system,” IEEE Trans. Power Electronics, vol. 12, no. 1, pp. 87-95, Jul./Aug. 1997.

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