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.
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.
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[3]
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