scholarly journals Disturbance Observer-Based Fuzzy SMC of WECSs Without Wind Speed Measurement

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 147-155 ◽  
Author(s):  
Ton Duc Do
Keyword(s):  
Wind Speed ◽  
Disturbance Observer ◽  
Speed Measurement ◽  
Wind Speed Measurement

Determining permissible Doppler lidar beam deviation angles in wind speed measurement

1991 ◽  
Vol 34 (9) ◽  
pp. 906-911
Author(s):  
A. A. Kormakov ◽  
L. A. Kosovskii ◽  
N. V. Pakhomushkina ◽  
G. A. Pogosov
Keyword(s):  
Wind Speed ◽  
Doppler Lidar ◽  
Speed Measurement ◽  
Wind Speed Measurement

Wind speed measurement

1987 ◽  
Vol 81 (6) ◽  
pp. 2001-2001
Author(s):  
Maurice C. Heard
Keyword(s):  
Wind Speed ◽  
Speed Measurement ◽  
Wind Speed Measurement

Improvement of Wind Speed Measurement Model by Meteorological UAV and System Design

2012 ◽  
Vol 542-543 ◽  
pp. 591-594
Author(s):  
Shu Dao Zhou ◽  
Yong Qi Jin ◽  
Ying Qiang Wang ◽  
Min Wang
Keyword(s):  
Wind Speed ◽  
System Design ◽  
Measurement System ◽  
Measurement Model ◽  
Calculation Model ◽  
Related Data ◽  
Speed Measurement ◽  
Design Diagram ◽  
Wind Speed Measurement ◽  
The Impact

At present, the error of wind speed measurement by meteorological UAV is great, in order to solve this problem, this paper identified the major sources of error by the analysis of the wind measurement model. Found that the airspeed error caused by the aircraft acceleration for the airspeed is very small, so classic airspeed measurement calculations often ignore the impact of aircraft acceleration, but the value of wind speed is smaller, so that the error caused by aircraft acceleration relative to the wind speed cannot be ignored. Therefore, this article added aircraft acceleration to re-establish the airspeed measurement model, and got an improved wind speed of calculation model. In order to verify the model, the wind speed measurement system was been designed, the system design diagram and related data processing, solver method were presented.

scholarly journals Uncertainties identification of the blade-mounted lidar-based inflow wind speed measurements for robust feedback-feedforward control synthesis

2019 ◽  
Author(s):  
Róbert Ungurán ◽  
Vlaho Petrović ◽  
Lucy Y. Pao ◽  
Martin Kühn
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Feedforward Control ◽  
Control Synthesis ◽  
Induction Effect ◽  
Control Input ◽  
Speed Measurement ◽  
Induction Zone ◽  
Feedforward Controller ◽  
Wind Speed Measurement

Abstract. The current trend toward larger wind turbine rotors leads to high periodic loads across the components due to the non-uniformity of inflow across the rotor. On this regard, we introduce a blade-mounted lidar on each blade to provide a preview of inflow wind speed that can be used as a feedforward control input for the mitigation of such periodic blade loads. We present a method to easily determine blade-mounted lidar parameters, such as focus distance, telescope position, and orientation on the blade. However, such method is accompanied by uncertainties in the inflow wind speed measurement, which may also be due to the induction zone, wind evolution, cyclops dilemma, unidentified misalignment in the telescope orientation, and the blade segment orientation sensor. Identification of these uncertainties allows their inclusion in the feedback-feedforward controller development for load mitigation. We perform large-eddy simulations, in which we simulate the blade-mounted lidar including the dynamic behaviour and the induction zone of one reference wind turbine for one above rated inflow wind speed. Our calculation approach provides a good trade-off between a fast-and-simple determination of the telescope parameters and an accurate inflow wind speed measurement. We identify and model the uncertainties, which then can directly be included in the feedback-feedforward controller design and analysis. The rotor induction effect increases the preview time, which needs to be considered in the controller development and implementation.

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