Intelligent mechanical sensorless MPPT control for wind energy systems

Wind energy systems (WESs) are usually equipped with mechanical sensors to measure wind speed, rotor shaft speed, and generator rotor position/speed for system monitoring, control, and protection. The use of these sensors increases cost, size, weight, and hardware wiring complexity and reduces relia...

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Veröffentlicht in:2012 IEEE Power and Energy Society General Meeting S. 1 - 8
1. Verfasser: Wei Qiao
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.07.2012
Schlagworte:
Artificial neural network (ANN)
Estimation
Generators
intelligent control
maximum power point tracking (MPPT)
Rotors
sensorless control
Shafts
wind energy system (WES)
Wind speed
Wind turbines
ISBN:1467327271, 9781467327275
ISSN:1932-5517
Online-Zugang:Volltext
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Abstract Wind energy systems (WESs) are usually equipped with mechanical sensors to measure wind speed, rotor shaft speed, and generator rotor position/speed for system monitoring, control, and protection. The use of these sensors increases cost, size, weight, and hardware wiring complexity and reduces reliability of WESs. The problems incurred in using mechanical sensors can be solved through mechanical sensorless control. This paper presents the principles of mechanical sensorless maximum power point tracking (MPPT) control for WESs based on an overview of existing work on the subject. Several intelligent mechanical sensorless control algorithms for WESs are presented, including: 1) a hill-climb search (HCS)-based wind speed sensor-less MPPT control algorithm, 2) various artificial neural network (ANN)-based wind speed sensorless MPPT control algorithms, and 3) an ANN-sliding mode observer (SMO)-based wind speed, generator rotor position and shaft speed sensorless MPPT control algorithm. The effectiveness of these intelligent mechanical sensorless MPPT control algorithms are demonstrated by computer simulations as well as experiments on practical WESs.
AbstractList Wind energy systems (WESs) are usually equipped with mechanical sensors to measure wind speed, rotor shaft speed, and generator rotor position/speed for system monitoring, control, and protection. The use of these sensors increases cost, size, weight, and hardware wiring complexity and reduces reliability of WESs. The problems incurred in using mechanical sensors can be solved through mechanical sensorless control. This paper presents the principles of mechanical sensorless maximum power point tracking (MPPT) control for WESs based on an overview of existing work on the subject. Several intelligent mechanical sensorless control algorithms for WESs are presented, including: 1) a hill-climb search (HCS)-based wind speed sensor-less MPPT control algorithm, 2) various artificial neural network (ANN)-based wind speed sensorless MPPT control algorithms, and 3) an ANN-sliding mode observer (SMO)-based wind speed, generator rotor position and shaft speed sensorless MPPT control algorithm. The effectiveness of these intelligent mechanical sensorless MPPT control algorithms are demonstrated by computer simulations as well as experiments on practical WESs.
Author Wei Qiao
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  surname: Wei Qiao
  fullname: Wei Qiao
  email: wqiao@engr.unl.edu
  organization: Dept. of Electr. Eng., Univ. of Nebraska-Lincoln, Lincoln, NE, USA
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Snippet Wind energy systems (WESs) are usually equipped with mechanical sensors to measure wind speed, rotor shaft speed, and generator rotor position/speed for system...
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SubjectTerms Artificial neural network (ANN)
Estimation
Generators
intelligent control
maximum power point tracking (MPPT)
Rotors
sensorless control
Shafts
wind energy system (WES)
Wind speed
Wind turbines
Title Intelligent mechanical sensorless MPPT control for wind energy systems
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