Title :
Intelligent mechanical sensorless MPPT control for wind energy systems
Author_Institution :
Dept. of Electr. Eng., Univ. of Nebraska-Lincoln, Lincoln, NE, USA
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.
Keywords :
intelligent control; maximum power point trackers; neural nets; power generation control; rotors; variable structure systems; wind power plants; ANN-sliding mode observer; artificial neural network; generator rotor position; hardware wiring complexity; hill climb search; intelligent mechanical sensorless MPPT control; maximum power point tracking; mechanical sensors; rotor shaft speed; rotor speed; wind energy systems; wind speed; Estimation; Generators; Rotors; Shafts; Wind speed; Wind turbines; Artificial neural network (ANN); intelligent control; maximum power point tracking (MPPT); sensorless control; wind energy system (WES);
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
DOI :
10.1109/PESGM.2012.6345443