Title :
Self-tuning maximum power point tracking control for wind generation systems
Author :
Mesemanolis, A. ; Mademlis, C.
Author_Institution :
Dept. of Electr. Eng., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece
Abstract :
In this paper, a new Maximum Power Point Tracking (MPPT) control scheme for wind generation systems is proposed. A new procedure based on an adaptive neuro-fuzzy training technique is proposed for the self-tuning of the MPPT controller parameters in order to compensate for the unmodeled nonlinearities and degradation due to mechanical aging of various parts of the wind turbine. The suggested control scheme can be easily implemented because neither the measurement of the wind speed nor the knowledge of the wind turbine characteristics are required. Moreover, it has fast dynamic response and thus it can follow the fast dynamics of the wind. The effectiveness and fast dynamic performance of the proposed control scheme has been verified experimentally.
Keywords :
fuzzy control; maximum power point trackers; neurocontrollers; power generation control; wind power plants; wind turbines; MPPT controller parameter; adaptive neuro-fuzzy training technique; fast dynamic response; mechanical aging; self-tuning maximum power point tracking control; wind generation system; wind turbine characteristics; Blades; Generators; Optimized production technology; Torque; Training; Wind speed; Wind turbines; Squirrel cage induction generator; adaptive neuro-fuzzy systems; optimal control; variable speed drives; wind energy conversion system;
Conference_Titel :
Clean Electrical Power (ICCEP), 2013 International Conference on
Conference_Location :
Alghero
Print_ISBN :
978-1-4673-4429-6
DOI :
10.1109/ICCEP.2013.6587022