Open AccessModel‐free adaptive learning control scheme for wind turbines with doubly fed induction generators
Author(s) -
Abouheaf Mohammed,
Gueaieb Wail,
Sharaf Adel
Publication year - 2018
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2018.5353
Subject(s) - wind power , control theory (sociology) , turbine , induction generator , controller (irrigation) , computer science , control engineering , reinforcement learning , grid , rotor (electric) , adaptive control , pitch control , engineering , control (management) , artificial intelligence , mathematics , aerospace engineering , mechanical engineering , agronomy , geometry , biology , electrical engineering
The classical control mechanisms of the wind turbines are generally based on precise modelling approaches to ensure robust and effective interplay between the wind turbines and the main power grids in both autonomous and grid‐connected modes. This study presents an innovative intelligent control system for the doubly fed induction generator wind turbines. The proposed system uses model‐free control polices. The online controller is based on a policy iteration reinforcement learning paradigm along with an adaptive actor‐critic technique. It is shown to be robust against the turbine's high non‐linearities and stochastic variations in the input–output conditions. These are associated with single and double rotor doubly fed large‐scale induction generators driven by wind turbines in the range of 5–7 MW. The performance of the controller is validated against challenging scenarios of coexisting undesired situations like severe wind changes with load excursions and abrupt shifts in the loads.