Open AccessMaximum power extraction improvement using sensorless controller based on adaptive perturb and observe algorithm for PMSG wind turbine application
Author(s) -
Putri Ratna Ika,
Pujiantara Margo,
Priyadi Ardyono,
Ise Toshifumi,
Purnomo Mauridhi Hery
Publication year - 2018
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.815
H-Index - 97
eISSN - 1751-8679
pISSN - 1751-8660
DOI - 10.1049/iet-epa.2017.0603
Subject(s) - control theory (sociology) , maximum power principle , duty cycle , permanent magnet synchronous generator , maximum power point tracking , turbine , wind power , controller (irrigation) , power optimizer , rectifier (neural networks) , power (physics) , engineering , voltage , computer science , electrical engineering , physics , inverter , mechanical engineering , agronomy , stochastic neural network , control (management) , artificial intelligence , machine learning , quantum mechanics , recurrent neural network , artificial neural network , biology
Wind energy conversion systems (WECSs) can extract maximum power by controlling the wind turbine rotational speed. This study presents a novel sensorless maximum power extraction control for small‐scale WECS using a permanent magnet synchronous generator (PMSG), to improve the maximum power extraction. The proposed method uses the output voltage and current of a rectifier to determine the duty cycle of the boost converter, without requiring the wind speed information and turbine characteristics. The step size of the duty cycle is changed adaptively, based on the difference between the rectifier output power and the previous duty cycle to obtain fast convergence, until the maximum power point is attained. The performance of the proposed sensorless maximum power extraction control is evaluated both by simulation, using PowerSIM and laboratory experiments, for variable wind speed conditions. The proposed maximum power extraction controller has a simple structure, low cost, and a good response to wind speed variations. The proposed method can extract a higher maximum power and has a higher efficiency of 93.87%, than the conventional perturb and observe method.