Wind Turbines Integration into Power Systems: Advanced Control Strategy for Harmonics Mitigation

Author(s):  
Alex Reis ◽  
José Carlos de Oliveira ◽  
Leandro Pains Moura
2017 ◽  
Vol 2017 (13) ◽  
pp. 1170-1175 ◽  
Author(s):  
Jinxin Ouyang ◽  
Mengyang Li ◽  
Ting Tang ◽  
Di Zheng ◽  
Rui Yu ◽  
...  

2018 ◽  
Vol 33 (2) ◽  
pp. 1811-1823 ◽  
Author(s):  
Tat Kei Chau ◽  
Samson Shenglong Yu ◽  
Tyrone Lucius Fernando ◽  
Herbert Ho-Ching Iu ◽  
Michael Small

2012 ◽  
Vol 27 (2) ◽  
pp. 713-722 ◽  
Author(s):  
Lihui Yang ◽  
Zhao Xu ◽  
Jacob Ostergaard ◽  
Zhao Yang Dong ◽  
Kit Po Wong

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3429 ◽  
Author(s):  
Chu ◽  
Yuan ◽  
Hu ◽  
Pan ◽  
Pan

With increasing size and flexibility of modern grid-connected wind turbines, advanced control algorithms are urgently needed, especially for multi-degree-of-freedom control of blade pitches and sizable rotor. However, complex dynamics of wind turbines are difficult to be modeled in a simplified state-space form for advanced control design considering stability. In this paper, grey-box parameter identification of critical mechanical models is systematically studied without excitation experiment, and applicabilities of different methods are compared from views of control design. Firstly, through mechanism analysis, the Hammerstein structure is adopted for mechanical-side modeling of wind turbines. Under closed-loop control across the whole wind speed range, structural identifiability of the drive-train model is analyzed in qualitation. Then, mutual information calculation among identified variables is used to quantitatively reveal the relationship between identification accuracy and variables’ relevance. Then, the methods such as subspace identification, recursive least square identification and optimal identification are compared for a two-mass model and tower model. At last, through the high-fidelity simulation demo of a 2 MW wind turbine in the GH Bladed software, multivariable datasets are produced for studying. The results show that the Hammerstein structure is effective for simplify the modeling process where closed-loop identification of a two-mass model without excitation experiment is feasible. Meanwhile, it is found that variables’ relevance has obvious influence on identification accuracy where mutual information is a good indicator. Higher mutual information often yields better accuracy. Additionally, three identification methods have diverse performance levels, showing their application potentials for different control design algorithms. In contrast, grey-box optimal parameter identification is the most promising for advanced control design considering stability, although its simplified representation of complex mechanical dynamics needs additional dynamic compensation which will be studied in future.


2021 ◽  
Vol 1055 (1) ◽  
pp. 012153
Author(s):  
D Sarathkumar ◽  
M Srinivasan ◽  
Albert Alexander Stonier ◽  
Ravi Samikannu ◽  
Narasimha Rao Dasari ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document