Blade Angle Control Using TLBO Based Modified Adaptive Controller

Wind energy is one of the fastest-growing energy sources of green energy in the world. Research efforts are aimed to address the challenges to greater use of wind energy. Thus, the paper presents a blade angle control based on a new modified adaptive PI controller. The controller relies on teaching...

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Bibliographic Details
Published in2020 15th International Conference on Computer Engineering and Systems (ICCES) pp. 1 - 6
Main Authors Shawqran, Ahmed M., El-Marhomy, Abdallah, Attia, Mahmoud A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.12.2020
Subjects
adaptive control
adaptive PI
Adaptive systems
asynchronous generators
blade angle control
Blade angle controller
blades
DFIG
doubly fed induction generator
Doubly fed induction generators
energy sources
green energy
induction generator system
modified adaptive controller
modified adaptive PI controller
optimisation
Optimization
PI control
power system control
proportional-integral- differential (PID)
Teaching learning- based optimization TLBO
teaching learning-based optimization
three-term control
TLBO
Transient analysis
wind energy
wind power plants
wind turbine systems
wind turbines
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Summary:Wind energy is one of the fastest-growing energy sources of green energy in the world. Research efforts are aimed to address the challenges to greater use of wind energy. Thus, the paper presents a blade angle control based on a new modified adaptive PI controller. The controller relies on teaching learning-based optimization algorithms (TLBO) to optimally evaluate its initials. The effectiveness of the proposed controller is verified by simulation results for six 1.5-MW wind turbines doubly fed induction generator (DFIG) system. The validation composes a comparison with conventional adaptive controller under normal and faulty conditions. The modified adaptive PI showed improved mechanical and electrical behaviors for the wind turbine relying on its second order amplifier. The amplifier works as analogue filter that improves the system dynamic characteristics. The new controller showed robustness to the changes in system parameters and the nonlinearity of the wind turbine systems. The superiority of the new controller has been proved when compared with conventional PID controller.
DOI:10.1109/ICCES51560.2020.9334607