Black Widow Optimization-Based Optimal PI-Controlled Wind Turbine Emulator

K. Premkumar, M. Vishnupriya, Thanikanti Sudhakar Babu, B. V. Manikandan, T. Thamizhselvan, A. Nazar Ali, Md. Rabiul Islam, Abbas Z. Kouzani and M. A. Parvez Mahmud
Additional contact information
K. Premkumar: Department of EEE, Rajalakshmi Engineering College, Tamilnadu 602105, India
M. Vishnupriya: Department of ECE, Saveetha School of Engineering, Tamilnadu 602105, India
Thanikanti Sudhakar Babu: Institute of Power Engineering, Department of Electrical Power Engineering, Universiti Tenaga National, Selangor 43000, Malaysia
B. V. Manikandan: Department of EEE, Mepco Schlenk Engineering College, Tamilnadu 626005, India
T. Thamizhselvan: Department of EEE, Rajalakshmi Engineering College, Tamilnadu 602105, India
A. Nazar Ali: Department of EEE, Rajalakshmi Engineering College, Tamilnadu 602105, India
Md. Rabiul Islam: School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
Abbas Z. Kouzani: School of Engineering, Deakin University, Geelong, VIC 3216, Australia
M. A. Parvez Mahmud: School of Engineering, Deakin University, Geelong, VIC 3216, Australia

Sustainability, 2020, vol. 12, issue 24, 1-19

Abstract: In this article, the parameters of the proportional-integral (PI) controller of the wind turbine (WT) emulator, i.e., proportional and integral gain of the PI controller, are optimized using a black widow optimization algorithm (BWOA). The proposed system is developed and analyzed using MATLAB/Simulink environment. The performance of the BWOA optimized PI controller is compared with a BAT algorithm, particle swarm optimization, and genetic algorithm optimized PI controller to measure the effectiveness of the proposed control system. The developed system is tested for different operating conditions such as static wind speed settings, static pitch angle conditions, step-change in wind speed settings, and step-change in pitch angle settings. Finally, the proposed system is realized in real-time by hardware experimentations. The results of the experimentation are compared with simulation results as well. The presented simulation and hardware result shows good agreement, which confirms the effectiveness of the proposed method. Thereby, the proposed optimization-based PI-controlled wind emulator can be recommended for emulating the characteristics of any type of WT with a low-cost system.

Keywords: BAT algorithm; black widow optimization algorithm; genetic algorithm; particle swarm optimization; proportional-integral (PI) controller; wind turbine emulator (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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