Collective Blade Pitch Angle Control with PID and Fuzzy Logic Controller
Year 2022,
Volume: 14 Issue: 3, 321 - 332, 31.12.2022
Murat Lüy
,
Nuri Alper Metin
,
Zafer Civelek
Abstract
Generators for wind turbines with variable speeds are more potent than those with set speeds. However, the variable speed machine's voltage and frequency shift as a result of erratic wind speed. A proper control method raises the power's quality. The dynamic properties of the combined wind generator system must be researched in order to regulate the fluctuating wind generator output when it is employed in the system. More dynamic performance can be achieved by designing better controllers. Pitch angle control was carried out in this study's wind turbine design using the MATLAB/Simulink environment Pitch angle control is accomplished using PID and a fuzzy logic controller (FLC). The simulation research looked at these control techniques, the amount of oscillation in the reference power value, the duration to achieve the reference value, and the variations in blade pitch angle.
References
- Ahmed, R. T. (2009). “Design a position control of the blade pitch angle for variable speed wind turbine generators. Engineering and Technology Journal”, 27(1681-6900).
- Bakdi, A., Kouadri, A., & Mekhilef, S. (2019). A data-driven algorithm for online detection of component and system faults in modern wind turbines at different operating zones. Renewable and Sustainable Energy Reviews, 103, 546-555, 10.1016/j.rser.2019.01.013.
- BTM Consult, (2001) “International Wind Energy Development; World Market Update 2000,”.
C. -K. Chang and S. -G. Zheng, (2021) “Combined Predictive Feedforward and Feedback Control for Blade Pitch of Wind Turbine,” International Automatic Control Conference (CACS), 2021, pp. 1-6, 10.1109/CACS52606.2021.9639044.
- Civelek Z., Lüy M., Çam E., Barışçı N. (2014) “PI Kontrolör ile Rüzgâr Türbininin Hatve Açısının Kontrolü” ISEM2014, , Akademik Platform.
- Civelek, Z. (2020). “Optimization of fuzzy logic (Takagi-Sugeno) blade pitch angle controller in wind turbines by genetic algorithm. Engineering Science and Technology, an International Journal”, 23(1), 1-9, 201904010.
- Elfergani, A., Elsharif, M. A., Hamd, R. H., Saad, S. M., El Naily, N., & Mohamed, F. A. (2018). Advanced self-tuned pitch angle control based on fuzzy logic for grid connected variable-speed wind turbine system. In 2018 9th International Renewable Energy Congress (IREC) (pp. 1-6). IEEE.
- EWE, (1999) “Wind energy - The Facts. “European Wind Energy Association, Brussels, Belgium”.
- Jiang, S. J., Chu, S. C., Zou, F. M., Shan, J., Zheng, S. G., & Pan, J. S. (2023). A parallel Archimedes optimization algorithm based on Taguchi method for application in the control of variable pitch wind turbine. Mathematics and Computers in Simulation, 203, 306-327.
- Kharchouf, I., Essadki, A., Fdaili, M., & Nasser, T. (2018). Comparative study of MPPT and pitch angle using PI and fuzzy logic controllers. In 2018 6th International Renewable and Sustainable Energy Conference (IRSEC) (pp. 1-6). IEEE.
- Lüy, M. & Metin, N. A. (2022). PID Control Medium Size Wind Turbine Control with Integrated Blade Pitch Angle . International Scientific and Vocational Studies Journal , 6 (1) , 22-31, 10.47897/bilmes.1091968.
- M. Elsisi, M.-Q. Tran, K. Mahmoud, M. Lehtonen and M. M. F. Darwish, (2021) “Robust Design of ANFIS-Based Blade Pitch Controller for Wind Energy Conversion Systems Against Wind Speed Fluctuations,” in IEEE Access, vol. 9, pp. 37894-37904, 10.1109/ACCESS.2021.3063053.
- Mastacan, L., & Dosoftei, C. C. (2018). Temperature fuzzy control system with Mamdani controller. In 2018 International Conference and Exposition on Electrical And Power Engineering (EPE) (pp. 0352-0356). IEEE, ICEPE.2018.8559861.
- Nejad, A. R., Keller, J., Guo, Y., Sheng, S., Polinder, H., Watson, S., ... & Helsen, J. (2022). “Wind turbine drivetrains: state-of-the-art technologies and future development trends”. Wind Energy Science, 7(1), 387-411.
- Pahasa, J., & Ngamroo, I. (2016). Coordinated control of wind turbine blade pitch angle and PHEVs using MPCs for load frequency control of microgrid. IEEE Systems Journal, 10(1), 97-105, 10.1109/JSYST.2014.2313810.
- Poureh, A., Chamani, M., & Bahri, A. (2023). “Nonlinear analysis of gain scheduled controllers for the NREL 5-MW turbine blade pitch control system.” International Journal of Electrical Power & Energy Systems, 145, 108578.
- Saihi, L., Bakou, Y., Ferroudji, F., Berbaoui, B., & Djilali, L. (2019). MPPTF & pitch fuzzy controller of a wind turbine system using DFIG. In 2019 1st International Conference on Sustainable Renewable Energy Systems and Applications (ICSRESA) (pp. 1-6). IEEE.
- Shen, H., Ruiz, A., & Li, N. (2023). Fast online reinforcement learning control of small lift-driven vertical axis wind turbines with an active programmable four bar linkage mechanism. Energy, 262, 125350.
- Yuan, Y., Chen, X., & Tang, J. (2020). Multivariable robust blade pitch control design to reject periodic loads on wind turbines. Renewable Energy, 146, 329-341.
PID ve Bulanık Mantık Denetleyiciyle Kollektif Kanat Hatve Açısı Kontrolü
Year 2022,
Volume: 14 Issue: 3, 321 - 332, 31.12.2022
Murat Lüy
,
Nuri Alper Metin
,
Zafer Civelek
Abstract
Değişken hızlı rüzgar türbini jeneratörleri, sabit hızlı rüzgar türbinlerine göre daha güçlüdür. Ancak kararsız rüzgar hızı, değişken hızlı makinenin gerilim ve frekansında değişmlere neden olmaktadır. Uygun bir kontrol tekniği ile gücün kalitesi iyileştirilir.Sistemde kullanıldığında, dalgalanan rüzgar jeneratörü çıkışının kontrol edilmesi gerekir, bu nedenle kombine rüzgar jeneratörü sisteminin dinamik özelliklerinin incelenmesi gerekir. Daha dinamik performans için daha iyi denetleyici tasarlanabilir. Bu çalışmada, MATLAB/Simulink ortamında rüzgar türbini tasarlanmış ve hatve açısı denetim işlemi gerçekleştirilmiştir. Hatve açısı denetimi için PID ve Bulanık Mantık Denetleyici (BMD) kullanılmıştır. Bu denetim algoritmaları referans güç değerinde salınım miktarı, referans değere ulaşım süreleri ve kanat hatve açısındaki değişimler benzetim çalışmasında incelenmiştir.
References
- Ahmed, R. T. (2009). “Design a position control of the blade pitch angle for variable speed wind turbine generators. Engineering and Technology Journal”, 27(1681-6900).
- Bakdi, A., Kouadri, A., & Mekhilef, S. (2019). A data-driven algorithm for online detection of component and system faults in modern wind turbines at different operating zones. Renewable and Sustainable Energy Reviews, 103, 546-555, 10.1016/j.rser.2019.01.013.
- BTM Consult, (2001) “International Wind Energy Development; World Market Update 2000,”.
C. -K. Chang and S. -G. Zheng, (2021) “Combined Predictive Feedforward and Feedback Control for Blade Pitch of Wind Turbine,” International Automatic Control Conference (CACS), 2021, pp. 1-6, 10.1109/CACS52606.2021.9639044.
- Civelek Z., Lüy M., Çam E., Barışçı N. (2014) “PI Kontrolör ile Rüzgâr Türbininin Hatve Açısının Kontrolü” ISEM2014, , Akademik Platform.
- Civelek, Z. (2020). “Optimization of fuzzy logic (Takagi-Sugeno) blade pitch angle controller in wind turbines by genetic algorithm. Engineering Science and Technology, an International Journal”, 23(1), 1-9, 201904010.
- Elfergani, A., Elsharif, M. A., Hamd, R. H., Saad, S. M., El Naily, N., & Mohamed, F. A. (2018). Advanced self-tuned pitch angle control based on fuzzy logic for grid connected variable-speed wind turbine system. In 2018 9th International Renewable Energy Congress (IREC) (pp. 1-6). IEEE.
- EWE, (1999) “Wind energy - The Facts. “European Wind Energy Association, Brussels, Belgium”.
- Jiang, S. J., Chu, S. C., Zou, F. M., Shan, J., Zheng, S. G., & Pan, J. S. (2023). A parallel Archimedes optimization algorithm based on Taguchi method for application in the control of variable pitch wind turbine. Mathematics and Computers in Simulation, 203, 306-327.
- Kharchouf, I., Essadki, A., Fdaili, M., & Nasser, T. (2018). Comparative study of MPPT and pitch angle using PI and fuzzy logic controllers. In 2018 6th International Renewable and Sustainable Energy Conference (IRSEC) (pp. 1-6). IEEE.
- Lüy, M. & Metin, N. A. (2022). PID Control Medium Size Wind Turbine Control with Integrated Blade Pitch Angle . International Scientific and Vocational Studies Journal , 6 (1) , 22-31, 10.47897/bilmes.1091968.
- M. Elsisi, M.-Q. Tran, K. Mahmoud, M. Lehtonen and M. M. F. Darwish, (2021) “Robust Design of ANFIS-Based Blade Pitch Controller for Wind Energy Conversion Systems Against Wind Speed Fluctuations,” in IEEE Access, vol. 9, pp. 37894-37904, 10.1109/ACCESS.2021.3063053.
- Mastacan, L., & Dosoftei, C. C. (2018). Temperature fuzzy control system with Mamdani controller. In 2018 International Conference and Exposition on Electrical And Power Engineering (EPE) (pp. 0352-0356). IEEE, ICEPE.2018.8559861.
- Nejad, A. R., Keller, J., Guo, Y., Sheng, S., Polinder, H., Watson, S., ... & Helsen, J. (2022). “Wind turbine drivetrains: state-of-the-art technologies and future development trends”. Wind Energy Science, 7(1), 387-411.
- Pahasa, J., & Ngamroo, I. (2016). Coordinated control of wind turbine blade pitch angle and PHEVs using MPCs for load frequency control of microgrid. IEEE Systems Journal, 10(1), 97-105, 10.1109/JSYST.2014.2313810.
- Poureh, A., Chamani, M., & Bahri, A. (2023). “Nonlinear analysis of gain scheduled controllers for the NREL 5-MW turbine blade pitch control system.” International Journal of Electrical Power & Energy Systems, 145, 108578.
- Saihi, L., Bakou, Y., Ferroudji, F., Berbaoui, B., & Djilali, L. (2019). MPPTF & pitch fuzzy controller of a wind turbine system using DFIG. In 2019 1st International Conference on Sustainable Renewable Energy Systems and Applications (ICSRESA) (pp. 1-6). IEEE.
- Shen, H., Ruiz, A., & Li, N. (2023). Fast online reinforcement learning control of small lift-driven vertical axis wind turbines with an active programmable four bar linkage mechanism. Energy, 262, 125350.
- Yuan, Y., Chen, X., & Tang, J. (2020). Multivariable robust blade pitch control design to reject periodic loads on wind turbines. Renewable Energy, 146, 329-341.