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Assareh, Ehsanolah, Poultangari, Iman, Ghanbarzadeh, Afshin. (1402). Application of combined mathematical modeling/optimization methods coupled pitch controller in wind turbine using hybrid MLP neural network and firefly algorithm. فناوری آموزش, 13(2), 241-250. doi: 10.22061/jcarme.2018.2482.1238
Ehsanolah Assareh; Iman Poultangari; Afshin Ghanbarzadeh. "Application of combined mathematical modeling/optimization methods coupled pitch controller in wind turbine using hybrid MLP neural network and firefly algorithm". فناوری آموزش, 13, 2, 1402, 241-250. doi: 10.22061/jcarme.2018.2482.1238
Assareh, Ehsanolah, Poultangari, Iman, Ghanbarzadeh, Afshin. (1402). 'Application of combined mathematical modeling/optimization methods coupled pitch controller in wind turbine using hybrid MLP neural network and firefly algorithm', فناوری آموزش, 13(2), pp. 241-250. doi: 10.22061/jcarme.2018.2482.1238
Assareh, Ehsanolah, Poultangari, Iman, Ghanbarzadeh, Afshin. Application of combined mathematical modeling/optimization methods coupled pitch controller in wind turbine using hybrid MLP neural network and firefly algorithm. فناوری آموزش, 1402; 13(2): 241-250. doi: 10.22061/jcarme.2018.2482.1238

Application of combined mathematical modeling/optimization methods coupled pitch controller in wind turbine using hybrid MLP neural network and firefly algorithm

Journal of Computational & Applied Research in Mechanical Engineering (JCARME)
مقاله 10، دوره 13، شماره 2 - شماره پیاپی 26، خرداد 2024، صفحه 241-250    اصل مقاله (861.46 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22061/jcarme.2018.2482.1238
نویسندگان
Ehsanolah Assareh* 1؛ Iman Poultangari2؛ Afshin Ghanbarzadeh3
1Department of Mechanical Engineering, Islamic Azad University Dezful Branch, Dezful, Khouzestan, Iran
2Department of Electrical Engineering, on, Islamic Azad University Dezful Branch, Dezful, Khouzestan, Iran
3Department of Mechanical Engineering, Shahid Chamran University, Ahvaz, Khouzestan, Iran
تاریخ دریافت: 30 فروردین 1396،  تاریخ بازنگری: 15 شهریور 1397،  تاریخ پذیرش: 21 شهریور 1397 
چکیده
With pitch angle control, wind turbines can retain power generated at high speeds of wind and avoid severe mechanical stress. By varying the angle of the blades of the wind turbines, they can keep the power generated up near the maximum amount. A controller based on PI is suggested due to control angle of the pitch of the wind turbine blades in the present study. Therefore, PI controller gains are tuned via hybridization of firefly evolutionary algorithm and MLP artificial neural network so that the controller at its output sends a suitable control signal to the pitch actuator and thus varies the blades pitch angle appropriately to preserve power of the generator at a nominal amount even at high wind speeds. Simulating and analyzing the results was done by employing a five MW wind turbine made by National Renewable Energy Laboratory based on FAST software code. The simulation of the method showed that its performance is good. 
کلیدواژه‌ها
Wind turbine؛ Pitch control؛ Firefly algorithm؛ MLP neural network
مراجع
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