Fazlollahi, Vahid, Taghizadeh, Mostafa, Ayatollah zade Shirazi, Farzad. (1398). Modeling and Neuro-fuzzy Controller Design of a Wind Turbine in Full-load Region Based on Operational Data. نشریه مهندسی عمران امیرکبیر, 51(2), 139-152. doi: 10.22060/miscj.2019.15315.5130
Vahid Fazlollahi; Mostafa Taghizadeh; Farzad Ayatollah zade Shirazi. "Modeling and Neuro-fuzzy Controller Design of a Wind Turbine in Full-load Region Based on Operational Data". نشریه مهندسی عمران امیرکبیر, 51, 2, 1398, 139-152. doi: 10.22060/miscj.2019.15315.5130
Fazlollahi, Vahid, Taghizadeh, Mostafa, Ayatollah zade Shirazi, Farzad. (1398). 'Modeling and Neuro-fuzzy Controller Design of a Wind Turbine in Full-load Region Based on Operational Data', نشریه مهندسی عمران امیرکبیر, 51(2), pp. 139-152. doi: 10.22060/miscj.2019.15315.5130
Fazlollahi, Vahid, Taghizadeh, Mostafa, Ayatollah zade Shirazi, Farzad. Modeling and Neuro-fuzzy Controller Design of a Wind Turbine in Full-load Region Based on Operational Data. نشریه مهندسی عمران امیرکبیر, 1398; 51(2): 139-152. doi: 10.22060/miscj.2019.15315.5130

Modeling and Neuro-fuzzy Controller Design of a Wind Turbine in Full-load Region Based on Operational Data

AUT Journal of Modeling and Simulation
مقاله 7، دوره 51، شماره 2، اسفند 2019، صفحه 139-152    اصل مقاله (1.72 M)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22060/miscj.2019.15315.5130
نویسندگان
Vahid Fazlollahi1؛ Mostafa Taghizadeh* 2؛ Farzad Ayatollah zade Shirazi3
1PhD Student in Shahid Beheshti University
2Department of Mechanical and Energy engineering, Shahid Beheshti University
3Department of Mechanical engineering, University of Tehran
چکیده
In this paper, dynamic modeling of a Vestas 660 kW wind turbine and its validation are performed based on operational data extracted from Eoun-Ebn-Ali wind farm in Tabriz, Iran. The operational data show that the turbine under study, with a classical PI controller, encounters high fluctuations when controlling the output power at its rated value. The turbine modeling is performed by deriving the non-linear dynamic equations of different subsystems. Then, the model parameters are identified such that the model response matches the actual response. In order to validate the proposed model, inputs to the actual wind turbine (wind speed, pitch angle and generator torque) are fed to the model in MATLAB as well as FAST tool, and the output powers are compared. In order to improve the control performance and alleviate fluctuations in the full-load region, considering the nonlinear and complex behavior of the system, a neuro-fuzzy controller is designed and simulated to control the pitch angle. In this controller, neural network is used to adjust the membership functions of the fuzzy controller. Simulation results of the designed neuro-fuzzy controller indicate the improved performance of the closed-loop system compared to the actual and simulated results from the classical PI controller.
کلیدواژه‌ها
Wind Turbine؛ FAST؛ Neuro Fuzzy Controller؛ Power Control
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