Implementation of ANFIS based controller on IG wind farm for improved performance

In this paper, the transient performance of a 9-MW Induction Generator (IG) wind farm is improved by implementing an Adaptive Neuro Fuzzy Inference System (ANFIS) based controller on the turbine in MATLAB/SIMULINK environment using phasor analysis. Initially, the parameters of PI controller is developed using conventional method. Then, with the help of PI controller, the ANFIS based controller is trained. This developed controller reduces peak overshoot and settling time of active power and torque-speed characteristics in contrast to PI controller. Further, the system is linearized and the obtained results in time domain have been validated for stability by using Pole-Zero plot.

[1]  Scott D. Sudhoff,et al.  Analysis of Electric Machinery and Drive Systems , 1995 .

[2]  Vivek Pahwa,et al.  Design and Implementation of ANFIS Based Controller on Variable Speed Isolated Wind-Diesel Hybrid System for Better Performance , 2017 .

[3]  B. Blazic,et al.  STATCOM Control for Operation with Unbalanced Voltages , 2006, 2006 12th International Power Electronics and Motion Control Conference.

[4]  R. Chedid,et al.  Intelligent control of a class of wind energy conversion systems , 1999 .

[5]  Milan S. Ćalović,et al.  Neuro-fuzzy controller of low head hydropower plants using adaptive-network based fuzzy inference system , 1997 .

[6]  Mohamed I. Mosaad,et al.  Model reference adaptive control of STATCOM for grid integration of wind energy systems , 2018 .

[7]  Kwang Y. Lee,et al.  Distributed generation system control strategies with PV and fuel cell in microgrid operation , 2016 .

[8]  P. N. Paraskevopoulos,et al.  Modern Control Engineering , 2001 .

[9]  Dong Yue,et al.  Hybrid model for renewable energy and loads prediction based on data mining and variational mode decomposition , 2018 .

[10]  Jyh-Shing Roger Jang,et al.  Fuzzy Modeling Using Generalized Neural Networks and Kalman Filter Algorithm , 1991, AAAI.

[11]  G. Bortolotto,et al.  Voltage-frequency control of a self-excited induction generator , 1999 .

[12]  Lidong Zhang,et al.  Offshore wind integration to a weak grid by VSC-HVDC links using power-synchronization control: A case study , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[13]  Jeich Mar,et al.  An ANFIS controller for the car-following collision prevention system , 2001, IEEE Trans. Veh. Technol..

[14]  Nimrod Vázquez,et al.  Fuzzy Logic Control With an Improved Algorithm for Integrated LED Drivers , 2018, IEEE Transactions on Industrial Electronics.

[15]  Arsha S. Chandran,et al.  A review on active & reactive power control strategy for a standalone hybrid renewable energy system based on droop control , 2018, 2018 International Conference on Power, Signals, Control and Computation (EPSCICON).

[16]  B. Singh,et al.  Analysis and design of STATCOM-based voltage regulator for self-excited induction generators , 2004, IEEE Transactions on Energy Conversion.

[17]  J.-S.R. Jang,et al.  Input selection for ANFIS learning , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

[18]  Ming Cheng,et al.  Improvement of Operating Performance for the Wind Farm With a Novel CSC-Type Wind Turbine-SMES Hybrid System , 2012, IEEE Transactions on Power Delivery.

[19]  Narinder Kaur,et al.  Enhanced Performance of Isolated Wind-Diesel (IWD) Hybrid System feeding Heavy Load under various Operating Conditions , 2016 .