Design and Implementation of Type-2 Fuzzy Logic Controller for DFIG-Based Wind Energy Systems in Distribution Networks

Handling the uncertainties in the wind speed and the grid disturbances is a major challenge to the DFIGs to fulfill the modern grid code requirements. This paper proposes the design and implementation of a novel control strategy using interval type-2 fuzzy sets for grid integration of doubly fed induction generator (DFIG) based wind turbines. The presence of third dimension in the type-2 membership function offers an additional degree of freedom in the design of the proposed controller to contribute to power oscillations damping and voltage recovery following parameter uncertainties in the network. The vector control with proposed strategy for DFIG is able to handle uncertainties in the operating conditions of the distributed network like faults, load changes, and wind speed. The performance of the controller is evaluated by connecting the wind turbine to IEEE 34-bus test system considering the various uncertainties. The real time simulations are carried out using real time digital simulator (RTDS) with hardware in loop (HIL) configuration to support the feasibility of the controller for real time applications.

[1]  Hani Hagras,et al.  Towards the Wide Spread Use of Type-2 Fuzzy Logic Systems in Real World Applications , 2012, IEEE Computational Intelligence Magazine.

[2]  N. C. Kar,et al.  Design and Implementation of Neuro-Fuzzy Vector Control for Wind-Driven Doubly-Fed Induction Generator , 2011, IEEE Transactions on Sustainable Energy.

[3]  Lingling Fan,et al.  Mitigating SSR Using DFIG-Based Wind Generation , 2012, IEEE Transactions on Sustainable Energy.

[4]  Mohand Ouhrouche Transient analysis of a grid connected wind driven induction generator using a real-time simulation platform , 2009 .

[5]  Hani Hagras,et al.  A Self-Tuning zSlices-Based General Type-2 Fuzzy PI Controller , 2015, IEEE Transactions on Fuzzy Systems.

[6]  Frede Blaabjerg,et al.  Proportional-resonant controllers and filters for grid-connected voltage-source converters , 2006 .

[7]  Vigna Kumaran Ramachandaramurthy,et al.  Fault ride through and voltage regulation for grid connected wind turbine , 2011 .

[8]  A. Abu-Siada,et al.  Improvement of LVRT capability of variable speed wind turbine generators using SMES unit , 2011, 2011 IEEE PES Innovative Smart Grid Technologies.

[9]  Jerry M. Mendel,et al.  Interval type-2 fuzzy logic systems , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).

[10]  Marian P. Kazmierkowski,et al.  Control in Power Electronics , 2013 .

[11]  Frede Blaabjerg,et al.  Control in Power Electronics: selected problems , 2002 .

[12]  Jon Clare,et al.  Doubly fed induction generator using back-to-back PWM converters and its application to variable-speed wind-energy generation , 1996 .

[13]  Kit Po Wong,et al.  A Comprehensive LVRT Control Strategy for DFIG Wind Turbines With Enhanced Reactive Power Support , 2013, IEEE Transactions on Power Systems.

[14]  Ahmed Al-Durra,et al.  Modeling and Control Strategies of Fuzzy Logic Controlled Inverter System for Grid Interconnected Variable Speed Wind Generator , 2013, IEEE Systems Journal.

[15]  Zhe Chen,et al.  Improving Fault Ride-Through Capability of Variable Speed Wind Turbines in Distribution Networks , 2013, IEEE Systems Journal.

[16]  Nicholas A. Vovos,et al.  A Genetic Algorithm-Based Low Voltage Ride-Through Control Strategy for Grid Connected Doubly Fed Induction Wind Generators , 2014, IEEE Transactions on Power Systems.

[17]  Frede Blaabjerg,et al.  Control in Power Electronics , 2002 .

[18]  Qing Liu,et al.  Investigation on the Faulty State of DFIG in a Microgrid , 2011, IEEE Transactions on Power Electronics.

[19]  A. Abu-Siada,et al.  Application of SMES Unit to Improve DFIG Power Dispatch and Dynamic Performance During Intermittent Misfire and Fire-Through Faults , 2013, IEEE Transactions on Applied Superconductivity.

[20]  Orhan Kaplan,et al.  Fuzzy PI controlled inverter for grid interactive renewable energy systems , 2015 .

[21]  Han-Xiong Li A comparative design and tuning for conventional fuzzy control , 1997, IEEE Trans. Syst. Man Cybern. Part B.

[22]  Jerry M. Mendel,et al.  Interval Type-2 Fuzzy Logic Systems Made Simple , 2006, IEEE Transactions on Fuzzy Systems.

[23]  Jerry M. Mendel,et al.  Interval type-2 fuzzy logic systems , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).

[24]  Lidong Zhang,et al.  Offshore Wind Integration to a Weak Grid by VSC-HVDC Links Using Power-Synchronization Control: A Case Study , 2014, IEEE Transactions on Power Delivery.

[25]  Frede Blaabjerg,et al.  Proportionalresonant controllers and filters for gridconnected voltagesource converters , 2006 .

[26]  Masaharu Mizumoto,et al.  Some Properties of Fuzzy Sets of Type 2 , 1976, Inf. Control..

[27]  P. Student,et al.  Application of SMES to Enhance the Dynamic Performance of DFIG during Voltage Sag and Swell , 2014 .

[28]  Jie Wu,et al.  Integral variable structure direct torque control of doubly fed induction generator , 2011 .

[29]  Anca Daniela Hansen,et al.  Fault ride-through capability of DFIG wind turbines , 2007 .

[30]  Xiao-Ping Zhang,et al.  Coordinated Design of Multiple Robust FACTS Damping Controllers: A BMI-Based Sequential Approach With Multi-Model Systems , 2015, IEEE Transactions on Power Systems.