Maheswari Muthusamy,A.K. Parvathy,



Doubly Fed Induction Generator,LVRT,ANFIS,Computational Intelligence,


Wind energy is increasingly used as renewable energy worldwide. According to grid codes, wind turbines (WT) should essentially be coupled to grid throughout as well as following fault and source reactive power toward the grid with an objective of maintaining grid voltage. Doubly fed induction generator (DFIG), a wind turbine type enabling speed adjustment, is getting established currently in wind industry. Many DFIGs employ crowbar-based system to shelter the converter at the rotor side during disturbed and/or distorted grid voltage circumstances. Although it helps in protecting the generator, it does not warrant an appropriate grid support. This shortcoming led to designing anew coordinated controller that excludes or even cancels the need of a crowbar. This paper proposes fault confrontation controller (FCC) design to augment the feature -of low voltage ride through (LVRT) in this turbine. Considering the system’s nonlinear nature, an attractive FCC was constructed using computational intelligence (CI) techniques, namely fuzzy logic, back propagation network (BPN) and adaptive neuron fuzzy inference system (ANFIS).The simulation study demonstrates that the ANFIS system gives the best results for the proposed system.


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