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- W4360923468 abstract "This study offers an adaptive neuro-fuzzy controller (NFC) for a wind energy conversion system (WECS) based on a doubly fed induction generator (DFIG) that may run in standalone mode. The adaptive- network-based fuzzy inference system (ANFIS) architecture is the foundation upon which the NFC is built since it offers the singular benefit of rapid convergence while integrating the resilience of fuzzy logic and flexibility of neural network algorithm. The load side converter (LSC) control of ANFIS is intended for the independent operation of DFIG-WECS. By keeping output voltage consistent, the suggested approach shows increased dynamic performance under conditions of fluctuating wind speed and load. Due to the precise control of the LSC, the supply frequency to the load is kept consistent even while the turbine rotation changes with changing wind speed. The rotor side converter's proportional-integral (PI) control maintains the flux alignment. The simulation outcomes demonstrate the controller's exceptional performance through its effective management of supply frequency and load-voltage under variations in wind speed and demand load power." @default.
- W4360923468 created "2023-03-26" @default.
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- W4360923468 date "2022-09-25" @default.
- W4360923468 modified "2023-09-28" @default.
- W4360923468 title "DEVELOPMENT OF INTELLIGENT CONTROLLER FOR POWER RIPPLE MITIGATION OF DFIG BASED WIND ENERGY SYSTEM" @default.
- W4360923468 doi "https://doi.org/10.30780/ijtrs.v07.i09.002" @default.
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