This paper presents a novel controller inspired by the cerebellum, a key component of the brain responsible for motor coordination and cognitive actions, to enhance the performance of a doubly fed induction generator (DFIG) based wind energy conversion system. A computational model for the controller is introduced and implemented by mimicking the functionalities of various layers in the brain, such as the granule layer (input layer), molecular layer (learning layer) and Purkinje layer (output layer). For certain critical variations of a wind energy conversion system, the proportional-integral (PI) controller-based indirect vector control approach could not show the desired response as the PI controllers are best suitable for linear systems. To overcome this limitation a new intelligent controller inspired by the human brain has been implemented. A cerebellum inspired controller is used for the effective control of the rotor side converter (RSC) and grid side converter (GSC) in a DFIG. system. The efficacy of the controller is demonstrated under various critical conditions, such as wind speed changes, changes in reactive power and grid voltage variation. The simulation results demonstrate the excellent dynamic performance of the grid integrated DFIG. system when compared with that of the classical PI controller approach by reducing the static error, overshoot and response time.
A Novel Intelligent Controller Influenced by Cerebellum for Decoupled Power Flow Control of DFIG. Based Wind Energy Conversion System
2024-07-31
1905778 byte
Conference paper
Electronic Resource
English
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