CONTROL OF DOUBLY FED INDUCTION GENERATOR USING ARTIFICIAL NEURAL NETWORK CONTROLLER
DOI:
https://doi.org/10.59277/RRST-EE.2023.68.1.8Keywords:
Variable speed wind turbine, Doubly fed induction generator, Field oriented control, Conventional direct power control, Total harmonic distortion, Maximum power point tracking, Artificial neural networkAbstract
In this paper, we propose a direct power control (DPC) based on an artificial neural network (ANN-DPC) for the doubly-fed induction generator (DFIG), which is applied to the wind turbine system. The main objective of this intelligent technique is to replace the switching table and the hysteresis comparators with a neural control to reduce the ripple to the level of current and power. Field-oriented control (FOC) is traditionally achieved using a conventional proportional-integral controller (PI). The power ripples are reduced, and a reasonable total harmonic distortion rate is ensured by using an ANN-DPC.
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