An Intelligent Parameter Identification Method of DFIG Systems Using Hybrid Particle Swarm Optimization and Reinforcement Learning

An Intelligent Parameter Identification Method of DFIG Systems Using Hybrid Particle Swarm Optimization and Reinforcement Learning

Precise modeling of power systems is vital to ensure stability, reliability, and secure operations. In power industrial settings, model parameters can become skewed over time due to prolonged device usage or modifications made to the control systems. Doubly-Fed Induction Generator (DFIG), one of the...

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Bibliographic Details
Main Authors: Xuanchen Xiang, Ruisheng Diao, Shonda Bernadin, Simon Y. Foo, Fangyuan Sun, Ayodeji S. Ogundana
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Deep reinforcement learning (DRL)
doubly-fed induction generator (DFIG)
hybrid SAC-PSO
parameter calibration
parameter identification
particle swarm optimization (PSO)
Online Access:https://ieeexplore.ieee.org/document/10474372/

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