Modeling and Chaos Dynamics Analysis of Doubly-Fed Induction Generator Based on Incommensurate Fractional-Order

• Published in: IEEE transactions on energy conversion Vol. 40; no. 2; pp. 911 - 927
• Main Authors: Zhang, Yuchen, Lyu, Yanling, Hou, Shiqiang, Xue, Shulei, Liu, Hang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Affine transformations; Analytical models; Bifurcation; Bifurcation theory; Chaos; chaotic dynamics; Control systems; Doubly fed induction generators; doubly-fed induction generator (DFIG); Dynamical systems; Excitation; Generators; incommensurate fractional-order (IFO); Inductance; Induction generators; Mathematical models; Nonlinear dynamical systems; Nonlinear dynamics; Oscillators; Parameters; Qualitative analysis; Rotors; the 0-1 test for chaos
• ISSN: 0885-8969; 1558-0059
• DOI: 10.1109/TEC.2024.3472771

The performance of complex doubly-fed induction generator (DFIG) systems is subject to the detrimental effects of chaotic dynamics. However, existing analyses of the chaotic states of DFIG systems ignore external excitations that can profoundly affect the operating state of the system, and integer-order models have been typically employed even though the inductance of DFIG systems has been demonstrated to have a fractional-order characteristic. The present work addresses these issues by conducting nonlinear dynamics analyses of an incommensurate fractional-order DFIG system according to different system operating parameters and model orders under external excitation conditions. Firstly, a fractional-order DFIG model is established with realistic parameters, and is transformed into a structure that greatly facilitates an analysis of its nonlinear dynamics by applying time-scale and affine transformations. The results of qualitative and quantitative analyses yield detailed descriptions of the nonlinear dynamics of the system under the action of multi-parameter coupling. Accordingly, the obtained analyses provide a theoretical basis and support for the design, operation, and control of DFIGs.