Modeling, control and fault diagnosis of an isolated wind energy conversion system with a self-excited induction generator subject to electrical faults

• Published in: Energy conversion and management Vol. 82; pp. 11 - 26
• Main Authors: Attoui, Issam, Omeiri, Amar
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.06.2014; Elsevier
• Subjects: algorithms; Applied sciences; Computer simulation; Diagnostic systems; diagnostic techniques; Energy; energy conversion; Exact sciences and technology; Fault detection and diagnosis; Fault diagnosis; Faults; Fractional-Order Controllers; generators (equipment); Induction generators; iron; linear models; Natural energy; Rotors; SEIG; spectral analysis; Stators; Wind energy; Wind energy conversion systems; wind power; Wind turbines; Fractional-Order Controllers; Fault detection and diagnosis; SEIG; Wind energy conversion systems; Wind energy; Energetic system; Induction generators; Energy conversion; Modeling
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2014.02.068

•A new model of the SEIG is developed to simulate both the rotor and stator faults.•This model takes iron loss, main flux and cross flux saturation into account.•A new control strategy based on Fractional-Order Controller (FOC) is proposed.•The control strategy is developed for the control of the wind turbine speed.•An on-line diagnostic procedure based on the stator currents analysis is presented. In this paper, a contribution to modeling and fault diagnosis of rotor and stator faults of a Self-Excited Induction Generator (SEIG) in an Isolated Wind Energy Conversion System (IWECS) is proposed. In order to control the speed of the wind turbine, while basing on the linear model of wind turbine system about a specified operating point, a new Fractional-Order Controller (FOC) with a simple and practical design method is proposed. The FOC ensures the stability of the nonlinear system in both healthy and faulty conditions. Furthermore, in order to detect the stator and rotor faults in the squirrel-cage self-excited induction generator, an on-line fault diagnostic technique based on the spectral analysis of stator currents of the squirrel-cage SEIG by a Fast Fourier Transform (FFT) algorithm is used. Additionally, a generalized model of the squirrel-cage SEIG is developed to simulate both the rotor and stator faults taking iron loss, main flux and cross flux saturation into account. The efficiencies of generalized model, control strategy and diagnostic procedure are illustrated with simulation results.