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Air-gap eccentricity fault causes rotor–stator rub and consequently damage to Synchronous Generators (SGs). In this paper, a fault diagnosis approach to diagnose the eccentricity fault for SGs is presented. In this approach, the state matrix eigenvalues based on the subspace identification are estimated, and those are used for fault diagnosis. Two dq models of SGs in faulty and healthy conditions are employed to present the theoretical foundation of the method. As the main advantage, the introduced fault diagnosis method is working properly for either linear or nonlinear loads of SGs. The stator and field currents and voltages, and rotor rotational speed are required signals in the introduced approach. The method is validated using experimental data of SGs in Iran-Safir (ER24) diesel–electric locomotives. [Display omitted] • Air-gap eccentricity fault diagnosis in synchronous generators. • Fault diagnosis using the estimated eigenvalues of the state-space model of the synchronous generators based on the subspace identification. • The introduced fault diagnosis method works properly for linear and nonlinear loads. • The introduced fault diagnosis has been validated using experimental data of synchronous generators in Iran-Safir (ER24) diesel–electric locomotives. [ABSTRACT FROM AUTHOR]

This paper addresses an integrated and developed approach to the design of an Axial Flux Permanent Magnet Wind Generator (AFPMWG). The proposed analytical method of design employs the size equations and precise inductance calculations simultaneously, as well as considering the mechanical constraints of the back-iron disc of the rotor. An Elitist Genetic Algorithm (EGA), such as a high capability optimization method, has been used to solve the equations and design of a wind generator with predefined rating power. The objectives of the coreless AFPMWG design process are minimizing the magnet consumption, maximizing machine efficiency, and achieving maximum sinusoidal induction voltage, considering the wind properties of the geographical area of utilization. The optimal calculation of the permanent magnet thickness is also taken into consideration in this work. The flux density distribution in all parts of the machine has been investigated for the magnetic saturation phenomenon. In this regard, special attention is paid to rotor back discs, which are made from nonlinear material with an optimum thickness. The inductance of the leakage flux of the coreless machine has been considered by parallel computation via the Finite Element Method (FEM) and analytical equations. Finally, three-dimensional and two-dimensional finite element analyses are used to validate the performance of the machine design according to the characteristics of Iran wind resources. The results show the high ability of the proposed approach in AFPMWG design and in considering the objectives and constraints carefully. [ABSTRACT FROM AUTHOR]

• A new algorithm for out-of-step detection and prediction. • Based on the trend of the generator acceleration power and speed deviation. • Based on the general concept of the stability, local data, and online applications. • Tested on IEEE 39 bus New England and Iran electrical power network systems. In this paper, by using generator acceleration power and rotor speed deviation, a new algorithm for out-of-step prediction is proposed. In this online method, the trajectory of acceleration power according to rotor speed deviation is drawn in a Cartesian coordinate system. After fault clearance, the trend of this curve will be predicted using the ellipse function curve fitting. The concept of the proposed algorithm and its validity are presented too. Simplicity, real-time prediction, and fast calculation are some of the proposed method's advantages. The performance of this algorithm is examined in IEEE 39-bus New England and Iran electrical power network systems. The results show the proposed approach represents a valuable alternative for out-of-step protection with fast and effective performance. The simulations are carried out using the Power Factory® software, and the proposed algorithm has been developed in MATLAB. [ABSTRACT FROM AUTHOR]