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• Novel fault classification algorithm (FCA) for GUPFC-compensated transmission lines. • FCA is based on the loci of active and reactive powers calculated using PMU signals. • Presenting faulty area and faulty circuit detection algorithms using new indices. • The proposed method is robust and independent of the operating modes of the GUPFC. • Easily applicable in regular fault locators available in the protection industry. The paper presents a fault area detection and classification algorithm in the phasor domain for double-circuit lines compensated by a generalized unified power flow controller (GUPFC). In the first step, by defining and using a voltage index, the algorithm determines the side of the GUPFC in which the fault has occurred. In the second step, by defining and employing a current index, the algorithm will be able to identify the circuit of the line on which the fault has happened. Finally, the fault is classified. In this step, the algorithm detects the faulty phase by analyzing the loci of three-phase active and reactive powers at the line terminal. The algorithm uses the current and voltage phasors of the line terminals measured by the phasor measurement units (PMUs) in one cycle before and during the fault. The GUPFC and the test system have been modeled in MATLAB/Simulink. The presented algorithm is tested and evaluated under different conditions including different fault types and fault resistances for all normal series and shunt fault types. The results obtained from simulations verify the accurate performance of the algorithm for various fault conditions. [ABSTRACT FROM AUTHOR]

• This paper presents a new method to discriminate internal fault from other cinditions. • Important features are extracted using the Clark's transform and modified hyperbolic S-transform. • The proposed method shows desirable performance in the events accompanied by current transformer. • The proposed method is not affected by the noise. In this paper, a new method is proposed for discriminating internal faults from other abnormal conditions in power transformers such as inrush currents, external faults, over-excitation, and ultra-saturation. Since the differential current signals are non-stationary, a powerful tool such as S-transform is needed for their time-frequency analysis. In this study, some important characteristics are extracted using the Clark's transform and modified hyperbolic S-transform according to which different conditions are distinguished and classified. These features include energy contour of first level, variance index, standard deviation of second harmonic component, and a special criterion. In this paper, all possible transient conditions and the effects of the saturation of current transformers are considered. Various simulations for different operating conditions of transformer are performed via PSCAD/EMTDC software. Also, the entire process of modified hyperbolic S-transform and the proposed algorithm are done in MATLAB software. Simulation results show that the proposed algorithm can be reliably used for the identification and classification of different faults in transformers. [ABSTRACT FROM AUTHOR]