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This paper proposes a new algorithm for the detection and classification of faults in transmission lines in the presence of distributed generation. The proposed algorithm uses wavelet transform-based detail and approximation coefficients of voltage and current signals over one cycle after fault inception at one end of the transmission line. The line impedance calculated from the ratio of the voltage and current approximation coefficients is fed to the fuzzy inference system to classify faults. The proposed algorithm has been tested successfully in a real-time digital simulator for nonlinear high impedance faults in the presence of wind farm, considering the effects of CT saturation. All types of faults with the variation of pre-fault loading condition, line parameters, line length and source impedance can be correctly classified using the proposed algorithm. [ABSTRACT FROM AUTHOR]

• High impedance fault detection in multi-feeder radial distribution system. • Detection and classification of faults and faulty line identification in presence of wind farm. • Power spectral density of current signals used to detect fault. • Wavelet covariance matrix used to calculate power spectral density. The recent progress in the area of signal processing has led to the development of intelligent schemes for fault classification and faulty phase selection in distribution system. The conventional algorithms find limitations to detect high impedance fault (HIF) and HIF remains a great concern for utilities as it can cause serious danger and accident if not detected properly. This study presents an algorithm for the detection and classification of HIF in a multi-feeder radial distribution system based on the calculation of power spectral density of faulty current signals. Discrete wavelet transform has been used to decouple the time information from the frequency information to detect and classify HIF effectively. The proposed technique has been extensively assessed under various dynamic situations including the presence of distributed generation and nonlinear load. This technique does not involve any training or learning process nor it involves any concern about data synchronization. The fault detection time is improved as it requires only half cycle of post fault current signal to detect and classify faults successfully. It is noteworthy to mention that the proposed technique considers only one end terminal current data. The comparative assessment reveals that this method can overcome the limitations of other existing techniques. [ABSTRACT FROM AUTHOR]

• Internal fault detection from phase angles of negative sequence currents. • Phasor diagram of internal fault detection. • Fault location method. 1–26 Double-circuit transmission lines are used in modern power systems to enhance the transmission capability and to improve system reliability and safety. However, the protection of double-circuit lines is a challenging task as the presence of flexible ac transmission system (FACTS) in modern power grid impairs the performance of the conventional distance protection schemes. Moreover, the high impedance faults cannot be detected by relays as they become under-reach. This paper proposes a negative sequence current based scheme for locating faults and identifying faulty circuit/ line in double circuit transmission line compensated by UPFC at one end. In the proposed scheme the current signals are collected from both ends of the line to be protected. Then the negative sequence components of the currents are calculated. The discrimination between internal and external fault is achieved from the phase angles of the negative sequence currents and the fault location is determined from the ratio of the negative sequence currents. Prior knowledge about the type of fault is not required for fault location estimation. Extensive fault simulation studies including high impedance faults have been performed. The scheme is immune to the fault inception angle and fault resistance. [ABSTRACT FROM AUTHOR]