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A method for fault type discrimination and faulted phase identification using instantaneous local current measurements is proposed. Seven current components are obtained from the measured three-phase instantaneous currents through a transformation and band passed filtered to remove the fundamental components and high frequency content. Upon detecting a fault, nine fault discrimination indices are computed taking different ratios of the maximum rates of change of these filtered current components. The indices are used to (i) separate ground faults from the phase-to-phase and three-phase faults, (ii) discriminate phase-to-ground from phase-to-phase-to-ground faults, (iii) differentiate phase-to-phase faults from the three-phase faults, and (iv) identify the faulted phases. As the indices are ratios, decisions are less affected by the fault resistance. The algorithm was validated using a power system simulated in PSCAD/EMTDC. Extensive testing involving more than 10,000 fault scenarios showed that fault type and faulted phases can be successfully identified. The algorithm found some difficulty in identifying the phases involved in phase-to-phase-to-ground faults at certain fault inception angles, and one of the thresholds can be affected by the transposition scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the applicability of IEC 61850-9-2 LE-sampled values in transients-based protection by implementing a line protection intelligent electronic device (IED), incorporating a transients-based hybrid protection algorithm suitable for series-compensated transmission lines. The IED is capable of subscribing, decoding, and processing sampled values to be used in the implemented protection algorithms. The proposed method of protection can distinguish between internal and external faults by comparing the polarities of wavelet coefficients of the line currents at either end of the line. The power system section, which the proposed protection scheme is tested upon, is implemented in a real-time digital simulator. Attention is given to replicate the constraints faced by an actual relay in the implementations of the IED. The results indicate that IEC 61850-sampled values can be effectively used in a transients-based protection scheme that is capable of operating under challenging conditions. [ABSTRACT FROM PUBLISHER]

Part I of this paper describes the design and implementation of an islanding detection method based on transient signals. The proposed method utilizes discrete wavelet transform to extract features from transient current and voltage signals. A decision-tree classifier uses the energy content in the wavelet coefficients to distinguish islanding events from other transient generating events. The verification tests performed in Part I, for a two generator test system having a synchronous generator and a wind farm, showed more than 98% classification accuracy with 95% confidence and a response time of less than two cycles. In Part II, the proposed methodology is applied to an extended test system with a voltage-source converter-based dc source. The proposed relay's performance is compared with the existing passive islanding detection methods under different scenarios. Furthermore, the effect of noise on the performance of the proposed method is studied. The transient-based islanding detection methodology exhibits very high reliability and fast response compared to all other passive islanding detection methods and shows that the relay can be designed with a zero nondetection zone for a particular system. [ABSTRACT FROM AUTHOR]

This paper presents the development and hardware implementation of a classification scheme to distinguish the transients originated by faults from other types of transients. In the proposed scheme, a set of Hidden Markov Model-based classifiers is employed to recognize the fault transients. Input features for the classifiers are the energy contained in wavelet coefficients of the measured current waveforms. A laboratory prototype of the fault recognition system was implemented on a floating-point digital–signal-processor (DSP)-based hardware platform. The classification system was tested using the transient signals generated by a real-time waveform playback unit. The test waveforms were generated by simulating an actual extra-high-voltage transmission system on an electromagnetic transient simulation program. The operation of the classification system was further verified using waveforms obtained from an actual fault recorder. The performance of the classifier was investigated under different practical scenarios, such as current transformer saturation, measurement noise, and lightning faults. [ABSTRACT FROM PUBLISHER]

The paper first shows that the transient stability status of a power system following a large disturbance such as a fault can be early predicted based on the measured post-fault values of the generator voltages, speeds, or rotor angles. Synchronously sampled values provided by phasor measurement units (PMUs) of the generator voltages, frequencies, or rotor angles collected immediately after clearing a fault are used as inputs to a support vector machines (SVM) classifier which predicts the transient stability status. Studies with the New England 39-bus test system and the Venezuelan power network indicated that faster and more accurate predictions can be made by using the post-fault recovery voltage magnitude measurements as inputs. The accuracy and robustness of the transient stability prediction algorithm with the voltage magnitude measurements was extensively tested under both balanced and unbalanced fault conditions, as well as under different operating conditions, presence of measurement errors, voltage sensitive loads, and changes in the network topology. During the various tests carried out using the New England 39-bus test system, the proposed algorithm could always predict when the power system is approaching a transient instability with over 95% success rate. [ABSTRACT FROM PUBLISHER]