This paper proposes a brand-new adaptive phasor measurement unit (PMU) based protection scheme for both transposed and untransposed parallel transmission lines. The development of the scheme is based on the distributed line model and the synchronized phasor measurements at both ends of lines. By means of eigenvalue/eigenvector theory to decouple the mutual coupling effects between parallel lines, the fault detection and location indices are derived. The two proposed indices are used in coordination such that the internal and external fault events can be distinguished completely. By on-line estimation of the line parameters under the actual power system conditions, the proposed scheme will respond more accurately to power system faults. Extensive simulation results using EMTP have verified that the accuracy of the fault location achieved is up to 99.9%. The proposed protection system responds well and fast with regard to dependability and security. All the results show that the performance of the proposed detection/location indices is independent of fault types, locations, resistance, source impedance, fault inception angles, and load flows.

A New Adaptive PMU-Based Protection Scheme for Transposed/Untransposed Parallel Transmission Lines

A new fault detection/location technique with consideration of arcing fault discrimination based on phasor measurement units for extremely high voltage/ultra-high voltage transmission lines is presented in this two-paper set. Part I of this two-paper set is mainly aimed at theory and algorithm derivation. The proposed fault detection technique for both arcing and permanent faults is achieved by a combination of a fault detection index |M| and a fault location index |D|, which are obtained by processing synchronized fundamental phasors. One is to detect the occurrence of a fault and the other is to distinguish between in-zone and out-of-zone faults. Furthermore, for discriminating between arcing and permanent faults, the proposed technique estimates the amplitude of arc voltage by least error squares method through the measured synchronized harmonic phasors caused by the nonlinear arc behavior. Then, the discrimination will be achieved by comparing the estimated amplitude of arc voltage to a given threshold value. In addition, in order to eliminate the error caused by exponentially decaying dc offset on the computations of fundamental and harmonic phasors, an extended discrete Fourier transform algorithm is also presented.

A new PMU-based fault detection/location technique for transmission lines with consideration of arcing fault discrimination-part I: theory and algorithms

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Support vector machine based fault classification and location of a long transmission line

This paper presents a new approach to distance relaying using fuzzy neural network (FNM). The FNN can be viewed either as a fuzzy system, a neural network or fuzzy neural network. The structure is seen as a neural network for training and a fuzzy viewpoint is utilized to gain insight into the system and to simplify the model. The number of rules is determined by the data itself and therefore a smaller number of rules is produced. The network is trained with the backpropagation algorithm. A pruning strategy is applied to eliminate the redundant rules and fuzzification neurons, consequently a compact structure is achieved. The classification and location tasks are accomplished by using different FNN's. Once the fault type is identified by the FNN classifier the selected fault locating FNN estimates the location of the fault accurately. Normalized peaks of fundamental voltage and current waveforms are considered as inputs to all the networks and an additional input derived from the DC component is fed to fault locating networks. The peaks and DC component are extracted from sampled signals by the EKF. Test results show that the new approach provides robust and accurate classification/location of faults for a variety of power system operating conditions even with resistance in the fault path.

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A novel fuzzy neural network based distance relaying scheme

Application of extreme learning machine for series compensated transmission line protection

This paper presents some improvements of the differential equation algorithm for transmission line protection. The improvements are: fault classification; new filtering; and a new algorithm for three-phase faults. Simulation results indicate a nominal operation time of 5-7 ms for three-phase faults and slightly higher for other fault types.

J.T. Thorp

Papers

Some improvements in the three-phase differential equation algorithm for fast transmission line protection