Learning and evolution are two fundamental forms of adaptation. There has been a great interest in combining learning and evolution with artificial neural networks (ANNs) in recent years. This paper: 1) reviews different combinations between ANNs and evolutionary algorithms (EAs), including using EAs to evolve ANN connection weights, architectures, learning rules, and input features; 2) discusses different search operators which have been used in various EAs; and 3) points out possible future research directions. It is shown, through a considerably large literature review, that combinations between ANNs and EAs can lead to significantly better intelligent systems than relying on ANNs or EAs alone.

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Evolving artificial neural networks

A comprehensive review on the methods used for fault detection, classification and location in transmission lines and distribution systems is presented in this study. Though the three topics are highly correlated, the authors try to discuss them separately, so that one may have a more logical and comprehensive understanding of the concepts without getting confused. Great significance is also attached to the feature extraction process, without which the majority of the methods may not be implemented properly. Fault detection techniques are discussed on the basis of feature extraction. After the overall concepts and general ideas are presented, representative works as well as new progress in the techniques are covered and discussed in detail. One may find the content of this study helpful as a detailed literature review or a practical technical guidance.

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Fault detection, classification and location for transmission lines and distribution systems: a review on the methods

This paper presents a new method for the boundary protection of series-compensated transmission lines, as well as fault classification. The boundary protection is based on detecting distinct frequency bands contained in the transient fault current wave. Discrete wavelet transform, using db4 as a mother wavelet, is used to capture two bands of frequencies in the transient current signal. The spectral energies of these two bands are obtained and used to determine if the fault is internal or external to the protected zone. Fault classification is done using the discrete wavelet transform. Using Haar as the mother wavelet, the coefficients of a frequency band in the range of 1 kHz-3 kHz are obtained for the three phase and ground currents. The average value of the coefficients of each current wave is then computed and used to classify the faulted phases. The basic principle of the protection scheme is described and its response to the series-compensated transmission lines is studied for a wide range of compensation levels, fault conditions, fault types, and fault locations. The stability of the algorithm under various load switching cases is also tested. Fault simulations are performed using power system computer-aided design/electromagnetic transient and direct current program and the results are then interfaced to MATLAB, where the algorithm is implemented. It is found that the proposed method gives reliable results in the boundary protection and fault classification of series-compensated lines.

Usage of wavelet transform in the protection of series-compensated transmission lines

This paper presents a combined wavelet-support vector machine (SVM) technique for fault zone identification in a series compensated transmission line. The proposed method uses the samples of three line currents for one cycle duration to accomplish this task. Initially, the features of the line currents are extracted by first level decomposition of the current samples using discrete wavelet transform (DWT). Subsequently, the extracted features are applied as inputs to a SVM for determining the fault zone (whether the fault is before or after the series capacitor, as observed from the relay point). The feasibility of the proposed algorithm has been tested on a 300-km, 400-kV series compensated transmission line for all the ten types of faults through detailed digital simulation using PSCAD/EMTDC. Upon testing on more than 25000 fault cases with varying fault resistance, fault inception angle, prefault power transfer level, percentage compensation level, and source impedances, the performance of the developed method has been found to be quite promising.

Combined Wavelet-SVM Technique for Fault Zone Detection in a Series Compensated Transmission Line

A novel technique for fault detection and classification in the extremely high-voltage transmission line using the fault transients is proposed in this paper. The novel technique, called wavelet singular entropy (WSE), incorporates the advantages of the wavelet transform, singular value decomposition, and Shannon entropy. WSE is capable of being immune to the noise in the fault transient and not being affected by the transient magnitude so it can be used to extract features automatically from fault transients and express the fault features intuitively and quantitatively even in the case of high-noise and low-magnitude fault transients. The WSE-based fault detection is performed in this paper, which proves the availability and superiority of WSE technique in fault detection. A novel algorithm based on WSE is put forward for fault classification and it is verified to be effective and reliable under various fault conditions, such as fault type, fault inception time, fault resistance, and fault location. Therefore, the proposed WSE-based fault detection and classification is feasible and has great potential in practical applications.

Fault Detection and Classification in EHV Transmission Line Based on Wavelet Singular Entropy

The paper describes the signal processing techniques developed for a new protection technique for EHV transmission lines. The signal processing unit, which forms a major part of the protection scheme, utilises fault-generated high-frequency signals derived from the signal measurement circuit to determine whether the fault is internal or external to the protected zone. The protection scheme has been designed using computer-aided techniques which closely emulate the hardware currently under development and which is being implemented using present-generation hardware.

Non-unit protection technique for EHV transmission systems based on fault-generated noise. Part 1: signal measurement

Single-pole autoreclosure is quite extensively used in long-line applications and involves tripping only the faulted phase for single-phase earth faults. Reliable and fast phase selection is thus imperative in order to avoid potential problems of system insecurity and instability. Conventional phase selectors, primarily based on power frequency measurands, can suffer some impairment in performance because of their heavy dependency on varying system and fault conditions. However, the advent of artificial neural networks (ANNs), with their ability to map complex and highly nonlinear input/output patterns, provides an attractive potential solution to the long-standing problems of accurate and fast phase selection. This paper describes the design of a novel phase selector using ANNs. The technique is based on utilising fault generated high frequency noise (captured through the high voltage coupling capacitor of a conventional capacitor voltage transformer) to essentially recognise the various patterns generated within the frequency spectra of the fault generated noise signals on the three phases, for the purposes of accurately deducing the faulted phase. The paper demonstrates a new concept and methodology in phase selection which will facilitate single-pole autoreclosure applications in power systems.

A New Approach to Phase Selection Using Fault Generated High Frequency Noise and Neural Networks

The authors present a new concept: ‘adaptive optimal reclosure’ under transmission line faults by integrating the adaptive and optimal reclosure techniques. Simulation studies prove that the proposed technique is able to first detect the persistence time of fault path arc and then capture the optimal reclosure time, thereby enhancing system stability.

New concept in transmission line reclosure using high-frequency fault transients

A new high-speed protection technique based on fault generated high frequency (HF) voltage signals is developed and applied to the protection of EHV series compensated power transmission lines. It is a nonunit protection technique as it relies totally on locally derived information, but it has the discriminative properties normally associated with unit protection schemes. The protection scheme has been designed using CAD techniques including emulation of analogue interfaces and hardware. It is shown that the new relay scheme is able to overcome many difficult protection problems encountered on such EHV power lines using conventional methods, and discriminates clearly between internal and external faults, producing a fast trip output.

A novel non-unit protection for series compensated EHV transmission lines based on fault generated high frequency voltage signals

Contemporary methods for fault location on overhead lines and underground cables can be classified into two fundamental types: (i) methods based on the measurement of post-fault line impedance; and (ii) methods based on the measurement of the fault generated travelling wave component. This paper presents the application of these new techniques to fault location on transmission and distribution line/cable systems. The technique utilises the specially designed fault locators to capture the fault generated high frequency voltage or current transient signals from the faulted line/cable. The propagation time of the high frequency components is used to determine the fault position.

Z.Q. Bo

Papers

Non-unit protection technique for EHV transmission systems based on fault-generated noise. Part 1: signal measurement

A New Approach to Phase Selection Using Fault Generated High Frequency Noise and Neural Networks

New concept in transmission line reclosure using high-frequency fault transients

A novel non-unit protection for series compensated EHV transmission lines based on fault generated high frequency voltage signals

A novel fault locator based on the detection of fault generated high frequency transients