A.T. Johns

An Alternative Approach to Adaptive Single-Pole Auto Reclosing in High-Voltage Transmission Systems Based on Variable Dead Time Control

This paper presents a new concept, based on variable dead time control, in adaptive single-pole auto reclosing (SPAR). The proposed scheme can give rise to a high rate of successful reclosing by adapting to variable dead times. The significance of this algorithm is that it uses the waveform patterns of the voltage transients following initial breaker opening. The performance of this proposed method is tested under a variety of fault locations on the Korean 765 kV system, and the outcome of the study clearly indicates that variable dead time auto-reclosing scheme can be used as an attractive and effective means of better management and operation of a high-voltage transmission system.

A practical approach to accurate fault location on extra high voltage teed feeders

The basis of an alternative approach for accurately locating faults on teed feeders is described. The technique developed uses fault voltages and currents at all three ends. The method is virtually independent of fault resistance and largely insensitive to variations in source impedance, teed and line configurations, including line untransposition. The basic theory of the technique is presented. It is extensively tested using simulated primary system voltage and current waveforms, which include the transducer/hardware errors encountered in practice. The performance clearly shows a high degree of accuracy. >

A novel fault classification technique for double-circuit lines based on a combined unsupervised/supervised neural network

Summary form only as given. The work described in this paper addresses the problems encountered by conventional techniques in fault type classification in double-circuit transmission lines; these arise principally due to the mutual coupling between the two circuits under fault conditions, and this mutual coupling is highly variable in nature. It is shown that a neural network based on a combined unsupervised/supervised training methodology provides the ability to accurately classify the fault type by identifying different patterns of the associated voltages and currents. The technique is compared with that based solely on a supervised training algorithm (i.e., bad-propagation network classifier). It is then tested under differed fault types, location resistance and inception angle; different source capacities and load angles are also considered. All the test results show that the proposed fault classifier is very well suited for classifying fault types in double-circuit lines.

Model system tests on a new numeric method of power system frequency measurement

A numerical technique for the evaluation of power system frequency has been implemented on a TMS320C31 digital signal processor. The frequency measuring equipment has been tested on programmable relay testing equipment, using known reference signals, and on a micromachine based power system simulator. The results show the frequency measuring equipment gives fast and accurate measurement under both steady-state and dynamic conditions. The response of the equipment to instantaneous changes in phase and amplitude is found to be undesirable if the algorithm is to be applied to frequency measuring protection relays.

Design and implementation of an adapative single pole autoreclosure technique for transmission lines using artificial neural networks

Adaptive single pole autoreclosure (SPAR) offers many advantages over conventional techniques. In the case of transient faults, the secondary arc extinction time can be accurately determined and in the case of a permanent fault, breaker reclosure can be avoided. This paper describes, in some detail, the design and implementation of a SPAR technique using artificial neural networks (ANNs). The design described includes special methods for extracting features from post-circuit breaker opening fault data, which is a prerequisite for setting up training data sets. The technique is then implemented in hardware based on a high performance T800 transputer system and some results obtained from laboratory tests of this equipment are presented.

An overview of the condition monitoring of overhead lines

Abstract Overhead lines are the most cost effective and frequently used carriers for electric energy. Exposure to environment accelerates deterioration; if this not detected and repaired quickly, some of it will degenerate into serious problems with time. Electrical Utilities, under pressure to reduce maintenance costs, increase line loading and increase quality of power supply, run inspection programs to locate and repair any significant failure at the earliest possible stage. However, present inspection techniques are often expensive and time consuming. Research and development into on-line condition monitoring techniques is thus timely and is as yet at an embryonic stage. This paper reviews the investigation into overhead line deterioration, briefly outlines the inspection methods available at present, and finally introduces a current project being undertaken in the Power and Energy Systems Research Group at the University of Bath in collaboration with two major utilities in the UK, into on-line condition monitoring of overhead lines.

Frequency relaying based on instantaneous frequency measurement [power systems]

A frequency relay capable of under/over frequency and rate of change of frequency measurements has been implemented on a digital signal processor using an instantaneous frequency measuring algorithm. Careful attention to the filtering aspects of the relay is needed under dynamic conditions due to frequency modulation of the input signal. An algorithm for avoiding unwanted relay operation due to impulsive changes in the input signal is presented. Results are shown for simulated tests using computer-based relay testing equipment, and for overloads on a micromachine power system simulator.

PROTECTION SCHEME FOR EHV TRANSMISSION SYSTEMS WITH THYRISTOR CONTROLLED SERIES COMPENSATION USING RADIAL BASIS FUNCTION NEURAL NETWORKS

ABSTRACT Since die complex variation of line impedance measured is controlled by thyristors and is accentuated as the capacitors own protection equipment operates randomly under fault conditions in controllable series compensated transmission systems (CSC), conventional distance protection schemes are limited to certain applications. The authors have extensively addressed the development of new protection techniques for such systems using multilayer percetrons. The basic idea of the method is to design a protection scheme using a neural network approach by catching die feature signals in a certain frequency range under fault conditions. This is different from conventional schemes that are based on deriving implicit mathematical equations based on the infoimation obtained by complex filtering techniques. This paper presents some recent results of employing radial basis function neural networks (RBFN) for this particular application. The use of RBFN is because it has a number of advantages over multilayer ...

Educational use of EMTP MODELS for the study of a distance relaying algorithm for protecting transmission lines

This paper presents the implementation of a distance relaying algorithm using EMTP MODELS, in which we have simplified the procedures of system modeling and distance relaying system by using a single structure of MODELS. The technique presented is based on integrating the modeling of the power system and the protective system in one program module. The purpose of this paper is to provide systematic relaying concepts by modeling a digital relaying system using MODELS functions within EMTP in a closed-loop manner, principally to facilitate and enhance an understanding of the basic concepts of distance relaying of final year undergraduate students/postgraduate students/young engineers who are new to the subject of power system protective relaying. Various elements of digital distance relaying are organized to generate a systematic approach to modeling the actual hardware of digital relaying systems. Case studies relating to the most commonly encountered single phase-to-ground fault and phase-to-phase fault are presented and various fault distances and fault inception angles are considered.

A novel approach to fault diagnosis in multicircuit transmission lines using fuzzy ARTmap neural networks

The work described in this paper addresses the problems of fault diagnosis in complex multicircuit transmission systems, in particular those arising due to mutual coupling between the two parallel circuits under different fault conditions; the problems are compounded by the fact that this mutual coupling is highly variable in nature. In this respect, artificial intelligence (AI) technique provides the ability to classify the faulted phase/phases by identifying different patterns of the associated voltages and currents. In this paper, a Fuzzy ARTmap (Adaptive Resonance Theory) neural network is employed and is found to be well-suited for solving the complex fault classification problem under various system and fault conditions. Emphasis is placed on introducing the background of AI techniques as applied to the specific problem, followed by a description of the methodology adopted for training the Fuzzy ARTmap neural network, which is proving to be a very useful and powerful tool for power system engineers. Furthermore, this classification technique is compared with a Neural Network (NN) technique based on the error backpropagation (EBP) training algorithm, and it is shown that the former technique is better suited for solving the fault diagnosis problem in complex multicircuit transmission systems.