Fault Detection and Classification in Transmission Line Based on Wavelets
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Fault Detection and Classification in Transmission Line Based on WaveletsBased on Summation of Sixth Level detail CoefficientsBased on Wavelet Singular Entropy (WSE)ABSTRACT                       The major items of equipment in a power system are generators, transformers and transmission lines. Transmission lines transfer bulk amount of power. The transmission losses as well as power transfer capacity depends on voltage level of transmission lines. Transmission lines are exposed to atmosphere, the faults due to transmission lines are about 50% as compared to different types of faults that occur in the power system. In most power system relaying algorithms, the first step always involves fault detection which is followed by fault classification. This thesis presents an improved algorithm for fault detection and classification on transmission line using sixth level detail coefficients of fault current signals and voltage signals. The results from different case studies demonstrate that this algorithm effectively overcomes the difficulties associated with conventional voltage and current based measurements that occur due to factors such as fault inception angle, fault impedance and fault distance.                    A novel technique for fault detection and classification in the transmission line using the fault transients is proposed. 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.. 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.INTRODUCTION                            Fault detection and classification are two of the most important tasks involved in transmission-line relaying. They must be accomplished and as fast and accurate as possible to deenergize the system from the harmful faults and restore the system after faults. The performance of a power system is affected by faults on transmission lines, which results in interruption of power flow. Quick detection of faults and accurate estimation of fault location, help in faster maintenance and restoration of supply resulting in improved economy and reliability of power supply. Wavelet Transform (WT) is an effective tool in analyzing transient voltage and current signals associated with faults both in frequency and time domain. Faults upon overhead transmission lines are usually characterized by transients soon after the fault inception (fault induced transients) as a consequence of travelling waves. The analysis of these fault-induced transients can provide extensive information about the fault type, detection, location, direction, and sustained time in satisfactory agreement with real application in high-speed protective relays.

Fault-induced transients are non-stationary in both time and frequency domains. In this way, voltages and currents with fault-induced transients can be properly analyzed by using the DWT. This transformation is a well-known powerful tool to detect transients in power system disturbances, such as fault-induced transients in three-phase overhead transmission lines. Much research has been focused on wavelet-based techniques applied on analyzing power system transients, detecting and classifying faults, and estimating the fault location. According to, the effectiveness of the wavelet analysis is largely influenced by the choice of the mother wavelet. The choice of the appropriate mother wavelet depends on the nature of the signal and on the type of information to be extracted from the signal. Three different mother wavelets: haar, Daubechies, and Symlet families in order to select the most suitable wavelet applied for fault detection and classification by using the analysis of voltages and currents with fault-induced transients. In this thesis Wavelet multi resolution analysis is found to be most suitable for extracting the information from transient fault signals. Second and third order harmonics are dominant in the fault signals and are hence chosen for the analysis (d6 coefficients) and Db4 as mother wavelet. Using wavelet MRA technique, the summation of detail coefficients for sixth level are extracted from the current signal. From the magnitude of detail coefficient summations, the presence of fault in a particular phase is detected. A generalized algorithm based on wavelets has been verified for the classification of transmission line faults. The most important of this algorithm is independent of fault location, impedance and inception angle.TRANSMISSION LINE FAULT DETECTION AND CLASSIFICATION                                                                               A Fault in electrical equipment is defined as a defect in the electrical circuit due to which current is deviated from the intended path. The nature of fault simply implies any abnormal condition which causes a reduction in the basic insulation strength between phase conductors. Actually the reduction of insulation strength is not considered as a fault until it creates some effect on the system. The probability of the failure or occurrence of abnormal conditions is more on transmission lines-about one half of the faults occur on the power lines. This can be explained by the fact that the transmission lines are widely branched, have greater length, operate under variable weather conditions and are subject to the action of atmospheric disturbances of electrical nature.                        Frequency of Fault Occurrence in a Power System                   Equipment          Percentage of Total              Overhead Lines                     50                  Cables                     10              Transformers                     10               Switchgear                     15               Control equipment                      3              Instrument Transformers                       2                       Miscellaneous                     10The most common and dangerous fault, that occur in a Power system is the short circuit or shunt fault. They occur as a result of breakdowns in the insulation of current carrying phase conductors relative to earth or in the insulation between phases. Various kinds of short circuits in Overhead transmission lines and the frequency of occurrence is shown in the below Table.

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Fault Detection And Transmission Line. (July 16, 2021). Retrieved from https://www.freeessays.education/fault-detection-and-transmission-line-essay/