1 Abstract— In this paper, a fuzzy logic-based faults classification scheme is proposed to identify all the ten types of shunt faults for a three phase transmission line. The technique is developed on the basis of extensive simulation studies carried out on the transmission line using MATLAB toolbox. It requires to be measured the three phase post fault currents at one end (at relaying point) in r.m.s. at fundamental frequency (50/60Hz). In order to reduce the harmonic contents and D.C.components, discrete fourier transform (DFT) for one cycle at fundamental frequency is included. To illustrate performance of the proposed technique, it is applied to a large number of test cases, which is generated for different type of faults. The output of the technique shows the high degree of acceptance for a wide variation of the system’s fault operating conditions. The technique identifies faults created at different load angles, very high resistance involved and at various fault inception time as well. It is valid for any change in fault inception time. Hence the method is reliable and robust. Index Terms—Fault classification, post fault currents, DFT, Fuzzy logic and Transmission line. I. INTRODUCTION Distance protection is one of the most common methods used to protect transmission lines. The main target of the technique is to calculate impedance at the fundamental frequency between the relay and the fault point. According to the calculated impedance, the fault is identified as internal or external to the protection zone. This impedance is calculated from the measured voltage and current signals at the relay location. In addition to the fundamental frequency, the signals usually contain some harmonics and dc component, which affect the accuracy of the phasor estimation. Recently, distance relays have experienced much improvement due to the adoption of digital relaying. Various intelligent techniques like artificial-neural-network (ANN) - based approach, expert system-based approach, fuzzy logic and fuzzy neural- network-based approach as in [2]-[5] and wavelet based technique in [6] have been reported in the literature. The neural-network-based approaches have been quite successful in identifying the type of fault but it requires a considerable amount of training effort for good performance, especially under a wide variation of operating conditions (such as system loading level, fault resistance, fault inception instance, etc.) Wavelet based technique to identify the fault is computationally complex [9]. Similarly, the expert system-based techniques too, are quite time consuming as these depends largely on the domain knowledge of the experts. However, a simple fuzzy logic-based approach for the fault classification proved quite fast and accurate. But only the nature of the fault (whether LG or LLG), along with the credibility factor is identified, whereas the phases involved in the fault have not been explicitly determined as in [2]. Thus, this method tries to determine only the asymmetrical faults involving ground. Also, no LL fault has been considered in this work. To improve upon this, a fuzzy– neural approach has been suggested in [3]. In this method, only the nature of the fault is determined. Thus, this method can be considered as an improved version of [2]. However, this method also requires extensive training of the ANN. Thompson Adu also proposed in [7], a fault classification technique suitable for a fault recorder which can identify all ten types of shunt faults but time taken to classify the fault is not discussed. In this paper, a fuzzy logic based technique is proposed to identify the type of faults for digital distance protection. The proposed work here can be considered as an improvement over the existing fuzzy-logic based method as proposed in [9], in the sense that both are fuzzy logic based schemes and require the consideration of the post fault currents at one end (at relay location).The proposed technique in [9] is applicable for a variation in the fault operating conditions for resistance up to 200 Ohm, fault distance up to 100% and load angle being up to 30 degree but variation in fault inception time is not discussed. Whereas the present work is valid for the variation in fault resistance as high as up to 1000 Ohm, variation in load angle from 0 to 50 and up to -30 degree, variation in fault distance up to full length and for any variation in fault inception times are acceptable. Moreover, it has already been explained in [2] that it is very difficult to determine the fault types by the traditional (i.e., deterministic) techniques. Hence, because of its capability of determining accurately all the ten types of shunt faults easily, the proposed method can also be Fault Classification of Three Phase Transmission Line using Fuzzy Logic Majid Jamil, Md.Abul Kalam and A.Q.Ansari Department of Electrical Engineering, Jamia Millia Islamia, New Delhi-110025, India majidjamil@hotmail.com,kalam.a@rediffmail.com and aqansari@ieee.org