Journal for Research| Volume 02| Issue 03 | May 2016 ISSN: 2395-7549
Fuzzy Logic Approach for Fault Diagnosis of Three Phase Transmission Line (March 2016) Farhin R. Sheikh M.E Student Department of Electrical Engineering MGITER Navsari
Dr. Ami T. Patel Head of Department Department of Electrical Engineering MGITER Navsari
Abstract Transmission line among the other electrical power system component suffers from unexpected failure due to various random causes. Because transmission line is quite large as it is open in environment. A fault occurs on transmission line when two or more conductors come in contact with each other or ground. This paper presents a proposed model based on MATLAB software to detect the fault on transmission line. Fault detection has been achieved by using Fuzzy Logic based intelligent control technique. The proposed method aims in presenting a fast and accurate fault diagnosis method to classify and identify the type of fault which occurs on a power transmission system. In this paper, some of the unconventional approaches for condition monitoring of power systems comprising of relay Breaker, along with the application of soft computing technique like fuzzy logic. Results show that the proposed methodology is efficient in identifying fault in transmission system. Keywords: Transmission Line Faults, Fuzzy Logic, Transmission Lines Protection _______________________________________________________________________________________________________ I.
INTRODUCTION
The objective of the faulted section diagnosis method is to identify faulted components in the power station e.g. generation units, power transformers, autotransformers, service transformers, buses and lines that based on the status of protective relays and circuit breakers. To reduce the outage time and ensure stable and reliable supply for electric power for customers, it is essential for control centers to quickly identify the faulted section in power system prior to start restoring actions. Therefore, the operators must have the capability to estimate and restore the faulted section in an optimal procedure. An effective diagnosis system is required to suggest the possible way to remove faults and assist the operator to protect the systems. Recently, the possibility of implementing the heuristic rules using expert systems has motivated extensive works on the application of expert systems in fault diagnosis. Considerable efforts have been made toward developing fault diagnosis system. Most of these efforts are based on Expert Systems (ES) [1 – 3]. Although ES based approach offers powerful solutions to the fault diagnosis, but it has shortcomings, e.g. the procedure of knowledge acquisition and knowledge base revision or maintenance is quite burdensome. In addition, dealing with the large amount of data is difficult due to the conventional knowledge representation and inference mechanisms. During the last two decades, much research work has been done for estimating the fault section diagnosis in a power system by using several artificial intelligence approaches. Such as, artificial neural networks [4, 5], genetic algorithm (GA) [6], fuzzy Petri nets [7,8], family eugenics based evolution theory [9] and immune algorithm [10]. However, the only wor k addressing the power plant control and fault diagnosis [11] that aimed to control and supervision the plant system control of the station but not related to the protection system of all station through generation units, transformers, buses and lines. Since there are some wrong and missed signals in a power system, which may be caused by data transmission error or loss, in addition to mal operation and no operation of circuit breakers or relays, uncertainty reasoning is highly recommended to diagnose the system's faulted section. Among the existing uncertainty reasoning approaches, the fuzzy relations approach is accurate, which applied on the power system that include the transmission lines and bus bars [12]. There are 11 possible fault types resulting from the different combinations of three phases and the ground. The fault resistance range from a few ohms, as occur in cases of arc between phases, to hundreds of ohms, as occur in cases when a fallen conductor touches a dry surface. The fault resistance has considerable effect on the accuracy of fault location algorithms. Over current relays and fuses are responsible for isolating permanent faults, leading to customer outages. Transmission protection systems are designed to identify the location of faults and isolate only the faulted section. The key challenge to the transmission line protection lies in reliably detecting and isolating faults compromising the security of the system. The appropriate percentage of occurrence of various types of faults is given below: 1) Single line to ground fault – 70-80% 2) Line-to-Line to ground fault – 10 -17% 3) Line-to- Line fault – 8-10% 4) Three phase fault - 3 %
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