IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 5, Issue 2 (Mar. - Apr. 2013), PP 56-63 www.iosrjournals.org www.iosrjournals.org 56 | Page Fault Diagnosis Based on Fuzzy Relations Using Protective Relays and Circuit Breakers B.Babu, G.Ashok Kumar, Md.Shiraj, B.Sudheer H.O.D/EEE, Project Co-Ordinator, Asst.Prof., Student Abstract: In order to deal with the incomplete information and uncertainties imposed on fault section diagnosis, this paper proposed a fault section diagnosis method based on fuzzy relations for power generation stations, substations and transmission lines. The proposed method utilizes information of protective relays and circuit breakers to build sagittal diagrams which represent the fuzzy relations for power stations, substations and transmission lines. It diagnoses the faulted sections correctly for complicated multiple faults as well as simple faults. The proposed scheme also examines the mal -operation of circuit breakers based on the relays information and determines the faulted section (item). The section's possibility of being faulty is given by degree of the membership of the fault section candidates. Computer simulation of a real system such High Dam power station (Hydro Plants Generation Company HPGC) in Egypt shows that employing this type of diagnosis is useful in diagnosing faults that have uncertainty. Hence, it helps the control center operation engineers to make a reasonable decision and strong practicability of fault diagnosis methods to the real power station. 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 work 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 maloperation and nonoperation 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]. In this paper, the fuzzy relations based set theory for fault diagnosis of power stations including, generation units, power transformers, autotransformers, service transformers, reactors, bus bars and lines is proposed to deal with uncertainties. It is represented by sagittal diagrams through the complete protection scheme of them. This method provides the most likely faulted section or sections as the form of degree of membership as well as the faulted sections candidates. The proposed method is tested for High Dam Power Station 11/15.75/220/500KV. Test results show that the proposed method is useful in the final decision process of fault diagnosis by reducing the faulted section candidates. II. Protection Systems A. Protection System of a Generation Unit Protection relays are hardware devices responsible for sensing different actuating quantities that indicating