The biggest challenge in the continuity of electrical power system supply is the occurrence of faults. These faults are inevitable, but when a power system has a well coordinated protection system, it must be able to detect and isolate faults very fast to avoid damage and power outage. The faults must be cleared very quickly so as to restore the power to the isolated areas. These faults are cleared with devices which sense the fault and immediately respond and disconnect the faulty section from the good ones.
To protect the power system transmission lines, faults must be detected and isolated accurately. The control centre of a power system contains large member of alarms which receives signals from different protection schemes for different types of fault.
The operators in the control centre must work on the large amount of data obtained to know the required fault information. And due to the large number of calculations needed to be made so as to obtain this required information for the fault, it takes a longer time.
These are the challenges to the protection of electrical power system transmission line, which are to detect, classify and isolate faults as fast as possible. But we know conventionally that when a fault occurs in the power systems, the fault current and voltage will develop a transient DC component and high frequency transient component in addition to power frequency component.
This entire component will cause an increase in the magnitude of fault current and voltages with respect to fault type and location, and the system condition.
Intelligent systems have been in use for fault diagnosis in power systems for some time now. Among the intelligent system is the artificial neural network (ANN) which has been applied to several power system operations and protection. There are other non intelligent system methods that can be employed in fault diagnosis. These include thevenin theorem, bus-impedance matrix and symmetrical component methods. But, in this work, symmetrical components and ANN methods were used and compared to know the best. Both methods were applied to the Matlab toolbox simpowersystem blockset modeled New – Haven/Nkalagu/Abakaliki transmission line under faulty and normal conditions. For faulty conditions, three phases, line to line, line to ground and double line to ground faults were considered. When symmetrical component was applied, fault currents, fault impedances, sequence impedances and symmetrical components of current during the faulty conditions were obtained as detected and classified faults. Fault Isolation was not able to be achieved using symmetrical component. The application of ANN to simpowersystem blockset modeled New – Haven/Nkalagu/Abakaliki transmission line is such that, the ANN has three stages, detection, classification and isolation stages. Each stage has its own ANN network selected and uses the phase voltages and currents during normal and faulty conditions as inputs of their selected networks. The ANN was able to detect the faults, classify them and isolate the faulty zone for proper protection of the transmission line. This makes it superior to other methods mentioned above. Also, it is widely used in different areas of power systems, it is simple, achieves accurate and faster result even when applied to a large network. The capability of neural network to generalize as well as tolerate faults makes it a reliable tool to be used in handling unseen faults conditions.
1.1 Statement of problem
A fault is developed in an electrical power transmission line when the normal current flow is diverted from the intended path to another path due to a defect in the electrical circuit. This defect in the electrical circuit can be as a result of reduction in the insulation strength between the phase conductors and earthed screen surrounding the conductors. 
This insulation breakdown causes damage or creates short circuit current in the system.
Excess current (over current) and reduction in impedances between conductors or conductors and earth are the resultant effects caused by the reduction in the insulation strength.
The study of fault in power system transmission lines is a very important part of power system analysis. Faults are bound to occur on the transmission lines, since there are some inevitable or unavoidable factors which are associated with causing a negative effect on the transmission lines.
Among the entire fault that occurs in a complete power system including the transmission lines, almost one and half of the faults occur on transmission lines. 
This is because; the transmission lines are widely branched, have greater length, operate under variable weather conditions and are subject to the action of atmospheric disturbance.
In view of these problems, faults on the transmission lines must be monitored, detected and cleared to ensure steady transmission of power to users.
In this work, two methods where used to diagnose the faults on the transmission line and are compared to know the best.
1.2 Objectives of the study
The objective of this study is to implement a complete, accurate and efficient scheme for distance protection of power system transmission lines. In order to perform or achieve this goal, the task is subdivided into different neural networks for fault detection, classification and isolation (location) in different zones on the transmission lines.
Also to compare the results obtained with the method of ANN with those obtained using the method of symmetrical components.
- Significance of the study
As the day goes by, the population of the masses increases, thereby increasing the load on the electrical power system in the country.
Thus, the importance of this study is to obtain a faster, error free, less ambiguous, simpler, accurate and efficient method that can be employed with a protection scheme in the electrical power system for the quick diagnosis of fault on the transmission line.
It is also important and serves as a guide or solution to power system protection problems in the utility companies like PHCN, Researchers in various research institutions (energy institutions), Government officers, Policy makers etc.
- Scope of the study
The scope of the study is the 330/132kv power system transmission lines from New-Haven through Nkalagu to Abakaliki transmission stations.[email protected][email protected]