Adaptive fault diagnosis of large interconnected power networks using genetic algorithms

One of the most important requirements of a power network is to provide reliable supply of power. Power system components such as buses, lines and transformers which are distributed geographically over a wide area are prone to faults because of environmental conditions. overvoltages and insulation failure. Modern power networks are becoming larger in size owing to the interconnection with neighbouring power systems. The satisfactory operation of such large interconnected power networks requires a fast and accurate fault diag-nosis in the network. The breakthrough in information processing technology has led to the development of newer tools that are capable of solving complex problems. This paper reviews various techniques that have been tried on the fault diagnosis of electrical power systems and proposes a new method based on Genetic algorithms for adaptive fault diagnosis of large interconnected power systems