Comparison between evolutionary programming and a genetic algorithm for fault-section estimation

The paper proposes an application of evolutionary programming (EP) to fault-section estimation in power systems. Several techniques have been employed to solve this problem so far. A genetic algorithm (GA) has been reported to be one of these techniques. In order to measure the efficiency of EP and make comparisons, a GA has also been used to solve the same problem. Different parameters which affect the EP convergence have been investigated. Two object-oriented software codes have been developed to implement the algorithms. A sample power system is used to examine the algorithms. It shows that EP is superior to the GA for the type of coding strategy and evolution as defined for the GA.