抄録
Switching surges are of primary importance in insulation co-ordination of EHV and UHV networks, as well as in designing insulation of apparatuses. The magnitude and shape of the switching overvoltages vary with the system parameters, network configuration and the point-on-wave where the switching operation takes place. Although some studeis were carried out for design of the networks, but power systems are gradually developed and their configuration is changed. It is important for the utilities to ensure that the peak overvoltage and global risk of the network resulting from the switching operations are well within safe limits. Optimization problems of power networks are very difficult to solve because the power networks are complex and widely distributed. This paper presents a simulation optimization approach in order to find the peak value of switching overvoltages and optimum location of arresters, as protective device, in EHV and UHV networks. In the proposed method, the Artificial Neural Network (ANN) as meta model estimates the peak value of overvoltages and global risk of failure generated by switching transients. An optimization method based on genetic algorithm (GA) determines the best positions of surge arresters on power networks so as to minimize the global risk of the network.
