Document Type: Article
Department of Electrical Engineering, College of Engineering, Fars Science and Research Branch, Islamic Azad University, Fars, Iran
Fars Regional Electric Company, Shiraz, Iran
Department of Power and Control Engineering, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
Department of Electrical Engineering, College of Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran
Contingency ranking is one of the most important stages in the analysis of power system security. In this paper, an integrated algorithm has been proposed to address this issue. This algorithm employs neural networks method to quickly estimate the power system parameters and Stochastic Frontier Analysis (SFA) in order to calculate the eciency of each contingency. Network security indices (voltage violation and line
flow violation) and economic indices (locational marginal price and congestion cost) have been simultaneously considered to rank the contingencies. The eciency of each contingency shows its severity, and indicates that it aects network security and economic indices concurrently. The proposed algorithm has been tested on IEEE 14-bus and 30-bus test power systems. Simulation results show the high eciency of the algorithm. Test results
indicate that predicted quantities are estimated accurately and quickly. The proposed method is capable of producing fast and accurate network security and economic indices, so that it can be used for online ranking.