The Application of Neural Network on The Contingency Analysis of Iraqi Super Grid Network


Many of the problems that occur on electrical power system can cause serioustrouble with in such a quick time period that the operator (in control room) could nottake action fast enough. This is often the case with cascading failures. Because of thisaspect of power system operation, modern operation computers are equipped withcontingency analysis programs that model possible system troubles before they arise.Therefore, this work has developed an Artificial Neural Network technique to alarmthe operators in control room to any outage in power system elements (Generatingunit or Transmission line) depending upon the results of AC load flow after eachseparation in these elements.The aim of this work is to improve the database system of Iraqi Control Centersby adopting the facility of the Artificial Neural Network (ANN) technique to identifythe transmission line or the generation unit separate’s in the electrical network. Thework comprises four major parts which are; the development of the load flowprogram using Newton-Raphson Method, building the structure of Neural Networkprogram (Radial Basis Function Neural Network), the engagement between the twoprograms, and the development of Visualization Technique for presenting the resultsvia using Matlab language (Version 6.5). After the Engagement between theVisualization and other programs, the network under consideration (Iraqi Super GridNetwork 400Kv) was studied and analyzed.