The Application of Neural Network on The Contingency Analysis of Iraqi Super Grid Network
AbstractMany of the problems that occur on electrical power system can cause serious
trouble with in such a quick time period that the operator (in control room) could not
take action fast enough. This is often the case with cascading failures. Because of this
aspect of power system operation, modern operation computers are equipped with
contingency analysis programs that model possible system troubles before they arise.
Therefore, this work has developed an Artificial Neural Network technique to alarm
the operators in control room to any outage in power system elements (Generating
unit or Transmission line) depending upon the results of AC load flow after each
separation in these elements.
The aim of this work is to improve the database system of Iraqi Control Centers
by adopting the facility of the Artificial Neural Network (ANN) technique to identify
the transmission line or the generation unit separate’s in the electrical network. The
work comprises four major parts which are; the development of the load flow
program using Newton-Raphson Method, building the structure of Neural Network
program (Radial Basis Function Neural Network), the engagement between the two
programs, and the development of Visualization Technique for presenting the results
via using Matlab language (Version 6.5). After the Engagement between the
Visualization and other programs, the network under consideration (Iraqi Super Grid
Network 400Kv) was studied and analyzed.
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