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Contingency Analysis, Analytical method, RBF-NN method, Active and Reactive Performance Indices, Ranking.

Contingency analysis is a tool used by power system engineers for planning and assessing power system reliability. The conventional analytical method which is mathematical model based, is not only tedious and time consuming in view of the large number of components in the network but always left some critical components unassessed due to non-convergence of the power flow analysis of such, hence the contingency analysis of such system could not be said to be completed.

In this work, contingency analysis of line components of a standard IEEE-30 Bus and real 330-kV Nigerian Transmission Company of Nigeria (TCN) network (28Bus) systems were investigated using Radial Basis Function Neural Network (RBF-NN) which is artificial intelligence based.

The contingency analysis was carried out by solving the non-linear algebraic equations of steady state model for the standard IEEE-30 Bus and TCN-28 Bus power networks using Newton-Raphson (N-R) power flow method. RBF-NN method was used for the computation of Reactive and Active performance indices (PIR and PIA ) which were ranked in order to reveal the criticality of each line outage. Simulation was carried out using MATLAB R2013a version. The non-converged lines in both systems were reinforced and re-analysed. The results of contingency analyses of the reinforced systems show more robust systems with complete line ranking.