Authors : S. Sutha and N. Kamaraj
Abstract: In deregulated operating regime power system security is an issue that needs due thoughtfulness from researchers in the horizon of unbundling of generation and transmission. Real power contingency ranking is an inherent part of security assessment. The target of contingency ranking and screening is to rapidly and precisely grade the decisive contingencies from a large list of plausible contingencies and rank them according to their severity for further rigorous analysis. In the proposed work, Wavelet Transform Based Artificial Neural Networks (WNN) is used for real power contingency ranking of the system. The results from offline AC load flow calculation are used to train the WNN for estimating the performance index. The effectiveness of the purported method is exhibited by contingency ranking on IEEE 14 bus, IEEE 5 bus systems and comparisons are made with conventional method. Good calculation accuracy, faster analysis times are obtained by using WNN.
S. Sutha and N. Kamaraj , 2008. Real Power Contingency Ranking Using Wavelet Transform Based Artificial Neural Network (WNN) . International Journal of Electrical and Power Engineering, 2: 116-121.