The advantage of fast computation capability of an artificial neural network (ANN) is used to introduce an iterative scheme for security assessment of power systems. Two related approaches are shown which demonstratedly work satisfactorily. The idea of feedback in a single-layer feedforward neural network is experimented yielding higher accuracy. The ANN is trained by using a set of data obtained from off-line analysis of the power network. After training, an approximate solution for a given condition may be found almost immediately. The approximate solution obtained is judged adequate for assessing the security of the power system. A case study is also presented for demonstrating the applicability of the approach.
B. H. Chowdhury and B. M. Wilamowski, "Security Assessment Using Neural Computing," Proceedings of the First International Forum on Applications of Neural Networks to Power Systems, 1991, Institute of Electrical and Electronics Engineers (IEEE), Jan 1991.
The definitive version is available at http://dx.doi.org/10.1109/ANN.1991.213497
First International Forum on Applications of Neural Networks to Power Systems, 1991
Electrical and Computer Engineering
Keywords and Phrases
Artificial Neural Network; Feedback; Feedforward Neural Nets; Iterative Scheme; Neural Computing; Power System Analysis Computing; Power Systems; Security Assessment; Single-Layer Feedforward Neural Network; Training
Article - Conference proceedings
© 1991 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.