The authors present a number of different configurations of a neural network and identify a particular case which is most suitable for power flow analysis in real-time applications. The advantage of fast computation of the artificial neural network (ANN) is used for obtaining power flow solutions in real time. The inputs to the ANN are the real and reactive power generating and demand in the system, and the output data are the complex bus voltages. A few configurations of the neural network were experimented with, and the best results were achieved with a single-layer feedforward neural network with nonlinear feedback. By using the trained neural network, an approximate solution of power flow can be obtained almost immediately. One particular configuration of the ANN can be used for determining corrective strategies during abnormal conditions of the power system
B. H. Chowdhury and B. M. Wilamowski, "Fast Power Flow with Capability of Corrective Control Using a Neural Network," Proceedings of the 35th Midwest Symposium on Circuits and Systems, 1992, Institute of Electrical and Electronics Engineers (IEEE), Jan 1992.
The definitive version is available at https://doi.org/10.1109/MWSCAS.1992.271112
35th Midwest Symposium on Circuits and Systems, 1992
Electrical and Computer Engineering
Keywords and Phrases
Abnormal Conditions; Artificial Neural Network; Complex Bus Voltages; Corrective Control; Corrective Strategies; Fast Power Flow; Feedforward Neural Nets; Learning (Artificial Intelligence); Load Flow; Nonlinear Feedback; Power Engineering Computing; Power Flow Analysis; Reactive Power; Real Power; Real-Time Applications; Single-Layer Feedforward Neural Network; Trained Neural Network
Article - Conference proceedings
© 1992 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.