Fast Power Flow with Capability of Corrective Control Using a Neural Network
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Abstract
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
