Analysis of electromechanical modes using an artificial neural network

An approach based on artificial neural networks is proposed for the analysis of electromechanical modes in Taiwan power system. To evaluate the dynamic performance of a power system in system operation and planning, the dominant eigenvalues for the worst-damped electromechanical mode must be computed. A multilayer feedforward artificial neural network is developed. It is well known that eigenvalues are complicated functions of many system variables such as bus loads, line flows, generation schedule, bus voltages etc. An important procedure in neural network design is to select those features which most affect system eigenvalues. A clustering artificial neural network is thus designed for feature selection. To demonstrate the effectiveness of the approach, results from eigenvalue analyses of Taiwan power system are reported.<>