Transmission Lines Switching Overvoltages Evaluation Using Radial Basis Function Neural Network
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| Title | Transmission Lines Switching Overvoltages Evaluation Using Radial Basis Function Neural Network |
| Authors | |
| Abstract | In this paper, a radial basis function (RBF) neural network based approach is used to estimate transient overvoltages on transmission lines during power system restoration. In the early stages of the restoration, the transmission lines are lightly loaded; resonance therefore is lightly damped, which in turn means the resulting resonance voltages may be very high. Developed Artificial Neural Network (ANN) is trained with equivalent circuit parameters of the network as input parameters; therefore trained ANN has proper generalization capability. The simulated results for 39-bus New England test system, show that the proposed technique can estimate the peak values of switching overvoltages with acceptable accuracy. |
| Publisher | Advances in Computational Mathematics and its Applications |
| Date | 2012-01-21 |
| Source | 2167-6356 |
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