Prediction model of galloping of iced transmission lines based on PSO-SVM algorithm

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Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (3) : 280-286.

ZOU Hongbo1,2, SONG Jiale1,2, LIU Yuan2, DUAN Zhifeng2, ZHANG Xinyu2, SONG Lu2

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Abstract

The galloping of transmission lines often leads to electrical accidents such as wear of fittings, flash-over, and disconnection, which has a great negative impact on the safety of the power system. The dynamic response of the iced quad bundle conductor under the action of average wind and fluctuating wind was simulated by ANSYS software under the conditions of different spans, wind speeds, etc. Then, the early warning model was constructed based on the PSO_SVM（particle swarm optimization—support vector machines） algorithm and the data set obtained from the simulation, which takes the span, wind speed and initial wind angle of attack as the input, and whether galloping as the output. At the same time, the prediction results of the PSO_SVM model are compared with those of other intelligent algorithms such as BP(back propagation), SVM（support vector machine）, and GA_SVM（genetic algorithm—optimization support vector） models to verify the practicability and effectiveness of the prediction model. It is proved that the prediction results of the PSO_SVM model have higher accuracy, which has a certain reference significance for the early warning of the galloping of iced transmission lines.

Key words

particle swarm optimization / neural network / support vector machine（SVM） / galloping of transmission lines

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ZOU Hongbo1,2, SONG Jiale1,2, LIU Yuan2, DUAN Zhifeng2, ZHANG Xinyu2, SONG Lu2. Prediction model of galloping of iced transmission lines based on PSO-SVM algorithm[J]. Journal of Vibration and Shock, 2023, 42(3): 280-286

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