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Prediction method of icing thickness of transmission line based on MEAO

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Abstract

Transmission line icing is very important for safe operation of transmission network. Icing thickness of transmission line has characteristics including nonlinear growth, complicated influencing factors, long-term prediction and low accuracy. Based on intelligent prediction algorithms such as BP neutral network and support vector machine, the work proposed intelligent prediction method of icing thickness optimized by mind evolution algorithm. After modeling on basis of crucial factors of transmission line icing, we conducted simulation experiments of temperature, humidity and wire tension. Result shows that prediction model, with better performance than original intelligent method, can be used to more accurately predict icing thickness of transmission line.

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Acknowledgements

This work was supported by the Fundamental Research Funds for the Central Universities (No. 2016MS151).

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Authors and Affiliations

  1. School of Control and Computer Engineering, North China Electric Power University, 619 Yonghua North Road, Baoding, 071003, China

    Wei Xiong, Hejin Yuan & Lang You

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  1. Wei Xiong
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  2. Hejin Yuan
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  3. Lang You
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Correspondence to Wei Xiong.

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Xiong, W., Yuan, H. & You, L. Prediction method of icing thickness of transmission line based on MEAO. Cluster Comput 21, 845–853 (2018). https://doi.org/10.1007/s10586-017-0923-3

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  • DOI: https://doi.org/10.1007/s10586-017-0923-3

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