Neural network method for predicting accidents due to formation of ice on power lines overhead
Keywords:
forecasting glaze load, neural network, meteopost, overhead power lineAbstract
The problem of prevention of faults caused by overhead power line glazing is considered. With this purpose, in the most fault-prone areas, automatic monitoring posts for glaze loads and meteorological parameters are installed the data of which are used to predict glazing. A neural network method for such prediction is proposed and has been tested on real data.References
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L. Makkonen, E. Lozowski // Proc. 11th International Workshop on Atmospheric Icing of Structures. — Montreal, Canada, 2005. — P. 55—62.
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Vol. II. — P. 599–606.
4. Jones K. F. A simple model for freezing rain ice loads / K. F. Jones // Atmospheric Research. — 1998. — Vol. 46. —
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5. Makkonen L. Modeling power line icing in freezing precipitation / L. Makkonen // Atmospheric Research. — 1998. — Vol. 43. — P. 131—142.
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N. M. Martin. — New York : CRC Press, 1998. — 368 p.
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J. D. Schaffer, D. Whitley, L. J. Eshelman // Proc. Int. Workshop Combinations of Genetic Algorithms and Neural Networks. — Baltimore, June 6, 1992. — P. 1—37.
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Published
2010-11-12
How to Cite
[1]
S. V. Popov, N. M. Cheremysyn, O. V. Parkhomenko, and K. A. Shkuro, “Neural network method for predicting accidents due to formation of ice on power lines overhead”, Вісник ВПІ, no. 1, pp. 161–163, Nov. 2010.
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Energy generation and electrical engineering
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