Short-Term Reliability Evaluation of Transmission System Using Lightning Strike Probability Prediction


The transmission lines are exposed to the atmosphere nature and will be affected by adverse weather such as lightning storm, so that it will affect the reliability of transmission system. This paper studies the fault probability model of transmission line during the lightning storm, and evaluates the short-term reliability of transmission system in the forecasting weather condition. Firstly, build the lightning strike fault probability model of the transmission line based on historical lightning record information, then calculate the lightning strike probability under the forecasting weather conditions, furthermore evaluate the reliability index of transmission system. Utilizing IEEE RTS-79 system to verify the validity of the proposed model and the results show that lightning has great negative influence on the transmission lines and the reliability of transmission system. The reliability evaluation model proposed in this paper can guide the short-term operation and online scheduling for transmission system operators.

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Wang, J. , Yang, Q. , Xiong, X. and Weng, S. (2014) Short-Term Reliability Evaluation of Transmission System Using Lightning Strike Probability Prediction. Journal of Power and Energy Engineering, 2, 647-655. doi: 10.4236/jpee.2014.24087.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Yang, Q., Sima, W.X., Feng, J. and Yuan, T. (2008) Research on the Lightning Shielding Performance of the Yun- Guang UHVDC Transmission Lines. High Voltage Engineering, 34, 442-446.
[2] Li, P. (2000) A New Viewpoint about Lightning Trip-Out of UHV Transmission Lines. Power System Technology, 24, 63-65.
[3] Xia, W.-H. (1998) The Analysis of Lightning Protect ion for EHV and UHV Transmission Lines in Russia. High Voltage Engineering, 24, 76-79.
[4] Zhou, H. and Yu, Y.H. (2005) Discussion on Several Important Problems of Developing UHV ac Transmission in China. Power System Technology, 29, 1-9.
[5] Wang, H.-C. (1999) Mechanism of Lightning Shielding Failure. High Voltage Engineering, 25, 52-54.
[6] Tong, H.-W., Chen, L.-Y. and Zhang, B. (2013) External Lightning Risk Assessment Model for Transmission Line. East China Electric Power, 9, 1906-1910.
[7] Billiton, R. and Acharya, J.R. (2006) Weather-Based Distribution System Reliability Evaluation. Proceedings of IEEE Generation, Transmission and Distribution Conference, Stevenage, 499-506.
[8] Zhou, Y.J., Pawha, A. and Yang, S. (2006) Modeling Weather-Related Failures of Overhead Distribution Lines. IEEE Transactions on Power System, 21, 1683-1690.
[9] Wang, J.X., Zhang, Y. and Sun, Y. (2011) Influence of Large-Scale Ice Disaster on Transmission System Reliability. Proceedings of the CSEE, 31, 49-56.
[10] Feng, J., Xiao, X.-Y., Cui, Z., Feng, G. and Ma, C. (2012) Synthetic Risk Assessment of Catastrophic Failures in Power System Based on Entropy Weight Method. East China Electric Power, 7, 1144-1147.
[11] Cui, Z., Xiao, X.-Y., Feng, G. and LI, C.S. (2012) Assessment of Power Grid Catastrophic Event Forewarning Based on Comprehensive Risk. East China Electric Power, 9, 1507-1511.
[12] Huang, C. and Wang, J. (1995) Fuzzy Information Optimum Processing Techniques and Its Application. Beijing University of Aeronautics and Astronautics Press, Beijing.
[13] Billinton, R. and Allan, R.N. (1992) Reliability Evaluation of Engineering Systems: Concepts and Techniques. Plenum Publishers.
[14] Transmission and Distribution Committee of the IEEE PES. IEEE Std-1243-1997 (1997) IEEE Guide for Improving the Lightning Performance of Transmission Lines.
[15] Chang, Y., Chen, D.S. and Guo, Z.H. (2010) Research on the Relationship of Doppler Radar and the Lightning Warning. Meteorological and Environmental Sciences, 33, 36-39.
[16] Li, W., Sheng, D.-R., Chen, J.-H., et al. (2007) The Application of Double BP Neural Network Combined Forecasting Model in Real-time Data Predicting. Proceedings of the CSEE, 27, 94-97.

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