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Robust Model for Weather-Related Contingency Probability Estimation Used for Risk Based Security Assessment

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Weather is one of major factors that profoundly has an impact to the performance of a transmission line. Advanced knowledge and accurate estimation of the failure rate related to weather provides better overview on the probability of transmission line outage. Precise probability estimation is vital in risk based security assessment so as to reflect more accurate risk index value that enable correct judgments on power system security level. This paper introduced two approaches in the construction of an improved model to estimate the failure rate of a transmission line considering lightning and rain weather. The first approach is based on the identification of the best linear model that has the least error and significant correlation between the independent and dependent variables. The second focused on the robust estimator that has resistance to the presence of outliers in solving the multiple linear regression. In realizing the effectiveness of the proposed method, the results are compared with the traditional Ordinary Least Square (OLS) method. The results revealed that the proposed method using MM-estimator shows a significant improvement over OLS performance.
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Contingency Probability; Risk Based Security Assessment; Robust Model; Data Pooling; Failure Rate Model

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H. Wan, Risk based security assessment for operating electric power systems, Doctor of Philosophy dissertation, Graduate Collage Iowa State University, 1999.

A. Dissanayaka, U. D. Annakkage, B. Jayasekara, and B. Bagen, "Risk-Based Dynamic Security Assessment," IEEE Transactions on Power Systems, vol. 26, pp. 1302-1308, 2011.

M. Marsadek, A. Mohamed, and Z. M. Nopiah, "Risk of static security assessment of a power system using non-sequential Monte Carlo simulation," Journal of Applied Sciences 11(2), pp. 300-307, 2011.

J. McCalley, S. Asgarpoor, L. Bertling, R. Billinion, H. Chao, J. Chen, et al., "Probabilistic security assessment for power system operations," in IEEE Power Engineering Society General Meeting, 2004., 2004, pp. 212-220 Vol.1.

W. Hua, J. D. McCalley, and V. Vittal, "Risk based voltage security assessment," IEEE Transactions on Power Systems, vol. 15, pp. 1247-1254, 2000.

M. Marsadek, A. Mohamed, and Z. M. Nopiah, "Assessment and classification of line overload risk in power systems considering different types of severity function," in WSEAS Transaction on Power System, 2010, pp. 182-191.

N. Ming, J. D. McCalley, V. Vittal, and T. Tayyib, "Online risk-based security assessment," IEEE Transactions on Power Systems, vol. 18, pp. 258-265, 2003.

S. S. Halilcevic, F. Gubina, and A. F. Gubina, "Prediction of Power System Security Levels," IEEE Transactions on Power Systems, vol. 24, pp. 368-377, 2009.

Z. Yujia, A. Pahwa, and Y. Shie-Shien, "Modeling Weather-Related Failures of Overhead Distribution Lines," IEEE Transactions on Power Systems, , vol. 21, pp. 1683-1690, 2006.

X. Fei, J. D. McCalley, Y. Ou, J. Adams, and S. Myers, "Contingency Probability Estimation Using Weather and Geographical Data for On-Line Security Assessment," in International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), 2006., 2006, pp. 1-7.

S. R. Kasim, M. M. Othman, N. F. A. Ghani, I. Musirin, A. Mohammed, and A. Hussain, "Determination of power system risk by means of bootstrap technique," Australian Journal of Basic and Applied Sciences, pp. 4534-4558, 2009.

F. Weihui, Z. Sanyi, J. D. McCalley, V. Vittal, and N. Abi-Samra, "Risk assessment for special protection systems," IEEE Transactions on Power Systems, vol. 17, pp. 63-72, 2002.

F. Weihui, J. D. McCalley, and V. Vittal, "Risk assessment for transformer loading," IEEE Transactions on Power Systems, vol. 16, pp. 346-353, 2001.

S. Varshney, L. Srivastava, and M. Pandit, "ANN based integrated security assessment of power system using parallel computing," International Journal of Electrical Power & Energy Systems, vol. 42, pp. 49-59, 11// 2012.

C. Grigg, P. Wong, P. Albrecht, R. Allan, M. Bhavaraju, R. Billinton, et al., "The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee," IEEE Transactions on Power Systems, vol. 14, pp. 1010-1020, 1999.

P. Kankanala, A. Pahwa, and S. Das, "Regression models for outages due to wind and lightning on overhead distribution feeders," in Power and Energy Society General Meeting, 2011 IEEE, 2011, pp. 1-4.

G. Min, A. Pahwa, and S. Das, "Bayesian Network Model With Monte Carlo Simulations for Analysis of Animal-Related Outages in Overhead Distribution Systems," IEEE Transactions on Power Systems,, vol. 26, pp. 1618-1624, 2011.

J. Yong, J. D. McCalley, and T. Van Voorhis, "Risk-based resource optimization for transmission system maintenance," IEEE Transactions on Power Systems, vol. 21, pp. 1191-1200, 2006.

S. Shen, D. Koval, and S. Shen, "Modelling extreme-weather-related transmission line outages," in Electrical and Computer Engineering, 1999 IEEE Canadian Conference on, 1999, pp. 1271-1276 vol.3.

O. G. Alma, "Comparison of Robust Regression Methods in Linear Regression," Int. J. Contemp. Math. Sciences, vol. 6, pp. 409-421, 2011.

C. Anderson and R. E. Schumacker, "A Comparison of Five Robust Regression Methods With Ordinary Least Squares Regression: Relative Efficiency, Bias, and Test of the Null Hypothesis," Taylor & Francis Online, vol. 2, pp. 79-103, 2003.

R. E. Schumacker, M. P. Monahan, and R. E. Mount, "A Comparison of OLS and Robust Regression using S-Plus," in Multiple Linear Regression Viewpoints, 2002.

V. J. Yohai, "High Breakdown-Point and High Efficiency Robust Estimates for Regression," The Annals of Statistics, vol. 15, pp. 642-656, 1987.

S. Tadjudin and D. A. Landgrebe, "Robust parameter estimation for mixture model," IEEE Transactions on Geoscience and Remote Sensing, vol. 38, pp. 439-445, 2000.

Z. Banjac, B. Kovacevic, M. Veinovic, and M. Milosavljevic, "Robust least mean square adaptive FIR filter algorithm," Vision, Image and Signal Processing, IEE Proceedings -, vol. 148, pp. 332-336, 2001.

S. Fumin, S. Chunhua, A. Van Den Hengel, and T. Zhenmin, "Approximate Least Trimmed Sum of Squares Fitting and Applications in Image Analysis," IEEE Transactions on Image Processing, vol. 22, pp. 1836-1847, 2013.

R. E. Walpole, R. H. Myers, S. L. Myers, and K. Ye, Probability & Statistics For Engineers & Scientists, Seventh Edition ed.: Prentice Hall, 2002.

M. Marsadek and A. Mohamed, "Risk based security assessment of power system using generalized regression neural network with feature extraction," Journal Central South University Press and Springer-Verlag Berlin Heidelberg, vol. (2013) 20, pp. 466-479, 2013.

R. Orville, G. R. Huffines, W. R. Burrows, R. L. Holle, and K. L. Cummins, "The North American Lightning Detection Network (NALDN)-First Results:1998-2000," 2002.;2

Khan, B., Agnihotri, G., Rathore, P., Mishra, A., Naidu, G., A Cooperative Game Theory Approach for Usage and Reliability Margin Cost Allocation under Contingent Restructured Market, (2014) International Review of Electrical Engineering (IREE), 9 (4), pp. 854-862.

Bassi, F., Giannuzzi, G., Giuntoli, M., Pelacchi, P., Poli, D., Mechanical behaviour of multi-span overhead transmission lines under dynamic thermal stress of conductors due to power flow and weather conditions, (2013) International Review on Modelling and Simulations (IREMOS), 6 (4), pp. 1112-1122.


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