Composite Power System Reliability Modeling, Evaluation and Reliability-Based Analysis by Bayesian Networks
Subject Areas : electrical and computer engineering
M.
Eliassi
1
H.
Seifi
2
(Tarbiat Modares University)
3
(Tarbiat Modares University)
Abstract :
Bayesian Networks (BNs) as a strong framework for handling probabilistic events have been successfully applied in a variety of real-world problems, but they have received little attention in the area of composite power systems reliability assessment. Reliability assessment by BN provides some additional capabilities in comparison to conventional methods, both at the modeling and at the analysis levels. At the modeling level, several restrictive assumptions, implicit in the conventional methods, can be removed. At the analysis level, a variety of applicable reliability-based analysis which is hardly achievable in conventional methods, can be conveniently performed. This paper proposes a methodology based on Minimal Cutsets (MCs) to apply BNs to composite power system reliability modeling, reliability assessment and reliability-based analysis. To have a more accurate BN model, a new method of MC determination for composite power system is proposed. Bayesian structure is extracted, based on the determined MCs. Bayesian parameters are defined based on the logical relationships of nodes. To make the proposed method applicable to large composite power systems, virtual nodes are proposed and combined with Bayesian model. Also, a variety of reliability-based analyses are presented which are hardly achievable in conventional methods. The proposed method is validated by applying to RBTS and comparing the results with other reliability analysis methods. The proposed methodology is applied to the Reliability Test System (RTS), to show its feasibility in large networks.
[1] R. Billinton and R. N. Allan, Reliability Evaluation of Engineering Systems: Concepts and Techniques, 2nd Edition, Springer, 1992.
[2] R. Billinton and R. N. Allan, Reliability Evaluation of Power Systems, 2nd Edition, Plenum Press, 1996.
[3] B. S. Dhillon, Reliability, Quality, and Safety for Engineers, CRC Press, 2005.
[4] H. Pham, Handbook of Reliability Engineering, Springer, 2003.
[5] R. Billinton, "Bibliography on the application of probability methods in power system reliability evaluation," IEEE Trans. Power App. and Syst., vol. 91, no. 2, pp. 649-660, Mar./Apr. 1972.
[6] IEEE Subcommittee on the Application of Probability Methods Power System Engineering Committee, "Bibliography on the application of probability methods in power system reliability evaluation 1971-1977," IEEE Trans. Power App. and Syst., vol. 97, no. 6, pp. 2235-2242, Nov./Dec. 1978.
[7] R. A. Allan, R. Billinton, and S. H. Lee, "Bibliography on the application of probability methods in power system reliability evaluation 1977-1982," IEEE Trans. Power App. and Syst., vol. 103, no. 2, pp. 275-282, Feb. 1984.
[8] R. A. Allan, R. Billinton, S. M. Shahidehpour, and C. Cingh, "Bibliography on the application of probability methods in power system reliability evaluation 1982-1987," IEEE Trans. Power Syst., vol. 3, no. 4, pp. 1555-1564, Nov. 1988.
[9] R. A. Allan, R. Billinton, A. M. Breipohl, and C. H. Grigg, "Bibliography on the application of probability methods in power system reliability evaluation 1987-1991," IEEE Trans. Power Syst., vol. 9, no. 1, pp. 41-49, Feb. 1994.
[10] R. A. Allan, R. Billinton, A. M. Breipohl, and C. H. Grigg, "Bibliography on the application of probability methods in power system reliability evaluation 1992-1996," IEEE Trans. Power Syst., vol. 14, no. 1, pp. 51-57, Feb. 1999.
[11] R. Billinton, M. Fotuhi - Firuzabad, and L. Bertling, "Bibliography on the application of probability methods in power system reliability evaluation 1996-1999," IEEE Trans. Power Syst., vol. 16, no. 4, pp. 595-602, Nov. 2001.
[12] D. Heckerman, "A tutorial on learning with Bayesian networks," Technical Report MSR-TR-95-06, Microsoft Research, pp. 301-354, Mar. 1995.
[13] L. Portinale and A. Bobbio, "Bayesian networks for dependability analysis: an application to digital control reliability," in Proc. 15th Uncertainty in Artificial Intelligence Conf., pp. 551-558, San Francisco, 1999.
[14] A. Bobbio et al., "Improving the analysis of dependable systems by mapping fault trees into Bayesian networks," Reliab. Eng. Syst. Safety, vol. 71, no. 3, pp. 249-260, Mar. 2001.
[15] T. Koski and J. M. Noble, Bayesian Networks: an Introduction, Wiley Series in Probability and Statistics, 2009.
[16] J. G. Torres-Toledan and L. E. Sucar, "Bayesian networks for reliability analysis of complex systems," in Proc. 6th Ibero-American Conf. on AI, pp. 195-206, Berlin, 1998.
[17] C. Simon and P. Weber, "Evidential networks for reliability analysis and performance evaluation of systems with imprecise knowledge," IEEE Trans. Rel., vol. 58, no. 1, pp. 69-87, Mar. 2009.
[18] B. R. Cobb, R. Rumi, and A. Salmeron, Bayesian Network Models with Discrete and Continuous Variables, Advances in Probabilistic Graphical Models, Studies in Fuzziness and Soft Computing, Springer Berlin Heidelberg, 2007.
[19] D. Codetta - Raiteri et al., "A dynamic Bayesian network based framework to evaluate cascading effects in a power grid," Eng. Appl. Artif. Intel., vol. 25, no. 4, pp. 683-697, Jun. 2012.
[20] D. C. Yo, T. C. Nguyen, and P. Haddawy, "Bayesian network model for reliability assessment of power systems," IEEE Trans. Power Syst., vol. 14, no. 2, pp. 426-432, May 1999.
[21] H. Limin, Z. Yongli, and F. Gaofeng, "Reliability assessment of power systems by Bayesian networks," in Proc. International Conf. Power System Technology, vol. 2, pp. 876-879, Kunming, China, 13-17 Oct. 2002.
[22] J. Hu et al., "Reliability assessment of power systems based on element time sequential by Bayesian networks," in Proc. 3rd Int. Conf. Innovative Computing Information and Control, vol. 2, p. 579, Dalian, China, 18-20 Jun. 2008.
[23] Z. Yongli, H. Limin, Z. Liguo, and W. Yan, "Bayesian network based time-sequence simulation for power system reliability assessment," in Proc. Int. Conf. Artificial Intelligence, pp. 271-277, Atizapan de Zaragoza, Spain, 27-31 Oct. 2008.
[24] H. Lihua, H. Chenwei, W. Hui, and H. Limin, "Assessment of distribution system reliability based on Bayesian network and time sequence simulation," in Proc. 6th Int. Conf. Fuzzy Systems and Knowledge Discovery, vol. 2, pp. 481-486, Tianjin, China, 14-16 Aug. 2009.
[25] S. Zhao, H. Wang, and D. Cheng, "Power distribution system reliability evaluation by D-S evidence inference and Bayesian network method," in Proc. 11th IEEE Int. Conf. Probabilistic Methods Applied to Power Systems, PMAPS'10, vol. 2, pp. 654-658, Singapore, 14-17 Jun. 2010.
[26] T. Daemi, A. Ebrahimi, and M. Fotuhi-Firuzabad, "Constructing the bayesian network for components reliability importance ranking in composite power systems," Int. J. Electr. Power Energy Syst., vol. 43, no. 1, pp. 474-480, Dec. 2012.
[27] T. Daemi and A. Ebrahimi, "Detailed reliability assessment of composite power systems considering load variation and weather conditions using Bayesian network," Int. Trans. Electr. Energ. Syst., vol. 27, no. 3, pp. 305-317, Oct. 2012.
[28] H. Langseth and L. Portinale, "Bayesian networks in reliability," Reliab. Eng. Syst. Safe., vol. 92, no. 1, pp. 92-108, Dec. 2007.
[29] R. E. Neapolitan, Learning Bayesian Networks, Pearson Prentice Hall, 2004.
[30] J. Pearl, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, Morgan Haufmann Publishers, 1988.
[31] J. Abbasi, N. Moslemi, and A. Rabiee, "A new algorithm for enumeration of minimum cutsets of graph by branch addition," in Proc. IEEE/PES Transmission and Distribution Conf. and Exhibition: Asia and Pacific, 6 pp., Dalian, China, 2005.
[32] J. Cai et al., "The application of the minimum cutsets in reliability evaluation of power transmission and transformation system," Adv. Mater. Res., vol. 463-464, pp. 1175-1181, Feb. 2012.
[33] A. Gaun, H. Renner, and G. Rechberger, "Fast minimal cutset evaluation in cyclic undirected graphs for power transmission systems," in Proc. IEEE Power Tech Conf., 8 pp., Bucharest, Romania, 28 Jun.-2 Jul. 2009.
[34] C. M. Rocco and M. Muselli, A Machine Learning Algorithm to Estimate Minimal Cut and Path Sets from a Monte Carlo Simulation, Advances in Probabilistic Graphical Models, Probabilistic Safety Assessment and Management, Springer-Verlag, 2004.
[35] J. Y. Lin and C. E. Donaghey, "A Monte Carlo simulation to determine minimal cut sets and system reliability," in Proc. Reliability and Maintainability Symp., pp. 246-249, Atlanta, GA, US, 26-28 Jan. 1993.
[36] I. Helal, "A heuristic-based approach for enumerating the minimal path sets in a distribution network," IEEE Power Engineering Society General Meeting, 5 pp., Tampa, FL, US, 24-28 Jun. 2007.
[37] F. V. Jensen, Bayesian Networks and Decision Graphs, New York, Springer-verlog, 2001.
[38] N. A. Samaan, Reliability Assessment of Electrical Power Systems Using Genetic Algorithms, Doctor of Philosophy Dissertation, Dept. Elect. Eng., Texas A&M University, 2004.
[39] J. E. Ramirez-Marquez and D. W. Coit, "Composite importance measures for multi-state systems with multi-state components," IEEE Trans. Rel., vol. 54, no. 3, pp. 517-529, Sep. 2005.
[40] K. P. Murphy, "The Bayes net toolbox for Matlab," Computing Science and Statistics Inference, vol. 33, pp. 331-350, 2001.
[41] IEEE Reliability Test System Task Force of the Application of Probability Methods Subcommittee, "The IEEE reliability test system 1996," IEEE Trans. Power Syst., vol. 14, no. 3, pp. 1010-1020, Aug. 1992.