عنوان مقاله [English]
Continuous increase in fuel prices and its variations together with the emerged environmental pollutions cause to tendency to the renewable energy sources. However, the variable and uncertain natures of these generations as well as the market pressure due to the electricity market background threat the network security. Therefore, the recognition of the security index states in different operation conditions and considering the preventive and corrective actions are vital. Employment of the expected value of the uncertain variables for the power system security analysis would result in unrealistic outcomes and threatening of the power system security. Conventional approaches relying on the analysis of the large sum of scenarios such as Monte Carlo method are not efficient in the realistic large scale power systems due to the high computational burden and required time. This paper, in order to analysis the power system security, uses a point estimation method which consider the uncertainty while still has the satisfactory computational burden and time. The proposed method is examined on several power system test cases and its ability to effective uncertainty modeling in acceptable time is shown.
 International Energy Outlook, U.S. Energy Information Administration (EIA), 2014.
 European wind energy association, wind energy- the facts, earth scan, 2009.
 Hamon, C., Perninge, M., & Soder, L. "A Stochastic Optimal Power Flow Problem with Stability Constraints",
Part I and II, IEEE Transactions on, 28(2), 2013, PP.1839-1848.
 Jiang, R., Wang, J., & Guan, Y. "Robust unit commitment with wind power and pumped storage hydro, Power
Systems", IEEE Transactions on, 27(2), 2012, PP. 800-810.
 Schellenberg, A., Rosehart, W. and Aguado, J. "Cumulant-Based Probabilistic Optimal Power Flow (P-OPF)
with Gaussian and Gamma Distributions", IEEE Transactions on Power Systems, vol. 20, 2005, pp. 773-
 Canizares, C. A., & Kodsi, S. K. “Power system security in market clearing and dispatch mechanisms”, Power
Engineering Society General Meeting, IEEE, 2006.
 Milano, F., Cañizares, C. A., & Invernizzi, M. " Multiobjective optimization for pricing system security in
electricity markets", Power Systems, IEEE Transactions on, 18(2), 2003, PP. 596-604.
 Kaplan, S. "On the method of discrete probability distributions in risk and reliability calculations–application
to seismic risk assessment", Risk Analysis, 1(3), 1981, PP. 189-196.
 Rosenblueth, E. "Point estimates for probability moments", Proceedings of the National Academy of Sciences,
72(10), 1975, PP. 3812-3814.
 Hong, H. P. "An efficient point estimate method for probabilistic analysis", Reliability Engineering & System
Safety, 59(3), 1998, PP. 261-267.
 Morales, J. M., & Perez-Ruiz, J. "Point estimate schemes to solve the probabilistic power flow", Power
Systems, IEEE Transactions on, 22(4), 2007, PP. 1594-1601.
 Harr, M. E. "Probabilistic estimates for multivariate analyses". Applied Mathematical Modelling, 13(5),
1989, PP. 313-318.
 Amjady, N., & Sharifzadeh, H. "Security constrained optimal power flow considering detailed generator
model by a new robust differential evolution algorithm", Electric Power Systems Research, 81(2), 2011,
 Shahidehpour, M., Yamin, H., & Li, Z., Market Operations in Electric Power Systems, New York, NY: IEEE,
 Morales, J. M., Baringo, L., Conejo, A. J., & Mínguez, R. "Probabilistic power flow with correlated wind
sources", IET generation, transmission & distribution, 4(5), 2010, PP. 641-651.
 Jabr, R. A., & Pal, B. C. "ntermittent wind generation in optimal power flow dispatching", Generation,
Transmission & Distribution, IET, 3(1), 2009, PP.66-74.
 Cheng, H., Hou, Y., & Wu, F. "Probabilistic wind power generation model: Derivation and applications",
International Journal of Energy, (2), 2011, PP. 17-26.
 Billinton, R., & Gan, L. (1993). “Wind power modeling and application in generating adequacy assessment”,
In WESCANEX 93.'Communications, Computers and Power in the Modern Environment.'Conference
Proceedings., IEEE, 1993, pp. 100-106.