Probabilistic Steady-State Security Assessment of an Electric Power System Using A Monte Carlo Approach

In this paper it is proposed a probabilistic stead-state security assessment of an electric power system using a Monte Carlo method. This approach evaluates a probabilistic measure of the system security, instead of just a particular response to a specified contingency. Performance indices are used to assess the impact of the contingencies in the power system security. These indices allow to accurately evaluate the influence of the overloads, voltage limit violations and voltage stability problems in the power network. A probabilistic version the SECURsySTEM software package developed by the authors was applied to the IEEE 118 busbars test power system. During the simulation time, the occurrence of contingencies and the subsequent protective actions are assumed as a stochastic process. Finally, some conclusions that provide a valuable contribution to the understanding of the power system security analysis are pointed out.

[1]  A. Ozdemir,et al.  Contingency selection based on real power transmission losses , 1999, PowerTech Budapest 99. Abstract Records. (Cat. No.99EX376).

[2]  M. Pavella,et al.  A contingency filtering, ranking and assessment technique for on-line transient stability studies , 2000, DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382).

[3]  A. Ozdemir,et al.  Composite electric power system adequacy evaluation via transmission losses based contingency selection algorithm , 1999, PowerTech Budapest 99. Abstract Records. (Cat. No.99EX376).

[4]  Manuel A. Matos,et al.  Multicontingency steady state security evaluation using fuzzy clustering techniques , 2000 .

[5]  J.A.D. Pinto,et al.  The Performance Indices to Contingencies Screening , 2006, 2006 International Conference on Probabilistic Methods Applied to Power Systems.

[6]  George J. Anders,et al.  Probability Concepts in Electric Power Systems , 1990 .

[7]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .