International Science Index


9997082

Reliability Evaluation of Composite Electric Power System Based On Latin Hypercube Sampling

Abstract:

This paper investigates the suitability of Latin Hypercube sampling (LHS) for composite electric power system reliability analysis. Each sample generated in LHS is mapped into an equivalent system state and used for evaluating the annualized system and load point indices. DC loadflow based state evaluation model is solved for each sampled contingency state. The indices evaluated are loss of load probability, loss of load expectation, expected demand not served and expected energy not supplied. The application of the LHS is illustrated through case studies carried out using RBTS and IEEE-RTS test systems. Results obtained are compared with non-sequential Monte Carlo simulation and state enumeration analytical approaches. An error analysis is also carried out to check the LHS method’s ability to capture the distributions of the reliability indices. It is found that LHS approach estimates indices nearer to actual value and gives tighter bounds of indices than non-sequential Monte Carlo simulation.

References:
[1] R. Billinton and L. Salvaderi, "Comparison between two fundamentally different approaches to composite system reliability evaluation,” IEEE Trans. Power App. Syst., vol. PAS-104, 1985, pp. 3486-3492.
[2] M.V.F. Pereira, L.M.V.G. Pinto, S. H. F. Cunha, G. C. Oliveira, ” Monte Carlo based Composite Reliability Evaluation – Modeling Aspect and Computational Results ”,IEEE tutorial course ”Reliability assessment of composite generation and transmission systems”, IEEE special publication,1989.
[3] M.V.F. Pereira, N.J. Balu, "Composite generation/transmission reliability evaluation", Proceedings of the IEEE ,Vol.80,issue 4, April 1992, pp.470-491.
[4] A. Merlin and P. Oger, "Application of variance reduction technique to Monte Carlo simulation of power transmission system,” in Workshop Proceedings: Power System Reliability; Research Needs and Priorities, EPRI Report, Oct.1978, WS77-60.
[5] M. Mazumdar, "Importance sampling in reliability estimation, reliability and fault-tree analysis,” SIAM, Philadelphia, PA, 1975, pp.153-163.
[6] G. J. Anders, J. Endrenyi, M. V. F. Pereira, L. M. V. G. Pinto, G.C. Oliveira, and S. H. F. Cunha, "Fast Monte Carlo simulation techniques for power system reliability studies,” presented at the 1990 CE& Meeting, WG 38.03, Paris, France.
[7] Chris Marnay and Todd Strauss,” Effectiveness of Antithetic sampling and stratified sampling in Monte Carlo Chronological production cost modeling ” , IEEE Transactions on Power Systems, Vo1.6, No. 2,1991, pp.669-675.
[8] Panida Jirutitijaroen and Chanan Singh,” Comparison of Simulation Methods for Power System Reliability Indexes and Their Distributions”, IEEE Transactions on Power Systems, Vol. 23, No. 2, May 2008, pp.486-493.
[9] Zhen Shu and Panida Jirutitijaroen,” Latin Hypercube Sampling Techniques for Power Systems Reliability Analysis With renewable energy sources”, IEEE Transactions on Power Systems, Vol. 26,No. 4,2011, pp.2066-2073.
[10] McKay, M.D., Beckman, R.J., Conover, W.J., "A comparison of three methods for selecting values of input variables in the analysis of output from a computer code”, Technometrics 21, 239–245, 1979.
[11] J.C. Helton and F.J. Davis, "Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems,” Reliab. Eng.Syst. Safety, vol. 81, pp. 23–69, 2003
[12] D. E. Huntington and C. S. Lyrintzis , "Improvements to and limitations of Latin hypercube sampling”, Prob. Engg. Mech. Vol. 13, No. 4, pp. 245-253, 1998.
[13] Michael Stein, "Large Sample Properties of Simulations Using Latin Hypercube sampling”, Technometrics, Vol. 29, No. 2, May 1987, pp. 143-151.
[14] R. Billinton., S.Kumar, N. Chowdhury , K. Chu, K. Debnath, L. Goel, E.Khan, P. Kos, G. Nourbakhsh, J. Oteng-Adjei,” A reliability test system for educational purposes-basic data ", IEEE Transactions on Power Systems, Vol. 4, Issue:3 ,pp: 1238 –1244,Aug. 1989.
[15] IEEE Committee Report, "IEEE Reliability Test System”, IEEE transactions on Power apparatus and systems, Vol. PAS-98, No.6, 1979, pp.2047-2054.
[16] R. Billinton and L.Wenyuan, "Hybrid approach for reliability evaluation of composite generation and transmission systems using Monte-Carlo simulation and enumeration technique ", Generation, Transmission and Distribution, IEE Proceedings-C , Vol.138, No. 3,May 1991, pp. 233-241.
[17] T. X. Zhu, ”A New Methodology of Analytical formula deduction and sensitivity analysis of EENS in bulk power system reliability assessment”, Power Systems Conference and Exposition, 2006, PSCE '06. 2006 IEEE PES, pp. 825-831, Oct. 29 -Nov. 1 2006, Atlanta, GA.
[18] A. Jonnavithula, "Composite System reliability evaluation using sequential Monte Carlo simulation”, Ph.D. Thesis, University of Saskatchewan, Canada, 1997.