Paper Title:
Reliability Assessment of Power System Using Importance Sampling Technique Based on Layer Optimization Simulation
  Abstract

An improved importance sampling method with layer simulation optimization is presented in this paper. Through the solution sequence of the components’ optimum biased factors according to their importance degree to system reliability, the presented technique can further accelerate the convergence speed of the Monte-Carlo simulation. The idea is that the multivariate distribution’ optimization of components in power system is transferred to many steps’ optimization based on importance sampling method with different optimum biased factors. The practice is that the components are layered according to their importance degree to the system reliability before the Monte-Carlo simulation, the more forward, the more important, and the optimum biased factors of components in the latest layer is searched while the importance sampling is carried out until the demanded accuracy is reached. The validity of the presented is verified using the IEEE-RTS79 test system.

  Info
Periodical
Chapter
Chapter 9: System Design and Optimization
Edited by
Xingui He, Ertian Hua, Yun Lin and Xiaozhu Liu
Pages
554-558
DOI
10.4028/www.scientific.net/AMM.88-89.554
Citation
B. Wang, "Reliability Assessment of Power System Using Importance Sampling Technique Based on Layer Optimization Simulation", Applied Mechanics and Materials, Vols. 88-89, pp. 554-558, 2011
Online since
August 2011
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Price
$32.00
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