5.2 Decomposition and importance sampling for stochastic linear models

Abstract

Linear models that have uncertain parameters with known probability distributions are called stochastic linear models. This paper focuses on the difficulties introduced by these stochastic parameters and reviews different approaches to handle them. The following solution method uses decomposition techniques and importance sampling, and its illustration is based upon a case study of a power system with random fluctuations in demand and equipment availabilities. Numerical results are presented. © 1990.