A conditional Monte Carlo method for estimating the failure probability of a distribution network with random demands

Document Type

Conference Proceeding

Publication Date

12-1-2011

Abstract

We consider a model of an irreducible network in which each node is subjected to a random demand, where the demands are jointly normally distributed. Each node has a given supply that it uses to try to meet its demand; if it cannot, the node distributes its unserved demand equally to its neighbors, which in turn do the same. The equilibrium is determined by solving a linear program (LP) to minimize the sum of the unserved demands across the nodes in the network. One possible application of the model might be the distribution of electricity in an electric power grid. This paper considers estimating the probability that the optimal objective function value of the LP exceeds a large threshold, which is a rare event. We develop a conditional Monte Carlo algorithm for estimating this probability, and we provide simulation results indicating that our method can significantly improve statistical efficiency. © 2011 IEEE.

Identifier

84863294168 (Scopus)

ISBN

[9781457721083]

Publication Title

Proceedings Winter Simulation Conference

External Full Text Location

https://doi.org/10.1109/WSC.2011.6148075

ISSN

08917736

First Page

3832

Last Page

3843

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