Uncertainty quantification in simulations of power systems: Multi-element polynomial chaos methods

P. Prempraneerach, F.S. Hover, M.S. Triantafyllou and G.E. Karniadakis

Reliability Engineering and System Safety, 2010, vol. 95, issue 6, 632-646

Abstract: While probabilistic methods have been used extensively in simulating stationary power systems, there has not been a systematic effort in developing suitable algorithms for stochastic simulations of time-dependent and reconfiguring power systems. Here, we present several versions of polynomial chaos that lead to a very efficient approach especially in low dimensions. We consider both Galerkin and Collocation projections, and demonstrate how the multi-element decomposition of random space leads to effective resolution of stochastic discontinuous solutions. A comprehensive comparison is presented for prototype differential equations and for two electromechanical systems used in an electric ship.

Keywords: Uncertainty analysis; Monte-Carlo simulation; Power systems (search for similar items in EconPapers)
Date: 2010
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832010000281
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:95:y:2010:i:6:p:632-646

DOI: 10.1016/j.ress.2010.01.012

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().