Stochastic Monitoring of Distribution Networks Including Correlated Input Variables

Author

Valverde, Gustavo ; Saric, Andrija T. ; Terzija, Vladimir

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Univ. of Liege, Liege, Belgium

Volume

28

Issue

1

fYear

2013

fDate

Feb. 2013

Firstpage

246

Lastpage

255

Abstract

The evolving complexity of distribution networks with higher levels of uncertainties is a new challenge faced by system operators. This paper introduces the use of Gaussian mixtures models as input variables in stochastic power flow studies and state estimation of distribution networks. These studies are relevant for the efficient exploitation of renewable energy sources and the secure operation of network assets.

Keywords

Gaussian processes; Monte Carlo methods; distribution networks; least squares approximations; load flow; optimisation; power system measurement; power system security; power system state estimation; renewable energy sources; stochastic processes; 69-bus radial test system; Gaussian combination; Gaussian mixtures model; Monte Carlo simulation; distribution network; input variable correlation; network asset secure operation; optimization algorithm; renewable energy source; state estimation; stochastic monitoring; stochastic power flow study; weighted least square formulation; Approximation methods; Correlation; Input variables; Power demand; Probability density function; State estimation; Stochastic processes; Distributed power generation; load flow; power system measurements; probability distribution; random variables; state estimation; uncertainty;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/TPWRS.2012.2201178

Filename

6231710