Probabilistic optimal power flow

Author

Madrigal, Marcelino ; Ponnambalam, K. ; Quintana, Victor H.

Author_Institution

Waterloo Univ., Ont., Canada

Volume

1

fYear

1998

fDate

24-28 May 1998

Firstpage

385

Abstract

This paper presents a new formulation and solution approach to a probabilistic optimal power flow (POPF) problem. In this formulation, system demand is taken as a random vector of correlated variables, which allows us to consider the dependence between load types and locations. The POPF is clearly formulated and the optimality conditions are considered as a general nonlinear probabilistic transformation. A first-order second-moment method (FOSMM) is used to find their statistical characteristics. Computer results, and their comparisons to Monte Carlo simulation (MCS) approach, demonstrate the accuracy of our proposed methodology

Keywords

Monte Carlo methods; load flow; power systems; probability; Monte Carlo simulation; correlated variables; first-order second-moment method; load locations; load types; nonlinear probabilistic transformation; optimality conditions; power system demand; probabilistic optimal power flow; random vector; statistical characteristics; Ear; Load flow; Load forecasting; Load modeling; Moment methods; Power system modeling; Power system planning; Power system simulation; Random variables; Stochastic systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 1998. IEEE Canadian Conference on

Conference_Location

Waterloo, Ont.

ISSN

0840-7789

Print_ISBN

0-7803-4314-X

Type

conf

DOI

10.1109/CCECE.1998.682765

Filename

682765