Title :
Probabilistic optimal power flow
Author :
Madrigal, Marcelino ; Ponnambalam, K. ; Quintana, Victor H.
Author_Institution :
Waterloo Univ., Ont., Canada
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;
Conference_Titel :
Electrical and Computer Engineering, 1998. IEEE Canadian Conference on
Conference_Location :
Waterloo, Ont.
Print_ISBN :
0-7803-4314-X
DOI :
10.1109/CCECE.1998.682765
