Title :
Mixed integer linear programming formulation for robust state estimation
Author :
Yanbo Chen ; Feng Liu ; Shengwei Mei ; Jin Ma
Author_Institution :
State Key Lab. of Alternate Electr. Power Syst. with Renewable Energy Sources, North China Electr. Power Univ., Beijing, China
Abstract :
This paper proposes a mixed integer linear programming (MILP) formulation for robust state estimation (RSE). By using the exactly linearized measurement equations instead of the original nonlinear ones, the mixed integer nonlinear programming (MINP) formulation for RSE is converted to be a MILP one. The proposed formulation can not only guarantee to find the global optimum, but also enhance the computation efficiency significantly, making it very promising for online applications to practical large-scale power systems.
Keywords :
integer programming; linear programming; nonlinear programming; power system measurement; smart power grids; state estimation; MILP; MINP; RSE; computation efficiency; exactly linearized measurement equations; large-scale power systems; mixed integer linear programming formulation; mixed integer nonlinear programming formulation; robust state estimation; Equations; Mathematical model; Power systems; Robustness; State estimation; Vectors; State estimation; mathematical programming; robustness;
Conference_Titel :
Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2014 IEEE PES
Conference_Location :
Istanbul
DOI :
10.1109/ISGTEurope.2014.7028877
