Reduced order distributed particle filter for electric power grids

Author

Asif, Amir ; Mohammadi, Arash ; Saxena, Shanky

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., York Univ., Toronto, ON, Canada

fYear

2014

fDate

4-9 May 2014

Firstpage

7609

Lastpage

7613

Abstract

The paper develops a fusion-based, reduced order, distributed implementation of the unscented particle filter (FR/DUPF) for state estimation in complex nonlinear electric power grids (EPG). Based on partitioning the overall EPG system into n_sub localized but dynamically coupled subsystems, the near-optimal FR/DUPF provides a computational saving of up to a factor of n_sub over the centralized particle filter. In our Monte Carlo simulations of the IEEE 14-bus test system, the FR/DUPF state estimates are close to the actual values and virtually indistinguishable from the centralized particle filter.

Keywords

Monte Carlo methods; particle filtering (numerical methods); power grids; power system state estimation; reduced order systems; DUPF; EPG; FR; IEEE 14-bus test system; Monte Carlo simulations; centralized particle filter; complex nonlinear electric power grids; electric power grids; reduced order distributed particle filter; state estimation; unscented particle filter; Generators; Kalman filters; Monte Carlo methods; Power systems; State estimation; Vectors; Distributed estimation; Large scale dynamical systems; Nonlinear estimation; Particle filtering; Smart power grids;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on

Conference_Location

Florence

Type

conf

DOI

10.1109/ICASSP.2014.6855080

Filename

6855080