Kalman-filter algorithm and PMUs for state estimation of distribution networks

Author

Shabaninia, F. ; Vaziri, M. ; Amini, M. ; Zarghami, M. ; Vadhava, S.

Author_Institution

Shiraz Univ., Shiraz, Iran

fYear

2014

Firstpage

868

Lastpage

873

Abstract

Availability of data from Phasor Measurement Units (PMUs), characterized by their high accuracy to measure node voltage phasors, allows a simplification of the State Estimation (SE) problems. In this paper Iterated Kaiman Filter (IKF) algorithm, as a new method, has been used for SE of a test Active Distributed Network (ADN) integrating PMU measurements. In order to validate the results, Weighted Least Squares (WLS) method, as a common way for SE problems, is simulated. In this case study, IEEE 13-bus test system is used with considering one Distributed Generation (DG). Simulation results show the proper performance of the IKF method.

Keywords

Kalman filters; distributed power generation; iterative methods; least mean squares methods; phasor measurement; power system state estimation; ADN; IEEE 13-bus test system; IKF method; PMU measurement integration; SE problems; WLS method; active distributed network; distributed generation; iterated Kalman filter; node voltage phasor measurement; phasor measurement unit; state estimation; weighted least squares; Covariance matrices; Kalman filters; Measurement uncertainty; Phasor measurement units; Power measurement; State estimation; Voltage measurement; Active Distribution Network; Iterated Kalman Filter; State Estimation; Weighted Least Square;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Reuse and Integration (IRI), 2014 IEEE 15th International Conference on

Type

conf

DOI

10.1109/IRI.2014.7051983

Filename

7051983