Paper Info
Title
Kalman-filter algorithm and PMUs for state estimation of distribution networks
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.
Year
DOI
Venue
2014
10.1109/IRI.2014.7051983
Information Reuse and Integration
Keywords
Field
DocType
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,Active Distribution Network,Iterated Kalman Filter,State Estimation,Weighted Least Square
Least squares,Data mining,Units of measurement,Mathematical optimization,Computer science,Distribution networks,Phasor,Algorithm,Distributed generation,Iterated function,Voltage phasors,Kalman filter algorithm
Conference
Citations 
PageRank 
References 
0
0.34
1
Authors
4
Name
Order
Citations
PageRank
Faridoon Shabaninia1216.74
Mohammad Vaziri2113.96
Amini, M.300.34
Zarghami, M.401.35