Dissertation/Thesis Abstract

Three-Power Power System State Estimation Using Extended Kalman Filter with CompactRIO Implementation
by Le, Raymond, M.S., Southern Illinois University at Edwardsville, 2015, 73; 1600571
Abstract (Summary)

Extended Kalman Filter is proposed to estimate in-phase and quadrature sinusoidal voltages of a three-phase power system network after they are transformed from abc natural coordinate reference frame to alpha-beta stationary reference coordinate frame to separate the positive, negative and zero sequences. Performance quality of the proposed estimation algorithm is simulated under unbalanced condition with MATLAB and LabVIEW. The feasibility of practical implementation of the proposed algorithm is deployed on a CompactRIO real-time FPGA embedded system from National Instruments and verified on a three-phase power system. This experimental setup provides highly accurate verification of the effectiveness of the estimation model. It also provides a solid demonstration of the practicability of Extended Kalman Filter applied to power system state estimation

Indexing (document details)
Advisor: Wang, Xin
Commitee: Alkin, Oktay, LeAnder, Robert
School: Southern Illinois University at Edwardsville
Department: Electrical and Computer Engineering
School Location: United States -- Illinois
Source: MAI 55/02M(E), Masters Abstracts International
Subjects: Electrical engineering
Keywords: Extended Kalman filter, Power system, State estimation
Publication Number: 1600571
ISBN: 978-1-339-09538-7
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