DocumentCode :
3720774
Title :
Kalman filtering with a new state-space model for three-phase systems: Application to the identification of symmetrical components
Author :
Anh Tuan Phan;Gilles Hermann;Patrice Wira
Author_Institution :
Laboratoire Mod?lisation, Intelligence, Processus et Syst?mes (MIPS - EA 2332), Universit? de Haute Alsace, Mulhouse, France
fYear :
2015
Firstpage :
1
Lastpage :
6
Abstract :
In electrical energy transportation challenges, power quality issues like reducing harmonic pollution, reactive power and load unbalance, necessarily have to identify the symmetrical components of the three phases in a fast and precise way. This paper introduces a new state-space model to be used with an Extended Kalman Filter (EKF) in order to estimate in real-time the symmetrical components of distorted and time-changing power systems. The proposed model is therefore able to detect and to quantify the unbalance of general three-phase power systems. Indeed, the symmetrical components of the power system, i.e., their amplitude and phase angle values, can be deduced at each iteration from the proposed state-space model. The effectiveness of the method has been evaluated. Results and comparisons of online symmetrical components identification show the efficiency of the proposed method for disturbed and changing power systems.
Keywords :
"State-space methods","Power system dynamics","Power quality","Power system stability","Kalman filters","Mathematical model"
Publisher :
ieee
Conference_Titel :
Evolving and Adaptive Intelligent Systems (EAIS), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/EAIS.2015.7368807
Filename :
7368807
Link To Document :
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