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  4. Sequential Discrete Kalman Filter for Real-Time State Estimation in Power Distribution Systems: Theory and Implementation
 
research article

Sequential Discrete Kalman Filter for Real-Time State Estimation in Power Distribution Systems: Theory and Implementation

Kettner, Andreas Martin  
•
Paolone, Mario  
2017
IEEE Transactions on Instrumentation and Measurement

This paper demonstrates the feasibility of implementing real-time state estimators for active distribution networks in field-programmable gate arrays (FPGAs) by presenting an operational prototype. The prototype is based on a linear state estimator that uses synchrophasor measurements from phasor measurement units. The underlying algorithm is the sequential discrete Kalman filter (SDKF), an equivalent formulation of the DKF for the case of uncorrelated measurement noise. In this regard, this paper formally proves the equivalence of SDKF and the DKF, and highlights the suitability of the SDKF for an FPGA implementation by means of a computational complexity analysis. The developed prototype is validated using a case study adapted from the IEEE 34-node distribution test feeder.

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Type
research article
DOI
10.1109/TIM.2017.2708278
Web of Science ID

WOS:000407451100016

Author(s)
Kettner, Andreas Martin  
Paolone, Mario  
Date Issued

2017

Publisher

Institute of Electrical and Electronics Engineers

Published in
IEEE Transactions on Instrumentation and Measurement
Volume

66

Issue

9

Start page

2358

End page

2370

Subjects

Active Distribution Network (ADN)

•

Field-Programmable Gate Array (FPGA)

•

Phasor Measurement Unit (PMU)

•

Real-Time State Estimator (RTSE)

•

Sequential Discrete Kalman Filter (SDKF)

•

EPFL-Smartgrids

•

COMMELEC-NRP70

•

epfl-smartgrids

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
DESL  
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/138610
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