Modeling of HVDC in Dynamic State Estimation Using Unscented Kalman Filter Method

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5 Citations (Scopus)

Abstract

HVDC transmission is an integral part of various power system networks. This article presents an Unscented Kalman Filter dynamic state estimator algorithm that considers the presence of HVDC links. The AC - DC power flow analysis, which is implemented as power flow solver for Dynamic State Estimation (DSE), creates an updated admittance matrix. First, a hybrid AC/DC network model is developed to combine the AC network and DC links. Then a non-linear state estimator can solve for hybrid AC/DC states by applying the unscented Kalman filter (UKF) algorithm. It is demonstrated that UKF is easy to implement and accurate in estimation. The dynamic state variables of multi-machine power systems, which are generator rotor speed and rotor angle, are estimated to study transient behavior of the power system network. Finally, a dynamic state estimation model is built for a 14 bus power system network to evaluate the proposed algorithm for hybrid AC/DC networks.
Original languageEnglish
Title of host publicationProceedings of 2016 IEEE International Energy Conference (ENERGYCON)
Number of pages6
Place of PublicationLeuven
PublisherIEEE Press
Publication dateApr 2016
ISBN (Electronic)978-1-4673-8463-6
DOIs
Publication statusPublished - Apr 2016
EventIEEE International Energy Conference (ENERGYCON) 2016 - KU Leuven, Leuven, Belgium
Duration: 4 Apr 20168 Apr 2016
http://www.ieee-energycon2016.org/

Conference

ConferenceIEEE International Energy Conference (ENERGYCON) 2016
LocationKU Leuven
CountryBelgium
CityLeuven
Period04/04/201608/04/2016
Internet address

Keywords

  • HVDC Transmission
  • Power System Transients
  • Power System Stability
  • State Estimation

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