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Centralized Versus Distributed State Estimation for Hybrid AC/HVDC Grid
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0003-3946-7655
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2017 (English)In: IEEE International Conference on Innovative Smart Grid Technologies, (ISGT Europe 2017), IEEE conference proceedings, 2017Conference paper, Published paper (Refereed)
Abstract [en]

The need of transmission grid expansion has drawnthe attention towards high voltage DC (HVDC) as a solution.This brings new challenges for power system control applicationsuch as state estimation that are originally designed for AC powersystem. This papers studies centralized and distributed architecturesfor hybrid AC/HVDC state estimator (SE). Furthermore,the benefit of having bad data detection (BDD) and deployingphasor measurement units (PMU) in the state estimation areinvestigated. The method used for the SE is the weighted leastsquare (WLS) method. The SE will be developed based on thepower grid model ’The CIGRE B4 DC Grid Test System’. Theresults of the tests show that the addition of BDD and PMUimproved the error of the estimated values. Furthermore thedistributed architecture offered slightly less accurate AC valuesthan the centralized.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2017.
Keyword [en]
HVDC transmission, phase measurement units, state estimation, voltage source converter, weighted least square
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-209842OAI: oai:DiVA.org:kth-209842DiVA: diva2:1114919
Conference
IEEE International Conference on Innovative Smart Grid Technologies, (ISGT Europe 2017), 26 Sep - 29 Sep 2017, Torino, Italy
Note

QC 20171002

Available from: 2017-06-26 Created: 2017-06-26 Last updated: 2017-10-02Bibliographically approved

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