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Real-Time Estimation of AC-Grid Short Circuit Capacity for HVDC Control Application
KTH, School of Electrical Engineering (EES), Electric power and energy systems.ORCID iD: 0000-0003-3946-7655
KTH, School of Electrical Engineering (EES).
HVDC, ABB Sweden, Ludvika.
HVDC, ABB Sweden, Ludvika.
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2016 (English)In: IET Generation, Transmission & Distribution, ISSN 1751-8687, E-ISSN 1751-8695Article in journal (Refereed) Submitted
Abstract [en]

Being able to estimate the AC grid parameters fromthe perspective of a connected HVDC station allows adjustmentof converter control parameters or to select the converter’s operationalcontrol mode. Real-time estimation of such grid parameterscan result in more freedom for on-line or adaptive decisionsregarding the control adjustments. This paper shows that theRecursive Least Square (RLS) algorithm can be very efficientlyused such the real-time estimation of SCC. This technique formsa regression problem using algebraic complex equations with anobjective to minimize the error between estimated parametersand calculated parameters based on online measurements. ThisSCC estimation algorithm is first verified using a simple pointto point HVDC power transmission model in a non-real-timeenvironment. Thereafter, the algorithm has been reformulatedand simplified to make it non-complex without the use of matrices,in order to facilitate further implementation on an industrial realtimecontroller. The performance of the real-time implementationhas been evaluated using a HIL platform. A sensitivity analysishas been also carried out to study the impact of differentparameters and operational conditions on the performance ofestimation algorithm.

Place, publisher, year, edition, pages
Keyword [en]
estimation, HVDC, real-time, recursive least square, short circuit capacity
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-180714OAI: diva2:896373
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage

QC 20160901

Available from: 2016-01-21 Created: 2016-01-21 Last updated: 2016-09-01Bibliographically approved

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Babazadeh, DavoodMuthukrishnan, ArvindNordström, Lars
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