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Real-time reduced steady state model synthesis of active distribution networks using PMU measurements
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. KTH The Royal Institute of Technology. (SmarTSLab)ORCID iD: 0000-0003-3488-533X
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. KTH The Royal Institute of Technology. (SmarTSLab)ORCID iD: 0000-0002-6090-1674
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0003-0988-7624
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2016 (English)In: IEEE Transactions on Power Delivery, ISSN 0885-8977, E-ISSN 1937-4208, Vol. 32, no 1, 546-555 p.Article in journal (Refereed) Published
Abstract [en]

Due to the increase of generation sources in distribution networks, it is becoming more and more complex to develop and maintain models of these networks. Network operators need to determine reduced models of distribution networks to be used in grid management functions. This paper presents a novel method that synthesizes steady state models of unbalanced active distribution networks by the use of dynamic measurements (time series) from PMUs. As PMU measurements may contain errors and bad data, the paper presents the application of a Kalman Filter technique for real-time data processing. In addition, PMU data captures the power system’s response at different time-scales, which are generated by different types of power system events; the presented Kalman Filter has been improved to extract the steady state component of the PMU measurements to be fed to the steady state model synthesis application. Performance of the proposed methods has been assessed by real-time hardware-in-the-loop simulations on a sample distribution network.

Place, publisher, year, edition, pages
IEEE Press, 2016. Vol. 32, no 1, 546-555 p.
Keyword [en]
active distribution network, Kalman Filter (KF), model synthesis, PMU
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-192943DOI: 10.1109/TPWRD.2016.2602302ISI: 000394539200059Scopus ID: 2-s2.0-85010664762OAI: oai:DiVA.org:kth-192943DiVA: diva2:973983
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QC 20160928

Available from: 2016-09-23 Created: 2016-09-23 Last updated: 2017-10-16Bibliographically approved

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Mahmood, FarhanHooshyar, HosseinVanfretti, Luigi

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