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Bad Data Detection Using Linear WLS and Sampled Values in Digital Substations
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.ORCID iD: 0000-0002-6330-3055
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.ORCID iD: 0000-0003-3014-5609
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2018 (English)In: IEEE Transactions on Power Delivery, ISSN 0885-8977, E-ISSN 1937-4208, Vol. 33, no 1, p. 150-157, article id 7867789Article in journal (Refereed) Published
Abstract [en]

Smart Grids employ intelligent control applications that require high quality data: fast, secure, and error free. Several researchers have focused on providing techniques for low latency and secured data links for these applications. Bad data detection is however generally provided only at the central level due to limitations in legacy technologies employed in many substations. With the introduction of IEC61850 data sharing within the substation becomes more flexible and transparent allowing more sophisticated management of data quality. Hence, this paper proposes a substation level bad data detection algorithm to facilitate also these types of requirements from applications. The algorithm is based on automatically detecting the substation topology by parsing standard substation description files and online state of circuit breakers and disconnectors. By applying linear weighted least square based state estimation algorithm, bad data from failing current transformers (CT) can be detected. By conducting the verification of different types of bad data, the results show the output of bad data detection algorithm provides higher accuracy than output from both measurement and protective CT in both static and faulty situations.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. Vol. 33, no 1, p. 150-157, article id 7867789
Keywords [en]
bad data detection, digital substation, Linear WLS, process bus, sampled values
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-222247DOI: 10.1109/TPWRD.2017.2669110Scopus ID: 2-s2.0-85041035552OAI: oai:DiVA.org:kth-222247DiVA, id: diva2:1180312
Note

QC 20180205

Available from: 2018-02-05 Created: 2018-02-05 Last updated: 2018-02-05Bibliographically approved

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Yiming, WuHohn, FabianNordström, Lars

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