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A Machine Learning Method Creating Network Models Based on Measurements
Swedish Natl Grid Svenska Kraftnät, Market & Syst Dev Div, Sundbyberg, Sweden.;KTH Royal Inst Technol, Dept Elect Power & Energy Syst, Stockholm, Sweden..
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.ORCID iD: 0000-0002-8189-2420
Swedish Natl Grid Svenska Kraftnät, Market & Syst Dev Div, Sundbyberg, Sweden.;KTH Royal Inst Technol, Dept Elect Power & Energy Syst, Stockholm, Sweden..
Swedish Natl Grid Svenska Kraftnät, Market & Syst Dev Div, Sundbyberg, Sweden.;KTH Royal Inst Technol, Dept Elect Power & Energy Syst, Stockholm, Sweden..
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2018 (English)In: 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC), IEEE , 2018Conference paper, Published paper (Refereed)
Abstract [en]

Network models are essential to perform power flow analyses. In this paper a supervised regression method creating simplified network models using measurements is presented. It is an iterative method creating a network model by minimizing the difference between measurements and obtained power flow using measured net-exchanges for each node. The method is tested in a case study for the Nordic Synchronous Area considering each bidding zone as a node. The simplified network model is created using a training set and is validated using various validation methods. The obtained reactances are not correct in absolute terms; however results indicate that the obtained power flows using the created network model are accurate enough for several different applications.

Place, publisher, year, edition, pages
IEEE , 2018.
Keywords [en]
Machine learning, Nordic Power System, power flow analyses, simplified network model
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-238162DOI: 10.23919/PSCC.2018.8442822ISI: 000447282400121Scopus ID: 2-s2.0-85054003071OAI: oai:DiVA.org:kth-238162DiVA, id: diva2:1261441
Conference
2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC)
Note

QC 20181107

Available from: 2018-11-07 Created: 2018-11-07 Last updated: 2018-11-07Bibliographically approved

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Söder, LennartNordström, Lars

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