Online Learning-based Islanding Detection Scheme for Grid-Connected Systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU145957" target="_blank" >RIV/00216305:26220/22:PU145957 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9907714" target="_blank" >https://ieeexplore.ieee.org/document/9907714</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Online Learning-based Islanding Detection Scheme for Grid-Connected Systems
Original language description
Data aggregation in smart grids is a key component for emergency responses during abnormalities in the grid. To efficiently utilize the aggregated data, and achieve fast identification of these abnormalities, this paper develops an online islanding detection approach. The development of the technique is realized with an online learning algorithm implemented using the large-scale support vector machine (LaSVM). The algorithm adopts a classification problem for islanding detection in grid-connected systems by considering a set of independent variables and unknown variables. The independent variables are related to the known islanding events in the grid-connected system, and the unknown variables are related to the dynamics of the grid operating in real-time. The proposed approach solves this problem by training the known and unknown variables and identifying new instances through sequential minimal optimization. The training and validation results provided indicate 99.8 % accuracy for islanding detection under standard operating conditions of the grid-connected system.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2022 24th European Conference on Power Electronics and Applications (EPE'22 ECCE Europe)
ISBN
978-9-0758-1539-9
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
1-10
Publisher name
Neuveden
Place of publication
neuveden
Event location
Hannover
Event date
Sep 5, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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