Power Quality Event Classification in Distribution Grids Using Machine Learning

Thet Paing Tun, Gobind Pillai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

With the penetration of non-linear loads, renewables and distributed generation with power electronic converters, solutions for maintaining good power quality have become a major concern for the stakeholders of electrical power systems. In this paper, a machine learning based model for power quality event classification is developed and tested. 16 categories of the most commonly occurring power quality events are classified by means of wavelet transform and select machine learning based methods to evaluate the best performing machine learning model. The outcome of classifications and effectiveness of machine learning methods is evaluated using the ‘Classification Learners’ application in MATLAB. The selected machine learning model is implemented in Simulink for test distribution grid circuits. The results obtained from simulation showed acceptable accuracy and performance and demonstrated the efficiency of the model in different operating conditions.
Original languageEnglish
Title of host publication2021 56th International Universities Power Engineering Conference
Subtitle of host publicationPowering Net Zero Emissions, UPEC 2021 - Proceedings
PublisherIEEE
ISBN (Electronic)9781665443890
DOIs
Publication statusPublished - 30 Sep 2021
Event56th International Universities Power Engineering Conference - Middlesbrough, United Kingdom
Duration: 31 Aug 20213 Sep 2021
https://www.ieee-pes.org/meetings-and-conferences/conference-calendar/monthly-view/166-technically-cosponsored-by-pes/883-upec-2021

Publication series

Name2021 56th International Universities Power Engineering Conference (UPEC)

Conference

Conference56th International Universities Power Engineering Conference
Abbreviated titleUPEC
Country/TerritoryUnited Kingdom
CityMiddlesbrough
Period31/08/213/09/21
Internet address

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