Supervised machine learning-based protection for transmission line connected to PV plant

Khalfan Al Kharusi, Abdelsalam El Haffar, Mostefa Mesbah

نتاج البحث: Conference contribution

ملخص

This paper presents a supervised machine learning (ML)-based protection approach for identifying different types of transmission lines' faults, including faults during power swing, at several locations and variable fault resistances. Descriptive statistical features used in classification were extracted from spectrograms of measured signals at the relay point. Decision trees (DT)., support vector machines (SVM), k-nearest neighbors (k-NN), boosted and bagged ensemble tree classifiers were used for classification. Four feature selection algorithms, namely neighborhood component analysis (NCA), minimum redundancy maximum relevance (mRMR), sequential feature selection (SFS), and fit ensemble of learners, were applied to reduce the number of features. The synthetic minority class oversampling technique (SMOTE) balances the data to prevent biases toward the majority (non-fault) class. The results show that ensemble bagged trees with SMOTE achieve the maximum accuracy and the minimum false-negative rates. Feature selection algorithms show no improvement in the performance of the classifiers. The best classifier was then tested using data from an unseen scenario and showed accurate detection of the fault events. The classifier, however, was not able to detect faults during power swing after integrating a photovoltaic (PV) plant behind the relay point in the protected line.

اللغة الأصليةEnglish
عنوان منشور المضيفInternational Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2021
ناشرInstitute of Electrical and Electronics Engineers Inc.
رقم المعيار الدولي للكتب (الإلكتروني)9781665412629
المعرِّفات الرقمية للأشياء
حالة النشرPublished - أكتوبر 7 2021
الحدث2021 IEEE International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2021 - Mauritius, Mauritius
المدة: أكتوبر ٧ ٢٠٢١أكتوبر ٨ ٢٠٢١

سلسلة المنشورات

الاسمInternational Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2021

Conference

Conference2021 IEEE International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2021
الدولة/الإقليمMauritius
المدينةMauritius
المدة١٠/٧/٢١١٠/٨/٢١

ASJC Scopus subject areas

  • ???subjectarea.asjc.1700.1702???
  • ???subjectarea.asjc.1700.1705???
  • ???subjectarea.asjc.1700.1708???
  • ???subjectarea.asjc.1800.1802???
  • ???subjectarea.asjc.2100.2102???
  • ???subjectarea.asjc.2200.2208???
  • ???subjectarea.asjc.2200.2210???
  • ???subjectarea.asjc.2200.2213???

بصمة

أدرس بدقة موضوعات البحث “Supervised machine learning-based protection for transmission line connected to PV plant'. فهما يشكلان معًا بصمة فريدة.

قم بذكر هذا