Enhancing Situational Awareness: Predicting under Frequency and under Voltage Load Shedding Relay Operations

Ramin Vakili, Mojdeh Khorsand

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

Abstract

This paper proposes a machine-learning-based method to enhance online situational awareness in power systems by predicting under frequency load shedding (UFLS) and under voltage load shedding (UVLS) relay operations for several seconds after a disturbance. Voltage magnitudes/angles of electrically closest high voltage buses to the relay locations along with the relay settings are used as the input features to train random forest (RF) classifiers that predict UVLS/UFLS relay operations, respectively. A variety of contingencies considering different operation conditions and topologies of the Western Electricity Coordinating Council (WECC) system data representing the 2018 summer-peak load are studied offline using the GE positive sequence load flow analysis (PSLF) software. The results are used to create a comprehensive dataset for training and testing the classifiers. A comparison between the performances of RF models trained with different periods of input data is conducted in the presence of measurement errors.

Original languageEnglish (US)
Title of host publication2021 North American Power Symposium, NAPS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665420815
DOIs
StatePublished - 2021
Event2021 North American Power Symposium, NAPS 2021 - College Station, United States
Duration: Nov 14 2021Nov 16 2021

Publication series

Name2021 North American Power Symposium, NAPS 2021

Conference

Conference2021 North American Power Symposium, NAPS 2021
Country/TerritoryUnited States
CityCollege Station
Period11/14/2111/16/21

Keywords

  • Machine learning
  • online situational awareness
  • protection relays
  • random forest classifier
  • under frequency load shedding
  • under voltage load shedding

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems and Management
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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