Detection and Identification of Generator Disconnection Using Multi-layer Perceptron Neural Network Considering Low Inertia Scenario

Alejandro Verduzco, Paula Páramo Balsa, Francisco Gonzalez-Longatt, Manuel A. Andrade, Martha Nohemi Acosta Montalvo, José Luis Rueda, Peter Palensky

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

15 Downloads (Pure)

Abstract

This research paper presents a method that uses measurements of voltages angles, as provided by phasor measurement units (PMU), to accurately detect the sudden disconnection of a generation unit from a power grid. Results in this research paper have demonstrated, in a practical fashion, that a multi-layer perceptron (MLP) neural network (NN) can be appropriately trained to detect and identify the sudden disconnection of a generation unit in a multi-synchronous generation unit power system. Synthetic time-series bus voltage angles considering low inertia scenarios in the IEEE 39 bus system were used to train the MLP NN. The training process is speeded up by using four GPUs hardware. The simulations results have confirmed the successful detection and identification of the generator outage.
Original languageEnglish
Title of host publicationProceedings of the 2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)
PublisherIEEE
Pages424-429
Number of pages6
ISBN (Electronic)978-1-6654-8240-0
ISBN (Print)978-1-6654-8240-0
DOIs
Publication statusPublished - 2022
Event2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) - Anchorage, United States
Duration: 1 Jun 20223 Jun 2022
Conference number: 31st

Publication series

NameIEEE International Symposium on Industrial Electronics
Volume2022-June

Conference

Conference2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)
Country/TerritoryUnited States
CityAnchorage
Period1/06/223/06/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Artificial neural network
  • deep learning
  • machine learning
  • outage detection and identification
  • power system dynamics

Fingerprint

Dive into the research topics of 'Detection and Identification of Generator Disconnection Using Multi-layer Perceptron Neural Network Considering Low Inertia Scenario'. Together they form a unique fingerprint.

Cite this