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

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

Verduzco, Alejandro (Universidad Autónoma de Nuevo León)
Páramo Balsa, Paula (University of Seville)
Gonzalez-Longatt, Francisco (University of South-Eastern Norway)
Andrade, Manuel A. (Universidad Autónoma de Nuevo León)
Acosta Montalvo, Martha Nohemi (University of South-Eastern Norway)
Rueda, José L. (TU Delft Intelligent Electrical Power Grids)
Palensky, P. (TU Delft Intelligent Electrical Power Grids)

2022

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.

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

http://resolver.tudelft.nl/uuid:d06f79f0-dcb5-4bd7-b652-b82f376a09fd

https://doi.org/10.1109/ISIE51582.2022.9831751

IEEE

2023-01-25

978-1-6654-8240-0

Proceedings of the 2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)

2022 IEEE 31st International Symposium on Industrial Electronics (ISIE), 2022-06-01 → 2022-06-03, Anchorage, United States

IEEE International Symposium on Industrial Electronics, 2022-June

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.

Institutional Repository

conference paper

© 2022 Alejandro Verduzco, Paula Páramo Balsa, Francisco Gonzalez-Longatt, Manuel A. Andrade, Martha Nohemi Acosta Montalvo, José L. Rueda, P. Palensky