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Power System Control and Protection Models Based on Artificial Intelligence – A Tensorflow Approach Cover

Power System Control and Protection Models Based on Artificial Intelligence – A Tensorflow Approach

By: Alen Bernadić  
Open Access
|Oct 2022

Abstract

Artificial intelligence (AI) and Deep learning (DL) methods in power systems are being tested and prepared for practical use in many applications. In this work an artificial neural network models for fault identification and classification and switching logic control in middle voltage (MV) power electricity network is presented. Models are implemented in Google’s Python based tool Tensorflow with belonging program libraries. For fault detection and classification example a few thousand simulations are conducted in order to obtain enough fault current and voltage samples for high accuracy artificial neural network (ANN) with backpropagation model. Achieved accuracy and speed of presented deep learning model, open a possibility for application in digital relay protection devices. Second example is implementation of switching control rules in HV/MV substations. Presented models are patterns for power system controlling centres as part of broader controlling and protection logic.

DOI: https://doi.org/10.2478/bhee-2022-0004 | Journal eISSN: 2566-3151 | Journal ISSN: 2566-3143
Language: English
Page range: 27 - 33
Submitted on: Oct 10, 2021
Accepted on: Jun 20, 2022
Published on: Oct 13, 2022
Published by: Bosnia and Herzegovina National Committee CIGRÉ
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2022 Alen Bernadić, published by Bosnia and Herzegovina National Committee CIGRÉ
This work is licensed under the Creative Commons Attribution 4.0 License.