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Center of Inertia Frequency Estimation Using Deep Learning Algorithm Cover

Center of Inertia Frequency Estimation Using Deep Learning Algorithm

By: Emir Nukić and  Tatjana Konjić  
Open Access
|Oct 2022

Abstract

Increasing the number of generation units connected to the grid via power electronic devices potentially implies negative impacts on the power system frequency stability and, depending on the power system inertia value, implies the necessary contribution of wind power plants to inertial response of the system. An alternative approach to the active power control of wind power plants, without the impact of local frequency deviation on the output power, is the application of a control strategies based on the center of inertia frequency. Since control schemes based on the input variable of the center of inertia frequency require a satisfactory level of signal transmission capacity in real time and the advanced telecommunication infrastructure of the power system, the paper considers an alternative approach to estimate the input signal value. According to the developed long short-term memory recurrent neural network, paper presents the idea of center of inertia frequency estimation by monitoring the speed of several generators in the system and passing the sequence of input data for a certain time interval, after the occurrence of imbalance, to the artificial intelligence module.

DOI: https://doi.org/10.2478/bhee-2021-0012 | Journal eISSN: 2566-3151 | Journal ISSN: 2566-3143
Language: English
Page range: 4 - 13
Submitted on: Sep 1, 2021
Accepted on: Nov 1, 2021
Published on: Oct 26, 2022
Published by: Bosnia and Herzegovina National Committee CIGRÉ
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2022 Emir Nukić, Tatjana Konjić, published by Bosnia and Herzegovina National Committee CIGRÉ
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.