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Engineering Proceedings
Volume 47
Issue 1
10.3390/engproc2023047006
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Proceeding Paper

Power System Dynamic Data Generation Based on Monte Carlo Simulations for Machine Learning Applications †

by
Jaime Cepeda
Departamento de Energia Electrica, Facultad de Ingenieria Electrica y Electronica, Escuela Politecnica Nacional, Quito 170525, Ecuador
†
Presented at XXXI Conference on Electrical and Electronic Engineering, Quito, Ecuador, 29 November–1 December 2023.
Eng. Proc. 2023, 47(1), 6; https://doi.org/10.3390/engproc2023047006
Published: 4 December 2023
(This article belongs to the Proceedings of XXXI Conference on Electrical and Electronic Engineering)
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Abstract

A problem with applying machine learning for analyzing power system dynamics is the lack of specific datasets. In this realm, defining a strong methodology to obtain power system dynamic data is an important task prior to the application of any machine learning tool. This is particularly important considering the current growing research in the field of self-healing grids. Thus, this paper presents a well-defined stochastic methodology that can be used to generate dynamic data that can afterwards be analyzed using machine learning tools. The proposed method is based on a Monte Carlo simulation and this paper presents the procedure to perform it.
Keywords: dynamic data; Monte Carlo simulation; probability distribution functions dynamic data; Monte Carlo simulation; probability distribution functions

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MDPI and ACS Style

Cepeda, J. Power System Dynamic Data Generation Based on Monte Carlo Simulations for Machine Learning Applications. Eng. Proc. 2023, 47, 6. https://doi.org/10.3390/engproc2023047006

AMA Style

Cepeda J. Power System Dynamic Data Generation Based on Monte Carlo Simulations for Machine Learning Applications. Engineering Proceedings. 2023; 47(1):6. https://doi.org/10.3390/engproc2023047006

Chicago/Turabian Style

Cepeda, Jaime. 2023. "Power System Dynamic Data Generation Based on Monte Carlo Simulations for Machine Learning Applications" Engineering Proceedings 47, no. 1: 6. https://doi.org/10.3390/engproc2023047006

APA Style

Cepeda, J. (2023). Power System Dynamic Data Generation Based on Monte Carlo Simulations for Machine Learning Applications. Engineering Proceedings, 47(1), 6. https://doi.org/10.3390/engproc2023047006

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