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Article
Clustering methods for the efficient voltage regulation in smart grids
The Journal of Engineering
  • Brook Abegaz, Loyola University Chicago
Document Type
Article
Publication Date
12-8-2021
Pages
274-284
Disciplines
Abstract

In this paper, clustering methods are presented to enhance the stability of automatic voltage regulators using the efficient adjustment of their respective gains. The results show that implementations of some of the clustering algorithms provide better reliability and stability for the feedback-based voltage regulators as compared to the other methods, namely, a model predictive controller (MPC), a gaussian mixture model (GMM), a self-organizing mapping (SOM) and hierarchical clustering (HC) methods. Specifically, the K-Means clustering approach (KM) provided superior stability but a slower rise time of the output voltage of the voltage regulators as compared to the other methods. Furthermore, coordination of the clustering methods is tested for a 10 machine, 39 bus power grid system. The results show that the clustering approach could be applied to improve the efficiency of voltage regulation methods in smart grids and related cyber-physical systems.

Comments

© 2021 The Authors. The Journal of Engineering published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology

https://doi.org/10.1049/tje2.12111

Creative Commons License
Creative Commons Attribution-No Derivative Works 4.0 International
Citation Information
Brook Abegaz. "Clustering methods for the efficient voltage regulation in smart grids" The Journal of Engineering Vol. 2022 Iss. 3 (2021)
Available at: http://works.bepress.com/brook-abegaz/20/