Document Type

Article

Publication Date

6-10-2022

Publication Title

International Transactions on Electrical Energy Systems

Volume

2022

Pages

13

Publisher Name

Wiley & Hindawi

Abstract

The state-estimation and optimal control of multigeneration systems are challenging for wide-area systems having numerous distributed automatic voltage regulators (AVR). This paper proposes a modified Q-learning method and algorithm that aim to improve the convergence of the approach and enhance the dynamic response and stability of the terminal voltage of multiple generators in the experimental Western System Coordinating Council (WSCC) and large-scale IEEE 39-bus test systems. The large-scale experimental testbed consists of a six-area, 39-bus system having ten generators that are connected to ten AVRs. The implementation shows promising results in providing stable terminal voltage profiles and other system parameters across a wide range of AVR systems under different test scenarios including N-1 contingency and fault conditions. The approach could provide significant stability improvement for wide-area systems as compared to the implementation of conventional methods such as using standalone AVR and/or power system stabilizers (PSS) for the wide-area control of power systems.

Comments

Author Posting © 2022 Brook W. Abegaz and Sina Zarrabian. This article is posted here by permission of Wiley & Hindawi for personal use and redistribution. This article was published open access in International Transactions on Electrical Energy Systems, Volume.2022, (June 10, 2022), https://doi.org/10.1155/2022/3047761

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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