Concurrent Voltage and Frequency Regulation via Distributed Droop-Based Control Method in an Autonomous Microgrid

This paper proposes an intelligent droop-based control method for simultaneous enhanced regulation of voltage and frequency in a standalone microgrid. Droop control is renowned for its use in active and reactive power sharing, alongside voltage and frequency regulation in autonomous microgrids. It i...

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Bibliographic Details
Published in2023 IEEE AFRICON pp. 1 - 6
Main Authors Godwill Ndeh, Shu, Ngwashi, Divine Khan, Letting, Lawrence K., Louis Katche, Musong, Emmanuel, Tanyi
Format Conference Proceeding
LanguageEnglish
Published IEEE 20.09.2023
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Summary:This paper proposes an intelligent droop-based control method for simultaneous enhanced regulation of voltage and frequency in a standalone microgrid. Droop control is renowned for its use in active and reactive power sharing, alongside voltage and frequency regulation in autonomous microgrids. It is preferred over other control methods because it does not require communication systems for its implementation. Each distributed generator (DG) in a microgrid has a particular droop characteristic and it is usually interfaced with a converter. Changes in load demand give rise to a mismatch between power generation and consumption. This in turn alters the converter's output voltage with respect to the DG' \mathbf{s} droop characteristic. In case of significant load changes, the generalized droop control method fails to adequately regulate the frequency and voltage. Furthermore, line impedance variation causes poor reactive power sharing, giving rise to unequal voltage output for the different DGs. This paper presents a recurrent neural network (RNN) droop-based control method which is independent of microgrid parameters such as varied droop gains for the different DGs as well as feeder impedance mismatch. A microgrid model consisting of two DGs is developed in the MATLAB/Simulink environment and the proposed control strategy is validated through simulations The obtained results indicate a superior performance over the generalized droop control strategy with respect to the different scenarios for load change.
ISSN:2153-0033
DOI:10.1109/AFRICON55910.2023.10293370