JOURNAL ARTICLE

Enhancing DC Microgrids Stability by Integrating DAB Converters with Consensus Algorithms for Bus Voltage Drop Mitigation.

  • Published In: IEEJ Transactions on Electrical & Electronic Engineering, 2025, v. 20, n. 3. P. 475 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Pham, Minh Duc; Tran, Nguyen Dang Khoa; Truong, Phuoc Hoa; Nguyen, Duc Hung 3 of 3

Abstract

Renewable energy sources (RESs) have become a prominent trend in the development of energy systems in many countries. To manage RESs, microgrids have emerged as an efficient and optimal solution. However, a microgrid might occasionally have problems like overloading and voltage sag. To address this problem, this paper proposes a technique that combines a consensus algorithm and a dual active bridge (DAB) to transfer energy between two different microgrids. A detection technique for overloading and voltage sag is part of the proposed control approach. In these circumstances, the DAB facilitates consensus adjustments to the stable microgrid current to bring it into balance with the overloaded current. By applying this proposed control method, voltage drops are significantly reduced, leading to an improvement in the power system quality. The simulation results of the microgrid and a scaled‐down laboratory system are conducted to verify the feasibility of the proposed control scheme. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:IEEJ Transactions on Electrical & Electronic Engineering. 2025/03, Vol. 20, Issue 3, p475
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2025
  • ISSN:1931-4973
  • DOI:10.1002/tee.24198
  • Accession Number:183820497
  • Copyright Statement:Copyright of IEEJ Transactions on Electrical & Electronic Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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