Droop Coefficient Design and Optimization Using Genetic Algorithm-A Case Study of the More Electric Aircraft DC Microgrid

Hussaini, Habibu; Yang, Tao; Gao, Yuan; Wang, Cheng; Bai, Ge; Bozhko, Serhiy

Abstract

The droop control method is usually employed in the DC microgrids to share the load current demand among multiple sources due to its advantage of being independent of a communication network. However, the performance of the droop control method is affected by the mismatched transmission line resistance and the offset in the nominal voltage reference. This paper presents the design and optimization of the droop coefficient of converters, using the genetic algorithm to enhance the current sharing and the DC bus voltage regulation performance. The proposed approach is tested on the single bus multi-source electrical power system (EPS) for the more electric aircraft (MEA) applications. The effectiveness of the proposed approach is validated using a detailed simulation model of the MEA EPS developed in MATLAB Simulink.

Citation

Hussaini, H., Yang, T., Gao, Y., Wang, C., Bai, G., & Bozhko, S. (2022, October). Droop Coefficient Design and Optimization Using Genetic Algorithm-A Case Study of the More Electric Aircraft DC Microgrid. Presented at IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society, Brussels, Belgium

• Presentation Conference Type: Edited Proceedings
• Conference Name: IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society
• Start Date: Oct 17, 2022
• End Date: Oct 20, 2022
• Acceptance Date: Oct 17, 2022
• Online Publication Date: Dec 9, 2022
• Publication Date: Oct 17, 2022
• Deposit Date: Nov 19, 2024
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Pages: 3606-3611
• Series ISSN: 2577-1647
• Book Title: IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society
• ISBN: 978-1-6654-8026-0
• DOI: https://doi.org/10.1109/IECON49645.2022.9968785
• Public URL: https://nottingham-repository.worktribe.com/output/15432137
• Publisher URL: https://ieeexplore.ieee.org/document/9968785