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Title: | Droop Coefficient Design and Optimization Using Genetic Algorithm - A Case Study of the More Electric Aircraft DC Microgrid |
Authors: | Hussaini, Habibu Yang, Tao Gao, Yuan Wang, Cheng Bai, Ge Bozhko, Serhiy |
Keywords: | Design droop coefficient droop control genetic algorithm more electric aircraf optimization |
Issue Date: | Oct-2022 |
Publisher: | IEEE |
Citation: | H. Hussaini, T. Yang, Y. Gao, C. Wang, G. Bai and S. Bozhko, "Droop Coefficient Design and Optimization Using Genetic Algorithm-A Case Study of the More Electric Aircraft DC Microgrid," IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society, Brussels, Belgium, 2022, pp. 1-6, doi: 10.1109/IECON49645.2022.9968785. |
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. |
URI: | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/17835 |
ISSN: | Electronic ISSN: 2577-1647 Print on Demand(PoD) ISSN: 1553-572X |
Appears in Collections: | Electrical/Electronic Engineering |
Files in This Item:
File | Description | Size | Format | |
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Droop Coefficient Computation Using GA FINAL FINAL.pdf | 509.27 kB | Adobe PDF | View/Open |
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