Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/17835
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dc.contributor.authorHussaini, Habibu-
dc.contributor.authorYang, Tao-
dc.contributor.authorGao, Yuan-
dc.contributor.authorWang, Cheng-
dc.contributor.authorBai, Ge-
dc.contributor.authorBozhko, Serhiy-
dc.date.accessioned2023-01-25T20:01:32Z-
dc.date.available2023-01-25T20:01:32Z-
dc.date.issued2022-10-
dc.identifier.citationH. 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.en_US
dc.identifier.issnElectronic ISSN: 2577-1647-
dc.identifier.issnPrint on Demand(PoD) ISSN: 1553-572X-
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/17835-
dc.description.abstractThe 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.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectDesignen_US
dc.subjectdroop coefficienten_US
dc.subjectdroop controlen_US
dc.subjectgenetic algorithmen_US
dc.subjectmore electric aircrafen_US
dc.subjectoptimizationen_US
dc.titleDroop Coefficient Design and Optimization Using Genetic Algorithm - A Case Study of the More Electric Aircraft DC Microgriden_US
dc.typeArticleen_US
Appears in Collections:Electrical/Electronic Engineering

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