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dc.contributor.authorQian, Xiaoyan
dc.contributor.authorYang, Yun
dc.contributor.authorLi, Chendan
dc.contributor.authorTan, Siew-Chong
dc.date.accessioned2021-03-08T13:11:22Z
dc.date.available2021-03-08T13:11:22Z
dc.date.created2021-01-21T15:41:57Z
dc.date.issued2020
dc.identifier.issn2169-3536
dc.identifier.urihttps://hdl.handle.net/11250/2732199
dc.description.abstractVirtual resistance-based droop control is widely adopted as secondary-layer control for grid-connected converters in DC microgrids. This paper presents an alternative usage of the virtual resistances to minimize the total operating cost of DC microgrids under real-time pricing. The total operating cost covers the running cost of utility grids, renewable energy sources (RES), energy storage systems (ESS), fuel cells, and power loss on the distribution lines. An adaptive Differential Evolution (ADE) algorithm is adopted in this paper to optimize the virtual resistances of the droop control for the grid-connected converters of dispatchable units, such that the power flow can be regulated. The performances of the proposed strategy are evaluated by the case studies of a 12-bus 380 V DC microgrid using Matlab and a 32-bus 380 V DC microgrid using a Real-Time Digital Simulator (RTDS). Both results validate that the ADE can significantly reduce the operating cost of DC microgrids and outperform the conventional Genetic Algorithm (GA) in terms of cost saving. Comparisons among the microgrids with different numbers of dispatchable units reveal that the cost saving is more prominent when the expansion of dispatchable units.en_US
dc.language.isoengen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleOperating cost reduction of DC microgrids under real-time pricing using adaptive differential evolution algorithmen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.journalIEEE Accessen_US
dc.identifier.doihttps://doi.org/10.1109/ACCESS.2020.3024112
dc.identifier.cristin1876732
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal