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dc.contributor.authorIslam, MR
dc.contributor.authorLu, H
dc.contributor.authorIslam, MR
dc.contributor.authorHossain, MJ
dc.contributor.authorLi, L
dc.date.accessioned2021-01-06T05:26:54Z
dc.date.available2021-01-06T05:26:54Z
dc.date.issued2020
dc.identifier.issn0093-9994en_US
dc.identifier.doi10.1109/TIA.2020.2989522en_US
dc.identifier.urihttp://hdl.handle.net/10072/400728
dc.description.abstractThe growing penetration of distributed energy sources (DES), such as photovoltaic (PV) solar power, battery energy systems and electric vehicles (EVs) into low voltage distribution networks is creating serious challenges for distribution network operators. Uncertain nature of these DES and EV charging is a key factor to cause unbalance, which degrade network performance in terms of energy loss, voltage unbalance, and voltage profile of the distribution network, etc. Some methods were proposed to mitigate such negative impact of these uncertain DES and EV charging from both centralized and decentralized approaches by controlling charging or discharging power of EVs. However, these methods involve all active EVs to participate in coordination and this causes significant inconvenience to EV owners along with requirements of complex communication infrastructure and huge data processing overhead. This article proposes an Internet of Things -based centralized control strategy to coordinate EV and DES distribution by using the differential evolution (DE) optimization algorithm. The obtained results show that the proposed control strategy can improve network performance (voltage imbalance, neutral current, energy loss, and node voltage) significantly. In addition, the control strategy is less demanding on communication infrastructure and convenient for EV owners as well as having a lighter data processing overhead.en_US
dc.description.peerreviewedYesen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.ispartofpagefrom4552en_US
dc.relation.ispartofpageto4562en_US
dc.relation.ispartofissue4en_US
dc.relation.ispartofjournalIEEE Transactions on Industry Applicationsen_US
dc.relation.ispartofvolume56en_US
dc.subject.fieldofresearchInformation and Computing Sciencesen_US
dc.subject.fieldofresearchEngineeringen_US
dc.subject.fieldofresearchcode08en_US
dc.subject.fieldofresearchcode09en_US
dc.titleAn IoT- Based Decision Support Tool for Improving the Performance of Smart Grids Connected with Distributed Energy Sources and Electric Vehiclesen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Articlesen_US
dcterms.bibliographicCitationIslam, MR; Lu, H; Islam, MR; Hossain, MJ; Li, L, An IoT- Based Decision Support Tool for Improving the Performance of Smart Grids Connected with Distributed Energy Sources and Electric Vehicles, IEEE Transactions on Industry Applications, 2020, 56 (4), pp. 4552-4562en_US
dc.date.updated2021-01-06T05:25:52Z
gro.hasfulltextNo Full Text
gro.griffith.authorHossain, Jahangir


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