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dc.contributor.advisorJames L. Kirtley.en_US
dc.contributor.authorWang, Xuntuo(Nelson Xuntuo)en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2021-01-06T20:18:00Z
dc.date.available2021-01-06T20:18:00Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/129312
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, September, 2020en_US
dc.descriptionCataloged from student-submitted PDF of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 181-191).en_US
dc.description.abstractThe smart micro-grid is an energy network, and researchers have spent decades working on technology development. Among most existing solutions, they focus on dynamic operation and stability issues, however the smart grid still exhibit these challenges: the electric energy network has complicated system structure, high cost, and low energy efficiency in operation. In light of popular applications, this thesis analyzes the smart grid at the local (residential) level into two categories: high-power network - electric network dealing with electric vehicles (EVs), and low-power network - electronics network dealing with smart mobile phones. This thesis proposes a centralization approach to tackle these addressed problems. On the electric network side, current micro-grid systems with high penetration of electric vehicles (EVs) have a bulky and low energy efficiency system to connect solar panels and the utility with EV batteries. This work proposes a smart and efficient EV charger to be the hub to make the system more energy efficient; On the electronics network side, multi-use application requires multiple power converters, this work proposes a centralized wireless power transfer system to be the hub charging multiple phones and low power devices using the grid power. Data mining is applied to the operation analysis of the electric network on economics where optimization strategies are discussed.en_US
dc.description.statementofresponsibilityby Nelson Xuntuo Wang.en_US
dc.format.extent191 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleSmart energy solutions to smart grid challengesen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.identifier.oclc1227780758en_US
dc.description.collectionPh.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienceen_US
dspace.imported2021-01-06T20:18:00Zen_US
mit.thesis.degreeDoctoralen_US
mit.thesis.departmentEECSen_US


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