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dc.contributor.advisorMarija D. Ilić.en_US
dc.contributor.authorMiao, Xia,Ph.D.Massachusetts Institute of Technology.en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2020-11-03T20:30:32Z
dc.date.available2020-11-03T20:30:32Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/128321
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2020en_US
dc.descriptionCataloged from PDF of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 136-144).en_US
dc.description.abstractIn this thesis we study the problem of enabling autonomous electrical energy systems (AEESs) by means of distributed control. We first propose a modular modeling approach that represents a general electrical energy system (EES) as a negative feedback configuration comprising a planar electrical network subsystem and a subsystem of single-port components. The input-output specifications of all components are in terms of power and voltage. This mathematical modeling supports the basic physical functionality of balancing power supply and demand at the acceptable Quality of Service (QoS). These input-output specifications are met by the controllable components equipped with the newly proposed distributed control. We show that these controllers enable stable and feasible system-level closed-loop dynamics. Moreover, an interactive algorithm for autonomous adjustments of their controller set points based on the information exchange with neighboring components is introduced. This serves as a proof-of-concept illustration of how components adjust their power and voltage toward a system-level equilibrium. Such process is the basis for autonomous reconfigurable operation of small microgrids. As the first step toward scaling up the proposed concepts, we consider the problem of enhanced automatic generation control (E-AGC) for systems with highly dynamic load variations, including effects of intermittent renewable generation. Further work is needed to fully generalize this approach for control design of large-scale EES. In addition to theoretical results, we also report the results of several numerical and hardware tests. These show the effectiveness of the proposed approach in fairly complex scenarios, including unplanned large faults and hard-to-predict fast-varying power disturbances.en_US
dc.description.statementofresponsibilityby Xia Miao.en_US
dc.format.extent144 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.titleToward distributed control for autonomous electrical energy systemsen_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.oclc1201325621en_US
dc.description.collectionPh.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienceen_US
dspace.imported2020-11-03T20:30:30Zen_US
mit.thesis.degreeDoctoralen_US
mit.thesis.departmentEECSen_US


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