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dc.contributor.advisorBalog, Robert S
dc.contributor.advisorAbu-Rub, Haitham
dc.creatorShadmand, Mohammad B.
dc.date.accessioned2016-05-04T13:23:43Z
dc.date.available2016-05-04T13:23:43Z
dc.date.created2015-12
dc.date.issued2015-12-14
dc.date.submittedDecember 2015
dc.identifier.urihttps://hdl.handle.net/1969.1/156521
dc.description.abstractRenewable energy sources continue to gain popularity. However, two major limitations exist that prevent widespread adoption: availability and variability of the electricity generated and the cost of the equipment. The focus of this dissertation is Model Predictive Control (MPC) for optimal sized photovoltaic (PV), DC Microgrid, and multi-sourced hybrid energy systems. The main considered applications are: maximum power point tracking (MPPT) by MPC, droop predictive control of DC microgrid, MPC of grid-interaction inverter, MPC of a capacitor-less VAR compensator based on matrix converter (MC). This dissertation firstly investigates a multi-objective optimization technique for a hybrid distribution system. The variability of a high-penetration PV scenario is also studied when incorporated into the microgrid concept. Emerging (PV) technologies have enabled the creation of contoured and conformal PV surfaces; the effect of using non-planar PV modules on variability is also analyzed. The proposed predictive control to achieve maximum power point for isolated and grid-tied PV systems speeds up the control loop since it predicts error before the switching signal is applied to the converter. The low conversion efficiency of PV cells means we want to ensure always operating at maximum possible power point to make the system economical. Thus the proposed MPPT technique can capture more energy compared to the conventional MPPT techniques from same amount of installed solar panel. Because of the MPPT requirement, the output voltage of the converter may vary. Therefore a droop control is needed to feed multiple arrays of photovoltaic systems to a DC bus in microgrid community. Development of a droop control technique by means of predictive control is another application of this dissertation. Reactive power, denoted as Volt Ampere Reactive (VAR), has several undesirable consequences on AC power system network such as reduction in power transfer capability and increase in transmission loss if not controlled appropriately. Inductive loads which operate with lagging power factor consume VARs, thus load compensation techniques by capacitor bank employment locally supply VARs needed by the load. Capacitors are highly unreliable components due to their failure modes and aging inherent. Approximately 60% of power electronic devices failure such as voltage-source inverter based static synchronous compensator (STATCOM) is due to the use of aluminum electrolytic DC capacitors. Therefore, a capacitor-less VAR compensation is desired. This dissertation also investigates a STATCOM capacitor-less reactive power compensation that uses only inductors combined with predictive controlled matrix converter.en
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectModel Predictive Controlen
dc.subjectHybrid Energy Systemsen
dc.subjectPhotovoltaic Systemsen
dc.subjectDC Microgriden
dc.subjectDroop Controlen
dc.subjectMaximum Power Point Trackingen
dc.subjectOptimizationen
dc.titleModel Predictive Control Techniques with Application to Photovoltaic, DC Microgrid, and a Multi-Sourced Hybrid Energy Systemen
dc.typeThesisen
thesis.degree.departmentElectrical and Computer Engineeringen
thesis.degree.disciplineElectrical Engineeringen
thesis.degree.grantorTexas A & M Universityen
thesis.degree.nameDoctor of Philosophyen
thesis.degree.levelDoctoralen
dc.contributor.committeeMemberBhattacharyya, Shankar P
dc.contributor.committeeMemberEnjeti, Prasad
dc.contributor.committeeMemberGautam, Natarajan
dc.type.materialtexten
dc.date.updated2016-05-04T13:23:43Z
local.etdauthor.orcid0000-0003-4455-0680


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