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dc.contributor.advisorBaldick, Rossen
dc.contributor.advisorKwasinski, Alexisen
dc.creatorKwon, Youngsungen
dc.date.accessioned2016-07-28T18:42:18Z
dc.date.available2016-07-28T18:42:18Z
dc.date.issued2015-12
dc.date.submittedDecember 2015
dc.identifierdoi:10.15781/T2X05XC7Ten
dc.identifier.urihttp://hdl.handle.net/2152/39298en
dc.description.abstractPower consumption of cellular communication infrastructure has been considered as a global issue due to its exceptional growth rate. In order to address the challenges posed by the increasing power consumption such as carbon emissions, many studies have been focused on designing green cellular networks where carbon emission can be mitigated by reducing power consumption at base stations. Although the previous studies have a common theme of the power saving strategies at base stations, most studies develop the power saving techniques are restricted to cases where the electricity is supplied from conventional grid instead of renewable energy sources. The use of renewable sources poses two main issues such as large footprint and power output variability due to the variation of the natural phenomena driving the sources. This research thus aims at addressing the cellular networks power consumption issue by considering a cluster of neighboring base station in a microgrid configuration, called sustainable wireless area (SWA) that can not only reduce the carbon emission effectively by being powered from distributed renewable sources, but also overcome the renewable power output variability issue by using local energy storage and renewable power prediction two-days. In this sense, this dissertation investigates a novel approach to realize sustainable power supply in a SWA, which incorporates the design of renewable sources, energy storage, and base station electric architecture, and a power control algorithm for their operation. With the aim of mostly powering base stations from renewable sources, the power control strategies are explored based on the predicted renewable energy and battery bank state of charge (SOC). Finally, the effectiveness of the control strategies is evaluated regarding on SWA resiliency and battery bank lifetime aspects.en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.subjectMicrogridsen
dc.subjectBattery bank state of chargeen
dc.subjectRenewable energyen
dc.subjectPower consumptionen
dc.titleMicrogrids for base stations : renewable energy prediction and battery bank management for effective state of charge controlen
dc.typeThesisen
dc.date.updated2016-07-28T18:42:18Z
dc.contributor.committeeMemberArapostathis, Aristotleen
dc.contributor.committeeMemberYu, Edwarden
dc.contributor.committeeMemberHebner, Roberten
dc.description.departmentElectrical and Computer Engineeringen
thesis.degree.departmentElectrical and Computer Engineeringen
thesis.degree.disciplineElectrical and Computer engineeringen
thesis.degree.grantorThe University of Texas at Austinen
thesis.degree.levelDoctoralen
thesis.degree.nameDoctor of Philosophyen
dc.type.materialtexten


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