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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01wh246s255
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dc.contributor.advisorJha, Niraj Ken_US
dc.contributor.authorChuah, Jun Weien_US
dc.contributor.otherElectrical Engineering Departmenten_US
dc.date.accessioned2013-09-16T17:26:38Z-
dc.date.available2013-09-16T17:26:38Z-
dc.date.issued2013en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01wh246s255-
dc.description.abstractEnergy is one of the most important resources required by modern human society. In 2010, energy expenditures represented 10% of global gross domestic product (GDP). By 2035, global energy consumption is expected to increase by more than 50% from current levels. The increased pace of global energy consumption leads to significant environmental and socioeconomic issues: (i) carbon emissions, from the burning of fossil fuels for energy, contribute to global warming, and (ii) increased energy expenditures lead to reduced standard of living. Efficient use of energy, through energy conservation measures, is an important step toward mitigating these effects. Residential and commercial buildings represent a prime target for energy conservation, comprising 21% of global energy consumption and 40% of the total energy consumption in the United States. This thesis describes techniques for the analysis and optimization of building energy consumption. The thesis focuses on building retrofits and building energy simulation as key areas in building energy optimization and analysis. The thesis first discusses and evaluates building-level renewable energy generation as a solution toward building energy optimization. The thesis next describes a novel heating system, called localized heating. Under localized heating, building occupants are heated individually by directed radiant heaters, resulting in a considerably reduced heated space and significant heating energy savings. To support localized heating, a minimally-intrusive indoor occupant positioning system is described. The thesis then discusses occupant-level sensing (OLS) as the next frontier in building energy optimization. OLS captures the exact environmental conditions faced by each building occupant, using sensors that are carried by all building occupants. The information provided by OLS enables fine-grained optimization for unprecedented levels of energy efficiency and occupant comfort. The thesis also describes a retrofit-oriented building energy simulator, ROBESim, that natively supports building retrofits. ROBESim extends existing building energy simulators by providing a platform for the analysis of novel retrofits, in addition to simulating existing retrofits. Using ROBESim, retrofits can be automatically applied to buildings, obviating the need for users to manually update building characteristics for comparisons between different building retrofits. ROBESim also includes several ease-of-use enhancements to support users of all experience levels.en_US
dc.language.isoenen_US
dc.publisherPrinceton, NJ : Princeton Universityen_US
dc.relation.isformatofThe Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the <a href=http://catalog.princeton.edu> library's main catalog </a>en_US
dc.subjectBuilding energy analysisen_US
dc.subjectBuilding energy optimizationen_US
dc.subjectGreen buildingsen_US
dc.subjectLocalized heatingen_US
dc.subjectOccupant-level sensingen_US
dc.subjectROBESimen_US
dc.subject.classificationElectrical engineeringen_US
dc.subject.classificationComputer engineeringen_US
dc.titleAnalysis and Optimization of Building Energy Consumptionen_US
dc.typeAcademic dissertations (Ph.D.)en_US
pu.projectgrantnumber690-2143en_US
Appears in Collections:Electrical Engineering

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