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dc.contributor.authorNosrat, Amiren
dc.date2010-12-24 20:53:05.425
dc.date.accessioned2016-01-18T18:33:53Z
dc.date.available2016-01-18T18:33:53Z
dc.date.issued2016-01-18
dc.identifier.urihttp://hdl.handle.net/1974/13932
dc.descriptionThesis (Master, Mechanical and Materials Engineering) -- Queen's University, 2010-12-24 20:53:05.425en
dc.description.abstractTwo identified strategies to reduce GHG emissions that threaten the global climate stability include 1)the utilization of renewable sources of energy such as solar electricity from photovoltaic (PV) devices and 2)more efficient use of fossil fuels. While electricity production through PV is considerably less harmful than conventional sources of electricity, its intermittency and frequent mismatch between peak production and peak loads has proven to be a major obstacle to wide-scale implementation. As such, coupling PV with more reliable base load electricity production technologies such as combined heat and power (CHP) has been proposed to have a significant positive impact on increasing utilization and penetration levels. To test this theory, first the simulation and optimization platform was developed to utilize these strategies for a hybrid PV and combined cooling, heating, and power (CCHP) systems aimed at both reducing life cycle costs (LCC) and emissions using multi-objective genetic algorithms. The developed platform was focused on Canada‘s residential end-use energy sector and was created as a stepping stone for larger decentralized communal residential, commercial/institutional, and industrial applications. Simulations run with the platform found that the optimization of the PV-CCHP system led to a fuel energy utilization of 83%, compared to a theoretical upper limit of 85%. These values can be compared to 68% for PV+CHP systems that did not account for cooling loads, which show the technical superiority of CCHP systems hybridized to PV. In addition, these results showed that photovoltaic grid penetration can be increased to 24% with the implementation of a distributed network of hybrid PV-CCHP systems. Furthermore, the optimized systems demonstrated significantly lower emission intensities when compared to centralized and residential scale electricity plants and residential heating equipment. While implementation of these systems provide the highest benefits in emission-intensive grids such as Alberta and Halifax, their use in hydro-intensive provinces (ie. Quebec and British Columbia) was found to have potentially rewarding environmental benefits as well depending on fuel types and efficiencies of heating systems.en
dc.language.isoengen
dc.relation.ispartofseriesCanadian thesesen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectCogenen
dc.subjectCogenerationen
dc.subjectCHPen
dc.subjectCombined Heat and Poweren
dc.subjectCCHPen
dc.subjectCombined Cooling, Heating, and Poweren
dc.subjectEnergyen
dc.subjectEnergy Conservationen
dc.subjectGreenhouse Gas Emissionsen
dc.subjectEmission Reductionsen
dc.subjectOptimizationen
dc.subjectPhotovoltaicen
dc.subjectSolar Photovoltaicen
dc.subjectSolar Penetration Levelen
dc.subjectSolar Energyen
dc.subjectTrigenerationen
dc.subjectRenewable Energyen
dc.subjectHybrid PV-CHPen
dc.titleSimulation and Optimization of Hybrid Photovoltaic (PV) and Combined Cooling, Heating, and Power (CCHP) Systems Using Multiobjective Genetic Algorithmsen
dc.typethesisen
dc.description.degreeM.A.Sc.en
dc.contributor.supervisorPearce, Joshua M.en
dc.contributor.departmentMechanical and Materials Engineeringen
dc.degree.grantorQueen's University at Kingstonen


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