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Energy Provisioning in Stand-alone and Grid-Connected Solar Powered Networks PDF

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Energy Provisioning in Stand-alone and Grid-Connected Solar Powered Networks ENERGY PROVISIONING IN STAND-ALONE AND GRID-CONNECTED SOLAR POWERED NETWORKS BY MOHAMMADSHEIKHZEFREH,B.Sc.,M.Sc. A THESIS SUBMITTED TO THE DEPARTMENT OF ELECTRICAL & COMPUTER ENGINEERING AND THE SCHOOL OF GRADUATE STUDIES OF MCMASTER UNIVERSITY IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY (cid:13)c Copyright by Mohammad Sheikh Zefreh, October 2013 All Rights Reserved DoctorofPhilosophy(2013) McMasterUniversity (Electrical&ComputerEngineering) Hamilton,Ontario,Canada TITLE: EnergyProvisioninginStand-aloneandGrid-ConnectedSo- larPoweredNetworks AUTHOR: MohammadSheikhZefreh M.Sc.,(ElectricalEngineering) IsfahanUniversityofTechnology,Isfahan,Iran SUPERVISOR: ProfessorTerenceD.Todd NUMBEROFPAGES: xviii,126 ii Abstract Solar energy is a clean and abundant renewable energy source which is currently used in manytypesofphotovoltaic(PV)designs. InpracticalPVsystems,solarpanelsareusedto harvest solarenergy and convert itinto a usableform of electricity. Due tothe intermittent nature of solar energy input however, battery storage, in combination with solar panels, mustbeusedtoprovideanuninterruptedsourceofpower. The process of assigning solar panel and battery configurations for a PV system is re- ferred to as energy resource provisioning. Unfortunately, energy provisioning costs are still relatively high, and this is one of the main obstacles that inhibits the adoption of solar power for many applications. These costs however, can be substantially reduced through cost-efficientresourceprovisioningmethods. Thefocusofthisthesisisonthedevelopment ofefficientalgorithmsandenergymanagementmethodsthatwillreduceenergyprovision- ingcostsinsolarpoweredsystems. First, we consider resource provisioning in solar powered wireless mesh networks. In practical solar powered systems, there are usually restrictions in the way that the mesh nodescanbepositioned,andthisresultsinatime-varyingandnode-dependentattenuation of the available solar energy. Unfortunately, conventional resource provisioning methods cannot take this into account and therefore the deployed system may be unnecessarily ex- pensive. Inthispartofthethesis,theresourceprovisioningproblemisconsideredfromthis iv pointofview. Wefirstreviewconventionalresourceprovisioningmechanismsandgivean examplewhichshowsthevalueofintroducingpositionalsolarinsolationawareness. APo- sition Aware Provisioning (PAP) algorithm is then introduced that takes known positional variations into consideration when performing the energy provisioning. Simulation results showthatreductionsintotalnetworkprovisioningcostcanbeobtainedusingtheproposed methodologycomparedtoconventionalalgorithms. In the second part of the thesis, we consider communication infrastructure that is oper- atedfromthepowergridwithasolarpoweredaddition. Resourceprovisioningandenergy management algorithms are introduced to minimize the capital expenditure (CAPEX) and operating expenditure (OPEX) costs. We first derive lower bounds on the costs using a linearprogramming(LP)formulationwheresolarcomponentsaresizedusingsolarinsola- tion and projected loading data. A variety of different node configurations are considered. Three energy scheduling algorithms are then introduced to optimize online OPEX costs, namely, Grid Purchase Last (GPL), Solar Load Optimization (SLO) and Solar Load Sim- ulation (SLS) algorithms. Simulation results show the extent to which a solar powered add-oncanreducetotalcost. Finally,weconsidersolarpoweredsystemswherepartoftheirenergydemandsarede- ferrable, up to some maximum tolerable delay. The objective is to exploit the flexibility of deferrableenergydemandsinawaythatdecreasesthetotalprovisioningcost. Amixedin- tegerlinearoptimizationprogramisderivedwhichgivesalowerboundontheprovisioning cost. ADelayAwareProvisioning(DAP)algorithmisthenproposedtodeterminepractical cost-efficient energy provisioning. The performance of DAP is compared to the provision- ing bound and the conventional Stand-alone Node Provisioning (SNP) algorithm. Results arepresentedwhichshowthesignificantprovisioningcostsavingsthatcanbeobtained. v Acknowledgements I would like to express my sincere gratitude to my supervisor, Professor Terence D. Todd, who patiently provided advice, guidance and encouragement throughout my doctoral pro- gramatMcMasterUniversity. IthasbeenanhonortodomyPh.D.underhissupervision. I extend my warm thanks to the members of my Ph.D. supervisory committee and to the members of the examining committee for reading my thesis and for their valuable sug- gestions. My sincere thanks also goes to Dr. George Karakostas for his helpful comments onChapter4. I would like to thank Dr. Amir A. Sayegh and Dr. Ghada H. Badawy whose helpful comments and assistance kept me going at the beginning of my Ph.D. research. I would also like to acknowledge the members of the Wireless Networking Group at McMaster University for sharing their valuable information and for providing a friendly working en- vironment. ItakethisopportunitytoparticularlythankHadiMeshgi,AbdullaA.Hammad, Hanan Hassanein, Naby Nikookaran, Maryam Mohseni and Abdulelah Alganas for their valuablehelpduringmyPh.D. My Ph.D. would not have been possible without my training at Isfahan University of Technology in Iran. I owe a great deal of gratitude to the many scholars at this university forencouragingmetopursuemydoctorate. It is difficult for me to express the level of encouragement and emotional support that vi wasconsistentlyprovidedbymyparents,whomIgreatlyrespect. Finally, thank you to my wife, Somayeh, for her selfless support, love and confidence inme. vii Abbreviations AC AlternativeCurrent BG Battery/GridConfiguration BS Basestation BUP BandwidthUsageProfile CAPEX CapitalExpenditure CPN ContinuouslyPoweredNode DAP DelayAwareProvisioningAlgorithm DC DirectCurrent EARTH EnergyAwareRadioandNetworkTechnologiesProject ER EnergyRevenue GO GridOnlyConfiguration GPL GridPurchaseLastAlgorithm GSMa GSMAssociation viii IEAP IterativeEnergyAwareProvisioning IF SolarInsolationFactor LP LinearProgramming MILP MixedIntegerLinearProgram OPEX OperatingExpenditure PAP PositionAwareProvisioningAlgorithm PBG SolarPanel/Battery/GridConfiguration PG SolarPanel/GridConfiguration PHEV Plug-inHybridElectricVehicles PV Photo-Voltaic RSD RelativeStandardDeviation SLO SolarLoadOptimizationAlgorithm SLS SolarLoadSimulationAlgorithm SNP Stand-AloneNodeProvisioning SNR SignaltoNoiseRatio SO SolarOnlyConfiguration SPP ShortestPathResourceProvisioning TOU TimeofUse ix

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