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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/27010
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dc.contributor.advisorBAUMAN, JENNIFER-
dc.contributor.authorMOBARAK, MUHAMMAD HOSNEE-
dc.date.accessioned2021-10-07T17:47:55Z-
dc.date.available2021-10-07T17:47:55Z-
dc.date.issued2021-
dc.identifier.urihttp://hdl.handle.net/11375/27010-
dc.description.abstractElectric vehicles (EV) have become very popular in recent years because they are a more sustainable, efficient, and environmentally friendly transportation option than traditional fossil-fuel vehicles. Increased EV charging can cause overheating, accelerated aging, and eventual early failure of the distribution transformers, as the distribution networks have not been established foreseeing a large number of EVs as loads. This thesis makes contributions in two main areas to help reduce the accelerated aging of distribution transformers as the number of EVs on the road continues to rise. Firstly, vehicle smart charging is investigated to spread out the EV charging loads and hence decrease transformer heating and aging. Most EV smart charging algorithms require the use of extensive and costly infrastructure, including sensors, communication networks, controllable chargers, and central smart agents. This thesis proposes a new vehicle-directed smart charging strategy, called Random-In-Window (RIW) which allows individual vehicles to spread out their charging without any costly additional infrastructure. Detailed simulation results prove the advantages of this proposed algorithm. Secondly, to further reduce EV charging loads on the grid, a large-scale solar-charged electric vehicle (SEV) is proposed. While RIW smart charging has only grid benefits, SEVs can contribute to grid benefit, driver benefit, and environmental benefit, as shown through detailed simulation results, making it a viable solution to transformer aging mitigation. To turn the SEV concept into reality, this research also proposes a fast maximum power point tracking algorithm for partially shaded conditions, and an algorithm which optimizes photovoltaic (PV) cell size and arrangement along with the power electronic converter design for on-board solar charging. Thus, the proposed solutions in this research can help reduce distribution transformer aging as EV penetrations continue to rise and increase the environmental benefits of EVs through optimized solar charging.en_US
dc.language.isoen_USen_US
dc.subjectElectric Vehicleen_US
dc.subjectSmart Chargingen_US
dc.subjectSolar Energyen_US
dc.subjectMPPTen_US
dc.subjectGMPPTen_US
dc.subjectOptimizationen_US
dc.subjectSolar-charged Electric Vehicleen_US
dc.titleMitigation of Electric Vehicle Charging Effects on Distribution Grids Through Smart-Charging and On-board Solar Chargingen_US
dc.typeThesisen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.description.degreetypeThesisen_US
dc.description.degreeDoctor of Philosophy (PhD)en_US
dc.description.layabstractOverheating, accelerated aging, and eventual early failure of the distribution transformers caused by EV charging stress is a pressing concern that needs to be addressed. This thesis proposes two new vehicle-directed smart charging strategies and a concept of solar-charged electric vehicle (SEV) to help reduce the accelerated aging of distribution transformers. System level analysis of the mitigation of transformer aging using these two approaches with added driver and environmental benefits warrants the manufacturing and design challenges of the SEVs. Thus, this thesis proposes a fast and novel global maximum power point tracking algorithm well suited to fast moving vehicles for maximum solar power extraction at all times, especially during partial shading conditions, and an optimization process of the on-board PV cell dimension and number of such cells in series and parallel in the array based on power electronic converter for higher efficiency, lower cost, and lower mass.en_US
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