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dc.contributor.authorAlhazmi, Yassir
dc.date.accessioned2016-08-31 18:56:54 (GMT)
dc.date.available2016-08-31 18:56:54 (GMT)
dc.date.issued2016-08-31
dc.date.submitted2016-08-18
dc.identifier.urihttp://hdl.handle.net/10012/10766
dc.description.abstractPlug-in electric vehicles (PEVs) are growing in popularity in developed countries in an attempt to overcome the problems of pollution, depleting natural oil and fossil fuel reserves and rising petrol costs. In addition, automotive industries are facing increasing community pressure and governmental regulations to reduce emissions and adopt cleaner, more sustainable technologies such as PEVs. However, accepting this new technology depends primarily on the economic aspects for individuals and the development of adequate PEV technologies. The reliability and dependability of the new vehicles (PEVs) are considered the main public concerns due to range anxiety. The limited driving range of PEVs makes public charging a requirement for long-distance trips, and therefore, the availability of convenient and fast charging infrastructure is a crucial factor in bolstering the adoption of PEVs. The goal of the work presented in this thesis was to address the challenges associated with implementing electric vehicle fast charging stations (FCSs) in distribution system. Installing electric vehicle charging infrastructure without planning (free entry) can cause some complications that affect the FCS network performance negatively. First, the number of charging stations with the free entry can be less or more than the required charging facilities, which leads to either waste resources by overestimating the number of PEVs or disturb the drivers’ convenience by underestimate the number of PEVs. In addition, it is likely that high traffic areas are selected to locate charging stations; accordingly, other areas could have a lack of charging facilities, which will have a negative impact on the ability of PEVs to travel in the whole transportation network. Moreover, concentrating charging stations in specific areas can increase both the risk of local overloads and the business competition from technical and economic perspectives respectively. Technically, electrical utilities require that the extra load of adopting PEV demand on the power system be managed. Utilities strive for the implementation of FCSs to follow existing electrical standards in order to maintain a reliable and robust electrical system. Economically, the low PEV penetration level at the early adoption stage makes high competition market less attractive for investors; however, regulated market can manage the distance between charging stations in order to enhance the potential profit of the market. As a means of facilitating the deployment of FCSs, this thesis presents a comprehensive planning model for implementing plug-in electric vehicle charging infrastructure. The plan consists of four main steps: estimating number of PEVs as well as the number of required charging facilities in the network; selecting the strategic points in transportation network to be FCS target locations; investigating the maximum capability of distribution system current structure to accommodate PEV loads; and developing an economical staging model for installing PEV charging stations. The development of the comprehensive planning begins with estimating the PEV market share. This objective is achieved using a forecasting model for PEV market sales that includes the parameters influencing PEV market sales. After estimating the PEV market size, a new charging station allocation approach is developed based on a Trip Success Ratio (TSR) to enhance PEV drivers’ convenience. The proposed allocation approach improves PEV drivers’ accessibility to charging stations by choosing target locations in transportation network that increase the possibility of completing PEVs trips successfully. This model takes into consideration variations in driving behaviors, battery capacities, States of Charge (SOC), and trip classes. The estimation of PEV penetration level and the target locations of charging stations obtained from the previous two steps are utilized to investigate the capability of existing distribution systems to serve PEV demand. The Optimal Power Flow (OPF) model is utilized to determine the maximum PEV penetration level that the existing electrical system can serve with minimum system enhancement, which makes it suitable for practical implementation even at the early adoption rates. After that, the determination of charging station size, number of chargers and charger installation time are addressed in order to meet the forecasted public PEV demand with the minimum associated cost. This part of the work led to the development of an optimization methodology for determining the optimal economical staging plan for installing FCSs. The proposed staging plan utilizes the forecasted PEV sales to produce the public PEV charging demand by considering the traffic flow in the transportation network, and the public PEV charging demand is distributed between the FCSs based on the traffic flow ratio considering distribution system margins of PEV penetration level. Then, the least-cost fast chargers that satisfy the quality of service requirements in terms of waiting and processing times are selected to match the public PEV demand. The proposed planning model is capable to provide an extensive economic assessment of FCS projects by including PEV demand, price markup, and different market structure models. The presented staging plan model is also capable to give investors the opportunity to make a proper trade-off between overall annual cost and the convenience of PEV charging, as well as the proper pricing for public charging services.  en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.subjectPlug-in Electric Vehiclesen
dc.subjectFast Charging Stationen
dc.subjectDemand Side Managementen
dc.subjectDistribution System Planningen
dc.titlePlanning Model for Implementing Electric Vehicle Charging Infrastructure in Distribution Systemen
dc.typeDoctoral Thesisen
dc.pendingfalse
uws-etd.degree.departmentElectrical and Computer Engineeringen
uws-etd.degree.disciplineElectrical and Computer Engineering (Electric Power Engineering)en
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.degreeDoctor of Philosophyen
uws.contributor.advisorSalama, Magdy
uws.contributor.affiliation1Faculty of Engineeringen
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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