Capacity Planning Frameworks for Electric Vehicle Charging Stations With Multiclass Customers

Bayram, İslam Şafak; Tajer, Ali; Abdallah, Mohamed; Qaraqe, Khalid

doi:10.1109/tsg.2015.2406532

Cited by 76 publications

(33 citation statements)

References 26 publications

(51 reference statements)

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“…If the long term solution involves upgrading grid components, considering the potential cost of such investments, the practical solution for the near term would be to develop intelligent control and scheduling techniques to aid power grid operations. Bayram et al [68] proposed a model that employed pricing mechanisms to control BEV demand. Analyzing the charging requirements, charging technology, and charging characteristics for different BEV users, they proposed a framework to adapt large and small two level grids.…”

Section: Discussionmentioning

confidence: 99%

Low Purchase Willingness for Battery Electric Vehicles: Analysis and Simulation Based on the Fault Tree Model

Long

Chen

et al. 2017

Sustainability

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Purchase intention is the key to popularizing battery electric vehicles (BEVs) and to developing the industry. This study combines classical theoretical and qualitative research, and applies fault tree analysis (FTA) methods to study factors that hinder BEV purchase, and identify the logical relationship between top fault events and basic events, by calculating minimal cut sets and minimal path sets. Activity based classification analysis was used to investigate the key basic event and key event combination (i.e., minimal cut sets) that hinders purchase intention, with the effectiveness and feasibility of the proposed method verified by Monte Carlo simulation. The results indicate (1) there were 26 minimal cut sets and 18 minimal path sets in the fault tree model, and the fault tree was defined by four key event combinations and five key basic events; and (2) by reducing key events' failure probability, the probability of fault tree cumulative occurrence was reduced from 0.86021 to 0.57406 over 100,000 Monte Carlo simulations, i.e., the willingness to purchase BEVs was significantly increased. Thus, the proposed FTA method was feasible and effective for addressing low purchase intentions. Consequently, some policy implications are suggested.

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Section: Discussionmentioning

confidence: 99%

Low Purchase Willingness for Battery Electric Vehicles: Analysis and Simulation Based on the Fault Tree Model

Long

Chen

et al. 2017

Sustainability

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“…The charging rate of the EV is calculated by (13), and thus, the SOC of the EV during the charging process can be calculated by (14):…”

Section: Charging Power Modelmentioning

confidence: 99%

Effectiveness Evaluation for a Commercialized PV-Assisted Charging Station

Liu

Cheng

2017

Sustainability

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Abstract:The Photovoltaic-assisted Charging Station (PVCS) is regarded as one of the most promising charging facilities for future electric vehicle (EV) energy supplementation. In this paper, the operation mode and profitability of a commercialized PVCS are analyzed under the energy policy of China. In order to evaluate the long-term effectiveness of using the PVCS to provide guidance for the investors of the stations, a set of evaluation indexes is introduced, including the quality of service, the environmental and economic benefits, and the impacts on the grid. Furthermore, an easily-achieved charging strategy which considers the quality of service and the self-consumption of PV energy is proposed. Finally, an effectiveness evaluation for different operational scenarios of the PVCS is completed, based on the actual statistical data. The simulation and evaluation results indicate that the PVCS has the potential to produce satisfactory environmental/economic benefits and to reduce the impacts and dependence of an EV's charging load on the grid.

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“…Similarly, Sharjah of UAE has started a peak load reduction program that enforces citizens to turn off non-essential appliances during peak hours. The GCC members are gradually transforming their transportation systems from oil-based to electric-based [27,28]. Dubai is installing 100 charging stations.…”

Section: Demand Side Managementmentioning

confidence: 99%

Smart Grids and Load Profiles in the GCC Region

Bayram

2017

EAI Endorsed Transactions on Smart Cities

Self Cite

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The members of the Gulf Cooperation Council (GCC), namely Qatar, Bahrain, Saudi Arabia, Kuwait, Oman, and United Arab Emirates (UAE), are facing challenges to meet the growing electricity demand and reduce the associated hydrocarbon emissions. Recently, there has been a pressing need for a shift towards smart power grids, as smart grids can reduce the stress on the grid, defer the investments for upgrades, improve the power system efficiency, and reduce emissions. Accordingly, the goal of this paper is to delineate an overview of current smart grid efforts in the GCC region. First, we present a detailed overview of the current state of the power grids. Then, we classify the efforts into three broad categories: (i) energy trading and exchange through GCC interconnection; (ii) integration of renewable resources; and (iii) demand side management technologies for shaping the demand profile. Furthermore, we provide the details of our API object level real-time GCC power demand automated program that creates the database for the load profiles of the GCC members. Accessing such information for research and development purposes is a critical step in the region, because due the conservative structure of the governing institutes, there is no publicly available dataset. Therefore, the data provided in this paper is critical and will serve as a main reference for the future research efforts.

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Capacity Planning Frameworks for Electric Vehicle Charging Stations With Multiclass Customers

Cited by 76 publications

References 26 publications

Low Purchase Willingness for Battery Electric Vehicles: Analysis and Simulation Based on the Fault Tree Model

Low Purchase Willingness for Battery Electric Vehicles: Analysis and Simulation Based on the Fault Tree Model

Effectiveness Evaluation for a Commercialized PV-Assisted Charging Station

Smart Grids and Load Profiles in the GCC Region

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