Journal
ENERGY
Volume 238, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2021.121948
Keywords
Electric vehicle (EV); Public charging stations; Geographic information system (GIS); Agent-based model; Optimal planning
Categories
Funding
- Program for Outstanding PhD Candidate of Shandong University
- China Scholarship Council
- Gustav Dahl Scholarship of MaEurolardalen University
- National Natural Science Foundation of China [U1864202]
- Shandong University Seed Fund Program for International Research Cooperation
- KK-stiftelsen (Synergi 19-FLEXERGY) [20200073]
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In this study, a novel framework is proposed to determine the optimal location and size of PCSs by considering charging behaviors and urban land uses. The model's effectiveness is demonstrated through a case study in Va euro steras, a Swedish city. Factors like charging demand, location and service range, and charging price impact the profitability and competitiveness of PCSs.
Intra-city Public Charging Stations (PCSs) play a crucial role in promoting the mass deployment of Electric Vehicles (EVs). To motivate the investment on PCSs, this work proposes a novel framework to find the optimal location and size of PCSs, which can maximize the benefit of the investment. The impacts of charging behaviors and urban land uses on the income of PCSs are taken into account. An agent based trip chain model is used to represent the travel and charging patterns of EV owners. A cell-based geographic partition method based on Geographic Information System is employed to reflect the influence of land use on the dynamic and stochastic nature of EV charging behaviors. Based on the distributed charging demand, the optimal location and size of PCSs are determined by mixed-integer linear programming. Va euro steras, a Swedish city, is used as a case study to demonstrate the model's effectiveness. It is found that the charging demand served by a PCS is critical to its profitability, which is greatly affected by the charging behavior of drivers, the location and the service range of PCS. Moreover, charging price is another significant factor impacting profitability, and consequently the competitiveness of slow and fast PCSs. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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