Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions

被引：11
作者：
de Lima T.D. [1 ]
Franco J.F. [2 ]
Lezama F. [3 ,4 ]
Soares J. [3 ,4 ]
Vale Z. [4 ]
机构：
[1] Departamento de Engenharia Elétrica, Universidade Estadual Paulista, Av. Brasil Sul, 56, Ilha Solteira,
[2] Escola de Engenharia de Energia da Universidade Estadual Paulista, Av. dos Barrageiros, 1881, Rosana
[3] GECA D, Politécnico do Porto, R. Dr. António Bernardino de Almeida, 431, Porto
[4] Politécnico do Porto, R. Dr. António Bernardino de Almeida, 431, Porto
来源：
Energy Informatics | 2021年 / 4卷 / Suppl 2期
基金：
巴西圣保罗研究基金会;
关键词：
Allocation of electric vehicle charging stations; Electric vehicle charging stations; EV charging forecast method; Renewable energy sources;
D O I：
10.1186/s42162-021-00157-5
中图分类号：
学科分类号：
摘要：
In the coming years, several transformations in the transport sector are expected, associated with the increase in electric vehicles (EVs). These changes directly impact electrical distribution systems (EDSs), introducing new challenges in their planning and operation. One way to assist in the desired integration of this technology is to allocate EV charging stations (EVCSs). Efforts have been made towards the development of EVCSs, with the ability to recharge the vehicle at a similar time than conventional vehicle filling stations. Besides, EVs can bring environmental benefits by reducing greenhouse gas emissions. However, depending on the energy matrix of the country in which the EVs fleet circulates, there may be indirect emissions of polluting gases. Therefore, the development of this technology must be combined with the growth of renewable generation. Thus, this proposal aims to develop a mathematical model that includes EVs integration in the distribution system. To this end, a mixed-integer linear programming (MILP) model is proposed to solve the allocation problem of EVCSs including renewable energy sources. The model addresses the environmental impact and uncertainties associated with demand (conventional and EVs) and renewable generation. Moreover, an EV charging forecast method is proposed, subject to the uncertainties related to the driver's behavior, the energy required by these vehicles, and the state of charge of the EVs. The proposed model was implemented in the AMPL modelling language and solved via the commercial solver CPLEX. Tests with a 24-node system allow evaluating the proposed method application. © 2021, The Author(s).
引用
收藏
相关论文
共 30 条
  • [1] Amini M.H., Islam A., Allocation of electric vehicles’ parking lots in distribution network, IEEE PES Innov Smart Grid Technol Conf ISGT, 2014, 20, pp. 1-5, (2014)
  • [2] Bagherzadeh L., Shayeghi H., Seyed-Shenava S.J., Optimal allocation of electric vehicle parking lots for minimizing distribution system costs considering uncertainties, 2019 Iran Conf Renew Energy Distrib Gener ICRE DG, 2019, pp. 19-20, (2019)
  • [3] Banol Arias N., Tabares A., Franco J.F., Lavorato M., Romero R., Robust joint expansion planning of electrical distribution systems and EV charging stations, IEEE Trans Sustain Energy, 3029, (2017)
  • [4] Cai L., Pan J., Zhao L., Shen X., Networked electric vehicles for green intelligent transportation, IEEE Commun Stand Mag, 1, 2, pp. 77-83, (2017)
  • [5] Canizes B., Soares J., Costa A., Pinto T., Lezama F., Novais P., Vale Z., Electric vehicles’ user charging behaviour simulator for a smart city, Energies, 12, 8, pp. 1-20, (2019)
  • [6] Coignard B.J., Macdougall P., Will Electric vehicles drive distribution grid upgrades, IEEE Electrification Magazine, 7, 2, pp. 46-56, (2019)
  • [7] de Lima T., Franco J.F., Lezama F., Soares J., Vale Z., Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources including CO 2 Emissions: Study Data, (2021)
  • [8] De Quevedo P.M., Munoz-Delgado G., Contreras J., Impact of electric vehicles on the expansion planning of distribution systems considering renewable energy, storage, and charging stations, IEEE Trans Smart Grid, 10, 1, pp. 794-804, (2019)
  • [9] Annual energy outlook 2020, (2020)
  • [10] Etezadi-Amoli M., Choma K., Stefani J., Rapid-charge electric-vehicle stations, IEEE Transactions on Power Delivery, 25, 3, pp. 1883-1887, (2010)
123