Assessment of public charging infrastructure push and pull rollout strategies: The case of the Netherlands

被引:48
作者
Helmus, J. R. [1 ,4 ]
Spoelstra, J. C. [2 ]
Refa, N. [3 ]
Lees, M. [1 ,5 ]
van den Hoed, R. [4 ]
机构
[1] Univ Amsterdam, Computat Sci Lab, Sci Pk 904, NL-1098 XH Amsterdam, Netherlands
[2] Technolution BV, Burg Jamessingel 1, NL-2803 WV Gouda, Netherlands
[3] ElaadNL, Utrechtseweg 310, NL-6812 AR Arnhem, Netherlands
[4] UASA, Amsterdam, Netherlands
[5] Natl Res Univ ITMO, St Petersburg 197101, Russia
关键词
EV (electric vehicle); Charging infrastructure; Key performance indicators; Policy; Rollout strategy; Supply vs demand; DATA-DRIVEN APPROACH; ELECTRIC VEHICLES; MOBILITY; DEMAND; STATIONS; NETWORKS; AREAS;
D O I
10.1016/j.enpol.2018.06.011
中图分类号
F [经济];
学科分类号
02 ;
摘要
Over recent years, numbers of electric vehicles (EVs) have shown a strong growth and sales are projected to continue to grow. For facilitating charging possibilities for EVs typically two rollout strategies have been applied; demand-driven and strategic rollout. This study focuses on determining the differences in performance metrics of the two rollout strategies by first defining key performance metrics. Thereafter, the root causes of performance differences between the two rollout strategies are investigated. This study analyzes charging data of 1,007,137 transactions on 1742 different CPs by use of 53,850 unique charging cards. This research concludes that demand-driven CPs outperform strategic CPs on weekly energy transfer and connection duration, while strategic CPs outperform their demand-driven counterparts on charging time ratio. Regarding users facilitated, there is a significant change in performance after massive EV-uptake. The root cause analysis shows effects of EV uptake and user type composition on the differences in performance metrics. This research concludes with implications for policy makers regarding an optimal portfolio of rollout strategies.
引用
收藏
页码:35 / 47
页数:13
相关论文
共 41 条
  • [1] Agentschap N. L., 2013, LAADINFRASTRUCTUUR O
  • [2] A demand-side approach to the optimal deployment of electric vehicle charging stations in metropolitan areas
    Andrenacci, N.
    Ragona, R.
    Valenti, G.
    [J]. APPLIED ENERGY, 2016, 182 : 39 - 46
  • [3] Electric vehicle charging infrastructure in Poland
    Benysek, G.
    Jarnut, M.
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2012, 16 (01) : 320 - 328
  • [4] Bessler S., 2012, World Electric Vehicle Journal, V5, P688
  • [5] Bunzeck I., 2014, P D INC SEM AMST
  • [6] CBS, 2016, CBS STAT MOT TYP LEE
  • [7] Customer-driven design of the recharge infrastructure and Vehicle-to-Grid in urban areas: A large-scale application for electric vehicles deployment
    De Gennaro, Michele
    Paffumi, Elena
    Martini, Giorgio
    [J]. ENERGY, 2015, 82 : 294 - 311
  • [8] GIS-driven analysis of e-mobility in urban areas: An evaluation of the impact on the electric energy grid
    De Gennaro, Michele
    Paffumi, Elena
    Scholz, Harald
    Martini, Giorgio
    [J]. APPLIED ENERGY, 2014, 124 : 94 - 116
  • [9] A comprehensive planning framework for electric vehicle charging infrastructure deployment in the power grid with enhanced voltage stability
    Dharmakeerthi, C. H.
    Mithulananthan, N.
    Saha, T. K.
    [J]. INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 2015, 25 (06): : 1022 - 1040
  • [10] E-Laad, 2012, HOE GAAT VERDER MET