Optimal location of battery electric vehicle charging stations in urban areas: A new approach

ABSTRACT Battery electric vehicles (BEV) are increasingly seen as one of the most suitable alternatives to internal combustion engine vehicles. An important issue involved in the dissemination of BEV relates with the deployment of the respective charging network and, in particular, with the locations of charging stations. Typically, the locations selected correspond to popular places such as city centers, shopping areas, train stations, and university campuses. Although these places are highly visible, the low parking times and high rotation rates often observed there could deliver an inadequate solution for the daily charging needs of users. In this article, a new approach to determine the location of BEV charging stations in urban areas is proposed. The approach relies on a detailed analysis of BEV charging needs, charging coverage, and adoption potential, as well as on an innovative type of location-allocation model. The usefulness of the approach is demonstrated for a set of hypothetical instances replicating the essential ingredients of real-world charging station location problems.

[1]  Kenneth S Kurani,et al.  Estimating the early household market for light-duty hydrogen-fuel-cell vehicles and other “Mobile Energy” innovations in California: A constraints analysis ☆ , 2006 .

[2]  Franklin Farell.  Roadmap to a Single European Transport Area: Towards a competitive and resource efficient transport system , 2014 .

[3]  Other.  The European environment - State and outlook 2010. Synthesis (Folder+SoER) , 2010 .

[4]  Zvi Drezner,et al.  Generalized coverage: New developments in covering location models , 2010, Comput. Oper. Res..

[5]  M. Kuby,et al.  A Model for Location of Capacitated Alternative-Fuel Stations , 2009 .

[6]  Other.  The contribution of transport to air quality: TERM 2012: Transport indicators tracking progress towards environmental targets in Europe , 2012 .

[7]  Peter G Furth,et al.  Optimal Bus Stop Spacing Through Dynamic Programming and Geographic Modeling , 2000 .

[8]  Alan T. Murray.  Strategic analysis of public transport coverage , 2001 .

[9]  Mark S. Daskin,et al.  What you should know about location modeling , 2008 .

[10]  R. Tay,et al.  New Vehicle Consumption and Fuel Efficiency: A Nested Logit Approach 1 1 An earlier version of this , 1998 .

[11]  Yong Zhang,et al.  Analyzing public awareness and acceptance of alternative fuel vehicles in China: The case of EV , 2011 .

[12]  Pierre Hansen,et al.  Variable neighborhood search: Principles and applications , 1998, Eur. J. Oper. Res..

[13]  Andrew F. Burke,et al.  Batteries and Ultracapacitors for Electric, Hybrid, and Fuel Cell Vehicles , 2007, Proceedings of the IEEE.

[14]  Ying-Wei Wang,et al.  Locating Passenger Vehicle Refueling Stations , 2010 .

[15]  Horst A. Eiselt,et al.  Location analysis: A synthesis and survey , 2005, Eur. J. Oper. Res..

[16]  Pavlos S. Kanaroglou,et al.  Household demand and willingness to pay for clean vehicles , 2007 .

[17]  Pierre Hansen,et al.  Variable Neighborhood Search , 2018, Handbook of Heuristics.

[18]  David L. Waltz,et al.  Vehicle Electrification: Status and Issues , 2011, Proceedings of the IEEE.

[19]  R. van Nes,et al.  Importance of Objectives in Urban Transit-Network Design , 2000 .

[20]  António Pais Antunes,et al.  Optimal Location of Charging Stations for Electric Vehicles in a Neighborhood in Lisbon, Portugal , 2011 .

[21]  Ulrich Eberle,et al.  Sustainable transportation based on electric vehicle concepts: a brief overview , 2010 .

[22]  Zvi Drezner,et al.  The gradual covering decay location problem on a network , 2003, Eur. J. Oper. Res..

[23]  Zuo-Jun Max Shen,et al.  Infrastructure Planning for Electric Vehicles with Battery Swapping , 2012, Manag. Sci..

[24]  K. Train,et al.  Forecasting new product penetration with flexible substitution patterns , 1998 .

[25]  Daniel Sperling,et al.  Testing Electric Vehicle Demand in `Hybrid Households' Using a Reflexive Survey , 1996 .

[26]  José Manuel Viegas,et al.  A new approach to modelling distance-decay functions for accessibility assessment in transport studies , 2013 .

[27]  C. C. Chan,et al.  The State of the Art of Electric, Hybrid, and Fuel Cell Vehicles , 2007, Proceedings of the IEEE.

[28]  Adam Szczepanek,et al.  Fast Charging vs. Slow Charging: Pros and cons for the New Age of Electric Vehicles , 2009 .

[29]  Stephen Skippon,et al.  Responses to battery electric vehicles: UK consumer attitudes and attributions of symbolic meaning following direct experience to reduce psychological distance , 2011 .

[30]  C. C. Chan,et al.  The state of the art of electric and hybrid vehicles , 2002, Proc. IEEE.

[31]  Riccardo Minciardi,et al.  Network planning of fuelling service stations in a near-term competitive scenario of the hydrogen economy , 2009 .

[32]  Richard L. Church,et al.  The maximal covering location problem , 1974 .

[33]  C. Erdem,et al.  Identifying the factors affecting the willingness to pay for fuel-efficient vehicles in Turkey: A case of hybrids , 2010 .

[34]  Jean-Daniel Saphores,et al.  Why are Californians interested in hybrid cars? , 2009 .

[35]  Javier Gutiérrez,et al.  Transit ridership forecasting at station level: an approach based on distance-decay weighted regression , 2011 .

[36]  G. Kramer,et al.  A multi-level perspective on the introduction of hydrogen and battery-electric vehicles , 2010 .

[37]  Alan T. Murray,et al.  Spatial Representation and Scale Impacts in Transit Service Assessment , 2004 .

[38]  Michael Kuby,et al.  Location of Alternative-Fuel Stations Using the Flow-Refueling Location Model and Dispersion of Candidate Sites on Arcs , 2007 .

[39]  Juan Carlos García-Palomares,et al.  Distance-Measure Impacts on the Calculation of Transport Service Areas Using GIS , 2008 .

[40]  K. Train,et al.  Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles , 1999, Controlling Automobile Air Pollution.