Program > By speacker > Baouche Fouad

Wednesday 26
New application domain on OR (health, biology, computer science, economy, energy, sustainable growth, cloud computing...), transfer to industry and software
Fouad Baouche
› 16:40 - 17:00 (20min)
› Bât. B - TD 35
Electric Vehicle Charging Stations Allocation Model
Fouad Baouche  1, *@  , Romain Billot  1@  , Rochdi Trigui  2@  , Nour-Eddin El Faouzi  1@  
1 : Laboratoire d'Ingénierie Circulation Transport  (LICIT)  -  Website
École Nationale des Travaux Publics de l'État [ENTPE], Université de Lyon, IFSTTAR
25 Avenue François Mitterrand, 69675 Bron Cedex -  France
Bron -  France
* : Corresponding author

In 2009, French authorities launched a national plan for the deployment of charging infrastructure in order to promote the electromobility. Key stakeholders and industrial such car manufacturers, energy distribution companies and researchers were encouraged to propose optimal solutions for the installation of charging stations (CS). These solutions should cover all types of configurations: public roads, parking, and workplace.

The French Environmental and Energy Management Agency (ADEME) set standards and norms for the allocation of charging stations while drawing the roadmap to the expansion of these infrastructures. The latter included three key parameters for the establishment of a national charging network, which are:

  • Standardization of the charging infrastructure: this includes all the issues such as the interoperability of charging structures, security, infrastructure competitiveness, user comfort and convenience, and an optimized management of the energy consumption.
  • Regulatory framework and a viable business model to ensure the integration and success of the electric vehicles. This includes a vehicles cost reduction to assure future users of the viability of this technology (recycling battery component).
  • Determination of an equilibrium between the location of the CS and the capacity of the electric vehicle battery in order to make the network more resilient to this type of mobility. Achieving a balance between these interactions is a key parameter to be taken into account in the strategy for the deployment of the charging infrastructure.

In this report, one of the main points that should be emphasized is the standard that must be applied when designing a charging station infrastructure. Concerning the type of CS, three types of terminals are identified: (i) slow charging points for home or long stay parking charging, (ii) semi-rapid charging points mainly at public park and (iii) fast CS along urban motorways and dense road traffic.

The expansion of Electric Vehicles (EV) implies an optimized and cost-effective deployment of CS. As a decision support tool for network design, we define a methodology to locate CS in a real case study network. This study uses OD matrix information from household travel survey mixed with a dynamic model to evaluate electric vehicles consumption based on realistic trips (urban cycles). These trips are computed based on routing tools and augmented with elevation information. This enables a characterization of energy needs in the City of Lyon. All these parameters are used as inputs of an integer linear model for the location of CS. The methodology adapts the classic fixed charge location model with a p-dispersion constraint. The results indicate that this methodology can help the future implementation of charging stations at an urban scale.

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