| Abstract: |
Electric Vehicles (EV) are a key element of future smart cities, providing a
clean transportation technology and potential benefits for the grid.
Nevertheless, limited vehicle autonomy and lack of charging stations are
preventing EVs to be broadly accepted. To address this challenge, French
GreenFeed project is working to develop an interoperable and universal
architecture to allow EV recharge across multiple cities and countries. In
this work, we consider such architecture and focus on price setting by its
main actors. We show how a Stackelberg game models the market, and we study
the outcomes when users choose a recharge station according to objective and
subjective parameters. Simulation shows the different actors' revenues, and
the social and user welfare for different scenarios. I. INTRODUCTION Electric
Vehicles (EV) and Hybrid Electric Vehicles are expected to dominate the
automobile industry in the near future [12]. They present the great advantage
of being environmentally friendly, dramatically reducing greenhouse gases
emissions with respect to fossil-fuel vehicles [8], while almost eliminating
noise pollution. Moreover, EVs are nowadays part of a whole evolutionary
energy context. Energy transition is taking place in several countries in
order to introduce distributed and renewable energy resources into the grid.
Electricity market is also changing into a deregulated market, where
time-variant tariffs are introduced, making demand side management solutions
possible. In this context, EVs become also attractive because of the ancillary
services they can offer to the grid. They can provide flexibility, by the
possibility to shift the battery recharge. They can also provide the grid with
the energy stored in their batteries through Vehicle to Grid (V2G)
technologies, when energy production is lower than demand, and can store
energy when supply exceeds demand. In spite of the aforementioned advantages,
EVs are facing some barriers to their large adoption, such as the so-called
range anxiety. This term refers to the fear that the vehicle will not have
enough range to reach the destination. With state-of-the-art batteries,
vehicle's autonomy is on the average 50 km and it can reach up to 160 km with
large batteries [10]. However, these figures may dramatically vary according
to driving manner and particular circumstances (e.g. temperature, weight,
etc.). In this context, it is of paramount importance to have ubiquitous, easy
and fast means to get the recharge service and to pay for it, regardless the
EV model, without problems of interoperability or users' contract. In this
sense, industry and research institutions, and standardisation bodies are
carrying out efforts to develop electromobility and charging solutions, such
as GreenFeed [3], green eMotion [2], standard ISO 15118 [5], the French
initiative for EV roaming Gireve [1], or the platform Hubject [4]. Ongoing
French project GreenFeed, aims to develop interoperable recharge solutions to
foster EVs penetration. The project has defined an architecture, following the
standard ISO 15118, that has the following main actors: EV Users (EVU),
e-Mobility Provider (EMO), Charging Point Operator (CPO) and e-Mobility
Operator Clearing House (EMOCH), as shown in Fig. 1a. Such architecture
structures a supply chain market for EV recharge. This work is part of the
outcome of GreenFeed project, and focuses on the problem of setting EV
recharge price at the different levels of the supply chain-one of the
questions raised by the project. We assume variable recharge costs faced by
the mobility providers (EMOs), but a fixed recharge price paid by the final
client (EVU). Fixed prices are attractive from the point of view of the EVU,
who is then shielded from electricity price volatility. We model the situation
as a Stackelberg game, where CPOs play first, setting a price to be paid by
the EMO, and where the EMO follows, setting a price for the recharge, which is
paid by the final client. In addition, we take into account clients decision
about where to get their EV recharged, considering subjective and objective
parameters about the CPOs. Our results show interesting insights which could
help CPOs and EMOs to set prices, and regulators to evaluate the market
structure induced by GreenFeed's architecture. Simulation allow us to show in
several scenarios the existence of a Nash equilibrium. The reminder of this
paper is organised as follows. Section II reviews related work. In Section III
we introduce the GreenFeed architecture, formally explain the market structure
and the problem under study. We then formalise the problem as a Stackelberg |