Is Deployment of Charging Station the Barrier to Electric Vehicle Fleet Development in EU Urban Areas? An Analytical Assessment Model for Large-Scale Municipality-Level EV Charging Infrastructures

Talluri Talluri,Grasso Grasso,Chiaramonti Chiaramonti

doi:10.3390/app9214704

Abstract

This work investigates minimum charging infrastructure size and cost for two typical EU urban areas and given passenger car electric vehicle (EV) fleets. Published forecasts sources were analyzed and compared with actual EU renewal fleet rate, deriving realistic EV growth figures. An analytical model, accounting for battery electric vehicle-plug-in hybrid electric vehicle (BEV-PHEV) fleets and publicly accessible and private residential charging stations (CS) were developed, with a novel data sorting method and EV fleet forecasts. Through a discrete-time Markov chain, the average daily distribution of charging events and related energy demand were estimated. The model was applied to simulated Florence and Bruxelles scenarios between 2020 and 2030, with a 1-year timestep resolution and a multiple scenario approach. EV fleet at 2030 ranged from 2.3% to 17.8% of total fleet for Florence, 4.6% to 16.5% for Bruxelles. Up to 2053 CS could be deployed in Florence and 5537 CS in Bruxelles, at estimated costs of ~8.3 and 21.4 M€ respectively. Maximum energy demand of 130 and 400 MWh was calculated for Florence and Bruxelles (10.3 MW and 31.7 MW respectively). The analysis shows some policy implications, especially as regards the distribution of fast vs. slow/medium CS, and the associated costs. The critical barrier for CS development in the two urban areas is thus likely to become the time needed to install CS in the urban context, rather than the related additional electric power and costs.

Highlights

Mitigating the effects of climate change through greenhouse gas (GHG) emissions reductions is one of the key challenges of the 21st century
This study focuses only on electric vehicle (EV) passenger cars since they account for the vast majority of EU-28 circulating road vehicles with an 87% share of total, while, in comparison, light commercial vehicles accounted for 9.8%
In order to define the optimal size of the EV charging infrastructure, the model needs as inputs, for each timestep of the analysis, the number of daily charging events related to both battery electric vehicle (BEV) and plug-in hybrid electric vehicle (PHEV) fleets and the corresponding energy requests; it needs a full characterization of the charging stations (CS) in terms of expected performances and costs

Summary

Introduction

Mitigating the effects of climate change through greenhouse gas (GHG) emissions reductions is one of the key challenges of the 21st century. At the core is the issue of overall energy consumption as well as the need for stronger decarbonization policies. Within this picture, transport sector plays a big role, globally and at European level: EEA data shows that in 2016, it accounted for a 33.2% share of EU-28 final energy consumptions and for a 24.3% share of GHG emissions [1]. 72% of GHG emissions and, within that sector, cars accounted for 60.7%. Half of EU-28 NOx emissions and at least 15% of PM10, PM2.5, SOx and CO emissions are transport-related [1,2]; European transport energy needs are fulfilled by fossil fuels use for more than a 94% share [1].

Results

Discussion

Conclusion