Forecast of the Demand for Electric Mobility for Rome–Fiumicino International Airport
Abstract
:1. Introduction
- The forecast of EV turnout at airport parking facilities at time horizon 2025–2030, for clusters of vehicles (chauffeurs, private cars, rental cars, and taxis).
- The estimation of charging points potentially required accommodating the forecasted EV turnout.
2. The Case Study
- Parking areas for passengers and operators.
- Sub-concession parking areas for car rentals, chauffeurs, and buses.
- Non-sub-concession parking areas for taxis, chauffeurs, buses, and shuttles.
- Public collective railway transport with the city of Rome: Ferrovia Laziale FL1 local train, Leonardo Express nonstop service.
- Public collective railway transport to major Italian cities: Trenitalia Frecciargento high-speed trains.
- Public and private collective road transport: shuttle buses by private companies.
- Public personal road transport: taxis.
- Private personal road transport: chauffeurs and car rentals.
3. Analysis of EV Development Scenarios at Different Levels
3.1. Global Level
- Boston Consulting Group [48], where the analysis led to a single scenario, presented here as BCG.
- Bloomberg NEF [49], under the assumption that in 2025, combustion engine cars and EVs will reach economic parity, presented here as BNEF.
- IEA [50], which proposes two scenarios: IEA new policy scenario (NPS), this is the most conservative scenario and includes the impact of announced policy ambitions, and a more ambitious one, IEA 30@30, which accounts for the pledges of the EVs EV30@30 campaign to reach 30% market share for electric vehicles by 2030.
3.2. European Level
- Boston Consulting Group [48] (BCG).
- Cambridge Econometrics [51], which develops a set of three scenarios, each assuming a different decarbonization pathway taken by most major car manufacturers to meet EU CO2 emissions reduction targets. The scenarios are presented as: CAM, CAM (Tech PHEV), and CAM (Tech OEM).
- Transport and Environment [52], which defines five scenarios, based on the incremental fuel efficiency upgrade of future ICE car fleet. The scenarios are presented as: TRA&ENV (b), TRA&ENV (lICE), TRA&ENV (hICE), TRA&ENV (BEV), and TRA&ENV (PHEV).
- IEA [50], which proposes only an NPS scenario to forecast new electric vehicles sales in Europe.
3.3. Italian Level
3.4. Definition of Reference Forecasting Scenarios for the Case Study
- Conservative scenario: significant incentive policies are not considered, and it is in line with the basic one of the Politecnico di Milano study [53], which envisages the least expansion.
- PNIEC scenario: it is in line with the objectives on electrical mobility included in the Italian Integrated National Plan for Energy and Climate (Piano Nazionale Integrato per l’Energia e il Clima 2030, PNIEC) [54] (to have 6,000,000 EVs circulating in 2030); consequently, it is the upper limit for the demand for Italian electric mobility in 2030.
- The number of cars sold in 2019, for every typology, is obtained from the historical analysis.
- The number of cars sold in the horizon year 2030 is such to make the fleet in circulation reach the corresponding value for the scenario considered.
4. Forecasting of Rome–Fiumicino Airport EV Development Scenarios
4.1. Data and Methodology
- Characterization of parking areas (via satellite imaging of public domain).
- Identification of internal collective transport lines (shuttles).
- Identification of public transport line.
- Data on stops in 2019 (duration, number of vehicles, and registration plates).
- Hourly detection of private traffic flows.
- Analysis of the consistency of parking areas (via identification of areas from satellite imaging and allocation to cluster of users) to allocate charging points.
- Analysis of the duration of stops (from data provided by ADR) to allocate type of charging points (slow/fast charging).
- Analysis of vehicle age distribution (from license plate data provided by ADR) to estimate the renewal rate by cluster and the consequent EV penetration.
- Estimation of EV access number by cluster; obtained by combining the age distribution profiles with the sales forecasts derived from the analysis of the scenarios.
- A block diagram summarizing the main steps of the methodology is shown in Figure 10.
- An expected life of 5 years for taxi cars.
- An expected life of 2.5 years for a rental car.
- The same age profile for airport operators’ vehicles as those of passengers.
- Saturation of the logistic curve 5 years forward for taxis and chauffeurs compared to private cars.
4.2. Results
- Vehicles accessing airport car parks (particularly the multistory car park) are often company cars, which are usually replaced more frequently than private cars.
- Old cars travel fewer kilometers per year, while users travelling more are forced to replace cars frequently due to wear, thus newer cars are likely to be a significant part of airport car park use.
5. Preliminary Sizing of Charging Infrastructure
6. Conclusions
- The estimated share of EVs accessing Fiumicino airport parks in 2025 is between 3% and 7%.
- The estimated share of EVs accessing Fiumicino airport car parks in 2030 is between 10% and 35%.
- The charging points potentially necessary to serve the share of EVs (private cars, taxis, NCC) affluent to the Fiumicino airport parks are 550–1100 in 2025 and 2300–7000 in 2030.
- The total power of recharging points relating to shuttles, buses, and TPL is estimated to be equal to 4.5 MW.
- The total power for airside vehicle recharging is estimated to be equal to 20 MW with contemporaneity assumed at 50%.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
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Field of Action | HEV | PHEV | BEV + REx | BEV | FCEV |
---|---|---|---|---|---|
Traction | Thermal and electric | Thermal and electric | Electric | Electric | Electric (battery/fuel cell) |
Energy storage | Battery and fuel tank | Battery and fuel tank | Battery and small fuel tank | Battery | Battery and hydrogen tank |
Battery charging | By heat engine (no plug) | From grid via plug | By small heat engine (for charging only) | From grid via plug | By fuel cell |
Field of Action | Advantage | Disadvantage |
---|---|---|
Powertrain, storage | High efficiency of powertrain (~90% vs. ~30% of combustion engines) | Heavy propulsion system (due to sizable battery, hybrid propulsion) |
Battery technology | Rechargeability | Limited life cycle, complex cell technology |
Comfort, driving | Excellent acceleration, power transfer (due to torque characteristic) | Limited range (due to current low energy density) |
Vehicle concept | New vehicle concepts | High design effort |
Costs | Decreasing life-cycle costs (due to lower maintenance costs) | High component costs (due to current battery price) |
Ecology, sustainability | No local emission | Current overall carbon footprint (due to current energy mix) |
Energy storage, charging | Integration of EVs into smart grids | Current limited infrastructure |
Parking Duration | Share of Total Parking Spot Usage * |
---|---|
<2 h | 2.8% |
>2 h | 97.2% |
Scenario | Horizon | Parking Category | Slow Charging Stations | Fast Charging Stations |
---|---|---|---|---|
Conservative Scenario | 2025 | Multistorey park | 354 | 14 |
Long-stay park | 270 | 0 | ||
2030 | Multistorey park | 1.494 | 56 | |
Long-stay park | 1.137 | 0 | ||
PNIEC Scenario | 2025 | Multistorey park | 645 | 26 |
Long-stay park | 492 | 0 | ||
2030 | Multistorey park | 2.939 | 108 | |
Long-stay park | 2.235 | 0 |
Vehicle | Power (kW) | Quantity | Capacity (kWh) | Consumption (MWh) |
---|---|---|---|---|
Passenger boarding lift | 10 | 16 | 15 | 28 |
Drinking water tank truck | 10 | 13 | 15 | 23 |
Lavatory truck | 10 | 13 | 15 | 23 |
Shuttle bus | 160 | 119 | 120 | 3998 |
Lift truck | 10 | 7 | 15 | 12 |
Catering | 10 | 22 | 15 | 38 |
Forklift | 10 | 13 | 15 | 23 |
Loader | 75 | 59 | 96 | 654 |
Onboard cleaning | 10 | 10 | 15 | 17 |
Minibus | 25 | 29 | 120 | 974 |
Conveyor belt | 33 | 106 | 36 | 641 |
Towable passenger stair | 13 | 186 | 35 | 990 |
Transporter | 33 | 49 | 36 | 296 |
Large tractor | 10 | 35 | 36 | 397 |
Small tractor | 68 | 65 | 204 | 2785 |
Total | 37,446 | 742 | 51,481 | 10,899 |
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Acri, R.A.; Barone, S.; Cambula, P.; Cecchini, V.; Falvo, M.C.; Lepore, J.; Manganelli, M.; Santi, F. Forecast of the Demand for Electric Mobility for Rome–Fiumicino International Airport. Energies 2021, 14, 5251. https://doi.org/10.3390/en14175251
Acri RA, Barone S, Cambula P, Cecchini V, Falvo MC, Lepore J, Manganelli M, Santi F. Forecast of the Demand for Electric Mobility for Rome–Fiumicino International Airport. Energies. 2021; 14(17):5251. https://doi.org/10.3390/en14175251
Chicago/Turabian StyleAcri, Romano Alberto, Silvia Barone, Paolo Cambula, Valter Cecchini, Maria Carmen Falvo, Jacopo Lepore, Matteo Manganelli, and Federico Santi. 2021. "Forecast of the Demand for Electric Mobility for Rome–Fiumicino International Airport" Energies 14, no. 17: 5251. https://doi.org/10.3390/en14175251