France case study - Model based analysis of the deployment of electric vehicles in the Paris Ile de France Region

1. Model based analysis of the deployment of electric
vehicle in the Paris Ile de France region
66TH Semi-annual IEA-ETSAP meeting
17-21 November, 2014 - Copenhagen
Edi Assoumou
Jérôme Houël
Jean-Paul Marmorat
Mines ParisTech, PSL Research Univeristy
Center for Applied Mathematics

2. Context
Mobility analysis
Integration into the optimization module
Main problematic
Problematic
1 Impact on the electric system (charging level)
2 Integration of EV in the transport system and mobility
patterns
CMA research
Mobility focus
Paris Ile de France Region
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 2/20

3. Context
Mobility analysis
Integration into the optimization module
Main problematic
Problematic
1 Impact on the electric system (charging level)
2 Integration of EV in the transport system and mobility
patterns
CMA research
Mobility focus
Paris Ile de France Region
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 2/20

4. Context
Mobility analysis
Integration into the optimization module
Grand Paris Project
EV-STEP : The Paris IDF local case study
Agenda
1 Context
2 Mobility analysis
3 Integration into the optimization module
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 3/20

5. Context
Mobility analysis
Integration into the optimization module
Grand Paris Project
EV-STEP : The Paris IDF local case study
Agenda
1 Context
Grand Paris Project
EV-STEP : The Paris IDF local case study
2 Mobility analysis
3 Integration into the optimization module
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 3/20

6. Context
Mobility analysis
Integration into the optimization module
Grand Paris Project
EV-STEP : The Paris IDF local case study
The electric issues of Grand Paris Project
Source : L’approvisionnement énergétique du Grand Paris à l’horizon 2030, DRIEE, 2013
Grand Paris Project exemple
18.3 % of the French population
Habitation
Transport
Electricity demand
Where
When
How
Use Quantity Additional demand
Subway 72 stations 400 MW
Habitation 800,000 housing 800 MW
Professional activities 1,000,000 jobs 1,000 MW
Data Center 500,000 m2 1,000 MW
Electric vehicles 1,000,000 EV 500 MW
Total ∼ 4 000 MW
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 4/20

7. Context
Mobility analysis
Integration into the optimization module
Grand Paris Project
EV-STEP : The Paris IDF local case study
The electric issues of Grand Paris Project
Source : L’approvisionnement énergétique du Grand Paris à l’horizon 2030, DRIEE, 2013
Grand Paris Project exemple
18.3 % of the French population
Habitation
Transport
Electricity demand
Where
When
How
Use Quantity Additional demand
Subway 72 stations 400 MW
Habitation 800,000 housing 800 MW
Professional activities 1,000,000 jobs 1,000 MW
Data Center 500,000 m2 1,000 MW
Electric vehicles 1,000,000 EV 500 MW
Total ∼ 4 000 MW
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 4/20

8. Context
Mobility analysis
Integration into the optimization module
Grand Paris Project
EV-STEP : The Paris IDF local case study
The electric issues of Grand Paris Project
Source : L’approvisionnement énergétique du Grand Paris à l’horizon 2030, DRIEE, 2013
Grand Paris Project exemple
18.3 % of the French population
Habitation
Transport
Electricity demand
Where
When
How
Use Quantity Additional demand
Subway 72 stations 400 MW
Habitation 800,000 housing 800 MW
Professional activities 1,000,000 jobs 1,000 MW
Data Center 500,000 m2 1,000 MW
Electric vehicles 1,000,000 EV 500 MW
Total ∼ 4 000 MW
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 4/20

9. Context
Mobility analysis
Integration into the optimization module
Grand Paris Project
EV-STEP : The Paris IDF local case study
EV-STEP : The Paris IDF local case study
Problem formulation for the local impact assessment
for the Paris IDF area : EV-CAP
Given ...
A set of trips and a fleet
Battery, charging infrastructures, price signals ... characteristics
Compute ...
A feasible charging plan
Minimize a cost function : e, tCO2, kW pic
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 5/20

10. Context
Mobility analysis
Integration into the optimization module
ENTD 2008
Study parameters
Mobility results
Agenda
1 Context
2 Mobility analysis
ENTD 2008
Study parameters
Mobility results
3 Integration into the optimization module
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 6/20

11. Context
Mobility analysis
Integration into the optimization module
ENTD 2008
Study parameters
Mobility results
Statistical analysis of the mobility trips in the Paris Ile de
France region
Source : Enquête Nationale Transport et Déplacements 2008, MEDDE, 2011
Characterization of car drivers profiles in the Ile de France
region
Shed light on the potential demand for electric vehicles
L’enquête nationale transport et déplacements 2008
The 5th survey at the national level since 1967
In IDF : 14,436 individuals interviewed for 42,130 trips
Number of vehicles per household
Distance, time, travel mode ...
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 7/20

12. Context
Mobility analysis
Integration into the optimization module
ENTD 2008
Study parameters
Mobility results
Study parameters
Local mobility (under 80 km)
A working day
Trips by car
3 main criteria studied
1 Number of trips per individual per day
2 Travel time of trips per individual per day
3 Distance of trips per individual per day
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 8/20

13. Context
Mobility analysis
Integration into the optimization module
ENTD 2008
Study parameters
Mobility results
Study parameters
Local mobility (under 80 km)
A working day
Trips by car
3 main criteria studied
1 Number of trips per individual per day
2 Travel time of trips per individual per day
3 Distance of trips per individual per day
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 8/20

14. Context
Mobility analysis
Integration into the optimization module
ENTD 2008
Study parameters
Mobility results
Study parameters
Local mobility (under 80 km)
A working day
Trips by car
3 main criteria studied
1 Number of trips per individual per day
2 Travel time of trips per individual per day
3 Distance of trips per individual per day
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 8/20

15. Context
Mobility analysis
Integration into the optimization module
ENTD 2008
Study parameters
Mobility results
Number of trips per individual per day (trip/pers/day)
Based on Enquête Nationale Transport et Déplacements 2008, MEDDE, 2011
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
0
20
40
Île-de-France - trip/pers/day
Share(%)
Area Aver SD
IDF 3,31 56%
0 2 4 6 8 10 12 14
0
20
40
Paris
0 2 4 6 8 10 12 14
0
20
40
Petite-couronne
0 2 4 6 8 10 12 14
0
20
40
Grande-couronne
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 9/20

16. Context
Mobility analysis
Integration into the optimization module
ENTD 2008
Study parameters
Mobility results
Number of trips per individual per day (trip/pers/day)
Based on Enquête Nationale Transport et Déplacements 2008, MEDDE, 2011
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
0
20
40
Île-de-France - trip/pers/day
Share(%)
Area Aver SD
IDF 3,31 56%
Paris 3 52%
PC 3,15 59%
GC 3,43 54%
0 2 4 6 8 10 12 14
0
20
40
Paris
0 2 4 6 8 10 12 14
0
20
40
Petite-couronne
0 2 4 6 8 10 12 14
0
20
40
Grande-couronne
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 9/20

17. Context
Mobility analysis
Integration into the optimization module
ENTD 2008
Study parameters
Mobility results
Distance of trips per individual per day (km/pers/day)
Based on Enquête Nationale Transport et Déplacements 2008, MEDDE, 2011
40 80 120 160 200
0
20
40
60
80
100
Île-de-France - km/pers/day
Accumulated(%)
Average : 34.7 km
Standard deviation : 90 %
3/4 : - 50 km
1/20 : + 100 kmNovember, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 10/20

18. Context
Mobility analysis
Integration into the optimization module
ENTD 2008
Study parameters
Mobility results
Travel time of trips per individual per day(min/pers/day)
Based on Enquête Nationale Transport et Déplacements 2008, MEDDE, 2011
0 100 200 300 400 500
0
20
40
60
80
100
Île-de-France - min/pers/day
Accumulated(%)
Average : 71,8 min
Standard deviation : 73 %
2/3 : - 1h30
1/10 : + 3h00
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 11/20

19. Context
Mobility analysis
Integration into the optimization module
ENTD 2008
Study parameters
Mobility results
Distribution of departure times
Based on Enquête Nationale Transport et Déplacements 2008, MEDDE, 2011
0 2 4 6 8 10 12 14 16 18 20 22 24
0
2
4
6
8
10
12
Île-de-France - Departure time
Share(%)
Begin at 6 AM
Finish at 8 PM
2 main pics
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 12/20

20. Context
Mobility analysis
Integration into the optimization module
ENTD 2008
Study parameters
Mobility results
Analysis of departure times as a function of number of trips
Based on Enquête Nationale Transport et Déplacements 2008, MEDDE, 2011
0 5 10 15 20
0
10
20
1st trip
0 5 10 15 20
0
10
20
2nd trip
Those who make
their first trip in the
morning and the
second in the
evening to their
main activity
0 5 10 15 20
0
10
20
3rd trip
0 5 10 15 20
0
10
20
4th trip
Those who use their
cars at lunchtime
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 13/20

21. Context
Mobility analysis
Integration into the optimization module
ENTD 2008
Study parameters
Mobility results
Constrained and unconstrained trips
Based on Enquête Nationale Transport et Déplacements 2008, MEDDE, 2011
0 2 4 6 8 10 12 14 16 18 20 22 24
0
2
4
6
8
10
Departure time
Share(%)
Cont.
No-Cont. Work < − >Home
School < − >Home
The first 2 trips majority constrained
Number, distance and times for no-constrained trip are
twice important than constrained
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 14/20

22. Context
Mobility analysis
Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
Agenda
1 Context
2 Mobility analysis
3 Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 15/20

23. Context
Mobility analysis
Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
Effects of changing conditions on the load curve
1 Geographical zones
"IDF_ALL region"
"Paris"
"Petite couronne"
"Grande couronne"
2 Price signals
time of the day
average
3 Charging levels
8 A
16 A
32 A
63 A
4 Preferential time of charge
free
supervised timing
5 V2G
6 Behavioral
SOC min
SOC max
number of reload events
7 Vehicle types
BEV
PHEV30
PHEV60
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 16/20

24. Context
Mobility analysis
Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
Load impact of an EV fleet in kW/vehicle
Understanding the potential of electricity demand impact
"Electricity transfers" in a V2G configuration
Geographic impact
Living in a place does not necessarily mean recharge there
EV should be more develop in densely areas
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 17/20

25. Context
Mobility analysis
Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
Load impact of an EV fleet in kW/vehicle
Understanding the potential of electricity demand impact
"Electricity transfers" in a V2G configuration
The structures which will ensure charging
Recharging will be mostly in private location
Not sure that infrastructure can correctly offer to make V2G
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 18/20

26. Context
Mobility analysis
Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
Conclusion
Conclusion
Tools to evaluate variability in usage/charging conditions at
low time granularity are needed to complement deployment
scenarios for electric vehicles
Our load curve evaluation for the Paris Ile de France case
study shows that fixed benchmarks curves can underestimate
future impacts in both maximum power and time of
occurrence
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 19/20

27. Model based analysis of the deployment of electric
vehicle in the Paris Ile de France region
66TH Semi-annual IEA-ETSAP meeting
17-21 November, 2014 - Copenhagen
Edi Assoumou
Jérôme Houël
Jean-Paul Marmorat
Thank you for your attention

28. Context
Mobility analysis
Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
Time between 2 trips
Based on Enquête Nationale Transport et Déplacements 2008, MEDDE, 2011
2 3 4 5 6 7 8 9 1011121314
0
100
200
300
Nb of trip
Time(min)
To see if people would come to
charge their car
330 min for those who do 2 trips, but
with a very important standard
deviation
More the drivers travel in the day,
less time they have between 2 trips
From 8 trips per day, the time
between two trips varies around 50
min
Nb Share Time between Standard
of trip % 2 trips (min) Deviation
2 44,8 334 78
3 12,8 196 63
4 19,5 161 41
5 6,9 123 37
6 6,1 108 28
7 3 95 28
8 1,6 67 23
9 0,4 55 24
10 0,4 54 16
11 0,1 38 23
12 0,4 59 22
13 0,2 47 1
ALL 100 226 94
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 21/20

29. Context
Mobility analysis
Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
Le module optimisation
Source : Local EV charging : a case study of the PARIS IDF area, ASSOUMOU & all, 2014
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 22/20

30. Context
Mobility analysis
Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
Puissance appelée par véhicule
Source : Local EV charging : a case study of the PARIS IDF area, ASSOUMOU & all, 2014
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 23/20

31. Context
Mobility analysis
Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
Load impact of an EV fleet in kW/vehicle
Understanding the potential of electricity demand impact
"Electricity transfers" in a V2G configuration
The needs vary depending on the reasons of trip
The charging demand should done at home, a slightly at work
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 24/20

32. Context
Mobility analysis
Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
Analyse des valeurs extrêmes : nb de dEP (dep/ind/jour)
Réalisé à partir de l’Enquête Nationale Transport et Déplacements 2008, MEDDE, 2011
4 5 6 7 8 9 10 11 12 13 14
0
20
40
IDF les 20 % qui se déplacent le plus
Parten%
1 2 3
0
20
40
60
80
IDF les 20 % -
Parten%
Zone Nb ET Tps ET Dist ET
IDF les 20 % - 1,81 22 % 50,2 72 % 27,6 98 %
IDF les 20 % + 6,21 28 % 111,3 56 % 52,5 69 %
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 25/20

33. Context
Mobility analysis
Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
Analyse des valeurs extrêmes : nb de dEP (dep/ind/jour)
Réalisé à partir de l’Enquête Nationale Transport et Déplacements 2008, MEDDE, 2011
4 5 6 7 8 9 10 11 12 13 14
0
20
40
IDF les 20 % qui se déplacent le plus
Parten%
1 2 3
0
20
40
60
80
IDF les 20 % -
Parten%
Zone Nb ET Tps ET Dist ET
IDF les 20 % - 1,81 22 % 50,2 72 % 27,6 98 %
IDF les 20 % + 6,21 28 % 111,3 56 % 52,5 69 %
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 25/20

34. Context
Mobility analysis
Integration into the optimization module
Effects of changing conditions on the load curve
Load impact of an EV fleet in kW/vehicle
Conclusion
Le module optimisation
Puissance appelée par véhicule
Le module optimisation
Source : Local EV charging : a case study of the PARIS IDF area, ASSOUMOU & all, 2014
November, 17 2014 Copenhagen Jérôme Houël Analysis of the deployment of EV in the Paris IDF region 26/20