electrification of mobility_finland lassila
DESCRIPTION
El 20 de noviembre se celebró en EOI la jornada "Electrificación del transporte y red eléctrica / Electrification of mobility and the electrical network":Esta es la ponencia de uno de los reconocidos expertos europeos que analizaron en esta jornada el impacto de la electrificación del transporte en la red eléctrica, tanto en sistemas de distribución centralizada como en los emergentes sistemas distribuidos e inteligentes.www.eoi.esTRANSCRIPT
1
• Energy Technology• Electrical Engineering• Environmental Engineering
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
Electric Cars– Challenge or Opportunity for the
Electricity Distribution Infrastructure?
Jukka LassilaTero Kaipia, Juha Haakana and Jarmo Partanen
Lappeenranta University of Technology
ELECTRIFICATION OF MOBILITYAND THE ELECTRICAL NETWORK
Madrid, SpainNovember 20th, 2009
• Energy Technology• Electrical Engineering• Environmental Engineering 2
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
Target of the studies
• Define method to analyse network effects of electric vehicles
• Make network analysis using actual distribution network data and load flows (city area and rural area feeders)
• Define best and worst scenarios and define needed network reinforcements
• Define network effects to the distribution fees paid by the end-customers
• Energy Technology• Electrical Engineering• Environmental Engineering 3
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
Input Parameters on Electric Car Network Simulation
Network simulations and analysis results- Load flow and loss calculations- Estimation of reinforcements required
Network simulations and analysis results- Load flow and loss calculations- Estimation of reinforcements required
National passenger transport survey- Spatial and temporal variations in passenger trips- Length of daily trips- Annual length of driving (region dependent) - Length of daily trips according to housing type- Length of daily trips according to residential area- Length of daily trips according to the month of year- Length of trips according to the time of day- Number of cars in households
Properties of electric cars- Energy consumption, kWh/km- Capacity of the batteries, kWh- Charging power, kW- Required charging time, h/day (battery properties)
Town planning statistics- Workplaces according to the area and time of day- Residential areas (detached houses, terraced houses,
apartment houses)
Penetration of electric cars- Development of electric car markets
Tariffs and supplier- Distribution fee
National passenger transport survey- Spatial and temporal variations in passenger trips- Length of daily trips- Annual length of driving (region dependent) - Length of daily trips according to housing type- Length of daily trips according to residential area- Length of daily trips according to the month of year- Length of trips according to the time of day- Number of cars in households
Properties of electric cars- Energy consumption, kWh/km- Capacity of the batteries, kWh- Charging power, kW- Required charging time, h/day (battery properties)
Town planning statistics- Workplaces according to the area and time of day- Residential areas (detached houses, terraced houses,
apartment houses)
Penetration of electric cars- Development of electric car markets
Tariffs and supplier- Distribution fee
Area-specific additional
energy
__ kWh/day(working hours/
leisure time)
Area-specific additional
energy
__ kWh/day(working hours/
leisure time)
Electricity distribution network- Network topology and customer information- Feeder and hourly-specific actual load curves- Network volume - Replacement value- Parameters: loss costs, load growth, lifetime,
unit price of network components
Electricity distribution network- Network topology and customer information- Feeder and hourly-specific actual load curves- Network volume - Replacement value- Parameters: loss costs, load growth, lifetime,
unit price of network components
LANDBO
MASSBY
KALLBÄCK
MARTINKYLÄ
0
1
2
3
4
5
6
7
8
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00
Thursday (hours)
Pow
er [M
W]
Charging profile
Hours
Pow
er
• Energy Technology• Electrical Engineering• Environmental Engineering 4
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Case Network
LANDBO
MASSBY
KALLBÄCK
MARTINKYLÄ
Whole distribution company- 110/20 kV primary substations: 4- 20 kV feeders: 22 - Habitants/end-customers: 19 470 / 11 000- Workplaces: 5 333- Houses: 7 932 (5992 detached houses,
525 terraced houses, 1287 apartment houses, 128 others)
- 20/0.4 kV distribution substations: 470- Peak load: 50 MW- Annual energy: 200 GWh- 20 kV lines and cables: 433 km- 20 kV underground cabling rate: 16 %
20 kV feeder 1. (densely populated area) - Peak load: 8 MW- Annual energy: 36 GWh
- Residential 58 %, industry 22 %, public 13 % and service 7 %
- Habitants/end-customers: 4171 / 2278- Workplaces: 1 577- Houses: 1 840 (659 detached houses, 266
terraced houses, 888 apartment houses)- 20/0.4 kV distribution substations: 39- 20 kV lines and cables: 21 km- 20 kV underground cabling rate: 33 %
1.
2.20 kV feeder 2. (rural area) - Peak load: 2 MW- Annual energy: 6 GWh
- Residential 95 %, agriculture 2 %, industry 3 %
- Habitants/end-customers: 1037 / 444- Workplaces: 84- Houses: 372 (all detached houses)- 20/0.4 kV distribution substations: 27- 20 kV lines and cables: 31 km- 20 kV underground cabling rate: 6 %
Winter Winter
Summer Summer
• Energy Technology• Electrical Engineering• Environmental Engineering 5
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Case Network - Load curve
• Energy Technology• Electrical Engineering• Environmental Engineering 6
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Electric Vehicles - Properties
• Needed energy: 0.1 – 0.2 kWh/km• Capasity: 30 kWh/car• Charging power: 3.6 kW/car
(Charging power max 3.6 kW = 230 V x 16 A)
Photo presents car pre-heating pole used widely in Finland and Nordic countries.
• Energy Technology• Electrical Engineering• Environmental Engineering 7
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Case area
LANDBO
MASSBY
KALLBÄCK
MARTINKYLÄ
• Habitants: 19 470 • Electricity end-customers: 11 000• Workplaces: 5 333• Houses: 7 932
– 5992 detached, 525 terraced, 1287 apartment, 128 others)
• Personal cars: 11 000• Travelling distances: 20 900 km/car,a
= 57 km/car,day
• Needed charging energy: 11.5 kWh/car,day46 GWh/a (all cars)
• Energy Technology• Electrical Engineering• Environmental Engineering 8
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Case Network – Electric car
charging profiles
Transmission capacity in the network?Losses and loss costs?
The same amount of charging energy in each profile!
Direct night-time charging Split-level night-time charging
Working-hour and time-off charging
Optimised charging
0:00 9:00 16:00 22:00
0:00 9:00 16:00 22:00 0:00 9:00 16:00 22:00
0:00 9:00 16:00 22:00
• Energy Technology• Electrical Engineering• Environmental Engineering 9
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Case Network - Losses
0
50
100
150
200
250
300
350
400
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00
Load
loss
es [k
W]
Direct night-time charging
Split-level night-time charging
Optimised chargingPresent losses
Working-hour and time-off charging
Losses in medium voltage network
• Energy Technology• Electrical Engineering• Environmental Engineering 10
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Case Network - Losses
0
20
40
60
80
100
120
140
160
180
200
Present losses Direct night-time charging
Split-level night-time charging
Working-hourand time-off
charging
Optimisedcharging
Cos
t of l
osse
s [€
/day
]
No remarkable differences in charging profiles from loss costs point of view in medium voltage network!
• Energy Technology• Electrical Engineering• Environmental Engineering 11
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Case Network – Feeder 1 (city area)
0123456789
10
0 2 4 6 8 10 12 14 16 18 20 220123456789
10
0 2 4 6 8 10 12 14 16 18 20 22
0123456789
10
0 2 4 6 8 10 12 14 16 18 20 22
Split-level night-time charging
Optimised chargingWorking-hour and time-off charging
City area feeder:- Peak load of the day: 6.6 MW- Minimum load of the day: 4.0 MW
- Number of electric cars: 2000- Driving distance: 57 km/car,day- Energy consumption: 0.2 kWh/km- Charging energy: 11.5 kWh/car,day
22.9 MWh/day for all cars
- Charging power: 3.6 kW/car- Additional power: 0 – 3.5 MW
(depending on charging method)
- Charging energy (E) is equal in each charging alternative
0123456789
10
0 2 4 6 8 10 12 14 16 18 20 22
Direct night-time charging
EE
Pea
k po
wer
[MW
] Present load
Feeder load with electric cars
• Energy Technology• Electrical Engineering• Environmental Engineering 12
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Case Network – Feeder 2 (rural area)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
0 2 4 6 8 10 12 14 16 18 20 22
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
0 2 4 6 8 10 12 14 16 18 20 22
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
0 2 4 6 8 10 12 14 16 18 20 220.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
0 2 4 6 8 10 12 14 16 18 20 22
Direct night-time charging Split-level night-time charging
Optimised chargingWorking-hour and time-off charging
Rural area feeder:- Peak load of the day: 1.25 MW- Minimum load of the day: 0.75 MW
- Number of electric cars: 750- Driving distance: 57 km/car,day- Energy consumption: 0.2 kWh/km- Charging energy: 11.5 kWh/car,day
8.6 MWh/day for all cars
- Charging power: 3.6 kW/car- Additional power: 0 – 1.75 MW
(depending on charging method)
Charging energy is equal in each charging alternative
Pea
k po
wer
[MW
]
• Energy Technology• Electrical Engineering• Environmental Engineering 13
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Case Network – Whole company
Whole company:- Peak load of the day: 36 MW- Minimum load of the day: 25 MW
- Number of electric cars: 11 000- Driving distance: 57 km/car,day- Energy consumption: 0.2 kWh/km- Charging energy: 11.5 kWh/car,day
126 MWh/day for all cars
- Charging power: 3.6 kW/car- Additional power: 0 – 24 MW
(depending on charging method)
0
10
20
30
40
50
60
0 2 4 6 8 10 12 14 16 18 20 22
0
10
20
30
40
50
60
0 2 4 6 8 10 12 14 16 18 20 220
10
20
30
40
50
60
0 2 4 6 8 10 12 14 16 18 20 22
0
10
20
30
40
50
60
0 2 4 6 8 10 12 14 16 18 20 22
Direct night-time charging Split-level night-time charging
Optimised chargingWorking-hour and time-off charging
Pea
k po
wer
[MW
]
Using intelligent charging system (Optimised charging) charging can be adjusted fully into low-load moments
• Energy Technology• Electrical Engineering• Environmental Engineering 14
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Case Network – Reinforcement costs
Using intelligent charging system (Optimised charging) charging can be adjusted fully into low-load moments
- Network value compared with the peak load in - low-voltage networks 320 €/kW- medium-voltage network 300 €/kW - primary substation level (110/20 kV) 100 €/kW
An example of defining required reinforcement investments on the medium voltage feeder
20 kV feeder 1. (densely populated area)
-Peak load of the day: 6.6 MW
-Additional power: + 3.0 MW
- Average marginal cost: 300 €/kW
Estimated need for reinforcement:
300 €/kW x 3000 kW = 900 000 €
• Energy Technology• Electrical Engineering• Environmental Engineering 15
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Case Network – Reinforcement costs
- Replacement value: 50 M€ ( 2.9 M€/a calculated by p = 5 % and t = 40 a)
- Annual present delivered energy: 200 GWh/a Network value per delivered energy 1.46 cent/kWh
- Estimated additional annual charging energy required by electriccars: + 46 GWh/a ( 11 000 cars, 20 900 km/car,a and 0.2 kWh/km,car)
- Depending on charging method, estimation of the required investments in a new transformer and transmission capacity in the whole distribution network is 0 – 20 M€ (0 – 1 060 k€/a).
New distribution fee: 1.18 – 1.66 cent/kWh after the network reinforcements
• Energy Technology• Electrical Engineering• Environmental Engineering 16
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Conclusions (1/3)
1. Description of the overall methodology; what background information is required and how it is used to determine the needfor electric car charging energy and power and to analyse the network effects.
2. Charging mode has a significant impact on the peak load level on the feeder. Without any intelligence included in the system, charging of electric cars may increase the peak power even threetimes higher compared with the present load level on the medium-voltage feeder. With an intelligent charging system, charging can be adjusted to a low-load moment, thereby avoiding overlapping of the existing peak load and the additional charging load. This may reduce the distribution fees of the electricity end-users, because more energy is delivered through the same system without a need for reinforcement investments. This is possible especially on feeders where the load varies considerably.
• Energy Technology• Electrical Engineering• Environmental Engineering 17
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Conclusions (2/3)
3. It is possible to cut the transmission/distribution fees charged to electricity end-users during the large-scale adoption of electric cars, if the charging system is well-planned and enough intelligence is included in it. And opposite situation with charging system without intelligent control.
4. Load variations of medium-voltage feeders have to be taken into account in the analyses. The charging mode used on the cityarea feeder does not provide the desired end result on the ruralarea feeder. An intelligent charging system has to be able to take into account to which feeder each electric car is connected and where it is charged.
• Energy Technology• Electrical Engineering• Environmental Engineering 18
LAPPEENRANTAUNIVERSITY OF TECHNOLOGY Conclusions (3/3)
5. Biggest challenges in low-voltage networks. In the worst case the triple extra capacity has to be invested (home, work, cottage). However in Finland we have a lot of experience of transposition of loads (sauna oven, electric space heating, water heaters, block heaters).
Jukka LassilaLappeenranta University of [email protected]+358 50 537 3636