jukka lassila – finland – session 6 – paper 0773
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Frankfurt (Germany), 6-9 June 2011
Jukka Lassila – Finland – Session 6 – Paper 0773
Network Effects of Electric Vehicles Case from Nordic Country
LUT Jukka Lassila Juha Haakana Jarmo Partanen
Fortum Kari Koivuranta Saara Peltonen
Frankfurt (Germany), 6-9 June 2011
Key questions
Jukka Lassila – Finland – Session 6 – Paper 0773
Defining of technical (MW) and economical (€) effects in electricity distribution networks
- Classification of information used in analysis- Defining of charging curves for electric vehicles - Developing power flow calculation- Defining of marginal cost of the present network
+MW
+€
Frankfurt (Germany), 6-9 June 2011
City
Rural area
Urban area
Case areao Located in Fortum Distribution network, Finland
o 20 kV network (6 feeders) from city, urban and rural areas
o Peak load on the feeder*: 3.6–8 MW /feeder
o Annual energy*: 10–32 GWh /feeder
o Number of delivery sites: 390–5200 /feeder
o Estimated number of cars: 980–4000 /feeder
* Without electric vehicles
Jukka Lassila – Finland – Session 6 – Paper 0773
EV information:-Driving distance: 50 km/day per car-Consumption: 0.2 kWh/km-Charging power: 3.6 kW/car
Frankfurt (Germany), 6-9 June 2011
0
100
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Nu
mb
er o
f EV
s
Hour
WorkdaysWeekends
Num
ber
of
cars
Present load curve of the medium-voltage feeder (peak week of the year, without EVs)
Estimation of amount of EVs charged during the day on the feeder
Peak
pow
er
[kW
]
0
1 000
2 000
3 000
4 000
5 000
6 000
12.1.2009 13.1.2009 14.1.2009 15.1.2009 16.1.2009 17.1.2009 18.1.2009 19.1.2009Day
Mon Tue Wed Thu Fri Sat Sun
Even
ing
Day
Nig
htM
orni
ng
Frankfurt (Germany), 6-9 June 2011
Load curves with EVs (100% and 50%)
Present load
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
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12:0
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Pe
ak p
ow
er [M
W]
Without EVs 100 % penetration level 50 % penetration level
Mon Tue Wed Thu Fri Sat Sun
In residential area (urban area) evening and night-hours are the most challenging from the network capacity point of view
Frankfurt (Germany), 6-9 June 2011
Peak power with EVs (7.6 MW)
Present peak power (5.6 MW)
One-year load curve with EVs (the topmost curve) from the feeder. The bottom curve illustrates the powers without EVs. The curves include the peak powers of each day; the minimum loads of the days are not presented.
One-year load curve with EVs
Frankfurt (Germany), 6-9 June 2011
Feeder Present load curve of the medium-voltage feeder (peak week of the year, without EVs)
EV daily charging curve, without basis load (weekday/weekend)
Feeder 1
HH: 1649
Feeder 2
HH: 980
Feeder 3
HH: 1153
Feeder 4
HH: 1593 WP: 120 S: 800
Feeder 5
HH: 4061 WP: 110 S: 102
Feeder 6
HH: 118 WP: 1210 S: 300
Present load curve (lower) and load curve with EVs (upper) for one year
Present load curve (lower) and load curve with EVs (upper) for one week (peak week of the year)
Frankfurt (Germany), 6-9 June 2011
Reinforcement costs (method of marginal cost)
Network value compared with the peak- low-voltage networks 360 €/kW- medium-voltage network 230
€/kW - primary substation level 100
€/kW
Power flowPower flow
Peak p
ow
er
An example of defining required reinforcement investments on the medium voltage feeder
20 kV feeder (Feeder 1)
-Present peak load of the day: 5.6 MW
-Additional power because of EVs: +2.0 MW
- Average marginal cost: 230 €/kW
Estimated need for reinforcement:
230 €/kW x 2000 kW = 460 000 €
Frankfurt (Germany), 6-9 June 2011
Summary of the feeder-specific results
Total additional load without load control for the case feeders in the MV-network is 10.3 MW. An estimation for reinforcement needs is 2.4 M€. When the reinforcements of the LV-networks and 110/20 kV primary substations are taken into account, the total reinforcement investments will be 7 M€.
Replacement value of the case network would increase by 41 % from the present 17 M€ to 24 M€.
20 kV medium-voltage feeders F1 F2 F3 F4 F5 F6
Present peak [MW] 5.6 5.0 5.5 3.7 8.0 3.6
Number of EVs 1 650 980 1 150 2 500 4 000 1 600
Peak with EVs [MW] 7.6 6.0 6.8 5.0 10.6 5.7
Peak increase in MV network 136% 120% 124% 135% 133% 158%
Reinforcement needs [M€] 0.46 0.23 0.30 0.30 0.60 0.49
Frankfurt (Germany), 6-9 June 2011
Optimised charging (red curve) for the feeder. All the energy for EVs can be taken from the network without increasing the present peak power.
Optimised charging
Optimised charging
Powers [MW] F1 F2 F3 F4 F5 F6
Present peak 5.6 5.0 5.5 3.7 8.0 3.6
Peak with EVs, no optimization 7.6 6.0 6.8 5.0 10.6 5.7
Peak with EV optimisation 5.6 5.0 5.5 3.7 8.0 3.6
There is demand for Smart Grid functions to optimise charging of electric vehicles. With successful optimisation reinforcement of 7 M€ could be avoided in this case area.
Frankfurt (Germany), 6-9 June 2011
Summary of the study
Intelligent control of charging of EVs is strongly recommended in order to avoid a) unnecessary reinforcement investments and b) an increase in distribution fees paid by the end-customers
Without intelligent control of charging, the load growth can be significant, varying from 20 to 50 % in the case feeders
With intelligent charging (smart grids) most of the reinforcement investment could be avoided or delayed
To understand the network effects of EVs, the present electrotechnical condition of the distribution network has to be studied first, and careful estimation of the penetration schedule has to be made
More efforts have to put for developing charging profiles which consists both normal household consumption load curve and EV charging curve for different purposes
Jukka Lassila – Finland – Session 6 – Paper 0773
Frankfurt (Germany), 6-9 June 2011
Jukka Lassila – Finland – Session 6 – Paper 0773
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