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

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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

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Frankfurt (Germany), 6-9 June 2011

Load curves with EVs (100% and 50%)

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Without EVs 100 % penetration level 50 % penetration level

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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

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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