1
The Impact of Charging Plug-in Hybrid Electric
Vehicles on the Distribution Grid
K. Clement, E. Haesen, J. Driesen
Abstract— Alternative vehicles based on internal combustion
engines (ICE), such as the hybrid electric vehicle (HEV), plug-in
hybrid electric vehicle (PHEV) and the fuel-cell electric vehicle
(FCEV), are becoming increasingly popular. HEVs are currently
commercially available and PHEVs will be the next phase in the
evolution of hybrid and electric vehicles.
The batteries of the PHEVs are designed to be charged at
home, from a wall socket in the garage, or on a corporate car
park. These extra electrical loads have an impact on the
distribution grid.
First, the amount of electrical energy the distribution grid has
to deliver for recharging the batteries of a PHEV fleet for the
period 2003-2050 for Belgium is estimated. The TREMOVE
model [1] provides the vehicle-kilometres and the number of
passenger vehicles. For 2030, this electrical energy is at
maximum 5.1% of the generated electricity in Belgium, assuming
that all HEVs are PHEVs and depending on the scenarios of the
PRIMES model [2]. This gives a first indication of the potential
for PHEV.
Secondly, this research aims to analyze the voltage profile and
power losses due to PHEV recharging in a residential network
representing a selection of streets. Uncontrolled power
consumption on a local scale can lead to grid problems.
Index Terms—distribution grid, energy consumption, load flow
analysis, plug-in hybrid electric vehicles.
I.
INTRODUCTION
Because of the large dependency of most countries on
imported fossil fuels and the soaring oil prices, it is essential
to look for alternatives. Other main drives in the development
of hybrid electric vehicles (HEVs) are an increasing concern
for energy efficiency and limiting greenhouse gases such as
CO2 to reduce global warming and to meet Kyoto restrictions.
Downsizing the internal combustion engine (ICE) is possible
without losing performance as the electric motor can generate
a power boost. The HEV always operates near optimum
efficiency and therefore consumes less energy to deliver the
same performance as a conventional vehicle (CV).
HEVs combine two or more different energy sources. The
most common combination is an ICE (petrol or diesel) and an
electric motor. There are several engine architectures
available, such as parallel and series hybrids. In series hybrids,
the wheels are driven by an electric motor. The energy for this
Kristien Clement is with ESAT- ELECTA, Kasteelpark Arenberg 10 bus
2445, 3001 Heverlee – Belgium. Email: Kristien.Clement@esat.kuleuven.be
motor is derived from the batteries or from the ICE with
generator. The ICE provides the average power and the
batteries take up the excess of energy and release it to provide
additional energy when required. In parallel hybrids, both the
ICE and the electric motor drive the wheels. The ICE works
jointly with the electric motor to deliver movement to the
vehicle. The size of the ICE and the electric motor differs
depending on the electric driving possibilities (light, mild and
full). Light HEVs have an ICE with a starter-generator
designed to quickly shut off and restart the ICE during stops
to save fuel. Mild HEVs have an electric motor of 10-20 kW
[3] which permits the start/stop function and also provides a
power boost to the ICE. Full HEVs are capable of driving in
electric-only mode for a limited range. The battery capacity
for HEVs is rather small. For example, the Toyota Prius has a
capacity of 2 kWh.
Plug-in hybrid electric vehicles (PHEVs) will be the next
phase in the evolution of hybrid electric vehicles. Their
batteries will be charged by plugging into electric outlets or
on-board electricity generation. These vehicles can drive full
power in electric-only mode. As such PHEVs offer valuable
fuel flexibility [4]. PHEVs may have a larger battery and a
more powerful electric motor compared to a HEV, but their
range is still very limited [5]. It is not possible to do the daily
mileage fully electric. The capacity of the batteries is about 10
kWh [6] and the power of the electric motor is about 70 kW.
There are several barriers to be overcome for the successful
commercialisation of the PHEV. The storage of the electrical
energy is the most difficult part of the vehicle because of the
limiting factor of the batteries. PHEV will probably cost more
than HEV because of the extra battery capacity. The PHEVs
have two main advantages to HEVs. Because of the extra
batteries the ICE can be better downsized and in contrary to
fuel-cell electric vehicles, the basic charging infrastructure for
PHEVs is existing, but adaptations will be necessary.
There are two main places where the batteries of PHEVs can
be recharged: either on a car park, public or corporate, or at
home. The focus here lies on the latter. From the PHEVowner point of view, the batteries of the PHEV have to be
charged over night so the driver can set off in the morning
with a full battery. From the grid operator point of view, the
power losses during charging have to be minimized and
overloads have to be avoided. Not only power losses, but also
power quality is essential to the grid operator. Night
recharging can increase the loading of base-load power plants
and smoothen their daily cycle [6, 7] or avoid additional
2
II. GENERAL OVERVIEW: TRENDS TO 2030
A. The Belgian vehicle fleet
TREMOVE [1] quantified the Belgian passenger vehicles for
the period 2005-2030 based on a simulation of consumer
behaviour within a business as usual scenario (Figure 1).
In 2005, half of the Belgian market exists of petrol ICE CVs
and the other half of diesel ICE CVs. The fleet of both diesel
and petrol HEVs will be enormously increased by 2030 up to
respectively 1 440 000 and 660 000 vehicles which is 35% of
the diesel vehicles and 30% of the petrol vehicles. For new
technologies, such as HEVs, it takes some time to penetrate
the market, but they will have an important share after some
years. HEVs will take over around 7% of the market by 2010
and around 30% by 2030. At 2010, the amount of diesel and
petrol HEVs is equal and contains both 90 000 vehicles. The
compressed natural gas (CNG) vehicles will have a share of
15% by 2030. Fuel-cell electric vehicles are not taking into
account due to their production and cost uncertainty.
vehicle-kilometres for diesel vehicles are enormously
increasing in contradiction with the petrol vehicles. Figure 2
shows that vehicle-kilometres per year of diesel vehicles
increase from 61 000 up to 70 000 million. In contrast, the
vehicle-kilometres per year of petrol vehicles decrease slightly
from 25 000 up to 23 000 million.
2003-2015
2015-2030
2030-2050
4.1-7.4
3.9-7
3.7-6.6
full HEVs, petrol
4.5-8
4.1-7.4
3.9-7
mild HEVs, petrol
4.9-8.8
4.6-8.3
4.3-7.7
light HEVs, petrol
3.2-5.7
3.1-5.5
3-5.4
full HEVs, diesel
3.4-6
3.2-5.8
3.1-5.5
mild HEVs, diesel
3.7-6.7
3.6-6.5
3.5-6.3
light HEVs, diesel
Table I: Fuel economy of light duty vehicles (Litres of petrol
equivalent/100km) [3]
1000 million vehicle-km/year
generator start-ups which would enhance the general
efficiency.
The electrical consumption for charging PHEVs will take in at
worse about 5% of the total electrical consumption in Belgium
[8] assuming that all HEVs are PHEVs and depending on the
scenarios of the PRIMES model. This would be taken from
the low voltage grid. The impact of charging the PHEVs
batteries is not yet understood, but the authors believe that it
could cause a high risk of overload.
140
120
100
80
60
40
20
0
1995
2000
2005
2010
2015
2020
2025
2030
year
CNG vehicle
Petrol vehicle
Diesel vehicle
LDV
HDV
number of vehicles
Figure 2 Transport volumes (1000 million vehicle-km/year) [1]
III. THE ELECTRICAL CONSUMPTION
7000000
6000000
5000000
4000000
3000000
2000000
1000000
0
1995
2000
2005
2010
2015
2020
2025
2030
year
Petrol HEV
Diesel HEV
Petrol CV
Diesel CV
CNG
A.
Approach
The aim of this paragraph is to determine the amount of
electrical energy of the distribution grid that is needed to
charge the batteries of the PHEV for fulfilling the daily
mileage. This amount of electrical energy can be compared
with the total electricity consumption in Belgium. The period
2005-2030 will be examined and will be narrowed to 20102030 because the HEVs breakthrough is not significant until
2010.
Figure 1: The evolution of the Belgian vehicle fleet [1]
B. The fuel economy of hybrid electric vehicles
Table I gives an idea of the efficiency of HEVs for the period
2003-2050 [3]. The study of McKinsey [9] expects a
consumption of 7.6 l/100 km for petrol ICE vehicles and
6.1 l/100 km for petrol HEVs for the year 2005. For 2020, the
consumption of ICE vehicles will decrease up to 6.0 l/100 km
and for hybrid vehicles up to 5.1 l/100 km.
C.
The transport volumes per vehicle type
TREMOVE has determined the vehicle-kilometres per year
and per vehicle type for Belgium, as shown in Figure 2. LDV
and HDV are respectively light and heavy duty vehicles. The
Table I gives the fuel consumption of HEVs. The batteries are
charged through on-board electricity generation using ICEs
fuelled with diesel or petrol. For a PHEV, not all the electrical
energy for recharging is generated on-board, but the batteries
can be charged with electrical energy from the distribution
grid. This can reduce both fuel consumption and fuel cycle
emissions because power plants may have higher energy
efficiency and lower emissions than vehicles. The size of the
battery is crucial.
It is difficult to predict the proportion of electric driving and
the proportion of driving on diesel or petrol of a PHEV. This
depends from vehicle to vehicle and from trip to trip. 50%
electrical driving is assumed here. This gives us the possibility
to calculate the electrical energy a PHEV consumes per day.
Taking into account that the battery can store a maximum of
electrical energy, the electrical energy delivered by the
distribution grid is limited and can be determined. Figure 1
gives only information about the HEV and not about PHEV,
but PHEV can be taken as an option within the HEV.
2010
2015
2020
2025
2030
Electrical
consumption
[TWh/year]
capacity [kWh/
vehicle-day]
daily km [km/
day-vehicle]
B.
Results
PHEVs are usually full hybrid electric vehicles. The efficiency
of the charger is also important. The battery will be charged
and discharged with an efficiency of 90%. The average driven
kilometres per vehicle type per day are computed. There is no
reason to assume that HEVs will drive fewer or more
kilometres compared to conventional vehicles. Assuming that
these vehicles drive 50% of the time electric, the daily and
yearly electrical consumption of these vehicles is shown in
Table II. The daily vehicle kilometres are based on the model
of TREMOVE. The maximum electrical consumption per
vehicle-day for diesel PHEVs is 16.38 kWh and for petrol
PHEV 10.87 kWh in the year 2010.
30.2
6.02-10.87
0.22-0.40
petrol PHEV
59.1
9.20-16.38
0.34-0.60
diesel PHEV
29.6
5.62-10.08
0.55-0.98
petrol PHEV
58.0
8.75-15.52
1.35-2.39
diesel PHEV
27.7
5.25-9.42
0.81-1.45
petrol PHEV
59.9
9.03-16.03
2.42-4.29
diesel PHEV
29.0
5.50-9.87
1.27-2.28
petrol PHEV
59.5
8.98-15.93
3.46-6.14
diesel PHEV
29.0
5.23-9.33
1.40-2.50
petrol PHEV
59.6
8.70-15.65
4.02-7.24
diesel PHEV
Table II: The electrical consumption of PHEVs
The Toyota Prius has a battery capacity of 2 kWh, but the
converting PHEV kits have battery capacities ranging from 5
to 12 kWh [10] and the prototype of the DaimlerChrysler
Sprinter has a capacity of 14.4 kWh, using Lithium-ion
batteries [11]. Petrol PHEVs can drive 50% electric without
on-board generation of electricity, so the electrical energy that
is stored in the battery is coming from the distribution grid.
Diesel PHEVs can not do their daily mileage with the energy
of the distribution grid, but they need also on-board
generation. It is essential to notice that the daily driven
kilometres differ from year to year and from type of fuel
(petrol or diesel). Petrol PHEVs have lower vehiclekilometres per year compared to diesel vehicles.
The total consumption of the HEVs for Belgium, assuming
that the fleet of hybrid vehicles will exist of 100% PHEVs is
giving in Table II. These figures can be compared with the
amount of generated electricity in Belgium to give an idea of
the percentage they will take of the yearly consumed
electricity.
Figure 3 shows the prediction of the Commission 2030 [2]
about the generated electricity according to the different
scenarios.
elektrical consumption
[TWh]
3
140
120
100
80
60
40
20
0
2000
2005
2010
2015
2020
2025
2030
year
baseline scenario
Bpk15n
Figure 3: Generated electricity: total electrical consumption [2]
In the Bpk15n scenario reduces Belgium its energy CO2
emissions by 15% in 2030 compared to the 1990 level. The
consumption according the Bpk15n scenario is 9.6% higher in
2030 compared to the baseline scenario. This information
gives us the possibility to determine the proportion of the
electrical consumption for charging PHEVs to the total
electrical consumption in Belgium and is given in Table III.
ratio for baseline
ratio for Bpk15n
scenario [%]
scenario [%]
0.3
0.3
petrol PHEV
2010
0.5
0.5
diesel PHEV
0.8
0.8
petrol PHEV
2015
2.0
1.9
diesel PHEV
1.1
1.1
petrol PHEV
2020
3.4
3.1
diesel PHEV
1.7
1.6
petrol PHEV
2025
4.6
4.2
diesel PHEV
1.8
1.6
petrol PHEV
2030
5.1
4.7
diesel PHEV
Table III: The electrical consumption of PHEVs compared with the
electrical consumption in Belgium
The electrical consumption for charging PHEVs will take in
the worse case about 5.1% of the total electrical consumption
in Belgium. It is also essential to remark that all this energy
will be taken of the low voltage grid, for example at the
standard electric outlet in the garage. Table III assumed a
constant electric drive proportion of 50%. A limit or boundary
condition for this variation is the amount of energy the
batteries can store, assuming that PHEVs will only be charged
at night and that there is no (quick) charge possibility during
the day.
IV. LOAD FLOW ANALYSIS
Before introducing the planning of the charging of PHEVs, it
is essential to know the impact of the charging without direct
control. Without direct controlling, the PHEVs are starting to
charge when they are plugged in or with a start-delay. Three
different cases are investigated. First the vehicles will start
charging between 0.00 and 2.00 a.m. until the battery is fullycharged. In a second case, the PHEVs are immediately
plugged in when arriving at home after work which is
between 6.00 and 8.00 p.m which is acceptable because at
4
21.00 p.m., most of the vehicles are parked [12]. In the last
case, charging during the day is regarded. The impact on the
low voltage grid in terms of power losses and voltage
deviations is investigated.
A. Grid topology
The radial network used for this analysis is the IEEE 34 node
test feeder shown in Figure 4. This network is downscaled
from 24.9 kV to 230 V so this grid topology represents a
residential radial network. The line impedances are adapted to
achieve tolerable voltage deviations and power losses. Each
node is a connection with a residential load and some of the
connections which are randomly chosen, have PHEVs
recharging.
~
Figure 4: Grid topology: grid with 34 nodes.
B. Load scenarios
Two load scenarios are analyzed.
• Low load scenario: from the available set, the daily load
profile with the highest peak during each season is chosen
together with three randomly chosen daily load profiles.
• High load scenario: from the available set, the four daily
load profiles with the highest daily averages during each
season are chosen.
Two seasons are distinguished: winter and summer. Each
scenario exists of four daily load profiles of Belgium. The
daily load profiles cover 24 hours and the energy consumption
is given per quarter of an hour. Figure 5 represents a randomly
chosen household load for one day.
900
800
power [W]
700
600
500
400
300
200
C. Backward-forward sweep method
The backward-forward sweep method is used for calculating
the node-currents, line-currents and node-voltages. This
method has two stages: the backward and the forward step. At
the initialization step, a flat profile of 230 V is taken for the
node-voltages. The backward and forward sweeps become a
matrix multiplication. In the backward step, the currents are
computed based on the voltages of the preceding iteration. In
the forward step, the voltages are computed based on the
voltage at the root node and the voltage drops of the lines
between the nodes. The currents and voltages are updated
iteratively until the stopping criterion, node-voltages based, is
reached. The charging of the PHEVs is treated as an extra load
of constant power together with daily load profiles.
D. Methodology
At the start of the day, for each node, one of the four daily
profiles of the selected load scenario is randomly determined.
For each scenario, four different cases depending on the
penetration of the PHEVs can be distinguished. In the first
case, no PHEVs are assumed so this is taken as reference case.
The next three cases have a PHEV penetration of respectively
10, 50 and 100%. The number of the PHEVs is depending on
the chosen scenario and the PHEVs are placed randomly. For
instance for the 50%-penetration case, one half of the nodes
will have a PHEV-load and these loads are randomly placed.
In the reference case, none of the nodes will have PHEVs
charging and in the 100% case, each of the nodes will have an
extra electrical load because of the PHEVs. These extra loads
of charging the PHEVs are added to the load of the
households which is of course always present.
The profile for charging the PHEVs is kept very elementary.
The batteries of the vehicles will be charged with a constant
power of 2.5 kW and an efficiency of about 90%. The period
of charging takes 4 hours. The start of the PHEVs charging is
randomly chosen for each individual vehicle within a specific
period of time.
The batteries of the vehicles will be empty at the end of the
day and fully-charged at the morning after. In the first case,
the start of the charging period is arbitrary chosen between
0.00 and 2.00 a.m. and is constant. Another important aspect
is to check the impact when the vehicles would be charged
when arriving at home (6.00 - 8.00 p.m.). The extra loads of
the vehicles are going together with a peak in the electricity
consumption of the households in the evening. In the last case,
the charging starts between 1.00 and 2.00 p.m.
For every quarter of an hour, the backward-forward sweep
method is performed for computing the voltage at each node
until convergence is obtained. The results are discussed in the
next paragraph.
100
0
0
1 2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
time [hours]
Figure 5: Household load during winter time.
E. Results
For illustrating the impact of charging PHEVs without direct
control, the power losses, the voltage deviations and profiles
are considered in this paragraph.
Table IV presents the ratio of the power losses to the total
energy consumption of the households and the PHEVs. The
5
scenario
season
0%
low scenario
high scenario
penetration of PHEV
10%
50%
100%
summer
2.6
2.9
6.7
winter
3.7
3.9
6.8
22.6
summer
2.9
3.1
6.7
23.8
24.4
winter
4.1
4.2
7.1
22.1
Table IV: ratio of power losses to total power in %, charging between
0.00 - 2.00 a.m.
Not only the power losses, but also the voltage deviations of
the grid voltage (230 V) are important for the operator of the
distribution grid which is presented in Table V. The voltage
deviations are only compared during the time of charging. The
impact of the number of PHEVs is larger than the impact of
the several scenarios for the same reason as mentioned above.
Voltage deviations up to 10% are acceptable, so for a
penetration of 10%, there is not a problem. But for a
penetration of 50% and 100%, the voltage deviations are
between 16 and more than 60%. This low power quality is not
allowed according to the norm EN50160.
scenario
low scenario
season
summer
230
220
voltage [V]
values are compared during the whole day and the average is
taken over 3000 samples. The impact of the degree of
penetration of the PHEVs is larger compared to the impact of
choice of scenario. The power of the charger is always higher
compared to the household loads which are presented in
Figure 5. The low impact of the scenarios can be explained by
the low maximum variation of the household loads during the
night for the different scenarios which is about 25% in the
worse scenario. A random peak of a household load during the
night is not going to change the line losses radically because
these losses are a kind of weighted average of all powers of
the whole network for a specific period of time. The increase
of the number of PHEVs indicates a significant increase in the
ratio of power losses.
210
200
190
180
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
time [hours]
50% PHEV
0% PHEV
Figure 6: Voltage profile with 50% PHEV compared to
voltage profile with 0% PHEV
It is important to know the impact of charging the vehicles
without direct control, thus immediately after arriving at
home. At 6.00 p.m., the largest part of the fleet is on the road
and this amount is decreasing from this moment till 9.00 p.m.,
when only about 2.5% of the vehicles are on the road. Table
VI and Table VII present respectively the power losses and
the voltage deviations for start charging at 8.00 p.m. The
impact is computed as an illustration to indicate why optimal
charging of the PHEVs is advisable.
These tables must be compared by Table IV and Table V.
Both the power losses and the voltage deviations are higher
for charging at 9.00 p.m. because the higher household loads.
scenario
season
0%
penetration of PHEV
10%
50%
100%
summer
low scenario
winter
2.6
3.4
8.8
29.3
3.7
4.6
10.4
29.6
summer
2.9
3.7
9.2
28.5
winter
4.1
5.0
10.8
29.7
Table VI: Ratio of power losses to total power in%, charging between
6.00 - 8.00 p.m.
high scenario
penetration of PHEV
0%
2.8
10%
50%
100%
4.9
16.6
62.0
3.2
winter
5.1
16.9
62.4
3.0
5.0
16.8
62.2
summer
high scenario
winter
3.6
5.3
17.3
62.5
Table V: Voltage deviations in %, charging between 0.00 - 2.00 a.m.
Figure 6 represents the voltage profile of node 33 for the cases
of 0% and 50% penetration of PHEVs. The high load scenario
in the winter is chosen and the daily household load profiles
for both nodes are the same. This figure represents only one
charging example. There is clearly a decrease of the voltage in
the case of 50% penetration during the charging period.
Between 2.00 and 4.00 a.m., all the vehicles are charging and
the voltage drop in these hours is the largest. The power
needed for charging these vehicles is a significant amount
higher compared to the household loads during the night.
scenario
low scenario
high scenario
season
penetration of PHEV
0%
10%
50%
100%
summer
4.2
7.3
20.8
64.2
winter
6.8
10.0
25.6
64.7
summer
4.9
8.1
22.3
63.1
winter
7.5
10.4
26.5
65.1
Table VII: Voltage deviations in%, charging between 6.00 - 8.00 p.m.
Charging during the day is also an option. Table VIII and
Table IX show the results. The impact on the distribution grid
is high for both the power losses and the voltage deviations.
But charging during the evening peak equals more or less the
charging during the day. Of course, this is not quick charging
with high power during the day, because the period of
charging is still 4 hours.
6
scenario
season
0%
low scenario
penetration of PHEV
10%
50%
Kristien Clement received the M.S. degree in electromechanical engineering in 2004 with specialization
Energy. Currently, she is working toward her Ph.D in
electrotechnical engineering at the K.U.Leuven
division ELECTA. Her research interests include
hybrid and electric vehicles.
100%
summer
2.6
3.2
8.5
30.9
winter
3.7
4.3
9.5
30.3
summer
2.9
3.5
8.7
29.9
4.1
4.8
10.3
30.3
winter
Table VIII: Ratio of power losses to total power in %, charging between
1.00 - 2.00 p.m.
high scenario
scenario
season
penetration of PHEV
0%
10%
50%
3.8
6.5
19.3
64.2
summer
6.3
8.6
22.7
64.8
winter
summer
4.1
6.9
19.9
64.5
high scenario
winter
7.4
9.8
25.1
65.1
Table IX: Voltage deviations in %, charging between 1.00 - 2.00 p.m.
low scenario
V. CONCLUSION
The charging of the PHEVs has a significant impact on the
transmission and the distribution grid for each time of the day.
For the distribution grid, the increase of the power losses and
voltage deviations are too essential to ignore. This shows the
importance of controlling the charging of the vehicles which
will be part of further investigation.
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Conference & Exposition , Atlanta, Georgia, USA, Oct.29-Nov.1, 2006;
pp. 741-747.
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Edwin Haesen (S’05) received his M.Sc. degree in
electrical engineering at the KU Leuven in 2004. For
his Master Thesis on “Technical Aspects of
Congestion Management” he received the European
Talent Award for Innovative Energy Systems 2005. He
is currently pursuing a Ph.D. at the KU Leuven as a
research assistant at the division ESAT-ELECTA. His
research interests are in the domain of power system
analysis and distributed generation.
Johan Driesen (S’93–M’97) was born in Belgium in
1973. He received the M.Sc. and Ph.D. degrees in
electrical engineering from Katholieke Universiteit
Leuven (K.U. Leuven), Leuven, Belgium, in 1996 and
2000 on the finite element solution of coupled
thermal-electromagnetic problems and related
applications in electrical machines and drives,
microsystems, and power-quality issues. Currently, he
is an Associate Professor with K.U. Leuven and
teaches power electronics and drives. In 2000–2001, he was a Visiting
Researcher with the Imperial College of Science, Technology and Medicine,
London, U.K. In 2002, he was with the University of California, Berkeley.
Currently, he conducts research on distributed generation, including
renewable energy systems, power electronics and its applications (e.g., in
drives and power quality).