challenges of phev penetration to the residential distribution network

8/13/2019 Challenges of Phev Penetration to the Residential Distribution Network

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AbstractAs Plug-in Hybrid Vehicles (PHEVs) take a greater

share in the personal automobile market, their penetration levels

may bring potential challenges to electric utility especially at the

distribution level. This paper examines the impact of charging

PHEVs on a distribution transformer under different charging

scenarios. The simulation results indicate that at the PHEV

penetration level of interest, new load peaks will be created,

which in some cases may exceed the distribution transformercapacity. In order to keep the PHEVs from causing harmful new

peaks, thus making the system more secure and efficient, several

PHEV charging profiles are analyzed and some possible demand

management solutions, including PHEV stagger charge and

household load control, are explored.

Index Terms-- Demand management, household load control,

PHEVs and stagger charge.

I. INTRODUCTION

ITH a recent hike in gas price and the concern about

global warming, major automotive manufacturers have

introduced plug-in hybrid electric vehicles (PHEVs) into theworld market. A plug-in hybrid is a vehicle that can be

plugged in to the electricity grid and can be driven by

electricity for at least 10 miles without consuming any

gasoline [1]. It is expected that by 2010, plug-in hybrids will

be widely available in the United States [2].

Since early 2007, plug-in hybrids have become a very

popular topic for research and development. Most of the

previous published studies related to PHEVs aimed at

studying the potential impacts of PHEV at the generation level.

Findings from Pacific Northwest National Laboratory (PNNL)

[3] indicated that existing electric power generation plants

would be used at full capacity for most hours of the day to

support up to 84% of the nations cars, pickup trucks andSUVs for a daily drive of 33 miles on average. Conclusions

from Oak Ridge National Laboratory (ORNL) [4] indicated

that most regions would need to build additional generation

capacity to meet the added demand when PHEVs are charged

in the evening. A National Renewable Energy Laboratory

(NREL) [5] study showed that a very large penetration of

This work was supported in part by the U.S. Department of Defense under

Grant W912HQ-08-C-0037.

S. Shao is with Virginia Tech Advanced Research Institute, Arlington,

VA 22203 USA (e-mail: [email protected]).

M. Pipattanasomporn is with Virginia Tech Advanced Research Institute,

Arlington, VA 22203 USA (e-mail: [email protected]).

S. Rahman is professor and director of Virginia Tech AdvancedResearch Institute, Arlington, VA 22203 USA (e-mail: [email protected]).

PHEVs would place increased pressure on peak units with an

uncontrolled charging strategy. However, no additional

generation capacity would be required for a large penetration

of PHEVs when charging cycles start in the off-peak periods.

Other research and development (R&D) in this field

includes basic research related to PHEV technology

development. For example, the author in [6] compared the use

of lithium-ion batteries and carbon/carbon ultra capacitors asthe energy storage technology for PHEVs. Authors in [7]

developed a bipolar battery utilizing a wafer cell design for

meeting the high-energy demands of modern PHEVs. Authors

in [8, 9] developed optimal power management of PHEVs.

The other aspects of PHEV research, which are as

important as the two aspects mentioned above, but have not

been discussed in the literatures at the time of writing this

paper, are to evaluate the adaptability of the residential

distribution network to support PHEVs. This paper addresses

this issue as it is very important to understand the implications

of adding PHEVs onto the electrical grid at the distribution

level. Depending on the location and time the vehicles are

plugged in, usage patterns of local distribution grids will be

changed.

The objective of this paper is to evaluate the impacts of

charging PHEVs on a residential distribution network with

different charging strategies. The distribution transformer

loading levels with PHEVs are analyzed and some possible

demand management strategies are investigated. This paper is

organized as follows: section II discusses the residential

distribution network of interest, together with the daily load

curves in both summer and winter months. Section III

describes the battery model developed in MATLAB/Simulink,

together with its charging and discharging characteristics. The

battery model developed is based on the specifications ofChevy Volt Li-ion battery. Section IV presents the hourly load

curves seen by a distribution transformer when PHEVs are

charged based on different charging strategies. The analysis

points out that charging PHEVs in a residential distribution

network will create new load peaks for a distribution

transformer. However, charging PHEVs at different times of

the day may result in a slight increase or decrease in the

distribution transformer efficiency, depending upon the

existing transformer loading levels, time of charge and the

PHEV charging strategy used. Furthermore, allowing quick

charge may easily result in overloading of a distribution

transformer even with the low PHEV penetration level beingdiscussed here. In Section V, some simple algorithms for

Challenges of PHEV Penetration to theResidential Distribution Network

Shengnan Shao, Student Member, IEEE, Manisa Pipattanasomporn,Member, IEEE,and SaifurRahman, Fellow, IEEE

W


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PHEV charge control and demand management are explored

for the utility companies to deal with new load peaks caused

by PHEV penetration.

II. RESIDENTIAL DISTRIBUTIONNETWORK MODEL AND

HOURLY LOAD CURVES

In general, a distribution network is referred to as all

distribution-level components located downstream of a

distribution substation. In the context of the Virginia Tech

Electric Service (VTES) in Blacksburg, VA, the distribution

substation steps down the voltage from 69kV to 12.47kV. The

distribution voltage is at 12.47kV and lower. There are several

distribution transformers, which step down the voltage further

to customer utilization voltages of 110V, 240V or 480V.

Depending on load sizes and types, distribution transformers

typically range in size from 25kVA to 75kVA per phase. A

typical 25kVA distribution transformer generally serves four

to seven homes in a neighborhood. The residential distributionnetwork studied in this paper is a typical 25kVA distribution

transformer that serves a neighborhood of five homes.

Hourly residential load curves of an average household are

available from the RELOAD database [10], which is used by

the Electricity Module of the National Energy Modeling

System (NEMS). The hourly residential load curve data are

available for twelve months (January to December), three day

types (typical weekday, typical weekend and typical peak day)

and nine load types (space cooling, space heating, water

heating, cooking, cloth drying, refrigeration, freezing, lighting

and others). As the load curves in the RELOAD database

represent hourly fractions of the yearly load, the load curves

will need to be scaled up by the annual household

consumption and divided by the number of hours in a year,

which is 8760. Therefore, the adjustment made to the hourly

RELOAD residential load curves for each load type can be

represented by (1):

(1)8760

annualhour

LL f=

where:

Lhour = Average hourly load (kWh/h)

f = Hourly fraction of yearly load

Lannual= Average annual household load

Since in Blacksburg, VA, the winter peak load appears in

January and the summer peak load appears in August, the

hourly load data used in this paper are taken from these two

months. Using (1) and the assumption that all houses have the

same hourly load shape, the load shape of five houses in both

winter and summer months can be illustrated in Fig. 1 and Fig.

2, respectively. In this case, the peak load in the winter month

is about 14kW while that in the winter month is about 13kW.

It is apparent that a typical distribution transformer (in this

case, a 25kVA transformer) is lightly loaded at about 35% on

average and about 52-57% at the peak.

Fig. 3 shows a typical 25kVA distribution transformer

efficiency curve, which represents the relationship between

transformer efficiency and its loading level in percent. This

relationship is quantified by assuming that the core loss (no

load loss) is 51 Watts [11] and the internal resistance (winding

loss) is 0.01 Ohm.

Fig. 1. Hourly winter load seen by a 25kVA distribution transformer, servingfive homes.

Fig.2. Hourly summer load seen by a 25kVA distribution transformer, serving

five homes.

It can be seen that the distribution transformer efficiency

varies from 97.2% to 98.7% during various loading conditions

and that a distribution transformer operates at its highest

efficiency when it is loaded at roughly 35%.

Fig. 3. Transformer efficiency curve.

III. PHEVBATTERY CHARACTERISTICS

To investigating the impacts of charging PHEVs on the


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distribution network, PHEV and its charging characteristics

are discussed in this section.

A. PHEV Battery Specifications

The battery model used in this paper is based on the

specifications of the Chevy Volts battery. Chevy Volt is ahybrid electric vehicle expected to be available in 2010.

Chevy Volt uses a lithium-ion battery that can provide all

electric driving range of 40 miles and has a plug-in recharge

capability. A gasoline-power engine is also used as an

onboard range extender for battery. Chevy Volt battery

specifications are shown in Table I.

TABLE I.CHEVY VOLT BATTERY SPECIFICATIONS [12]

Description Characteristics

Battery type Lithium-ion

Energy 16 kWh

Voltage 320 to 350VFull recharge time at 110V outlet 6 to 6.5 hours

Electric range 40 miles

In general, there are two basic modes of PHEV operation,

namely charge depleting and charge sustaining modes. Within

the electric range, i.e. 40 miles for Chevy Volt, the fully

charged PHEV is driven in the charge-depleting mode. During

this period, energy stored in the battery is used to power the

vehicle causing the battery state of charge (SOC) to gradually

decrease. Once the battery is depleted to its minimum level,

the vehicle switches to the charge-sustaining mode [13].

During this mode, electricity is transferred from the gasoline

engine generator to maintain the battery SOC to be higher

than the minimum level. In the case of Chevy Volt, the

gasoline engine is only used to charge the battery and is not

designed to drive the vehicle directly.

B. Battery Discharge Characteristics

The PHEV battery model is developed in Matlab/Simulink

based on the battery specifications described in Table I. The

discharge characteristic of the developed battery model is

displayed in Fig.4 as the relationship between battery voltage

(V) and battery capacity (Ah).

Fig. 4. Discharge characteristic of the developed battery model according to

the battery specifications described in Table I.

C. Battery Charge Characteristics

The charging circuit is designed such that the recharge time

at 110V outlet from 30% to 80% is approximately 6 to 6.5

hours according to the battery specifications provided by

Chevy Volt [14]. Fig. 5 displays four battery parameters

during the charging period, namely the battery rechargecurrent (A), battery voltage (V), battery SOC (%) and battery

recharge power (kW). Notice that it takes about 6.5 hours for

the battery to be fully charged.

Fig. 5. Charging characteristics of normal charge from a standard 110V/15A

outlet: (a) battery recharge current (A); (b) battery voltage (V); (c) battery

SOC (%); and (d) battery recharge power (kW).

According to Fig. 5, the required maximum charging power

for a PHEV is approximately 1.45kW, which can be drawn

from a standard 110V/15A outlet.

IV. HOURLY LOAD CURVES WITH PHEVSBased on the hourly load curves seen by a distribution

transformer during summer and winter months (Fig. 1 and Fig.

2) and the PHEV battery charging model developed in

MATLAB/Simulink (Fig. 5), hourly load curves with PHEVs

can be derived.

For the purpose of this study, we consider a 25kVA

distribution feeder that serves five houses with two PHEVs as

per our case study. The reason behind this assumption can be

explained as follows:

There are about 20 million cars sold every year in the USand the market share of PHEVs is expected to rise to 25%

between now and 2020 [4]. Assuming that the PHEVmarket share increases linearly, we can roughly estimate


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that there will be about 25 million PHEVs by the year

2020.

The projected number of passenger vehicles in 2020 iscalculated to be 285 million, according to the linear

regression analysis using the data [15] from 1990 to 2006.

25 million PHEVs out of 285 million passenger vehiclesis equivalent to the PHEV penetration rate of about 9%.

In 2006, there were about 235 million passenger vehiclesregistered in the U.S. [15]. It is estimated that there are

about 110 million households in 2006 [16]. This is

equivalent to about two cars per household. Since the

PHEV penetration rate is estimated at 9%, there is likely

to be at least one PHEV in every 5 households.

Since it is possible that there will be at least two PHEVs per

distribution transformer in the near future, the number of

PHEV per transformer considered here is two. Two different

PHEV charging strategies are considered, namely normalcharging and quick charging strategies. Each charging strategy

is described below:

A. Normal Charging Strategy

The normal charge is defined as the standard PHEV charge

from the 110V/15A outlet as specified in Chevy Volts

specifications.

a) All PHEVs start charging at 6 pm

In this case, two PHEVs are charged whenever they are

plugged in. During a typical weekday, we assume that all

vehicle owners arrive home close to 6 pm with the initial

PHEV SOC of 30%. Therefore, both PHEVs are plugged in tohousehold electrical outlets at 6 pm. Fig. 6 illustrates the

PHEV charging profile added to the winter and summer loads.

The blue line represents the total household load (kW), as

discussed in Fig. 1 and Fig. 2. The horizontal red line

represents the rated power (kW) for a 25 kVA distribution

transformer with 0.95 lagging PF load, which is 23.75 kW.

Fig. 6. Hourly load profiles seen by a 25kVA transformer serving five houses

and two PHEVs (all PHEVs are charged at 6 pm - normal charge).

It takes about 6.5 hours to fully charge PHEVs from 30%

SOC to 80% SOC. Therefore, both PHEVs are charged from 6

pm and will stop around 12:30 am. However, charging all

PHEVs at 6 pm coincides with the evening load peaks in both

summer and winter months. Hence, charging all PHEVs at 6

pm illustrates the worst case scenario that all PHEVs come

home with the minimum SOC and start charging at the sametime. However, this is possible and very likely to happen. In

this case, the maximum transformer loading levels increase to

68% in winter and 52% in summer.

b) All PHEVs are charged during off-peak hours

This case simulates the scenario when PHEV owners are

sensitive to the time-of-use rate structure. In this case, PHEV

owners will wait to charge their PHEVs during off-peak hours.

According to the Dominion Virginia Power (DOM) [17], the

off-peak hours during summer months start from 10 pm to

11am; and the off-peak hours during winter months start from

9 pm to 7am and 11 am to 5 pm. Although winter months has

two off-peak periods, the off-peak period during the day time

will not be taken into consideration because PHEVs are not

likely to be at the house during that time. Fig.7 illustrates the

off-peak PHEV charging profile added to the winter and

summer loads.


and two PHEVs (all PHEVs are charged during off-peak hours).

In this case, charging PHEVs during off-peak hours will

create new load peaks at the start of off-peak hours in bothsummer and winter months. The new load peaks created

during off-peak hours are a little higher than the original

peaks, i.e. 58% in winter and 52% in summer. This may imply

a slight increase in transformer efficiency during off-peak

periods (after midnight) because charging PHEVs during off-

peak will increase transformer loading level close to 35% - the

loading level that yields maximum transformer efficiency.

B. Quick Charging Strategy

Although the distribution transformer in both normal

charging strategies is not overloaded, there is another case that

should not be neglected. This is when the PHEVs are allowed

to be quick charged.

Hourly load (kW)Total loads with PHEVs

Transformer kW loading capacity

Hourly load (kW)

Total loads with PHEVsTransformer kW loading capacity


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Quick charge is a PHEV charging strategy when PHEVs

are allowed to be charged at a higher voltage and/or current to

achieve a faster charging duration. This characteristic is

allowed by several vehicle manufacturers. For example, the

body of Mitsubishi i-MiEV has two charging inlets: one for

standard 110V and the other for quick charge at a highervoltage. While it takes 14 hours to fully charge Mitsubishi i-

MiEV with standard 110V outlet, it only takes 30 minutes to

fully charge the vehicle with the quick charge.

Since some vehicle owners may not want to wait 6 to 6.5

hours for the recharge, it is possible that they will upgrade

their household electrical outlets to allow a quick charge at

home. The quick charge is usually done through a 240V/30A

outlet [4], which is available in some houses or can be easily

acquired through rewiring.

Fig. 8 shows the PHEV quick charging characteristics from

a 240V/30A outlet, namely battery recharge current (A),

battery recharge voltage (V), battery state of charge (SOC)

and battery recharge power (kW).

Fig. 8. Charging characteristics of quick charge from a 240V/30A outlet: (a)

battery recharge current (A); (b) battery voltage (V); (c) battery SOC (%); and

(d) battery recharge power (kW).

It is apparent that it takes less than 1.8 hours to recharge the

vehicle from 30% SOC to 80% SOC. However, higher peak

power is required, i.e. roughly 5.8 kW.

a) All PHEVs are quick-charged at 6 pm

To compare with the normal 6 pm charging scenario, two

PHEVs are assumed to start quick charging at 6 pm. Fig. 9

shows the PHEV charging profile added to the winter and

summer loads.

Fig. 9 illustrates that quick charging both PHEVs at 6 pm

will overload the transformer, i.e. it increases the peak load to

103% in winter and 98% in summer. It is important to note

that the load curves used in this study represent average

loads of a typical weekday in a residential distribution

network. In reality, the instantaneous distribution loads

fluctuate much more. Therefore, the new peak caused byquick charging PHEVs at household outlets as shown in Fig. 9

may be higher when instantaneous load demands are

considered.

Allowing PHEVs to be quick-charged apparently will

increase the transformer loss, thus reducing the system

operating efficiency. As shown in Fig. 3, increasing the

transformer loading from 35% to 100% reduces the

transformer operating efficiency by at least 1 percent. This

will result in adverse affects to the distribution utility as a

whole, if there is a large-scale PHEV penetration.


and two quick-charge PHEVs (All PHEVs are quick charged starting at 6 pm).

b) All PHEVs are quick-charged during off-peak hours

In this case, both PHEVs will be charged during off-peak

hours. Fig. 10 illustrates the PHEV quick-charging profiles

added to winter and summer load respectively.


and two quick-charge PHEVs (all PHEVs are quick charged during off-peak).

Hourly load (kW)

Total loads with PHEVs


Hourly load (kW)



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The analysis shows that when two PHEV quick charges

occur during off-peak hours, a new peak created by new

PHEV loads is much higher than the original peak. The peak

loads increase to 93% in winter and 86% in summer.

V. PHEVCHARGE CONTROL AND DEMAND MANAGEMENTAlthough allowing transformer overloads for a short time is

not an unusual practice for some utilities, this can become a

serious issue when a number of PHEVs are connected to a

distribution transformer, i.e. five PHEVs per distribution

transformer. To deal with the challenges caused by high

PHEV penetration, one apparent solution is to upgrade the

distribution transformers. However, there are more than 100

existing distribution transformers even in a small distribution

circuit in a small town like Blacksburg, VA. Upgrading these

distribution transformers will require new resources.

Instead of installing additional transformer capacity,

another possible approach is to perform demand management,which can be accomplished by (a) staggering the PHEV

charging time, or (b) performing household load control. The

implementation of the demand management with PHEVs is

built upon an existing infrastructure and is mainly a software-

based solution. In most cases, the software-based solution can

be considered more cost effective than a hardware-based

solution, i.e. upgrading distribution transformer.

The proposed demand management strategies requires

Advanced Metering Infrastructure (AMI) to monitor

household loads, together with a PHEV control unit and

remote switches. These remote switches are used to control

the ON/OFF status of PHEV outlets and household loads. Fig.

11 depicts the infrastructure required to implement demand

management strategies at a distribution transformer serving

five houses.

Fig. 11. Infrastructure required to implement PHEV charge control and

demand management, including AMI, a PHEV control unit and a remote

switch for PHEV control.

A. Methodology for PHEV stagger charge

In our study, the stagger charge implies that the PHEVs are

allowed to be charged only when the current load (kW) seen

by the distribution transformer is less than a specified value,i.e. when the current distribution transformer load does not

exceed its original peak load.

In the stagger charge method, the PHEV control unit

monitors the distribution transformer load information (based

on household loads from AMI) and continuously compares it

with a pre-determined loading value. PHEVs will be charged

if the transformer load is less than the pre-determined loadingvalue, i.e. original peak load. However, if the transformer

loading is greater than the pre-determined loading value,

charging PHEVs will be delayed until the transformer loading

falls below the threshold.

To simulate the stagger charge method, it is assumed that

PHEVs will be plugged in any time between 6 pm and

midnight. The simulation setup can be described as follows:

1. Two random numbers are generated to characterize thePHEV plug-in time, which can be any time between 6

pm and midnight.

2. The transformer load is constantly monitored. Thethreshold to delay the PHEV charge is set at the average

original peak seen by the distribution transformer.

In this case, if the transformer load is less than the original

peak load, charging PHEVs is allowed. However, if the

transformer load is over the limitation, charging PHEVs is

delayed. Fig. 12 shows the staggered PHEV charging at

normal rate added to winter and summer loads.


and two PHEVs (staggered charge at normal rate).

The same analysis could be conducted to quantify theimpact of stagger charge on the distribution transformer load

profile when the quick charge is allowed. The simulation

setup for the quick charge analysis is similar to that of the

normal charge case described above. Fig. 13 shows load

profiles with two quick-charge PHEVs when the stagger

charge methodology is used.

Hourly load (kW)



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and two quick-charge PHEVs (staggered)

It can be seen from Fig. 12 and Fig. 13 that the stagger

control can reduce the peak load caused by charging PHEV,

as opposed to other uncontrolled charging methods. Therefore,

the staggered charge method will help smooth the load seen

by the distribution transformer, thus mitigating the new peak

problem. This method is also suitable for managing a large

number of PHEVs in a residential distribution network. As a

result, new peaks will not be created. However, people whohave the quick-charge facility at home may not always want to

wait. Hence, the household load control method discussed

below is introduced as an alternative.

B. Household Load Control

In this study, the household load control implies that the

non-critical loads can be shed or deferred when PHEVs are

being charged. In the household load control method, real-

time electrical energy consumptions of all household loads

must be monitored. These household loads can be monitored

by AMI. With AMI, PHEV loads can be sensed at the time of

plug-in. Then, a PHEV control unit can shed or defer some

non-critical loads, like water heaters or clothes dryers, for a

short time to support the PHEV quick charge.

Because there exist only minimal impacts when a small

number of PHEVs are charged at the normal rate, this analysis

will only consider the household load control option with the

PHEV quick charging strategy. Fig. 14 shows the result from

the household load control method with PHEV quick charge.

According to Fig. 14, the new peak increases to about 15

kW. In contrast to the stagger charging method, the PHEV

owners will not have to wait longer for their quick charge.

The vehicles can finish charging within 1.8 hours from the

time they are plugged in. This household load control option

requires that a utility gives users who are willing to let their

non-critical loads be controlled some discounts. Additionally,the utility could charge the demand charge to the PHEV

owners with quick-charge capability.


and two quick-charge PHEVs (Quick charge with household load control)

In Table II we summarize the financial and transformer

operating efficiency impacts of the various charging scenarios

under the time-of-use (TOU) rates offered by the local electric

utility. The tariff schedule used is based on that of Dominion

Hourly load (kW)Total loads with PHEVs


Hourly load (kW)


TABLE II.IMPACT OF VARIOUS CHARGING SCENARIOS ON FINANCIAL AND TRANSFORMER OPERATING EFFICIENCY

Charging strategies Additional annual

cost to charge a

PHEV

Peak load (% of

transformer rating)

Transformer efficiency at

peak load (%)

Winter Summer Winter SummerBase case: without PHEVs $0 57.0% 52.0% 98.53% 98.59%Case 1: Normal charge

a) Charging at 6 pm $269.83 68.5% 63.5% 98.38% 98.45%b) Charging during off-peak $40.97 58.0% 52.0% 98.52% 98.59%Case 2: Quick charge

a) Charging at 6pm $438.12 103.1% 98.1% 97.84% 97.92%b) Charging during off-peak $40.97 92.8% 86.2% 98.00% 98.11%Case 3: PHEV charge control and demand management

a) Staggered normal charge, random plug-in time $40.97-$269.83 62.7% 57.7% 98.46% 98.53%b) Staggered quick charge, random plug-in time $40.97-$438.12 80.0% 75.1% 98.21% 98.28%c) Demand control-quick charge, random plug-in time $40.97-$438.12 82.5% 78.5% 98.17% 98.23%


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Virginia Power Residential Rates and Tariffs (Schedule 1T).

The rate is 15.004 c/kWh for all on-peak kWh and 1.403

c/kWh for all off-peak kWh [17]. Table II indicates that the

additional electricity cost due to the charging of the PHEV

from the supply at home is as low as $40.97 per car for the

whole year, or as high as $438.12 per car annually if quickcharging is used during peak hours. Thus, it is advisable to

avoid quick charging during peak hours, if possible. On the

other hand the impact on transformer overloading due to

charging of one or two PHEVs per one distribution

transformer is negligible. Therefore, the issues of transformer

upgrade will not arise for the level of PHEV penetration being

discussed here. However, with a large-scale PHEV

penetration, impacts of transformer overloading will be more

pronounced.

VI. CONCLUSIONS AND FUTURE WORK

In this paper, the challenges of PHEV penetration on aresidential distribution network are discussed and evaluated.

Research findings indicate that all PHEV charging strategies

considered in the paper will create new load peaks seen by a

distribution transformer. This will result in a slight decrease in

operating efficiency of distribution transformers, and in some

cases, the distribution transformer can be overloaded. The

paper investigates several possible solutions to deal with the

PHEV penetration challenges, including stagger charge or

household load control options. These demand management

strategies will require AMI and a simple local control

(software) infrastructure. Further research needs to be

conducted to explore the impact on of the large-scale PHEV

penetration the electricity infrastructure, especially at the

distribution level.

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18b92f6b52474852574900057fc3e/$FILE/Final_Presentation-

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battery-pack-and-generator-details-and-clarifications/.

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VIII. BIOGRAPHIES

Shengnan Shao (S08 - IEEE) is pursuing her Ph.D. degree in the

Department of Electrical and Computer Engineering at Virginia Polytechnic

Institute and State University, VA, USA. She received her M.S. degree in

2007 and B.S. degree in 2005 in Electrical Engineering from Tsinghua

University (THU), Beijing, China. She is now a research assistant at theAdvanced Research Institute of Virginia Tech. She is a member of the team

working on Intelligent Distributed Autonomous Power Systems (IDAPS)

project at the Virginia Tech Advanced Research Institute. Her fields of

interest include power distribution, power system protection and renewable

energy systems.

Manisa Pipattanasomporn (S'01, M'06 - IEEE) joined Virginia Tech's

Department of Electrical and Computer Engineering as an assistant professor

in 2006. She received her Ph.D. in electrical engineering from Virginia Tech

in 2004. She received the M.S. degree in Energy Economics and Planning

from Asian Institute of Technology (AIT), Thailand in 2001 and a B.S. degree

from the Electrical Engineering Department, Faculty of Engineering,

Chulalongkorn University, Thailand in 1999. She is currently researching the

application of a specialized microgrid called the Intelligent Distributed

Autonomous Power Systems (IDAPS) to improve the resiliency of electrical

energy infrastructures. Her fields of interest are renewable energy systems,

distributed energy resources and critical infrastructures.Saifur Rahman(S75, M78, SM83, F98 - IEEE) is the director of the

Advanced Research Institute at Virginia Tech where he is the Joseph Loring

Professor of electrical and computer engineering. He also directs the Center

for Energy and the Global Environment at the university. Professor Rahman

has served as a program director in engineering at the US National Science

Foundation between 1996 and 1999. He has served on the IEEE PES

Governing Board as VP of industry relations, and VP of publications between

1999and 2003. In 2006 he served as the vice president of the IEEE

Publications Board, and a member of the IEEE Board of Governors. In 2008

he is serving as the vice president for New Initiatives and Outreach for the

IEEE Power & Energy Society and a member of its Board. He is a member-at-

large of the IEEE-USA Energy Policy Committee. He is a distinguished

lecturer of IEEE PES, and has published over 300 papers on conventional and

renewable energy systems, load forecasting, uncertainty evaluation and

infrastructure planning.

challenges of phev penetration to the residential distribution network

Documents