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- AC05

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# Technical Challenges of Plug

- In Hybrid Electric Vehicles and Impacts to the US Power System : Distribution System Analysis

C Gerkensmeyer MCW Kintner

- Meyer JG DeSteese

January 2010DISCLAIMER

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## Technical Challenges of Plug

- In Hybrid Electric Vehicles and Impacts to the US Power System: Distribution System Analysis

C Gerke nsmeyer 1

MCW Kintner

- Meyer, Pacific Northwest National Laboratory
JG DeSteese, Pacific Northwest National Laboratory

January 2010

Prepared for the U.S. Department of Energy
under Contract DE

- AC05

- 76RL01830

Pacific Northwest National Laboratory Richland, Washington 99352

1 Consulting Engineeriii 

### Summary

Replacing a significant portion of the nation’s light vehicle fleet with plug

- in hybrid electric vehicles (PHEVs) offers the potential of reducing our dependence on petroleum fuels together with important economic and environmental benefits. The electric power grid is built to support peak loads and, as a consequence, suffers from low asset
utilization rates in off

- peak periods. In principle, this under

- utilized capacity could effectively power a national fleet of PHEVs with little need to increase the energy delivery capacity of the existing grid infrastructure. In practice, this ideal opportunity may be compromised by several factors including the size and distribution of the PHEV fleet, and the timing of vehicle charging activity.

Th is report documents work conducted by Pacific Northwest National Laboratory (PNNL) for the Dep artment of Energy (DOE) to address three basic questions concerning how typical existing electrical distribution system s would be impacted by the addition of
PHEVs to residential loads . These questions are:

 How many vehicles could the existing power de livery system support in the near
future?

 What time of day would PHEVs be charged?

 Where would the vehicles be charged?

The present study complements other research being performed for the DOE by the University of Michigan (UM) in collaboration with PNNL on various issues relating PHEV adoption and marketability.

The primary focus of this study was to estimate impacts of PHEV charging on the components of residential feeders. The first part of the analysis was designed to study PHEV charging impact s on the distribution system as a whole. A load flow study was performed for various PHEV penetrations to observe whether any principal components of main feeder s exceed their capacity because of PHEV charging.

The second part of th e analysis focuse d on the potential impact of the additional load on the distribution transformers serving each individual residence

. In both parts of the study computerized modeling of feeder

- level load flow compared the existing loading profile and component

- specific loads with those created by the superimposition of a hypothetical PHEV load distribution. Three electric utilities: Franklin PUD, Snohomish PUD and Puget Sound Energy (PSE) collaborated with this study by providing information that allowed system

- specific feeder mod eling.

A principal conclusion drawn from this study is that the addition of PHEV load at an individual residence may or may not have noticeable impacts on the existing distribution system depending on the overall penetration level and charging strategy used. The distribution utility’s system planning philosophy used to size distribution transformers and the backbone feeder system also plays a large part in determining whether or not, or
when in the future

, additional PHEV load would impact the system.iv This study developed a methodology that can be used directly or extrapolated by utilities to establish new tools for calculating the diversity factors used to size transformers for new and existing services. Further work to increase the accuracy of such t ools for assessing the potential impacts of new types of electrical load, such as PHEVs, is justified as an aid to distribution system planning. The results of this study also provide a basis for considering how the future integration of smart grid techno logies, such as energy storage or demand response techniques, may provide efficient strategies for minimizing the impact of additional PHEV load on the distribution system.v 

### Acknowledgements

We would like to thank the employees of Franklin PUD, Puget Soun d Energy

, and Snohomish PUD for their cooperation in supplying the feeder models and providing other
data as needed.vi 

### Acronyms

EV e lectric vehicle

PHEV p lug

- in hybrid electric vehicle

LDV l ight

- duty vehicles

UM University of Michigan

PUD Public U tilit y D ist rict

PSE Puget Sound Energy

V volt

A ampere

W w att

kVA k ilovolt

- a mpere, rating of transformer capacity

HEV h ybrid electric vehicle

PNNL Pacific Northwest National Laboratory

DOE Department of Energy

SOC state of charge

DOT Department of Transportation

SAE SAE International, formerly Society of Automotive Engineers

, a developer of organization standardsvii 

### Table of Contents

Summary

................................ ................................ ................................ ................................ ......... iii

Acknow ledgements

................................ ................................ ................................ ......................... v Acronyms

................................ ................................ ................................ ................................ ........ vi

1 Introduction

................................ ................................ ................................ ................................ 1
1.1 Related Studies on PHEV Adoption and Integration

................................ ............................ 1
1.1.1 Technological Barriers for Acceptable PHEV Performance and Cost (Task 1 Final Report)

................................ ................................ ................................ ............................. 1
1 .1.2 Plug

- in Hybrid Electric Vehicles (Task 2a Final Report)

................................ ............. 2
1.1.3 PHEV Marketplace Penetration (Task 2b Final Report)

................................ ............... 2
1.1.4 Market Models for Predicting PHEV Adoption and Diffusion (Task 2c Final Report)

................................ ................................ ................................ ................................ ...... 2
1.1.5 Impact of PHEVs on the Reliability of the Electric Grid (Task 3 Final Report)

................................ ................................ ................................ ................................ ...... 3
1.2 Focus of the Present Study

................................ ................................ ................................ .... 3

2 Key Assumptions

................................ ................................ ................................ ........................ 4
2.1 PHEV Market Penetration

................................ ................................ ................................ .... 4
2.2 Charging Scenarios

................................ ................................ ................................ ............... 5

3 Feeder Characterization

................................ ................................ ................................ ............ 8
3.1 Feeder Load Composition

................................ ................................ ................................ ..... 8
3.2 PUD Load Shapes

................................ ................................ ................................ ............... 10
3.3 PSE Load Shape

................................ ................................ ................................ .................. 13

4 Me thodology and Results

................................ ................................ ................................ ......... 14
4.1 Study Methodology

................................ ................................ ................................ ............. 14
4.1.1 Issues Considered

................................ ................................ ................................ ........ 14
4.1.2 Analytical Approach and Results Presentation

................................ ........................... 15
4.2 PHEV Impacts on Infrastructure Loading

................................ ................................ .......... 15
4.2.1 Franklin PUD

................................ ................................ ................................ .............. 15
4.2.2 PSE Distribution System

................................ ................................ ............................. 18
4.2.3 Snohomish PUD

................................ ................................ ................................ .......... 21
4 .3 Fast Charge Infrastructure Impacts

................................ ................................ ..................... 23
4.3.1 Franklin PUD Results for Quick Charging

................................ ................................ . 24
4.3.2 PES Results for Quick Charging

................................ ................................ ................. 25
4.3.3 Snohomish PUD Results for Quick Charging

................................ ............................. 27
4.4 Impacts on Secondary Distribution System Transformers

................................ ................. 28
4.4.1 Franklin PUD Results for Transformers Analysis

................................ ...................... 28
4.4.2 PSE Results for Transformers Analysis

................................ ................................ ...... 31
4.4.3 Snohomish PUD Results for Transformers Analysis

................................ .................. 34

5 Key Findings and Conclusions

................................ ................................ ................................ 38
5.1 Caveats

................................ ................................ ................................ ................................ 39
5.2 Conclusions

................................ ................................ ................................ ......................... 39

6 References

................................ ................................ ................................ ................................ . 41viii 

### List of Figures

Figure 2

- 1: PHEV Charging Profiles derived from the DOT Household Travel Survey Data Set (DOT, 2001). Load profiles represent a diversified load.

................................ .......... 6 Figure 2

- 2: Modified Case 2 Charging Curve

................................ ................................ ................. 7 Figure 2

- 3: Modified Case 5 Charging Curve

................................ ................................ ................. 7 Figure 3

- 1: Feeder Load Composition for Franklin PUD

................................ ................................ 8 Figure 3

- 2: Feeder Load Composition for PSE

................................ ................................ ............... 9 Figure 3

- 3: Feeder Load Composition for Snohomish PUD

................................ ........................... 9 Figure 3

- 4: Franklin and Snohomish PUD Load Shape for Apartment Loads

.............................. 10 Figure 3

- 5: Franklin and Snohomish PUD Load Shape for Residential Electric Heating
Loads

................................ ................................ ................................ ................................ ...... 11 Figure 3

- 6: Franklin and Snohomish PUD Load Shape for Residential Gas Heating Loads

........ 11 Figure 3

- 7: Franklin and Snohomish PUD Lo ad Shape for Commercial Loads

........................... 12 Figure 3

- 8: Franklin and Snohomish PUD Load Shape for Industrial Loads

................................ 12 Figure 3

- 9: Load Shap e for PSE Residential Loads

................................ ................................ ...... 13 Figure 4

- 1: Number of Franklin PUD Feeders with Equipment Failures by Type for 50%
PHEV Penetration

................................ ................................ ................................ ................... 16 Figure 4

- 2: Number of Franklin PUD Feeders with Equipment Failures by Type for
100% PHEV Penetration

................................ ................................ ................................ ........ 16 Figure 4

- 3:Number of Franklin PUD Feeders Supporting PHEV Penetrations With No Equ ipment Failures

................................ ................................ ................................ ................. 17 Figure 4

- 4: Franklin PUD Representative Feeder Load Curve for 50% PHEV Penetration

......... 18 Figure 4

- 5: Franklin PU D Representative Feeder Load Curve for 100% PHEV
Penetration

................................ ................................ ................................ .............................. 18 Figure 4

- 6: Number of PSE Feeders with Equipment Failures by Type for 50% PHEV
Penetration

................................ ................................ ................................ .............................. 19 Figure 4

- 7: Number of PSE Feeders with Equipment Failures by Type for 100% PHEV
Penetration

................................ ................................ ................................ .............................. 19 Figure 4

- 8: Number of PSE Feeders Supporting PHEV Penetrations With No Equipment Failures (note, total number of feeders is 8)

................................ ................................ ........... 20 Figure 4

- 9: PSE Representative Feeder Load Curve for 50% PHEV Penetration

........................ 20 Figure 4

- 10: PSE Representative Feeder Load Curve for 100% PHEV Penetration

.................... 21 Figure 4

- 11: Number of Snohomish PUD Feeders with Equipment Failures by Type for
100% PHEV Penetratio n

................................ ................................ ................................ ........ 21 Figure 4

- 12: Number of Snohomish PUD Feeders Supporting PHEV Penetrations with No Equipment Failures (note, total number of feeders is 8)

................................ .................. 22 Figure 4

- 13: Snohomish PUD Representative Feeder Load Curve for 50% PHEV
Penetration

................................ ................................ ................................ .............................. 22 Figure 4

- 14: Snohomish PUD Representative Feeder Load Curve for 100% PHEV
Penetration

................................ ................................ ................................ .............................. 23 Figure 4

- 15: Quick Charge Scenario Charging Profile

................................ ................................ .. 23 Figure 4

- 16: Number of Franklin PUD Feeders with Equipment Failures by Type in Quick Charge Scenario

................................ ................................ ................................ ........... 24 Figure 4

- 17: Number of Franklin PUD Feeders Supporting PHEV Penetrations With No Equipment Failures in Quick Charge Scenario

................................ ................................ ...... 24ix Figure 4

- 18: Franklin PUD Representative Feeder Load Curve in Quick Charge Scenario

......... 25 Figure 4

- 19: Number of PSE Feeders Supporting PHEV Penetrations With Eq uipment Failures by Type in Quick Charge Scenario

................................ ................................ ........... 25 Figure 4

- 20: Number of PSE Feeders with No Equipment Failures in Quick Charge
Scenario

................................ ................................ ................................ ................................ .. 26 Figure 4

- 21: PSE Representative Feeder Load Curve for Quick Charge Scenario

....................... 26 Figure 4

- 22: Number of Snohomish PUD Feeders Supporting PHEV Penetrations With Equipment Failures by Type in Quick Charge Scenario

................................ ........................ 27 Figure 4

- 23: Number of Snohomish PUD Feeders with No Equipment Failures in Quick Charge Scenario

................................ ................................ ................................ ...................... 27 Figure 4

- 24: Snohomish PUD Representative Feeder Load Curve for Quick Charge
Scenario

................................ ................................ ................................ ................................ .. 28 Figure 4

- 25: Franklin PUD Transformer Loading for Case 1

................................ ....................... 29 Figure 4

- 26: Franklin PUD Transformer Loading for Case 2

................................ ....................... 29 Figure 4

- 27: Franklin PUD Transformer Loading for Case 3

................................ ....................... 30 Figure 4

- 28: Franklin PUD Transformer Loading for Case 4

................................ ....................... 30 Figure 4

- 29: Franklin PUD Transformer Loading for Case 5

................................ ....................... 31 Figure 4

- 30: Franklin PUD Transformer Loading for Case 6

................................ ....................... 31 Figure 4

- 31: PSE Transformer Loading for Case 1

................................ ................................ ....... 32 Figu re 4

- 32: PSE Transformer Loading for Case 2

................................ ................................ ....... 32 Figure 4

- 33: PSE Transformer Loading for Case 3

................................ ................................ ....... 33 Figure 4

- 34: PSE Transformer L oading for Case 4

................................ ................................ ....... 33 Figure 4

- 35: PSE Transformer Loading for Case 5

................................ ................................ ....... 34 Figure 4

- 36: PSE Transformer Loading for Case 6

................................ ................................ ....... 34 Figure 4

- 37: Snohomish PUD Transformer Loading for Case 1

................................ ................... 35 Figure 4

- 38: Snohomish PUD Transformer Loading for Case 2

................................ ................... 35 Figure 4

- 39: Snohomish PUD Transformer Loading for Case 3

................................ ................... 36 Figure 4

- 40: Snohomish PUD Transformer Loading for Case 4

................................ ................... 36 Figure 4

- 41: Snohomish PUD Transformer Loading for Case 5

................................ ................... 37 Figure 4

- 42: Snohomish PUD Transformer Loading for Case 6

................................ ................... 371 

### 1 I ntroduction

The prospect of replacing a significant portion of the nation’s future light vehicle fleet with plug

- in hybrid electric vehicles (PHEVs) appears to offer a pathway to realize national energy policy goals that may be difficult to ach ieve by other means. Probably of most importance, a significant penetration of PHEVs would reduce the overall dependence of the transporta t ion sector on petroleum fuels and ease the presently high
cost of importing these fuels

.

Charging PHEVs from resi dential electrical outlet s is both practical and convenient from the owner’s perspective. In this regard, the existing electric power delivery system offers a natural advantage in being already built with the capacity to serve peak loads . As

a consequen ce , it tends to be under

- utilized during off

- peak periods. If charging strategies can be planned and coordinated to match the availability of this off

- peak capacity

, a national fleet of PHEVs could be accommodated with little need to increase the energy d elivery capacity of the existing grid infrastructure. In practice, this ideal opportunity may be compromised by several factors including the size and distribution of the PHEV fleet, and the timing of vehicle charging activity.

Th is report presents wo rk conducted by Pacific Northwest National Laboratory (PNNL) for the Department of Energy (DOE) to address three basic questions concerning how typical existing electrical distribution system s c ould be impacted by the addition of
PHEVs to residential loads . These questions are:

 How many vehicles could the existing power delivery system support in the near
future?

 What time of day would PHEVs be charged?

 Where would the vehicles be charged?

Th is study complements other research performed for the DOE by the University of Michigan (UM) in collaboration with PNNL on various issues relating to PHEV adoption

, marketability and impacts on the electric power grid

. A brief review of related
UM studies is presented below.

1.1 Related Studies on PHEV Adoption and Int egration Recent work performed by UM in collaboration with PNNL i s reported in the following
five document summations

.

1.1.1 Technological Barriers for Acceptable PHEV Performance and Cost (Task 1 Final Report)

Authors Filipi et al

. ( Filipi et al. 2009) deal wit h important issues that may represent latent barriers to achieving acceptable PHEV performance and/or cost. Particularly, the y discuss the contrast between Federal and “real

- world” driving cycles that may be used as a basis for vehicle design. The higher demand of “ naturalistic” driving has implications for several aspects of PHEV design that affect marketability. Not taking these considerations into account could result in possible consequences ranging from PHEV s2 being either underpowe red or excessively expensive. This study

, based on Michigan driving experience

, suggests that the “real

- world” contrast with Federal driving cycles may be regional.

1.1.2 Plug

- in Hybrid Electric Vehicles (Task 2a Final Report) The study by Curtin, Shrago, and Mikkelsen (Curtin e t al. 2009 ) is a comprehensive
review of many factors that can be expected to influence future public acceptance and market penetration potential of hybrid electric vehicles. The survey on which the study is based was performed using generally accepted qu estionnaire administration techniques
and relevant data and statistical analysis. The results support many intuitive expectations about the significance various factors have in determining the probability that an individual may decide to purchase a hybrid vehicle, including the determination of credible price elasticity in consumer response. In addition, the study identifies several

non

- intuitive correlations including, for example, “ consumers who purchase a PHEV are likely to trade

- in vehicles that are a lready relativel y fuel efficient.” The authors draw and justify reasonable conclusions from their work which provides a wealth of up

- to

- date information on the future marketability of hybrid vehicles.

1.1.3 PHEV Marketplace Penetration (Task 2b Final Report)
Sullivan, Salmeen, and Simon (Sullivan et al. 2009) address the marketability of PHEVs using an agent

- based simulation model to characterize new vehicle penetration into the marketplace under a variety of consumer, economic and policy conditions. This mo del comprises four classes of agents: consumers, government, fuel producers and vehicle producers/dealers that interact with each other and the environment as software

- encoded virtual decision makers. Agent

- based models have been applied to many complex

s ystems such as the spread of disease, the evolution of organisms, emergence of behavior in social systems, financial markets and organizational behavior. These applications provide general conceptual foundations for the authors’ application to the automob ile marketplace. The approach does not produce forecasts of future markets; rather it produces “what is possible” outcomes given sets of assumptions of how the individual agents decide. The authors make a case for concluding that this methodology can be credibly applied to estimating the penetration of PHEVs into the U. S. auto marketplace.

1.1.4 Market Models for Predicting PHEV Adoption and Diffusion (Task 2 c Final Report)

M cManus and Senter (M cManus and Senter 2009) d escribe six models and evaluate the

res ults they produce in predicting PHEV public acceptance and adoption. The authors assume the potential market for PHEVs is analogous to the historical precedent provided by hybrid electric vehicles (HEVs)

, but the products are not so similar that they can be considered simply generations of the same product. Benchmark market models with
fixed saturation levels are examined and found to have weaknesses that dominate their strengths. Two alternative approaches without fixed saturation levels are also evaluat ed. Of these, the consideration

- purchase model, focusing on the market behavior of consumers, is the market model that the authors prefer. The authors developed this model building on the strengths of the other models considered while overcoming some
of their limitations. The preferred model explicitly incorporates a consumer choice3 component that can be expanded well beyond its current simplified form. The common assumptions used in this study describe the domestic market for all light vehicles for
2010 through 2050, including sales of new vehicles, growth in the installed base of all light vehicles, and scrappage rates for all light vehicles.

1.1.5 Impact of PHEVs on the Reliability of the Electric Grid (Task 3 Final Report )
Lee, Varuttamaseni, Rahman, and Br iley ( L ee et al. 2009) consider the impact of PHEV charging and the timing of this load on the reliability of the electric power grid. The concern specifically addressed is that the additional load will increase the time distribution equipment operates at elevated temperatures thereby shortening the mean service life of components as a result of accelerated aging. The study successfully applies established probabilistic risk assessment methodology to components of a real

world electric distribution system and estimates reliability indices that allow this effect to be modeled quantitatively. The authors admit that the reliability indices they derive differ from those suggested by the operating experience of the studied utility system and
recommend this as a subject for further work. However, they establish that the aging
effect is credible and it could , as one example, shorten mean transformer by 20 years (i.e., from 60 to 40 years). They also assess this effect as it impacts system reliability.

1.2 Focus o f the Present Study The present study has a close relationship to the work of Lee et al

. summarized above because it expands consideration of impacts PHEVs may have on the electric power grid. This analysis answers the question of how the capacity of exis ting electrical distribution system s is impacted by the addition of PHEVs to residential loads. The first part of the analysis is designed to study the impact to the distribution system as a whole, u sing a load flow study of various PHEV penetrations to o bserve which, if any

, components of
main feeder s exceed their capacity.

The second part of this analysis focuses on the impact of the additional load on the distribution transformers serving each individual load. As the principal measure of this type o f impact, t he peak percent loading, ( provided by the relationship kW
load/t ransformer kVA capacity), is estimated for the existing loads and then with the
addition of PHEV load to a number of representative feeder s. In both portions of the study

, three el ectric utilities: Franklin Public Utility District ( PUD ) , Snohomish PUD and Puget Sound Energy (PSE) collaborated by providing information that allowed system

specific feeder modeling.

The balance of this report contains six secti ons. Section 2 discu sses penetration and charging profile cases that a hypothetical PHEV fleet might impose on the electric
distrib ution system. In Section 3

, the feeder characterization on which impact analyses are based is presented

. The analytical methodology and r esult s of PHEV load
simulations and impacts are discussed in Section 4. Key f indings and c onclusions are contained in Section 5 and reference s are listed in Section 6.4 

### 2 Key Assumptions The key assumptions that drive the outcome of the impac t analysis are the projection of the penetration of PHEVs, the assumptions related to the time of day when the vehicles are likely to be recharged, and the locations where the vehicles are connected to the electric grid. In other words, the following thre e questions need to be answered in a plausible and defensible fashion:

1. How many vehicles are likely to be supported by the grid at a future point in time ?
The answer relates to the penetration rate of PHEV as a function
2. What time a day w ould the vehicles be charged? The answer defines the daily load profile
3. Where would the vehicles be charged? To answer this question requires some assumptions about the grid infrastructure and the availability assumptions of public charging stations and the development of charging points for vehicle owners who live in apartment complexes or higher density urban dwellings without access to an
electrical outlet.

There is additional set of question s that has more recently emerged related to the rate of energy transfer to the battery in ter ms of kW of electrical demand. It is an ticipated that
the most common chargi ng rate would be based on a 120

- Volt (V) and 15

- Ampere (A) single

- phase power, which are most common in residential homes (Level 1 charging)

. Quick charging (Level 2 charging) would likely require charging at higher voltage and

current rat ings than the commonly used 120

- V , 15

- A circuits on residential homes 2

. Charging at 240 V and 30 A or even at 50 A would significantly increase the rate of electricity transfer to the battery, and thus, is likely to have higher impacts on the electric infrastructure both at the charging premise (in most cases the home) as well as the distribution system as a whole. The advantage would be a much shorter re

- charge time.

To address th ese different assumptions that span a reasonable range of likely future scenarios, we defined a portfolio of scenarios for the impacts assessment. The following sections will discuss the key assumptions.

2.1 PHEV Market Penetration There are many analytical a pproaches that attempt to model the customer acceptance and purchasing decisions of new and used vehicles [ Sentech 2009 ; Sullivan et al

. 2009 ; McManus and Senter 2009 ; Balducci 2008]. Rather than modeling and estimating a certain penetration of PHEVs for a future point in time, we framed the problem by hypothesizing a number of PHEVs per residential home (single detached homes) and then analyzing the likely impacts. Specifically, we defined a 100% PHEV scenario, meaning
that one PHEV per residential custom er (home), and a 50% scenario, in which every
second home has a PHEV.

2 SAE

– J1772 TM Standard defines Level 1 charging as: 120

- V single

- phase alternating current (AC), 12 A
on 15 A circuit or 15 A on a 20

- A circuit. Level 2 cha rging is defined as: 240

- V single

- phase up to 80 A.5 2.2 Charging Scenario s

In the absence of the real

- world data on charging patterns of PHEVs, one needs to postulate plausible charging scenarios that are based on driving patterns and parti cularly resting periods of vehicles that would allow the vehicle owner to re

- charge the PHEV battery. Although currently, the Department of Energy is collecting vehicle data from retrofit PHEVs that include charging patterns, these data sets are in the ea rly stages of covering a sufficient number of regions and customer driving patte r n s. Thus, they were considered not ready to be the sole sources for developing comprehensive charging profiles valid for the U.S. as a whole.

As an alternative approach to real driving data, this study developed charging profiles based on simulations derived from the U.S. Department of Transportation’s 2001 Household Traveling Survey. This data set comprises representative U.S. driving patterns for privately

- owned vehicles derived from individual respondents’ daily traveling diaries (DOT 2001) . The survey provided slightly over 35,000 samples of daily trips using light duty vehicles. Given the starting time and locations, the destinations and arrival times of each trip in t he survey, we determined the resting locations of a vehicle and its arrival and departure times at that location. Of interest for the purpose of this study were only two resting locations

, where any vehicle would reside for longer periods of time (i.e., mo re than 15 minutes) able to be plugged

- in for battery charging. These two locations were a) home and b) place of work. Shorter durations, for brief errands were considered not suitable for battery charging opportunities. Furthermore, the estimated
travel distance was used to determine the battery’s state of charge (SOC) at the point of arrival. The SOC determined the maximum electric energy that can be transferred into the battery until the battery is fully charged.

The following six charging cases repr esent scenarios covering the most likely range of charging strategies to be expected when PHEV s become more common:

 Case 1

– 120

- V charging at home

 Case 2

– 120

- V charging at home and work

 Case 3

– 120

- V charging a t home delayed until after 10 p.m.

 Case 4

– 50/50 120

- V/240

- V charging at home

 Case 5

– 50/50 120

- V/240

- V charging at home and work

 Case 6

– 50/50 120

- V/240

- V charging a t home delayed until after 10 p.m.

In all six cases, except for cases 2 and 5, the location of the vehicle charging is
exclusi vely at home. Cases 2 and 5 have additional charging locations at work
considered. Because no information exists regarding the precise work location

, we eliminated the opportunity of the charging at the work place entirely and focuse d solely on charging at home to estimate the associated impacts on the distribution as a result of
additional PHEV load at the residential customers location. Modifications for the cases 2 and 5 load profiles became necessary. The work

- site related charging was eliminated
from the charging profile such that only charging at home was considered, which for the most part occurs during the hours of 4:00 p.m. and 6:00 a.m. The modified cases are now
called Case 2M and Case 5M and are defined as follows:6  Case 2M

– 120

- V charging at h ome and work

– home only

 Case 5M

– 50/50 120

- V/240

- V charging at home and work

– home only.

Figures 2

- 1, 2

- 2 and 2

- 3 compare the load s and load timing imposed on a domestic feeder by a single PHEV in each of the above charging case s

. All curves represent the actual
load that would be measured at the battery of the PHEV assum ing that the battery charging circuit has an efficiency of 87% (Duvall 2002)

. Load duration in each case

acco u nts for the transfer of suff i c ient energy to recharge the PHEV battery f ollowing a typical daily driving pattern. Each curve is modified to represent the actual load that
would be seen at the secondary of the distribution transformer serving the individual
residence. For the “Charge at Home and Work” curves (Cases 2, 2M, 5 a nd 5M), only the residential, or “ c harge at h ome” contribution was used.

.

Figure 2

- 1 : PHEV Charging Profiles derived from the DOT Househ old Travel Survey Data Set (DOT 2001). Load profile s represent a diversified load.7 Figure 2

- 2 : Modified Case 2 Charging Curve

Figure 2

- 3 : Modified Case 5 Charging Curve8 

### 3 Feeder Characterization

To assess the differentia l impacts of PHEV charging, it was necessary to establish a
baseline characterization of the domestic feeders involved in terms of representative hourly load profiles and load composition. As noted earlier, three electric utilities: Franklin PUD, Snohomi sh PUD and Puget Sound Energy (PSE) collaborated by providing information that allowed system

- specific feeder modeling. Baseline feeder characterization is presented below for each of the collaborating utilities.

3.1 Feeder Load Composition

As the basis for the analysis, 34 of Franklin PUD’s feeders, 8 of Snohomish PUD’s feeders, and 8 of PSE’s feeders were considered

The Franklin PUD data set represented all feeders in its service territory. Because of the relatively small size compared to the other collab orating load serving entities

, we decided
to use the entire data set. For Snohomish PUD and PSE, because of the large size of their respective service territory and the available data, a small subset of primaril y residential
feeders were selected for this analysis. PSE was interested in analyzing two feeders with a mixed composition of commercial and residential load customers. The breakdown of the feeders and their load composition by customer type are shown in Figure 3

- 1 through Figure 3

- 3

.

Figure 3

- 1 : Feeder Load Composition for Franklin PUD9 Figure 3

- 2 : Feeder Load Composition for PSE

Figure 3

- 3 : Feeder Load Composition for Snohomish PUD10 3.2 PUD Load Shapes

Baseline l oad shapes for the Franklin PUD and Snohomish PUD systems were based on the default load curves supplied with the SynerGEE analysis package (SynerGEE 2009)

. The validity of the load profiles were confirmed by the planning engineers of both load serving entities. They were sufficiently representative of average load behavior without representing the conditions of a specific season. Figure 3

- 4 through Figure 3

- 5 illustrate the hourly load profile for feeders serving residential customers. The residential load shape in Figure 3

- 6 denotes the residential characteristi c modified by using natural gas for heating. Figure 3

- 7 and Figure 3

- 8 show the baseline feeder load shape for the
commercial and industrial sector s

. Although we assumed that PHEV were only charged

at t he premises of residential customers, load profiles by commercial and industrial were required for the load flow analysis because most feeders served a mix of the residential/commercial/industrial customer segments.

Figure 3

- 4 : Franklin and Snohomish PUD Load Shape for Apartment Loads11 Figure 3

- 5 : Franklin and Snohomish PUD Load Shape for Residential Electric Heating
Loads

Figure 3

- 6 : Franklin and Snohomish PUD Load Shape for Residential Gas Heating Loads12 Figure 3

- 7 : Franklin and Snohomish PUD Load Shape for Commercial Loads

Figure 3

- 8 : Franklin and Snohomish PUD Load Shape for Industrial Loads13 3.3 PSE Load Shape Hourly l oad shapes for the PSE system were also derived from SynerGEE curves with the exception of the r esidential load profile. This curve is bas ed on actual measured customer load profiles as provided by PSE. A n example of PSE’s residential load profile is shown in Figure 3

- 9 representing average winter peak loading conditions

.

Figure 3

- 9 : Load Shape for PSE Residential Loads14 

### 4 Methodology and Results

An analysis of PHEV impact was performed on each feeder

, as characterized in Section
3 . The PHEV charging profiles were superimposed on to the feeder baseload conditions
and load configuration s

. The impacts at t wo levels of hypothetical PHEV load penetration, 50% and 100% w ere investigated. A penetration of 100% means that every residential customer (non multi

- residential customer) owns a PHEV and charges it at home. A penetration of 50% assumes that every other residential customer has a PHEV.
The PHEV d istribution at the 50% penetration level w as uniformly distributed across all
residential customers to avoid load concentration.

The annual load growth of all other loads was n o t considered in th e analysis. It was

a ssumed that both the number of customers as well as their particular load characteristics
were frozen at the 2008 level. Further details of the methodology are described below.

4.1 Study Method o logy

The analysis is based on several primar y assumptions :

 PHEVs are distributed evenly through the system

 S pecific areas were n ot assumed to have a higher concentration of PHEVs

 PHEV s are charged o nly at single family residences

.

For Franklin PUD 3 and Snohomish PUD

, 4 it was assumed that each custo mer was allocated a service capacity of 7.5 kVA by each distribution transformer

. Dividing this
value into the nominal capacity of the transformer determined how many customers were
attached to each transformer. For the PSE analysis, the actual number of connected
customers at each transformer was available in the model and , therefore, was used in the study.

4.1.1 Issues Considered

The addition of significant electrical load , such as a PHEV, at multiple individual
residences can contribute potentially to overl oading components of the entire feeder depending on the timing and diversity of the new load. The rated capacities of existing
feeder components will have been chosen to handle the projected load at any residence
based on the average value of expected “n o rmal ” loads such as heating and cooling equipment , resistive elements such as water heaters and electric ranges, and standard lighting. The sizing of the distribution transformer that serves each residence is based on these expectations. I n turn

, all fee der components upstream of the distribution transformer are generally sized to supply downstream transformers operating at full nameplate capacity. Nameplate capacity generally exceeds the actual load for many hours in the day and is only fully exploited during peak periods. Thus, it should be generally feasible to control the timing of the PHEV demand so that this additional load
can be served within the rated capacit ies of existing feeder equipment.

3 M. Hay, private communication, Franklin PUD, September 2007

4 R. Fletcher, private communication, Snohomish PUD, June 200715 Feeder equipment and transformers , in particular, op erating at overload capacity generally shortens their li ves. By considering the amount of time new load s on a feeder

causes overrat ed operation and the duration of overload condition s , the tendency for reducing compone n t life expectancy can be illustrated

.

4.1.2 Analytical Approach and Results Presentation

The above issues were addressed in two distinct studies. For the study on distribution system infrastructure impacts, load flow studies were done with PHEV loads applied at single family residences. A tota l of 24 hourly l oad flow analys e s w ere performed using the Syne rGEE analysis package (SynerGEE 2009) for the following combination of cases
and conditions :

 E ach of the six charging scenarios described in Section 2 .2

 PHEV penetration levels of 50% and 100%

.

T he results were used to determine whether or not the rated capacity of any feeder components ( i.e., conductors, switches, fuses, and other protection and control devices)

w as exceeded. From this study, the total feeder current was also found.

In the s econd study o n the adequacy of distribution transformer capacity, load flow analys e s w ere also performed for each hour to compare the rated kVA of each transformer to the peak load it experienced.

The results of both studies are summarized in utility

- spec ific figures presented in the following sections.

4.2 PHEV I mpacts on Infrastructure Loading The figures in this section show the infrastructure loading impacts caused by charging
PHEV s at 50% and 100% penetration levels at single

- family residences on each of the
modeled feeders.

4.2.1 Franklin PUD

The d istribution system components that failed from overloading and the number of
feeders affected are indicated in Figures 4

- 1 and 4

- 2 for the various charging cases and
PHEV penetration rates

.16 Figure 4

- 1 : Number of Franklin PUD Feeders with Equipment Failures by Type for 50%
PHEV Penetration

Figure 4

- 2 : Number of Franklin PUD Feeders with Equipment Failures by Ty pe for
10 0% PHEV Penetration

The number of feeders able to support the two penetration rates for the six different charging cases with no equipment failures in the Franklin PUD study are shown in Figure
4

- 3.17 Figure 4

- 3 : Number of Franklin PUD Feeders Supporting PHEV Penetrations With No Equipment Failures

In this and the similar figures that follow, green , red and blue bars represent, respectively, feeders that can tolerate 100%, 50% and 0% PHEV penetrat ion in each charging scenario without increasing the rate of distribution system equipment failures. Thus, Figure 4

- 3 shows all 34 Franklin PUD feeders can support 100% penetration in Case 3. In contrast, the Case 6 charging scenario shows that only 19 of these feeders tolerate 100% penetration (green bar), 13 feeders would support 50% (red bar) and 2 feeders would not support any level of PHEV penetration (blue bar) without increasing equipment failure

rates.

L oad curves for a representative Franklin P UD feeder comparing the base load to the various charging profiles for the two penetration rates are shown in Figure 4

- 4 and Figure 4

- 518 Figure 4

- 4 : Fran klin PUD Representative Feeder Load Curve for 50% PHEV Penetration

Figure 4

- 5 : Franklin PUD Representative Feeder Load Curve for 100% PHEV
Penetration

4.2.2 PSE Distribution System

The devices that are prone to failure as a result of overloading are shown in Figures 4

- 6
and 4

- 7 for the various charging cases and penetration rates considered in the PSE system study19 Figure 4

- 6 : Number of PSE Feeders with Equipment Failures by Type for 50% PHEV
Penetration

Figure 4

- 7 : Number of PSE Feeders with Equipment Failures by Type for 100% PHEV
Penetration

The number of feeders able to support the two PHEV penetration rates for the six different charging cases with no equipment failures are shown in Figure 4

- 8

.20 Figure 4

- 8 : Number of PSE Feeders Supporting PHEV Penetrations With No Equipment
Failures (note, total number of fee ders is eight )

The load curves for a representative feeder comparing the base load to the various charging profiles for the two penetration rates in the PSE study are shown in Figures 4

- 9
and 4

- 1 0.

Figure 4

- 9 : PSE Representative Feeder Load Curve for 50% PHEV Penetration21 Figure 4

- 10 : PSE Representative Feeder Load Curve for 100% PHEV Penetration

4.2.3 Snohomish PUD

In the Snohomish PUD study, no device capa cities were exceeded for the 50% PHEV penetration rate in all of the eight representative residential feeders . The devices that failed from overloading at the 100% PHEV penetration rate are listed in Figure 4

- 11 for the various charging cases.

Figure 4

- 11 : Number of Snohomish PUD Feeders with Equipment Failures by Type for
100% PHEV Penetration22 The number of feeders able to support the two penetration rates for the six different charging cases with no equip ment failures in the Snohomish PUD study are shown in Figure 4

- 12

.

Figure 4

- 12 : Number of Snohomish PUD Feeders Supporting PHEV Penetrati ons w ith No Equipment Failures (note, total number of feeders is eig ht )

The load curves for a representative feeder comparing the base load to the various charging profiles for the two penetration rates in the Snowhomish study are shown in Figures 4

- 13 and 4

- 14

.

Figure 4

- 13 : Snohomish PUD Representative Feeder Load Curve for 50% PHEV
Penetration23 Figure 4

- 14 : Snohomish PUD Representative Feeder Load Curve for 100% PHEV
Penetration

4.3 Fast Charge Infrastructure Impac t s

In an earlier analysis (Schneider, et al. 2008)

, a quick charging scenario was investigated
for feeder s in the Pacific Northwest

. In the quick charging scenario, it i s assumed that all PHEVs would begin charging system

- wide within a 3

- hour period directly afte r people arrive home from work. The resulting charging profile is shown below in Figure 4

- 15

. Impacts on the electrical distribution infrastructure of the quick charge scenario were evaluated u sing the same methodology as described above and presented be low.

Figure 4

- 15 : Quick Charge Scenario Charging Profile24 4.3.1 Franklin PUD Results for Quick Charging Similar to the presentation of results in the previous section, equipment failures, feeder penetration sup port, and load curves are shown for Franklin PUD in Figures 4

- 16 to 4

- 18.

Figure 4

- 16 : Number of Franklin PUD Feeders with Equipment Failures by Type in Quick Charge Scenario

Figure 4

- 17 : Number of Franklin PUD Feeders Supporting PHEV Penetrations With No Equipment Failures in Quick Charge Scenario25 Figure 4

- 18 : Franklin PUD Representative Feeder Load Curve in Quick Charge Scenario

4.3.2 PES Results for Quick Charging The equipment failures, feeder penetration support, and load curves for the PSE system are shown in Figures 4

- 19 to 4

- 21

.

Figure 4

- 19 : Number of PS E Feeders Supporting PHEV Penetrations With Equipment Failures by Type in Quick Charge Scenario26 Figure 4

- 20 : Number of PSE Feeders with No Equipment Failures in Quick Charge
Scenario

Figure 4

- 21 : PSE Representative Feeder Load Curve for Quick Charge Scenario27 4.3.3 Snohomish PUD Results for Quick Charging

Snohomish PUD e quipment failures, feeder penetration support, and load curves are
shown in Fi gures 4

- 22 t o 4

- 24 for the q uick c harge s cenario

.

Figure 4

- 22 : Number of Snohomish PUD Feeders Supporting PHEV Penetrations With Equipment Failures by Type in Quick Charge Scenario

Figure 4

- 23 : Number of Snohomish PUD Feeders with No Equipment Failures in Quick Charge Scenario28 Figure 4

- 24 : Snohomish PUD Representative Feeder Load Curve for Quick Charge
Scenario

4.4 Impacts on S econdary D istribution S ystem T ransformers

The addition of a PHEV load can have a more significant impact on the individual
distribution transformers than on the system as a whole. While overloading a transformer may not have obvious immediate impacts , w hen a transformer is loaded beyond its nameplate rating, the life of the transformer will be diminished based on the duration and the severity of the overload condition (IEEE Std. C57.91)

. In the second part of this study, load flow analyses w ere perfo rmed for each hour of a typical day to compare the
rated kVA of each transformer with the peak load it experienced. The results are shown
below.

4.4.1 Franklin PUD Results for Transformers Analysis

Franklin PUD loaded transformer capacity for the various chargi ng cases and PHEV penetration rates are shown in Figures 4

- 25 to 4

- 3 0 in terms of number of transformers

versu s percentage of rated capacity.29 Figure 4

- 25 : Franklin PUD Transformer Loading for Case 1

Figu re 4

- 26 : Franklin PUD Transformer Loading for Case 230 Figure 4

- 27 : Franklin PUD Transformer Loading for Case 3

Figure 4

- 28 : Franklin PUD Transformer Loading for Case 431 Figure 4

- 29 : Franklin PU D Transformer Loading for Case 5

Figure 4

- 30 : Franklin PU D Transforme r Loading for Case 6

4.4.2 PSE Results for Transformers Analysis

Plots of the PSE transformer loaded capacity for the various charging cases and penetration rates are similarly shown in Figures 4

- 31 to 4

- 3 6

.32 Figure 4

- 31 : PSE Transformer Loading for Case 1

Figure 4

- 32 : PS E Transformer Loading for Case 233 Figure 4

- 33 : PS E Transformer Loading for Case 3

Figure 4

- 34 : PS E Transformer Loading for Case 434 Figure 4

- 35 : PS E Transformer Loading for Case 5

Figure 4

- 36 : PS E T ransformer Loading for Case 6

4.4.3 Snohomish PUD Results for Transformers Analysis

Finally, p lots of Snohomish PUD transformer loaded capacity for the various charging
cases and PHEV penetration rates are shown in Figures 4

- 37 to 4

- 42

.35 Figure 4

- 37 : Snohomish PUD Transformer Loading for Case 1

Figure 4

- 38 : Snohomish PU D Transformer Loading for Case 236 Figure 4

- 39 : Snohomish PU D Transformer Loading for Case 3

Figure 4

- 40 : Snohomish PUD Transformer Loading for Case 437 Figure 4

- 41 : Snohomish PU D Transformer Loadin g for Case 5

Figure 4

- 42 : Snohomish PU D Transformer Loading for Case 638 

### 5 Key Findings and Conclusions Analysis of PHEV charging impacts on the representative feeders of three utilities in the
Pacific North west showed that for the most part the rated capacity of individual distribution system components was not exceeded. This was true over a range of six
scenarios with different charging strategies. The most common component found prone to failure from ove rloading was the protective fuse. Fuse failures are generally easy to

re pair and their vulnerability can be mitigated by simply replac ing them with a higher
rated device.

Overall, the charging strategy defined as Case 1 ( 120

- V Charging at Home Profile ) provides the most rea sonable approach with the least impact. In contrast

, a quick charge
scenario

, in which the PHEV battery is completely recharged in the 3

- hour period after people arrive home from work

, has a broader range of system impacts . On one of the system s evaluated, this scenario caused some fuses, lines, switches and reclosers to be failure prone.

The PHEV charging curves considered in this study add feeder load diversity that generally helps to lessen their overall impact on the electrical distribution system. The quick charging curve removes this diversity and could significantly impact the system with a spike in demand and usage at a time when the system peak demand from other loads is already occurring

.

In some cases, t he additional lo ad introduced by PHEV charging was found to increase
the time secondary distribution transformer s operate in excess of rated capacity. Supported by the findings of Lee et al

. (2009), this will tend to ha ve a direct impact on
transformer l ife

. Depending o n whether utilities load their transformers lightly or heavily, these results could be significant. Those utilities that have heavily loaded
transformers should be able to use these results and the results of related studies (e.g., the UM study by Lee et a l.) to determine how the life of the transformer will be impacted

. In
contrast, utilities with lightly loaded transformers may be able to verify that the additional
PHEV load will not affect the life of their transformers.

Addition of PHEV load to an ind ividual residence may or may not have a noticeable effect on the existing distribution system depending on the overall penetration and charging strategy used. A utility’s initial philosophy used to size distribution transformers and the backbone feeder sy stem will also play a large part in determining
whether , in practice, the additional load will overload the system.

The load curves developed in this analysis can be used by electric utilities to modify their own load curves to prepare for the emergence a nd increased deployment of PHEVs and
other electric vehicles

. Utilities can use the results and further extrapolate them to create new formulas for calculating the diversity factor that is used to size transformers for new and existing services.39 5.1 Cavea ts Naturally occurring load growth was not considered in this study because of the uncertainties how energy efficiency and demand response strategies may influence future load behavior and load profiles. If they would have been considered to assess the imp acts of PHEVs for a future point in time, say 2020, congestion in the distribution system and capacity problem s may occur at PHEV penetration levels perhaps lower than those analyzed in this report.

The diversity of distribution system component vintages

, sizing and design practices varies greatly across the nation. W ith older infrastructure, which had been initially designed for much less load per residential customer than its current use , it is very likely that the PHEV impacts are more severe and impa ctful than to a relatively new infrastructure. Comparing the infrastructure analyzed in this report to those in older and established neighborhoods of coastal or mid

- western metropolitan areas, where some of the system components are 100 years or older, w e would consider the distribution feeder
infrastructure

– by and large

– newer and b y no means at the end o r beyond the end of its expected life time. As a consequence, the results obtai ned are more representative for newer system s that were originally des ign ed with significant capacity margins to accommodate load growth, than for those established early 20 th century neighborhoods.

5.2 Conclusions

For the near

- term, the emergence of PHEVs using 120

- V charging strategies is not likely

to have a significant impa ct on distribution system s with relatively new infrastructures. This result is not too surprising when considering that the additional demand of a PHEV would be comparable to or only slightly more than that of a 1000

- W electric hair dryer

. When, however, qu ick charging strategies are explored

, the analysis indicates that the y would likely impose a significant burden on common residential feeders operating at higher level s of load concentration. The se impacts are exacerbated when the load is non

diversified, i.e., the charging occurs concurrently or almost concurrently at peak load
times , as assumed in our quick charging scenario. Concurrency for the charging may not be too far fetched, particularly, when one considers neighborhood s of professionals who
have s imilar work hours and are likely to arrive home at similar times. In such an event, the high demand during quick charging would impact the secondary transformer first, with additional impacts on the upstream components of distribution system. Fuses inadeq uate for the high er demand could be replaced wit h high rated ones at low cost ; however, in most cases

, it would require additional up

- sizing of other line components at generally more significant cost.

The discussion on quick charging strategies has rece ntly attracted more attention because of numerous announcements by many credible manufacturers to make electric vehicles ( EVs ) commercially available. With the larger battery sizes of EVs (30 kWh and more)

, compared to those of PHEVs (10 kWh and more)

, it is likely to become desirable to charge at higher charging rates than a 120

- V/15

- A circuit w ill allow. Should 240

- V charging become the commonly adopted charging mode, the adoption of the quick charging scenario could become reality sooner rather than late r. However, it is not40 expected that utility planners will be surprised overnight by this new load growth.
Because of the high public awar e ness of PHEVs and EVs, it is expected that utility planners will monitor the growth of this emerging technology and p repare for its implementation accordingly. Furthermore, with the growing deployment of smart grid technologies into the distribution system and the efforts by the Society of Automotive Engineers (SAE) to develop communication standards between a vehicle an d a smart electric infrastructure, it is likely that sophisticated load management and smart charging technologies would be deployed that can diversify or even coordinate the charging of
PHEVs and EVs in a manner to mi tigate the ir impacts on the distribution system and the grid as a whole.41 

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