oioverview: c lif ic alifornia sids tatewide plug in

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O i C lif iS id Overview: Calif ornia Statewide Plugin Electric Vehicle If A Infrastructure Assessment Sacramento, California Dr. Marc Melaina Senior Engineer, NREL June 5, 2014 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

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Page 1: OiOverview: C lif iC alifornia SidS tatewide Plug in

O i C lif i S idOverview: California Statewide Plug‐in Electric Vehicle I f AInfrastructure Assessment

Sacramento, California

Dr. Marc MelainaSenior Engineer, NREL

June 5, 2014

NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

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Presentation Overview

• Introduction to NREL

• Purpose of Statewide Assessment and Key Results

• Methodology: How were the quantitative results determined? 

• How can the Energy Commission use the A F k i h f ?Assessment Framework into the future?

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National Renewable Energy Laboratory

Only National Laboratory Dedicated Solely to Energy Efficiency and Renewable Energy

• Leading clean‐energy innovation for 34 years

• 1,740 employees with world‐class facilities, p y

• Campus is a living model of sustainable energy

• Owned by the Department of Energy

• Operated by the Alliance for Sustainable EnergyOperated by the Alliance for Sustainable Energy

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Scope of NREL’s Mission

E Effi i R bl E S I i M k FEnergy Efficiency Renewable Energy Systems Integration Market Focus

Residential Buildings

Solar

Wi d d W t

Grid Infrastructure

Di t ib t d E

Private Industry

F d l A iCommercial Buildings

Personal and Commercial

Wind and Water

Biomass

Hydrogen

Distributed Energy Interconnection

Battery and Thermal Storage

Federal Agencies

Defense Dept.

State/Local Govt.Commercial Vehicles Geothermal Transportation International

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Purpose of the Assessment

• This is the first statewide analytical framework for EVSE infrastructure

• The Assessment establishes a framework• The Assessment establishes a framework for how to achieve the ZEV Action Plan Goal of EVSE Deployment Sufficient to support 1 0 Million ZEVs by 2020support 1.0 Million ZEVs by 2020

The assessment achieves the following:• Articulates the Energy Commission’s conclusions and 

recommendations regarding PEV infrastructure planning• Conveys stakeholder feedback collected from the PEV• Conveys stakeholder feedback collected from the PEV 

Infrastructure Plan Stakeholder Workshop, review comments on earlier draft versions, and results from discussions with key stakeholders

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stakeholders

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Summary of Quantitative Results

The EVSE charge point results below summarize key quantitative results from the statewide assessment 

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Resulting EVSE Stations by Type and Region

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Note: L1: Level 1 charger; L2: Level 2 charger; FC: fast charger

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How to Read the Main Summary Graphic

Explanation example

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Comparisons across Planning Regions

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Scenario Methodology• We do not yet have sufficient empirical market and consumer 

behavior data to develop a predictive model of EVSE expansion 

• Therefore, a scenario approach is warranted , pp

Some high‐level numbers…..

• Electricity demand = total miles * Wh/mile = 2 759 million kWh• Electricity demand = total miles * Wh/mile  =  2,759 million kWh

• This is 900,000 PEVs driving on average ~ 20 e‐miles per day

General approach: Allocate kWh by EVSE location and type

• Home, Public, and Workplace EVSE stations 

• Three types EVSE: Level 1, Level 2, Fast Charge

The 2020 goal is a snapshot of a rapidly expanding market This demand would increase rapidly with exponential PEVs sales, 

hi 4 0 billi kWh i 2025 d l 10 billi kWh b 2030

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reaching 4.0 billion kWh in 2025, and nearly 10 billion kWh by 2030.

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ZEV Rollout Scenario and Electricity Demand

• ZEV Action Plan Identifies 2020 and 2025 Goals

o Sufficient EVSE to support 1.0 million ZEVs by 2020

• ZEV likely compliance scenario proposes vehicle market share trends

• ARB‐VISION model used to account for ZEV fleet adoption dynamics

• New vehicles introduced to the fleet over time (stock turnover model) 

S l St kSales Stock

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Early Adopter Metric (EAM) Applies for All ZEVs Coachella�Valley���

43,300��

Central�Coast�(S.)��29,900��

Monterey�Bay��14,500��

Central�Coast��15,500�� Upstate��3,300��

North�Coast��pp

Based on household income and historical sales of HEVs and  San�Diego���

90,900��

San�Joaquin�Valley��41,100��

Capital�Area��51,000��

North�Coast��2,200��

luxury vehicles

Number of ZEVs by Region  Southern�California��460,600��Bay�Area��

EAM is a proxy for future market analysis results 

460,600��247,200��

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Two EVSE ScenariosFocus on Two Key Trends

Consumer Demand

Overall consumer demand  ng Public Access: Public Access:

A: Unfulfilled Demand B: High Public Access

for workplace and public charging

ublic

Cha

rgin High

Cost to Consumers:Moderate

Moderate

Cost to Consumers:High

EVSE Supply 

Total benefits to EVSE suppliers from increased em

and

for P

uD: Excess SupplyC: Home Dominant

suppliers from increased workplace and public access

onsu

mer

De

Public Access:Moderate

Cost to Consumers:

Public Access:Low

Cost to Consumers:

Co

T t l b fit t EVSE S li d I t ll f

LowModerate

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Total benefits to EVSE Suppliers and Installers from Increased Public Access

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General Analytic Approach

• The number of EVSE stations is determined by adjusting multiple input parameters and assumptions such that the two scenarios represent distinct trends in both EVSE expansion and the use of

How many stations?

represent distinct trends in both EVSE expansion and the use of EVSE stations by PEVs. 

Where?How many stations?Capacity (kW) by EVSE type? 

hChargepoints per EVSE? 

Charges per chargepoint per Type

L1, L2, DCFC

LocationHow many miles per charge?

g p g p pday?

• Early adopters• Urban density

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LocationHome, Work, Public

How many miles per charge? • Interstate mile basis for DCFCs

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Distribution of kWh by EVSE Type

• These high‐level input assumptions are balanced against a variety of EVSE supply metricsM h i i ill d h i b h i• Most charging is still done at home in both scenarios

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EAM Distribution Differs from General Population Distribution PEVGeneral Population DistributionSome regions have more early adopters than others. 

PEV Planning Regions

The percent of Early Adopters (Y axis) in each region is compared to the percent of total population (X axis) in the figures below:

Southern�California�

40%�

45%�

50%�

l�Reg

ions

12%�

ns�

Bay�Area�

20%�

25%�

30%�

35%�

Early�Ado

pter

s�in�Al

San�Diego��

6%�

8%�

10%�

y�Ado

pters�in�All�Re

gion

5%�

10%�

15%�

20%�

Percen

t�of�Tot

al�E

����See�Inset�

San�Joaquin�Valley�Capital�Area�

Coachella�Valley��

Central�Coast�(S.)�

Monterey�Bay�

Central�Coast�2%�

4%�

Percen

t�of�Total�Early

16

0%�

0%� 5%� 10%� 15%� 20%� 25%� 30%� 35%� 40%� 45%� 50%�

Percent�of�Total�Popula on�in�All�Regions�

Upstate�0%�

0%� 2%� 4%� 6%� 8%� 10%� 12%�

Percent�of�Total�Popula on�in�All�Regions�

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Demand Profiles and EVSE Capacity

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Number of Stations as a Function of Peak Hourly Demand and EVSE Capacity

This equation is used to determine the number of EVSE stations (N) by type and location (i) providing electricity to a particular PEV type (j) : p g y p yp j

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Number of Stations as a Function of Total Electricity Needed and Electricity Provided per EVSE Station

This equation is used to determine the number of EVSE stations (N) by type and location (i) providing electricity to a particular PEV type (j) : p g y p yp j

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Goal Seek Used to Set e‐miles per Charge to Specified Values (Input Assumptions)

• The two “open” variables in these equations are: βi,j and qevent,i,j• The other variables have been determined using consistent assumptions g p

about average technology attributes (stations and vehicles) and behavior (VMT and hourly charging profiles)

• Goal seek solves the capacity and electricity equations simultaneously 

βi,j = Capacity buffer for EVSE of type i providing electricity to PEV type jηj = Electricity consumption rate by PEV type j (Wh per mile)

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Demand Profiles Results

Broken out by EVSE location and type 

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Adjustments to Meet Expected Metrics

• Adjust assumptions above to satisfy acceptable values for the following metrics:

DEMAND METRIC• Some fraction of PEV do not need home charging. The 

Modeling Constraint

calculations balance the non‐home kWhs across the workplace and public EVSE station types 

• More MUDs in High Public Access Scenario

SUPPLY METRICS• EVSE units per square mile in urban areas

“Rule of Thumb” Metric• EVSE units per square mile in urban areas• Interstate miles (nominal) between FC stations• Approximately 200 FC stations total (based on other studies)

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How Will CEC Use These Scenarios?

Adaptive management strategy. Need more data on market trends.

Two of the investment strategy responses the Energy Commission may consider as additional data are collected and trends are characterized include the following:

Apparent deficiency in EVSE availability. If PEV sales or e‐miles driven in a given locality or region appear to be dampened due to a lack of EVSE availability, the Energy Commission may consider i i ff t t t f d EVSE d l tincreasing efforts to support focused EVSE deployment.Apparent lack of PEV market support. If conditions for PEV adoption appear to be favorable in a given locality or region, including sufficient EVSE availability and favorable early adopterincluding sufficient EVSE availability and favorable early adopter demographics, the Energy Commission may consider increasing efforts to support focused PEV market adoption. 

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Questions?Questions?

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Backup SlidesBackup Slides

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Additional Assumptions and Metrics

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