David PetersonUP206a – GIS (Estrada)December 6, 2010

Source: Ecotality

Mayor wants LA to be #1 city for EVs EVSE can influence adoption rates Where will public investment in

EVSEs generate highest benefit?

EVs require a completely new infrastructure to connect to electricity grid

Single-family residential: not an issue

Focus on Problem Areas: Multi-family residential Employment Centers Commercial Centers

Goal: Anticipate concentrations of EV ownership

Use 2008 Hybrid ownership data as proxy for EV ownership

Origins: Multifamily residential problem Destinations: Making sure they can

charge at destination

Absolute number of vehicles? Percent capture of total vehicles in LA? Percent of total vehicles within zip

code?

Rank Zip CodePct of Zip

CodePct of LA

OwnershipNumber of

Vehicles1 90017 20.85% 0.05% 284 2 90001 9.52% 0.00% 2 3 90402 8.73% 0.38% 921 4 90272 6.76% 0.71% 1,344 5 90290 6.42% 0.21% 371 6 90022 5.64% 0.17% 264 7 90035 5.38% 0.71% 1,074 8 90501 5.33% 1.69% 2,537 9 90056 5.15% 1.08% 1,558

10 90291 4.86% 0.88% 1,202

LA Hybrid Penetration - Percent of Local Zip Code

Zip Code 90501:•#1 for vehicles: 2,537•#8 In terms of Percent of Local Zip Code

Zip Code 90001:•#2 for Penetration of Local Zip Code•Only has 2 vehicles!

What’s the best measurement?

Rank Zip CodePct of Zip

CodePct of LA

OwnershipNumber of

Vehicles1 90501 5.33% 6.18% 2,537 2 90056 5.15% 3.79% 1,558 3 90272 6.76% 3.27% 1,344 4 90291 4.86% 2.93% 1,202 5 90071 2.70% 2.85% 1,170 6 90063 3.31% 2.75% 1,128 7 90035 5.38% 2.61% 1,074 8 91604 4.06% 2.45% 1,008 9 90064 2.95% 2.45% 1,006

10 90402 8.73% 2.24% 921

LA Hybrid Penetration - Number of Vehicles

41,079 hybrids in LA 12,948 in the top 10 (32%)

Rank Zip CodePct of Zip

CodePct of LA

OwnershipNumber of

Vehicles1 90501 5.33% 6.18% 2,537 2 90056 5.15% 3.79% 1,558 3 90272 6.76% 3.27% 1,344 4 90291 4.86% 2.93% 1,202 5 90071 2.70% 2.85% 1,170 6 90063 3.31% 2.75% 1,128 7 90035 5.38% 2.61% 1,074 8 91604 4.06% 2.45% 1,008 9 90064 2.95% 2.45% 1,006

10 90402 8.73% 2.24% 921

LA Hybrid Penetration - Number of Vehicles

In top 10, what is percent housing type?

Data Problem: don’t know housing type by hybrid vehicle ownership.

Assumption: Hybrid owners reflect zip code housing type distribution

Rank Zip CodeNumber of

Hybrid Vehicles

Single Family

Multi-Family

Other

1 90501 2,537 57% 41% 3%2 90056 1,558 67% 33% 0%3 90272 1,344 82% 15% 4%4 90291 1,202 42% 58% 0%5 90071 1,170 0% 0% 0%6 90063 1,128 78% 22% 1%7 90035 1,074 27% 73% 0%8 91604 1,008 48% 52% 0%9 90064 1,006 58% 42% 0%10 90402 921 66% 34% 0%

Housing Stock Compositon by Zip Code

90071: no housing, but ranks 5th (1,070) by total hybrids – must be government/business/etc.

Multifamily charging is an issue: Mix of SFR and MFR

Range 15% to 73% Mean: 41%

Index that combines vehicle ownership and multifamily housing Greater weight on more vehicles (1-4) Greater weight on more MFR (1-4)

Combine to create Investment Prioritization Index Hotspot Analysis Index=[vehicles_weighted]+

[MFR_weighted]

Rank Zip CodeNumber of Hybrid Vehicles

Single Family

Multi-Family

Other

1 90501 2,537 57% 41% 3%2 90291 1,202 42% 58% 0%3 91604 1,008 48% 52% 0%4 90056 1,558 67% 33% 0%5 90035 1,074 27% 73% 0%6 90064 1,006 58% 42% 0%7 90063 1,128 78% 22% 1%8 90272 1,344 82% 15% 4%9 90402 921 66% 34% 0%10 90071 1,170 0% 0% 0%

EVSE Investemnt Prioritization Index Ranking

Data Problem: don’t know exactly where hybrid owners commute

Assumption: use zip code trip distribution Methodology:

Weight % allocation of trips by actual number of hybrid vehicles in origin zip codes

Aggregate for a complete picture of destinations

Is destination charging a real concern? Average Commute range: 40 miles (r/t) Battery Range: 80-100 Miles Not a real concern given current travel

behavior, but people might travel differently with EVs

Destination Zip Code

One-Way Commute Trip

Percent of Total Trips

90501 2,523 32.3%90245 492 6.3%90045 397 5.1%90502 345 4.4%90248 314 4.0%90247 267 3.4%90717 251 3.2%90744 181 2.3%90017 147 1.9%90710 142 1.8%

Top Ten Commute Destinations for 90501

Rank Zip Code Trips Pct of Total1 90025 1,561 3.8%2 90024 1,278 3.1%3 90501 1,184 2.9%4 90012 1,161 2.8%5 90045 933 2.3%6 90017 820 2.0%7 90015 788 1.9%8 91367 779 1.9%9 90245 758 1.8%10 90210 749 1.8%

Top 10 Hybrid Destination Trips

Use Index to Allocate Funds to Origin Zip Codes that will benefit the most.

Know the top 10 destinations for these origins. Not imperative to invest in public charging

given vehicle range Need to monitor/track travel behavior Providing EVSEs at these stations could induce

greater adoption (but is it best use of public funds?

Appendix A: Models Appendix B: Original Map Layer Appendix C: Metadata Appendix D: Map with 7 Layers Appendix E: Skills

Model for Rasterizing Layers for index/hotspot analysis inputs

Model for 50-mile buffer

Model for Clipping Buffer to Land Contours

Slide 8 Inset Map Geoprocessing: clipped California zip code

files Slide 10

tables Slides 11/12:

Attribute sub-set selection based on number of hybrid vehicles

Slides 13/15 Tables

Slide 17: Sub-set selection; Pie charts

Slides 19/20/21 Rasterization of data layers using a model Creation of Index for Hotspot Analysis using

a model Use of Spatial Analyst

Slide 22: Table

Slide 25: Used model to create distance buffer from top

10 zip code centroids Slide 26:

Use of Network Analyst to generate database file and OD Cost matrix

Slide 27: Table

Slide 28/29: Attribute sub-set selection

Slide 30: Table

Slides 33-35: Models

Slide 36 Original Map Layer

Slide 37: Creation of Metadata

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