DC Fast Charging Infrastructure for Electrified Road Trips

DOCKETED Docket Number: 20-IEPR-02 Project Title: Transportation TN #: 234213 Presentation - DC Fast Charging Infrastructure for Electrified Document Title: Road Trips S3. 4 Dong-Yeon Lee, National Renewable Energy Laboratory Description:

Filer: Raquel Kravitz Organization: NREL Submitter Role: Public Submission Date: 8/3/2020 4:08:38 PM Docketed Date: 8/3/2020

Dong-Yeon (D-Y) Lee and Eric Wood National Renewable Energy Laboratory (NREL)

CEC IEPR Workshop August 6, 2020 Rationale & Objective

● From the charging infrastructure standpoint, to electrify road trips in CA: 1) How many charging stations (or plugs/connectors) do we need? 2) Where do we need those charging stations? 3) What is the impact of charging load on the electric grid?

● To answer those questions, a new charging infrastructure simulation tool (EVI-Pro RoadTrip) has been developed: EVI-Pro RoadTrip EVI-Pro – Focused on long-distance (100+ miles/day) travels. – Focused on short-distance travels. – Based on waypoint charging (stop to charge). – Based on destination charging (charge when stop).

● Scope: ▪ CA-bound/originated road trips ▪ Domestic (inter-state) & international ▪ DC fast charging (DCFC) ▪ Personal light-duty BEVs (battery electric vehicles)

NREL | 2 EVI-Pro RoadTrip: Overall Structure & Spatio-Temporal Resolution

Road Trip BEV Energy Use and Station Design Capacity Analysis Volume and Pattern Charging Simulation (Siting and Sizing)

Refueling Transportation Electric Grid Infrastructure

Spatial resolution (default: longitude & latitude) Temporal resolution (default: 1 minute)

Coords. (origin, destination, trip simulation, etc.) Seconds (trip simulation, vehicular energy use, etc.)

30m x 30m (land use type, etc.) Minutes (charging time, detour to charging stations, etc.)

TAZ (traffic analysis zone, capacity analysis, etc.) Hours (intra-state road trip duration, etc.)

County (county-level aggregation) Days (cross-country road trip duration, etc.)

State (state-wide total number of stations, etc.) Years (infrastructure build-out, BEV adoption, etc.)

NREL | 3 Volume & Pattern of Electrified Road Trips

● TAZ-by-TAZ* road trip activity: Caltrans (CA DOT) CSTDM* (V3) County-level characterization ● CA electrification projections: CEC Energy Assessments Division’s of electrified road trips (in millions) per day in 2030 forecasts by 2030 (Low: 1.5M BEVs; Aggressive: 3.1M BEVs) ● Non-CA electrification projections: EIA and IEA forecasts Long-Distance Travel (LDT) Volume (1,000s) in 2020, 2025, and 2030 600

500

400

30 4.2% 3.7% 2.6% 1.4%

Low Low

Low/

Aggressive Aggressive Aggressive All LDTs Electrified All LDTs Electrified All LDTs Electrified (CSTDM) (RoadTrip) (CSTDM) (RoadTrip) (CSTDM) (RoadTrip) 2020 2025 2030

* TAZ: Traffic analysis zone (commonly used in transportation planning) – adopted as a basic geographical entity for travel demand estimation in CSTDM. NREL | 4 * CSTDM: California Statewide Travel Demand Model Trip, Vehicle Energy Use, and Charging Simulation

Origin Open Source Time ● Three BEV types: SR (short range) Car, LR (long range) Car, and SUV. Routing Machine Coordinates ● Leveraged NREL’s FASTSim (vehicle dynamic simulation tool). Destination (OSRM) Distance ● Detailed energy use and charging simulation for each road trip sample.

An example of simulated road trip DC Fast Charging Power (kW) as a function of (Southern border to SF; Battery SOC (state-of-charge) 520 miles; 5,200 data points) 2020 SR-Car 2020 LR-Car 2020 SUV 2025 SR-Car 2025 LR-Car 2025 SUV 2030 SR-Car 2030 LR-Car 2030 SUV

350

300

250

200

150 Charging Power (kW) Power Charging 100

Each dot/circle 50 represents each trip. 0 0% 20% 40% 60% 80% 100% SOC NREL | 5 DCFC Station Siting & Sizing ● Locate stations in commercial areas & other preferred sites. ● Station sizing is based on station-by-station load profiles. ● CEC collected station developers’ input to prioritize ● The number of plugs: max simultaneous charging events. candidate sites. ● The number of plugs per station is capped at 10. ● Leveraged national land use data (NLUD, in 30m x 30m), as well as coordinate data of 6,000 gas stations in CA. Individual Charging Load Profiles for a DCFC Station (ID: 235) Station siting example Station ID: 793 300 Coord: -122.872, 38.626 TAZ ID: 542 200 Charging events/day: 10 100 Plugs: 2

Land use type: commercial (kW) Power Charging 0

Healdsburg, CA 0

150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950

Sonoma county 100

1000 1050 1100 1150 1200 1250 1300 1350 1400 Minute of Day

Simultaneous Charging Events for a DCFC Station (ID: 235) 10 68 charging events over the course of day 8 residential Peak simultaneous events: 10 6 4 Charging demands along the routes 2

Sim. Charging Events Charging Sim. 0

100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950

1000 1050 1100 1150 1200 1250 1300 1350 1400 Minute of Day crop/range-land

Other, 1% Other, NREL | 6 Results: Stations and Plugs/Connectors

Required Number of DCFC Plugs for Electrified Road Trips TAZ-by-TAZ net deficit of DCFC plugs required (Lower bound: 100% plug utilization rate Year 2030

Upper bound: 25% plug utilization rate) Aggressive BEV adoption stations stations 12,000 Lower bound (100% peak plug utilization rate)

400 kW 1,600 300 kW 10,000

200 kW stations stations 100 kW

8,000 1,200

6,000

DCFC stations stations DCFC

800 stations stations

4,000 SF Bay Area Los Angeles

1,000

The number of required DCFC plugs DCFC required of number The Equivalent to Equivalent 2,000

Currently, existing 0 stations are not considered in the Lower Upper Lower Upper Lower Upper Lower Upper Lower Upper process of station Low/ Low Aggressive Low Aggressive siting or network Aggressive BEV BEV BEV BEV Existing design in EVI-Pro BEV Adoption Adoption Adoption Adoption RoadTrip RoadTrip. Adoption 2020 2025 2030 1 100

Snapshot for each simulation year (2020, 2025, and 2030) Additional plugs required San Diego NREL | 7 without the consideration of existing conditions from previous years. Results: Load Profiles

● Network-wide total charging load reaches around 90 MW in peak hours in 2030 for Aggressive BEV adoption scenario (50 MW for Low scenario). ● Notable difference of load shapes between out-of-state inbound LDTs and the other types of LDTs (e.g., intra-state).

Total Charging Load (MW) Total Charging Load by BEV Type Total Charging Load by LDT Type by Year and BEV Adoption Scenario (Aggressive BEV adoption; 2030) (Aggressive BEV adoption; 2030) 90 2020 90 90 Out-of-state Through SUV 80 2025 Low Out-of-state Inbound 80 LR-Car 80 2025 Aggressive Out-of-state Outbound SR-Car 70 Intra-state 2030 Low 70 70 2030 Aggressive 60 60 60

50 50 50

40 40 40

wide Charging Load (MW)Load Charging wide

- -

30 30 30

Network Network 20 20 Network 20

10 10 10

0 0 0

0 2 4 6 8

10 12 14 16 18 20 22 24

10 12 14 16 18 20 22 24 Hour of Day (0 - 24) Hour of Day (0 - 24) Hour of Day (0 - 24) NREL | 8 Sensitivity Analysis: Charging Behavior & Technology

● Charging behavior related to plug-out SOC: ● Charging technology (speed, power, etc.) is still evolving. - TPM: Time penalty minimization (plug out at around 85% of SOC) ● What if Tesla V3-like kW-SOC curves are used? - ATO: Always top off (plug out at 99% of SOC)

DC Fast Charging Power (kW) as a Function of DC Fast Charging Power (kW) as a Function of Battery SOC (state-of-charge): Baseline (Spread-out) Battery SOC (state-of-charge): Tesla V3-like 800 2020 SR-Car 2020 LR-Car 2020 SUV 2020 SR-Car 2020 LR-Car 2020 SUV 2025 SR-Car 2025 LR-Car 2025 SUV 700 2025 SR-Car 2025 LR-Car 2025 SUV 2030 SR-Car 2030 LR-Car 2030 SUV 2030 SR-Car 2030 LR-Car 2030 SUV

350 600

300 500

250 400

200

300 Charging Power (kW) Power Charging 150

Charging Power (kW) Power Charging 200 100

50 100

0 0 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% SOC (State-of-Charge) SOC (State-of-Charge) NREL | 9 Impact of Charging Behavior & Technology

● Charging behavior (TPM vs. ATO): ● Charging technology (kW-SOC curves): - Significant impact on load profiles and plug counts. - Less-than-significant impact on load profiles or plug counts. - Plug composition (power rating) is mostly the same. - Drastic difference in terms of plug composition (power rating).

Total Charging Load (MW) for Total Charging Load (MW) for Different Charging Behaviors (ATO vs. TPM) Different kW-SOC Curves 100 2030 TPM (time penalty min) 2030 Baseline (spread-out) 150 2030 ATO (always top off) 80 2030 Tesla V3-like 60 100

wide Charging Load Charging wide -

wide Charging Load Charging wide 50 - 20

0 0

0 2 4 6 8

Network

0 2 4 6 8

10 12 14 16 18 20 22 24

10 12 14 16 18 20 22 24 Network Hour of Day (0 - 24) Hour of Day (0 - 24)

Required Number of DCFC Plugs for Electrified LDTs Required Number of DCFC Plugs for Electrified Road Trips (Lower bound: 100% plug utilization rate) 800 kW (Lower bound: 100% plug utilization rate) 700 kW 4,000 400 kW 2,000 600 kW 3,000 300 kW 500 kW 2,000 200 kW 1,000 400 kW 100 kW 1,000

0 300 kW

(for Lower Bound) Lower(for (For Lower Bound) Lower(For 0 Plugs DCFC of Number Baseline Tesla Baseline Tesla Baseline Tesla Number of DCFC Plugs DCFC of Number 200 kW TPM ATO TPM ATO TPM ATO V3-like V3-like V3-like 100 kW 2020 2025 2030 2020 2025 2030 NREL | 10 Results: Capacity Analysis – SCE (Southern California Edison) Case Study

Net capacity deficit (MW) < -2,000 -2,000 – -1,000 EVI-Pro RoadTrip EDGE -1,000 – -500 -500 – 0 0 (no remaining capacity) 0 – 2 Required capacity by TAZ Available hosting capacity by TAZ 2 – 4 May require 4 – 6 grid upgrade Net capacity deficit by TAZ 6 – 8 8 – 12

Simulated location of charging station

● TAZ-by-TAZ capacity deficit ranges from 0 to 20 MW. ● Data quality of hosting capacity is to be improved.

Year 2030 Aggressive BEV adoption NREL | 11 Policy Implications (informed by CEC Staff)

1. Need real world high-resolution data. ● Model usefulness depends on high quality input data that capture real-world travel/driving behavior and charging session characteristics.

2. Enhance grid integration at all levels. ● DCFC loading (for electrified road trips) at the system-level may align with solar power generation. ● Initial capacity analyses suggest that electrified road trips alone might be accommodated. However, when accounting for integrated electrical load (road trips, short distance travels, buildings, etc.), California should encourage efforts to manage network over-build (“turnover” pricing) and proactively mitigate grid impacts.

3. Plan for RoadTrip stations as part of a holistic expansion of the network. ● Technology improvements moderate the growth in the number of stations and plugs needed to serve more BEVs in 2030, compared to 2025, highlighting the importance of future proofing equipment and maximizing BEV-plug interoperability today. ● Integrating the RoadTrip analysis with EVI-Pro 2 can optimize the network of stations.

NREL | 12 Limitations & Future Work

● “V1” of EVI-Pro RoadTrip (a model is a model). ● Need more realistic and rigorous methods and data for better characterization of driving & charging. ● Long-distance travels (or road trips): Traditionally under-researched area in transportation field.

● Future work (not exhaustive): ❑ Consider infrastructure co-utilization by entire LDV fleet (short-distance travels, TNC, etc.). ❑ Internalize existing charging infrastructure in the overall station network design. ❑ More integrated and advanced analysis (decision-making) of driving (drivers) and charging (infrastructure). ❑ Account for dynamic aspects of the refueling network (e.g., coordinated charging, station congestion). ❑ More realistic method for DCFC station siting and sizing (e.g., by reaching out to relevant stakeholders). ❑ Stochastic approach for key parameters (e.g., heterogeneity of charging behavior). ❑ State-wide capacity analysis (beyond the SCE area).

NREL | 13 Thank You

D-Y Lee: [email protected]

NREL | 14 Appendix

NREL | 15 Road Trip Electrification Projections

● Road trip electrification is based on general light-duty vehicle electrification projections (BEV adoption). - California: 10% by 2030 (based on the forecasts made by CEC’s Energy Assessments Division) - Non-CA states: 2.5% by 2030 (based on EIA AEO – see next slide) - Mexico: 0.05% by 2030 (based on IEA projections) ● BEV adoption scenarios: - Baseline/aggressive (3.1M BEVs by 2030): Business as usual - Low (1.5M BEVs by 2030): Potential aftermath (e.g., slower electrification) of the ongoing pandemic (COVID-19)

Baseline (Aggressive) BEV Adoption Low BEV Adoption Daily travel volume of road trips in California Intra-state External Total Intra-state External Total

CSTDM (All) 215,151 344,058 559,209 215,151 344,058 559,209 2020 RoadTrip (Electrified) 4,226 3,762 7,988 4,226 3,762 7,988 CSTDM (All) 211,684 363,005 574,689 211,684 363,005 574,689 2025 RoadTrip (Electrified) 12,332 11,810 24,142 7,205 7,514 14,719 CSTDM (All) 210,844 372,856 583,700 210,844 372,856 583,700 2030 RoadTrip (Electrified) 20,425 20,323 40,748 10,212 11,503 21,715

NREL | 16 BEV Adoption in Non-CA States ● EIA AEO 2020 projection: 2–4% of total LDV (light-duty vehicle) stock in the U.S. will be BEVs by 2030. ● The range reflects 23 different scenarios EIA evaluated.

BEV Share in BEV Share in BEV Share in U.S. Car Stock U.S. Light Truck Stock U.S. LDV Stock 6% 6% 6% Reference Case Reference Case Reference Case

5% 5% 5%

4% 4% 4%

3% 3% 3%

2% 2% 2%

BEV Share in U.S. Car Stock Car U.S. in Share BEV

BEV Share in U.S. LDV Stock LDV U.S. in Share BEV BEV Share in U.S. Light Truck Stock Truck Light U.S. in Share BEV

1% 1% 1%

0% 0% 0%

2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Data source: EIA AEO 2020 NREL | 17 TAZs (Traffic Analysis Zones) & Gateways in CSTDM

● 5,454 internal TAZs - Used for short-distance (SHT) and long-distance (LNG) travel volume

● 53 external TAZs (gateways) - 3 ports (Port of Oakland, POLA, & POLB) - 50 roadways crossing CA boundary - Used for external (EXT) travel volume San Francisco CSTDM TAZ Area Distribution (80% TAZs < 5 square miles) 1,400 1,200 1,000 800

600 Frequency 400 200

0 2 3 5 6 8 9

11 12 14 15 17 18 20 21 23 24 TAZ Area (square miles) Los Angeles NREL | 18 Seed Coordinates for Origins and Destinations: CHTS + NLUD

CHTS (California Household Travel Survey): NLUD (National Land Use Data): About 0.2 million unique coordinates as reference points for origins/destinations; Down-sampled for residential and the spatial density is correlated with population centers. commercial spots (30m x 30m)

NREL | 19 Breakdown of Origin and Destination Coordinates by Sources/Types

● Replaced centroids (used when no CHTS coordinates are available) with NLUD coordinates. ● Reduced duplicate CHTS samples. ● In the final input data (trips) for simulation, NLUD coordinates account for about 11%.

Breakdown of Origin and Destination Coordinates by Sources/Types

CHTS NLUD Centroid EXT

350,000

300,000

250,000

200,000

150,000

100,000

50,000

0 Old New Old New Old New Old New Origin Destination Origin Destination Origin Destination Origin Destination LNG EXT Baseline Low

CSTDM (2030) EVI-Pro RoadTrip (2030) NREL | 20 Road Trip Pattern by Year (Baseline BEV Adoption)

2020 2025 2030

Travel volume increases over time, but the overall spatial pattern of road trips remains similar. NREL | 21 BEV Type, Population, and Specifications

CEC EAD Analysis: Vehicle Population Breakdown, 2020ꟷ2030 BEV specification example: Battery size (kWh) Car-SR Car-LR SUV 100%

11.6% SR Car/Sedan LR Car/Sedan SUV 90% 24.9% 200 200 200 180 180

28.4% ) 180 ) 180 180

80% 160 160 160 kWh) 46.4% 46.4% 47.4% 140 (kWh 140 125 125 125 125 140 125 125 120 120 100 100 100 120 100 100 100

70% 100 100 100 Capacity (kWh Capacity Capacity ( Capacity 80 60 80 80 60 42 45 45 45 45 60 60 60% 57.5% 40 40 40

40 40 40

Battery Battery 20 Capacity Battery 20 20 50% 0 0 0 54.2% 53.7%

40%

BMW i3 BMW

Baseline Baseline Baseline Baseline Baseline Baseline Baseline Baseline 31.7% Baseline

34.5%

Aggressive Aggressive Aggressive Aggressive Aggressive Aggressive Aggressive Aggressive

36.2% Aggressive

Nissan Leaf Nissan

Nissan Leaf+ Nissan Tesla Model S Model Tesla 30% X Model Tesla 2020 2025 2030 2020 2025 2030 2020 2025 2030 20% 30.9% 22.0% 10% 19.1% 20.9% 16.5% 17.9%

0% LDV-All LDV-BEV LDV-All LDV-BEV LDV-All LDV-BEV 2020 2025 2030 NREL | 22 Model Year (MY) Distribution (adapted from CEC EAD data)

SR-Car (2030) LR-Car (2030) SUV (2030) 2015 2015 2015 6% 2% 2020 16% 16% 2030 30% 2030 2020 33% 22% 2030 Baseline (Aggressive) 38% BEV Adoption 2020 19%

2025 2025 2025 44% 35% 39%

SR-Car (2030) LR-Car (2030) SUV (2030) 2015 2015 3% 2030 2015 2030 7% 2020 24% 20% 28% 2030 33% 21%

2020 Low BEV Adoption 27%

2020 2025 24% 32% 2025 2025 38% 43% NREL | 23 Road Trip Distance Statistics

Total Driving Distance (miles) - 2030, Baseline BEV Adoption (Average: 260 miles) 12,000

10,602 Intra-State Out-of-State All 10,000

8,000

6,931 6,134

6,000 5,964

4,736

Frequency

4,638 3,967

4,000 3,718

3,354

3,328

3,053

2,780

2,330

2,195

2,137

2,087

1,792

1,696 1,570

2,000 1,536

1,224

1,191

863

723

587

446

441

379

249

225

151

141

4 4

2 2

1 1

0 0 0 0 0 0 0 0 0

100 - 150 - 100 200 - 150 250 - 200 300 - 250 350 - 300 400 - 350 450 - 400 500 - 450 550 - 500 600 - 550 650 - 600 700 - 650 750 - 700 800 - 750 850 - 800 900 - 850 950 - 900 950 - 1000 - 950 Trip-by-Trip Total Driving Distance (miles)

NREL | 24 Trip Initialization ● CHTS-LDT (long-distance travel) indicates that trip start/departure time centers around 10–11 am. ● CHTS-LDT start time distribution (below) is used as reference for departure time.

Simulated Departure & Arrival Time for LDTs 5,000

4,500 Departure Arrival 4,000

3,500

3,000

2,500 Frequency 2,000

1,500

1,000

500

0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Hour of Day

(Based on California Household Travel Survey) NREL | 25 Energy Consumption Rate (kWh/mile)

● Generic energy consumption rate (kWh/mile) was developed from NREL’s FASTSim simulation with CEC/CARB/NREL vehicle specifications and millions of real-world drive cycles.

Energy Consumption Rate (kWh/mile) - FASTSim Result

0.8 Solid bars: 2020 Dashed bars: 2030 0.7

SUV 25th, 50th, & 75th percentiles 0.6

0.5 LR Car LR

0.4 SR Car

0.3

0.2 Energy Consumption Rate (kWh/mile) Rate Consumption Energy

0.1 Unadjusted 0.0 0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75 75-80 80-85 Average Speed (mph)

NREL | 26 Departure and Entry SOC (State-of-Charge) ● Departure SOC for intra-state road trips: FleetCarma NE data. ● Entry SOC for out-of-state inbound road trips: SOC at the point of entering the state (CA) boundary. ● Run EVI-Pro RoadTrip with FHWA TAF (Traffic Analysis Framework) O-D matrix (for 2040).

Entry SOC Distribution Entry SOC Distribution (ATO, 2030) (TPM, 2030)

SR-Car LR-Car SUV SR-Car LR-Car SUV 20% 20%

15% 15%

10% 10%

Percentage Percentage

5% 5%

0% 0% 0-10

External inbound 0-10

10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 https://www.fhwa.dot.gov/policyinformation/analysisfram (domestic only) 90-100 ework/docs/taf_final_report.pdf Entry SOC (%) Entry SOC (%)

NREL | 27 Estimating Entry SOC for “External Inbound” Trips ● FHWA TAF O-D (county-by-county LDT) + EVI-Pro RoadTrip

2,000 Travel Distance (miles) Distribution 1,500 1,000

Frequency 500 0

Total Travel Distance (miles)

2,500 Total Driving Time (hours) Distribution 2,000 1,500 1,000

Frequency 500 0

Total Driving Time (hours)

4,000 Total Charging Events Distribution 3,000 2,000

Frequency 1,000 0

NREL | 28 Total Charging Events Plug-In and Plug-Out SOC (State-of-Charge)

Charging Power as a Function of SOC 2020 Car - SR 2020 Car - LR 2020 SUV 2025 Car - SR 2025 Car - LR 2025 SUV 2030 Car - SR 2030 Car - LR 2030 SUV Plug-in SOC First bending point 100% SOC 350

300 Second bending point (reference plug-out SOC) 250

Driving 200

Time to 150

plug in 5 mile (kW) Power Charging

100 5% 0% SOC

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% SOC NREL | 29 Example Energy and Charging Simulation: External Trip

ATO (always top off); TPM (time penalty minimization); 1 rounds of charging for 30 minutes 2 rounds of charging for 22 minutes

Google Map

▪ Trip ID: 38212 ▪ Traveling from the southern border to SF ▪ Approximately 520 miles ▪ Average MPH: 52 (excluding charging) ▪ Simulation year: 2030 ▪ Vehicle: LR-Car ▪ MY: 2030 NREL | 30 Example Energy and Charging Simulation: Intra-State Trip

ATO (always top off); TPM (time penalty minimization); 3 rounds of charging for 57 minutes 3 rounds of charging for 34 minutes

Google Map ▪ Trip ID: 7148 ▪ Traveling from Joaquin to San Diego ▪ Approximately 470 miles ▪ Average MPH: 52 (excluding charging) ▪ Simulation year: 2030 ▪ Vehicle: SR-Car ▪ MY: 2030 NREL | 31 Prioritized Preferred Sites for DCFC Stations

Priority Group Land Use Type

Retail/shopping 1 Gas stations Lodge Airports 2 Port, train station Urban park General Park Natural park Off-highway vehicle staging area/trailhead Motorized park 3 Entertainment (stadiums) Designated recreation area Campground/ranger station Marina Resort/ski area Picnic/trailhead NREL | 32 Sensitivity Analysis Cases

● BEV type share (e.g., SUV-dominant). ● Battery size. ● Energy consumption rate (kWh/mile). ● Plug-in SOC (related to the radius of station service area or coverage). ● Plug-out SOC. ● kW-SOC curves. ● Ambient temperature and corresponding accessory load (e.g., heating). ● Potential sites for DCFC stations (e.g., gas station-centric). ● Station sizing – peak-hour plug utilization rate (e.g., 100% vs. 25%).

NREL | 33 (What-If) Alternative Station Siting Strategy: Gas Station-Centric ● Existing gas stations can absorb/host around 70% of DCFC stations needed. ● Forcing gas stations for potential sites transforms the overall structure as well - for example, see how the share of retail/shopping centers changes.

Final Station Sites by Land Use Types Final Station Sites by Land Use Types (2030, Baseline BEV Adoption, TPM Behavior) (2030, Baseline BEV Adoption, TPM Behavior) Default Station Siting Strategy Gas Station-Centric Siting Strategy Gas Stations Gas Stations

Retail/shopping centers Retail/shopping centers

Natural park Natural park

General park General park

Highways, railways Highways, railways

Airports (developed) Airports (developed)

Urban park Urban park

Areas of Critical Env. Areas of Critical Env. Concern, Research Natural Concern, Research Natural Area Area Campground/ranger Campground/ranger station station NREL | 34 Network-Wide Load Profiles (for Electrified Road Trips)

Network-wide Charging Load (MW) Profiles

300 2030 Baseline TPM 2030 Low TPM 2030 Baseline ATO 250 2030 Baseline TPM - BEV Range 2030 Baseline TPM - BEV Share (Equal) 2030 Baseline TPM - BEV Share (LDV Fleet) 200 2030 Baseline TPM - Buffer (2 miles) 2030 Baseline TPM - Buffer (10 miles) 2030 Baseline TPM - ECR (High)

150 2030 Baseline TPM - ECR (Low) wide Load (MW) Load wide - 2030 Baseline TPM - HVAC (@30F) 2030 Tesla V3-like

Network 100

0 0 2 4 6 8 10 12 14 16 18 20 22 24 Hour of Day (0 - 24)

Preliminary results. Subject to review/change. NREL | 35 Load Profiles: Difference relative to 2030 Baseline TPM

Network-wide Charging Load (MW) Profiles: Difference (relative to 2030 Baseline TPM) 250 2030 Low TPM 2030 Baseline ATO

200 2030 Baseline TPM - BEV Range 2030 Baseline TPM - BEV Share (Equal) 2030 Baseline TPM - BEV Share (LDV Fleet) 150 2030 Baseline TPM - Buffer (2 miles) 2030 Baseline TPM - Buffer (10 miles)

100 2030 Baseline TPM - ECR (High) 2030 Baseline TPM - ECR (Low)

wide Load (MW) Load wide 2030 Baseline TPM - HVAC (@30F) -

50 2030 Tesla V3-like Network

-50

-100 0 2 4 6 8 10 12 14 16 18 20 22 24 Hour of Day (0 - 24)

Preliminary results. Subject to review/change. NREL | 36 Load Profiles: Intra-Hour Variation

Intra-Hour Variation of Network-wide Charging Load (MW) Profiles

60 2030 Baseline TPM 2030 Low TPM 2030 Baseline ATO 50 2030 Baseline TPM - BEV Range 2030 Baseline TPM - BEV Share (Equal) 2030 Baseline TPM - BEV Share (LDV Fleet) 40 2030 Baseline TPM - Buffer (2 miles)

2030 Baseline TPM - Buffer (10 miles)

wide Load (MW) Load wide - 2030 Baseline TPM - ECR (High)

30 2030 Baseline TPM - ECR (Low) 2030 Baseline TPM - HVAC (@30F) 2030 Tesla V3-like

Hour Variation of Networkof Variation Hour

- Intra 10

0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Hour of Day (0 - 24)

Preliminary results. Subject to review/change. NREL | 37 Load Profiles: Intra-Hour Variation (scaled by the first hour)

Intra-Hour Variation (scaled by the first hour) of Network-wide Charging Load (MW) Profiles

10 2030 Baseline TPM 2030 Low TPM 9 2030 Baseline ATO 2030 Baseline TPM - BEV Range 8

2030 Baseline TPM - BEV Share (Equal)

wide Load (MW) Load wide - 2030 Baseline TPM - BEV Share (LDV Fleet) 7 2030 Baseline TPM - Buffer (2 miles) 2030 Baseline TPM - Buffer (10 miles)

) of Networkof ) 6 2030 Baseline TPM - ECR (High)

5 2030 Baseline TPM - ECR (Low) 2030 Baseline TPM - HVAC (@30F) 4 2030 Tesla V3-like

scaled by the first hour first the by scaled 3

2 Hour Variation ( Variation Hour

- 1 Intra 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Hour of Day (0 - 24)

Preliminary results. Subject to review/change. NREL | 38 Required Number of Connectors

Required Number of Connectors for Electrified Road Trips by 2030 (Lower bound, based on 100% peak-hour plug utilization rate)

100 kW 200 kW 300 kW 400 kW 500 kW 600 kW 700 kW 800 kW

0 1,000 2,000 3,000 4,000 5,000

2030 Baseline TPM

2030 Low TPM

2030 Baseline ATO

2030 Baseline TPM - BEV Range

2030 Baseline TPM - BEV Share (Equal)

2030 Baseline TPM - BEV Share (LDV Fleet)

2030 Baseline TPM - Buffer (2 miles)

2030 Baseline TPM - Buffer (10 miles)

2030 Baseline TPM - ECR (High)

2030 Baseline TPM - ECR (Low)

2030 Baseline TPM - HVAC (@30F)

2030 Tesla V3-like

Preliminary results. Subject to review/change. NREL | 39