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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 DC Fast Charging Infrastructure for Electrified Road Trips 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 7% 30 4.2% 3.7% 2.6% 1.4% 0 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 50 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 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 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 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 wide Charging Load (MW) Load Charging wide - 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 0 2 4 6 8 0 2 4 6 8 10 12 14 16 18 20 22 24 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 40 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.
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