This presentation details current models available for integrating electric vehicles onto the grid, case studies and possible improvements for future models.

1. IMAGE | GREENTECHMEDIA
ELECTRIC VEHICLE GRID SIMULATOR
WRI Electric Mobility | April 2, 2020

2. AGENDA
 Current model inputs and outputs
 Case studies
 Future model improvements

3. EV GRID SIMULATOR

4. SIMULATOR INPUTS
 Setting: Multiple use cases (commercial, industrial, residential)
 Level of analysis: Distribution transformer
 Time interval: 15-minute intervals over 24 hours

5. SIMULATOR INPUTS
 Vehicle energy efficiency (kWh/100km)
 Number of EVs
 Daily mileage*
 Arrival time
 Number of EVs participating in managed
charging
 Parking duration
 EV quantity to participate in V2G
 Base load
 Rated capacity
 Utility rate
 Number of chargers
 Charging power (kW)
 Charging frequency*
 Charging starting SOC
 Charging ending SOC*
 Number of smart chargers*
 Charging power: upper/lower limit
 Discharging power: upper/lower limit
* Indicates input is preferred but optional

6. SIMULATOR OUTPUTS
Distribution transformer impact
 Increases in peak load
 Increased capacity required
 Time of peak load
 Peak-valley difference
EV load characteristics
 Max EV load
 EV ratio in peak load
 EV load over time
 Utilization factor

7. MODEL INSIGHTS
 Optimized EV charging strategy
 Time-sensitive electricity cost analysis
 Electricity cost and demand charge mitigation
 Determine VGI potential based on vehicle and infrastructure
specifications.
 Energy potential of parked vehicles
 Viability of various VGI applications

8. CASE STUDY: FREIGHT DEPOT
 Hypothetical scenario at commercial freight facility.
 Developed to observe a large quantity of vehicles returning to
charge at a single location.
 Key questions:
 Will distribution transformer be overloaded as electrification increases?
 How will managed charging mitigate overloading and potentially avoid
demand charges?

9. CASE STUDY: FREIGHT DEPOT
Unmanaged Charging Managed Charging
Number of vehicles: 150
Max capacity: 2400 kW

10. CASE STUDY: SUZHOU, CHINA
 City of Suzhou is looking to re-align their energy system
to accommodate future growth and test new concepts
 Second largest city in China by electricity consumption
 One of the wealthiest cities in China, witnessing rapid EV growth

11. CASE STUDY: SUZHOU, CHINA
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0:00
1:15
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3:45
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kW
33%EV penetration 66%EV penetration
100%EV penetration Base load
Distribution capacity 80% of Distribution capacity
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kW
33%EV penetration 66%EV penetration
100%EV penetration Base load
Distribution capacity 80% of Distribution capacity
0
1000
2000
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0:00
1:15
2:30
3:45
5:00
6:15
7:30
8:45
10:00
11:15
12:30
13:45
15:00
16:15
17:30
18:45
20:00
21:15
22:30
23:45
kW
33%EV penetration 66%EV penetration
100%EV penetration Base load
Distribution capacity 80% of Distribution capacity
Case 1: Office Case 2: Commercial Complex Case 3: Residential Neighborhood
Suzhou modelling results indicate that residential distribution feeders
are most vulnerable to (or potentially hinder) large EV deployment

12. EV GRID SIMULATOR