Optimal De-Centralized Smart Home-Charging: Potential Study · EVs status (2017) 1.1 million sold...
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Optimal De-Centralized Smart Home-Charging: Potential Study Mahmoud Shepero Reza Fachrizal Joakim Munkhammar Built Environment Energy Systems Group (BEESG) Uppsala university 15 October 2018 1 / 14
Transcript of Optimal De-Centralized Smart Home-Charging: Potential Study · EVs status (2017) 1.1 million sold...
Optimal De-Centralized Smart Home-Charging: Potential Study
Mahmoud Shepero Reza Fachrizal Joakim Munkhammar
Built Environment Energy Systems Group (BEESG)Uppsala university
15 October 2018
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Outline
Current EV status
Charging algorithms
ResultsHouseholds’ LoadSmart chargingCapacity-fillingSummary of resultsFuture work
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EVs status
• (2017) 1.1 million sold EVs ⇒ 3.1 million EVs in the world.
• (2030) 1/3 of new car sales EVI 30@30.
• (2040) 1/3 of cars globally BNEF.
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Charging algorithms
Uncontrolled charging
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kW)
Postponed charging
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Capacity-filling
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Charging algorithms
Uncontrolled charging
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Postponed charging
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Capacity-filling
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Charging algorithms
Uncontrolled charging
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Postponed charging
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Capacity-filling
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Postponed charging vs Capacity-filling
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Postponed charging vs Capacity-filling
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Postponed charging vs Capacity-filling
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Postponed charging vs Capacity-filling
Postponed charging
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Capacity-filling
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Households’ Load
• Widen’s model [1] ⇒ 10 detachedhouses, no electric heating,2 inhabitants.
• Peak load = 6 kW.
0 2000 4000 6000Power (kW)
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Households’ Load
• Widen’s model [1] ⇒ 10 detachedhouses, no electric heating,2 inhabitants.
• Peak load = 6 kW.
0 2000 4000 6000Power (kW)
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Postponed charging
Number of days
0 4 5
0 3 3 5
0 1 1 1
0 0 0 0 8
0 0 0 0 0
0 0 0 0 0
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3.7 6.9 7.3 11 22Charging power (kW)
Fus
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kW)
Charging delay
00:00 03:38 03:59
00:00 00:32 00:50 00:32
00:00 00:01 00:02 00:21
00:00 00:00 00:00 00:00 00:03
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00:00 00:00 00:00 00:00 00:00
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3.7 6.9 7.3 11 22Charging power (kW)
Fus
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kW)
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Postponed charging
Number of days
0 4 5
0 3 3 5
0 1 1 1
0 0 0 0 8
0 0 0 0 0
0 0 0 0 0
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3.7 6.9 7.3 11 22Charging power (kW)
Fus
e si
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kW)
Charging delay
00:00 03:38 03:59
00:00 00:32 00:50 00:32
00:00 00:01 00:02 00:21
00:00 00:00 00:00 00:00 00:03
00:00 00:00 00:00 00:00 00:00
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3.7 6.9 7.3 11 22Charging power (kW)
Fus
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kW)
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Capacity-filling
Number of days
364 363 362
364 364 364 327
364 364 364 355
364 364 364 362 198
364 364 364 362 351
364 364 364 362 354
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3.7 6.9 7.3 11 22Charging power (kW)
Fus
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kW)
Charging haste
01:30 00:26 00:22
01:41 00:37 00:33 00:10
01:48 00:44 00:40 00:16
01:57 00:53 00:49 00:25 00:03
02:04 01:00 00:56 00:32 00:09
02:07 01:03 00:59 00:35 00:12
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3.7 6.9 7.3 11 22Charging power (kW)
Fus
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kW)
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Capacity-filling
Number of days
364 363 362
364 364 364 327
364 364 364 355
364 364 364 362 198
364 364 364 362 351
364 364 364 362 354
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3.7 6.9 7.3 11 22Charging power (kW)
Fus
e si
ze (
kW)
Charging haste
01:30 00:26 00:22
01:41 00:37 00:33 00:10
01:48 00:44 00:40 00:16
01:57 00:53 00:49 00:25 00:03
02:04 01:00 00:56 00:32 00:09
02:07 01:03 00:59 00:35 00:12
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3.7 6.9 7.3 11 22Charging power (kW)
Fus
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kW)
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Summary of results
• Postponed charging is rarely needed (only 8 days a year).
• Postponed charging causes at most 4 hours of charging delay.
• Capacity-filling charging shortens the charging time at least 200 days a year.
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Future work
• Controlled charging with unbalanced3-phase load.
• Impacts of the controlled chargingschemes on the aggregate load.
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References I
[1] Joakim Widen and Ewa Wackelgard. A high-resolution stochastic model ofdomestic activity patterns and electricity demand. Applied Energy, 87(6):1880–1892, 2010. doi: 10.1016/j.apenergy.2009.11.006.
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Residential arrivals on weekdays
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Residential arrivals on weekends
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