IEEE Electrification - June 2019 - 42

12 54.77 54.62 54.04 53.46 53.45 53.04 54.35 54.87 55.22 52.71 53.53 51.31 48.5 46.95 44.02 49.76 50.81 53.44 55.59 54.94 55.45 54.35 55.46 55.16

11 50.74 50.87 51.7 51.61 51.44 51.33 52.04 50.98 45.54 43.55 43.1 40.24 39.31 38.56 40.92 47.23 50.26 50.85 52.2 51.67 51.38 52.23 52.14 51.37

47.9 48.07 49.05 50.66 49.81 39.49 39.51 34.44 34.23 34.37 36.71 40.92 45.72 49.15 50.85 52.71 53.36 52.29 52.89 51.44 49.54
10 49.41 49.14 48.4

9 52.61 52.31 51.28 50.12 50.51 51.22 50.32 45.33 39.61 38.39 35.85 36.48 36.5 38.03 43.22 47.12 50.07 55.03 54.94 53.82 54.99 55.3 53.88 52.94

54.8 56.96 54.62 51.93 53.97 53.8 52.25
8 53.44 53.09 52.51 51.42 52.14 52.25 50.87 44.99 38.58 37.64 37.01 36.29 37.48 37.01 43.42 46.16 49.1

7 49.38 49.86 50.59 50.31 51.6 52.87 48.33 44.28 38.9 36.17 35.61 35.44 34.72 35.22 41.21 44.1 47.59 51.18 53.84 53.42 50.89 52.72 51.86 50.41

6 45.15 45.93 45.98 45.9 45.14 45.15 43.2 38.85 30.47 28.79 26.33 21.45 22.31 24.9 32.23 34.95 42.26 48.1 50.12 48.42 47.35 49.71 49.6 45.47

5 42.15 42.57 42.44 42.44 42.45 42.86 41.66 31.41 21.33 20.21 17.26 16.05 16.96 18.1 24.73 31.22 34.32 42.16 45.06 45.87 45.66 46.49 46.76 43.48

42.4 43.14 43.69 36.22 27.46 23.45 20.36 4.09 -2.32 11.41 24.31 32.02 37.81 44.13 46.73 46.54 46.47 46.56 46.41 43.83
4 42.35 42.91 42.97 42.7

3 48.43 47.91 47.61 47.63 47.41 47.87 49.1 49.01 37.5 33.93 30.38 20.97 19.35 27.16 28.61 34.7 44.12 47.98 48.98 49.5 49.65 49.49 48.85 48.13

2 51.67 52.02 52.01 51.55 51.6 51.83 53.87 54.15 52.1 43.31 39.58 39.03 39.1 39.95 37.07 40.5 49.67 50.9 53.08 53.4 52.29 51.04 52.86 51.5

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1 54.55 53.91 54.76 54.7 54.23 54.32 55.54 55.98 55.93 50.54 50.16 50.92 50.25 47.47 42.92 49.01 51.92 52.89 55.94 54.64 54.19 54.41 55.96 55.39

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Figure 2. The average hourly energy prices ($/MWh) in 2030 under
the base scenario.

42

I E E E E l e c t r i f i cati o n M agaz ine / J UN E 2019

workplace during work hours and at separate homes during other times. For this study, we modeled a group of five
vehicles, each having a 60-kWh battery and a maximum
charging and discharging power of 6.6 kW. We assumed
that each vehicle has access to a V2G-capable EVSE at
both home and work.
The tool can model several VGI use cases. To create a
baseline for determining the value of optimized EV dispatch, an "unmanaged" charging profile is generated.
Under an unmanaged charging strategy, whenever an EV
plugs in, it is charged immediately at maximum power
until a full state of charge (SOC) is reached. Dispatch can
then be conducted in either V1G mode or V2G mode so
that the incremental benefits of these technologies can be
determined. V1G and V2G dispatch can be optimized from
the perspective of customers (e.g., to maximize their bill
savings) or from the utility's perspective to minimize its
cost of supplying electricity, commonly known as the utility's avoided cost. The charging and discharging dispatch
can also be cooptimized with the sale of frequency-regulation ancillary service (AS) to the grid.
A common concern about V2G technology is that discharging the vehicle's battery will increase battery degradation, thus shortening its useful life for transportation.
To address these concerns, the optimization model can
penalize the discharge of energy from an EV's battery
to the grid and also penalize the SOC for being outside
of a specified range. For this study, we chose penalties
based on EV battery cycle life and cost of replacement and
penalized states of charge outside the range of 30 to 95%.

V2G Dispatch Flexibility Creates
Advantages Over V1G
Optimized dispatches of EV charging and discharging created with the Solar + Storage tool demonstrate why V2G is
a much more flexible resource than V1G. Figure 1 shows
example optimized dispatches under V1G and V2G modes
for a single vehicle plugged into the grid for 23 h on a Saturday, making one late evening trip at 9 p.m. The utility
avoided costs represent a typical early summer day in the
future California electric grid when solar overgeneration
causes negative midday energy market prices and loads
are paid for their consumption. As shown in Figure 1, discharging in the morning leaves the V2G vehicle with more
available battery capacity for charging during the period of
negative avoided cost than the V1G vehicle. The V2G vehicle can then discharge some energy from its fully charged
battery in the high-value evening hours, either before or
after taking a trip. By absorbing excess solar generation
through charging, the load of the V1G vehicle creates a
benefit for the utility of US$0.06 on this day. However,
because the V2G vehicle is able to charge far more energy
than the V1G vehicle at midday and then discharge to the
grid at high-value times, it creates a benefit of US$1.96 for
the utility. These values are absolute and not relative to
other charging profiles.
IEEE Electrification - June 2019

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