IEEE Power & Energy Magazine - July/August 2021 - 25

The results of project Electric Nation prove the ability
of smart charging to harness the flexibility available
from EV charg ing in the context of a trial.
Participant Attitudes
to Providing Flexibility
Was Participant Satisfaction Affected by
Experiencing Demand Management?
Throughout the trial period, the Electric Nation participants
completed surveys regarding their trial experience
and their attitudes toward smart charging. The participants
were asked a consistent set of questions about their attitudes
toward smart charging at each stage, allowing the results to
be linked to their experience in each trial. Figure 9 shows the
scores when the participants were asked to rate their satisfaction
with their charging arrangements, on a scale from
1 to 10 (10 = completely satisfied).
In both groups, satisfaction remained high at all stages
of the trial, with no statistically significant changes occurring.
The data were also analyzed to determine whether
the participants' experience in demand management
affected the satisfaction scores they gave. If the participants
whose charging was managed more frequently were
less satisfied, then this could indicate a lack of acceptability
for smart charging. In both of the trial cohorts,
this was not the case. Experiencing more demand management
(reduced charging speed) did not lead to lower
scores for the satisfaction or acceptability of their charging
arrangements.
Did the Participants Want to Have Control
Over Demand Management?
During trial 1 (see Table 1) the participants were not
informed when their charging was being managed and did
not have a way to override it or opt out. As shown in Figure 9,
despite this lack of control, participant satisfaction remained
high. Trial 2 introduced apps that gave participants a method
to influence how likely it was that their charging would be
managed. The systems used by GreenFlux and CrowdCharge
differed in the following ways:
✔ CrowdCharge: The users told the app how much
charge their vehicle currently had and how much they
needed for the next day (via journey plans). The system
would then prioritize those users whose journey
plans meant their charging could not be slowed down.
✔ GreenFlux: The participants had access to an app that
showed them in real time whether their charging was
being managed and allowed them to request " high priority "
to override management for their current charging
session.
july/august 2021
These differing approaches allow for comparisons to be
made of the level of interaction with the different systems.
Some key statistics from trial 2 are given as follows:
✔ CrowdCharge:
* During trial 2, 55% of those invited to sign up for an
app account did so.
* The users were able to enter three types of information:
regular journeys (a commute on certain
days of the week), one-off journeys, and state of
charge. During trial 2, 65% of account holders entered
at least one piece of data. Journey plans consisted
of mileage and the time of departure. The
state of charge was requested each time the app
was launched as without this information it is not
possible to know how much energy was required
for the next journey. Table 6 summarizes the data
entry frequencies.
The data entry frequencies were very low overall.
The state of charge should have been entered
81% 81% 80% 82%
85% 82% 80% 84%
14% 15% 16% 12%
5%
4% 4%
6%
12% 15% 14%
3% 3% 6%
2%
14%
CrowdCharge
GreenFlux
1-4
5-7
8-10
figure 9. The users' level of satisfaction with the charging
arrangements during each trial stage (10 = " Completely
Satisfied " ).
ieee power & energy magazine
25
Charge at Will
Trial 1
Trial 2
Trial 3
Charge at Will
Trial 1
Trial 2
Trial 3
IEEE Power & Energy Magazine - July/August 2021

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