IEEE Electrification - September 2020 - 99

the considered microgrid whose components, i.e., the
electrical network and the DERs and loads connected to
it, are simulated using the Typhoon HIL real-time emulator. For an islanded ac microgrid with inverter-interfaced
DERs and loads, AFE is the weighted average of the active
power injections from the DERs and the withdrawal from
the loads. Since the cRIO device is a central computing
device for the microgrid, it has access to the DER injections and withdrawals from the microgrid assets. It can
use this information to compute AFE, and in turn, use
the PI controllers for each DER to calculate the new operating points.
The setup for testing the distributed control scheme
comprises the same microgrid modeled in the Typhoon
HIL device, but instead of using the NI cRIO device for
centralized monitoring and control, we use six Arduinobased control nodes for the DERs and loads; see Figure 8
for details. Each DER and load control node uses the
local information (i.e., active power injection or withdrawal) as inputs to the distributed algorithms realized
to collectively compute the AFE. After that, the DER control nodes use the implemented PI controls to calculate
the new operating points to always ensure the secondary frequency control is fulfilled.

both schemes are illustrated in Figure 9. At the 30-s time
mark, the frequency falls below 60 Hz due to load increase,
and both control schemes bring it back to the nominal
value, as shown in Figure 9. At the 60-s time mark, after the
loss of a DER, both schemes ﬁx the frequency error with
the remaining two DERs compensating for the loss of generation. Finally, at the 120-s time mark, both schemes ﬁx
the frequency error post the loss of generation. The results
in Figure 9 indicate that the response time of the centralized scheme to eliminate the frequency error due to any
perturbations is shorter than that of the distributed
scheme. This is not surprising since the centralized controller has direct access to information on the set points
and active power injections of the DERs and loads, and
thus, it can compute the AFE and eliminate the frequency
error as soon as there is a perturbation. The increased time
in the distributed scheme is due to the computational time
incurred by the distributed algorithm used; please refer to
the final entry (Nigam et. al) in the "For Further Reading"
section for more details.

Resilience
For testing the resilience of the centralized control scheme
to a failure of the control node, we unplugged the cRIO

Comparison Results
For the six-bus ac-islanded micro--
grid under consideration, the total
power demanded by the loads is 3.3
per unit (p.u.) with individual loadings as 1.15, 1.25, and 0.9 p.u.,
respectively. Prior to the start of the
test, active power set points for the
DERs are 0.85, 1.5, and 0.95 p.u.,
respectively, making the total power
injection by the DERs to be 3.3 p.u.
Under these operating points, the
system-wide frequency is nominal
and at 60 Hz. We run a 150-s-long
C-HIL real-time simulation with the
following DER/load power profile:
xx
At the 30-s time mark, the load
at bus 6 changes to 1.4 p.u.
from 0.9 p.u.
xx
At the 60-s time mark, the
microgrid loses a DER at bus 1
from the network.
xx
At the 120-s time mark, the
microgrid loses load at bus 6.

Response Time
We recorded the frequency re--
sponse under both a centralized as
well as a distributed secondary frequency control scheme. The results
for the frequency response under

Bus Frequency (Hz)
60.2
60.1
60
60

59.9

59.8

59.8
59.5

59.7
20

60.5

80
Time (s)

100

120

Bus 1
Bus 2
Bus 3
Bus 4
Bus 5
Bus 6
140

(a)
Bus Frequency (Hz)

60.15
60.1
60.05

59.92
59.915
59.91
59.905
59.99 60

Bus 1
Bus 2
Bus 3
Bus 4
Bus 5
Bus 6

60
59.96
59.92
60

60.01

60
59.95
59.9
20

80
Time (s)

100

120

140

(b)
Figure 9. The frequency response for the (a) centralized and (b) distributed control scheme.

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IEEE Electrification - September 2020

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