Electricity + Control August 2017

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6 Electricity + Control AUGUST 2017
CONTROL SYSTEMS + AUTOMATION
AMI Systems are com-
monly known as smart
meters.
AMI Systems can be uti-
lised as drivers of smart
grid technologies.
AMI Systems’ data can
be used as inputs to
Analytics Smart Grid
Applications which can
trigger programs that
prevent equipment fail-
ure.
Take Note!
1
2
3
Figure 2: Virtual meter implementations on distribution
transformers.
Data Analysis
Once the MDM system has processed meter
data received from AMI systems, this can be fur-
ther made useful by Analytics Smart Grid Applica-
tions. In this case the ELM Analytics application
will perform the aggregation and other compu-
tation of the load at the distribution transformer,
giving a clear analysis of the status of the distribu-
tion transformers in the distribution network. The
analysis will allow utilities to react quickly should
anomalies be observed; an in-depth understand-
ing of the distribution grid can be acquired, allow-
ing optimal distribution grid planning.
Below are examples of how analytics functions
can be implemented and used to present the sta-
tus of the distribution network equipment. Firstly
from Figure 3 we have a view of the number of
overloaded transformers in the utility’s distribution
grid on daily basis.
Figure 3: Number of overloaded equipment (transform-
ers) on the distribution network.
From Figure 4 we can further dive into each trans-
former, to see how it is overloaded on daily basis,
which hours of the day contribute to the major
overloading of the transformer. From here we can
see that the transformer is overloaded (exceeding
the rated load demand) for approximately 20 hours
in a day.
Figure 4: Daily load curve on the distribution transformer.
We can look into the different loads connected to
the overloaded transformer, to understand why
the transformer is overloaded, how the customers
are connected and how they are utilising power.
Is re-allocation of customers needed or not. From
Figure 5 we can see that the customer with the
meter ‘Meter_01’ consumes almost five times the
power compared to other customers in its group.
This could be the reason the transformer is over-
loaded due to customer consuming much more
than it is planned for.
Figure 5: Daily Max Load Demand by customers con-
nected to a transformer.
The above is just basic analysis of what AMI data
can offer to create Smart Grid Applications that
can be used to optimise the distribution Grid, by
allowing its infrastructure to operate within safe
boundaries.
Conclusion
It is very clear that AMI systems can offer much
more than the ability to accurately produce a bill
to customers on their electricity consumption.
AMI systems can be utilised as drivers of smart
grid technologies. In this article we have seen how
AMI system data can be used as inputs to Analyt-
ics Smart Grid Applications, which analyse the dis-
tribution network equipment such as transform-
ers, detecting anomalies which may result into
SDP
Meters
Distribution
Transformer
Virtual
Meter
Substation
Meter
Substation
Transformer
Date (YYYY-MM-DD)
2016-05-292016-05-302016-05-312016-06-012016-06-022016-06-032016-06-042016-06-052016-06-062016-06-072016-06-082016-06-09
100
90
80
70
60
50
40
30
20
10
0
Transformer
Rating (kVA)
Hourly Max
Load (kVA)
0 2 4 6 8 10 12 14 16 18 20 22 24
Time (Hour)
180
160
140
120
100
80
60
40
20
0
Load kVA
Meter_01Meter_02Meter_03Meter_04Meter_05Meter_06Meter_07Meter_08Meter_09Meter_10Meter_11
Load (kVA)
60
50
40
30
20
10
0