Electricity + Control August 2017

CONTROL SYSTEMS + AUTOMATION

Substation Transformer

Substation Meter

Virtual Meter

180 160 140 120 100

Take Note!

Transformer Rating (kVA) Hourly Max Load (kVA)

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.

1

80 60 40 20 0 Load kVA

2

Distribution Transformer

0 2 4 6 8 10 12 14 16 18 20 22 24 Time (Hour)

SDP Meters

3

Figure 2: Virtual meter implementations on distribution transformers.

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.

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.

Load (kVA) 60 50 40 30 20 10 0

100 90 80 70 60 50 40 30 20 10 0

Meter_11

Meter_10

Meter_01

Meter_09

Meter_08

Meter_07

Meter_06

Meter_05

Meter_04

Meter_03

Meter_02

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

2016-06-01

2016-06-09

2016-06-08

2016-06-07

2016-06-06

2016-06-05

2016-06-04

2016-06-03

2016-06-02

2016-05-31

2016-05-30

2016-05-29

Date (YYYY-MM-DD)

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.

6 Electricity + Control

AUGUST 2017