Electricity + Control August 2017

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4 Electricity + Control AUGUST 2017
In recent years there has been a great drive,
in utilities, to deploy Advanced Metering In-
frastructure (AMI) systems, commonly known
as smart meters [1]. They are called smart meters
in a sense that they not only measure electrical
power consumed by utility customers but they can
record events such as power outages, tampering
etc. They are fitted with communications modules
allowing them to transmit the measured data to
utility data centres via telecommunications net-
works, allowing utilities to receive meter data in
almost real time.
The initial driver to deploy AMI systems was to
ensure accurate collection of consumption data
from customer points, ensuring accurate billing
of electricity usage. This is a great improvement
to the previously used method, where utility per-
sonnel were sent to customer sites to collect
consumption data, introducing human error in the
recording process of the consumption data. With
AMI systems, utilities can introduce software sys-
tems which collect and analyse the received me-
ter data, and generate bills automatically and send
to customers for payment.
The deployment of AMI systems, introduc-
es value to utilities, by coming forth as a Smart
Grid enabler. This is initially realised by introducing
web and mobile applications where customers
can view their historical power consumption, and
see the impact of their usage on the grid. These
platforms can influence customers to change or
optimise their power consumption to reduce the
load on the grid. Utilities can unlock further the
potential of deployed AMI systems, by analysing
the collected data to get an understanding of the
performance of the distribution network infrastruc-
ture.This may include analysis of the power quality
delivered to customers and analysis of equipment
(transformer) loading at distribution level. In this
article we will focus on describing how data from
AMI systems can be used to analyse equipment
loading on the distribution network, predict po-
tential for failure, and help with preventive main-
tenance and right sizing of distribution network
components. This analysis will greatly help utilities
in that failures on the distribution network equip-
ment not only result in immediate outages for cus-
tomers and large costs to utilities, but can present
a serious safety hazard to living creatures in the
vicinity and damage to property.
Overview of AMI enabling Smart Grid
Figure 1 is an overview of how AMI systems are
deployed by utilities, integrating them to Meter
Data Management (MDM) Systems and facilitat-
ing utilities to get more value from the systems by
introducing Analytics in the architecture. From the
diagram we can see that an AMI system is made
up of the Meter (Industrial, Commercial and Resi-
dential), the telecommunications infrastructure to
transmit the meter data and events, and the Head
End System (HES) for collection of the meter data
and storage in databases. The MDM system per-
forms synchronisations functions with Customer
Information Systems (CIS), to create a relationship
between AMI systems data and utility custom-
er information during installation. Thereafter the
MDM performs the processing of data received
Using AMI Data to
Analyse the Safety
of the Distribution
Network
Desmond Mabilo, Siemens
AMI systems can offer much more than the ability to accurately
produce a bill to customers on their electricity consumption.
CONTROL SYSTEMS + AUTOMATION
abbreviations
AMI – Advanced Metering
Infrastructure
CIS – Customer Information
Systems
ELM – Equipment (Transformer)
Load Management
HES – Head End System
MDM – Meter Data Management
SDP – Service Delivery Point
VEE – Validation, Estimation,
Editing