IEEE Power & Energy Magazine - January/February 2016 - 46

The existence of a standard information model
such as the CIM significantly reduces the
information exchange challenge.
patterns and gain insights into how the utility services are
being used. This new information can provide economic
value, but, more importantly, it can provide support for critical decisions that could increase the reliability of the electric
grid. while smart metering was initially looked at to provide
the automated collection of readings, it was also hoped that
it would provide visibility into the energy consumption and
events on a much more granular scale of time.
There are several other aspects of big data, beside its sheer
bulk, that push traditional enterprise information technology
beyond its limits, such that the utility's own systems cannot
support the new business semantics and processes associated with leveraging it. The utility is therefore impelled to
invest in new technology and/or new business partnerships.
The foremost of these aspects is latency, or the interval of
time between the initial capture of a datum and the initiation
or completion of a business process that uses it. The reduction
in the latency of meter readings from the order of weeks (up
to 30 days) to the order of hours (24, six, or four hours)-and
eventually to the order of minutes-is even more disruptive
for utility business processes than the increase in volume. if

consumers are told that a key benefit of smart metering is that
more granular data will enable them to optimize their patterns of energy consumption, they will naturally wish to gain
access to that information in a timely manner.
another problematic aspect of big data is the pervasive
need for data from one source to be enriched with data from
other sources. meter readings, per se, are only a point of
entry into the hugely expanded information landscape that
comes with the adoption of smart metering, as set forth
earlier. extracting the hidden value from meter data, for
business or consumer decision support, involves enriching
it with geographic, demographic, meteorological, and economic data from a range of sources both inside and outside
the utility, and the resulting enriched data may be destined
for consumption outside the utility as well, so that boundaries of ownership may be crossed either on the source side, or
on the consumption side, or both.
while any data describing energy consumption is, in principle, the property of the entity that consumed the energy,
there are technological and legal reasons why the utility
must act as custodian of the data. The utility's infrastructure




created
EndDeviceEvents
1
2009-11-04T18:52:50.001-05:00
Metering System




3dc53ee5-777e-50b4-8699-a1c224f45f3d
2009-11-04T18:52:50.001-05:00
Power off alarrm
1

 7a681339-facd-46be-b13e-3a8d70e30d50






figure 4. An example message encoded using IEC 61968-9 and IEC 61968-100 to convey a meter event.
46

ieee power & energy magazine

january/february 2016



Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - January/February 2016

IEEE Power & Energy Magazine - January/February 2016 - Cover1
IEEE Power & Energy Magazine - January/February 2016 - Cover2
IEEE Power & Energy Magazine - January/February 2016 - 1
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IEEE Power & Energy Magazine - January/February 2016 - Cover3
IEEE Power & Energy Magazine - January/February 2016 - Cover4
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