customer service point, providing visibility into grid operations that were historically unavailable. Some smart meters
support voltage profiles at several interval lengths for average, maximum and
minimum voltage readings in addition
to exceptions for high and low voltage occurrences. This voltage monitoring information can be used to identify
high or low voltage conditions, validate
customer complaints, support VVO/CVR
programs, and identify how meters are
connected to transformers and to which
phase the meter is connected.
Voltage bellwether meters can be
dynamically assigned to monitor distribution assets and feeder sections. It is
best for a utility to implement a voltage
configuration and collection strategy that
will allow the utility to achieve these
benefits with its existing meter and network infrastructure without impacting
more conventional billing operations.
Implementing a holistic voltage monitoring program can result in significant
benefits to a utility in several areas, including operational costs, energy efficiency,
system reliability, extended capital asset
life and increased customer satisfaction.
These drivers have always been important
to utilities; however, with the introduction
of distributed generation on the grid, utilities must now manage a more dynamic
two-way infrastructure with significant
load increases as electric vehicles and
other distributed generation resources
become more prevalent.
By providing distribution planners
and engineers with an awareness of
changing voltage conditions, utilities
can continue to provide the high quality
level of service expected by customers
patent-pending algorithm that determines meter-to-transformer association
from five-minute voltage data collected
over a seven to 30-day period. Applying
state-of-the-art machine learning techniques, meters are grouped by most likely transformer association and compared
to utility records for validation or correction or both. This algorithm correlates
voltage changes over time between individual meters and defines the meter
“affinity.” The higher the affinity the more
likely these meters are connected to the
same distribution transformer.
There are several benefits that result
from an accurate meter-to-transformer
model, including the ability to enable
asset management, outage management,
historic outage analysis and load balancing as well as improve the accuracy of
transformer load analysis programs.
Smart meters provide several out-age-related critical capabilities, including
real-time power monitoring and outage alarms, two-way communication for
power-on validation and acquisition of
historical outage data from each individual customer, with accuracy down to
the second. This data, combined with an
accurate connectivity model, allows the
utility to better understand the extent
of the outage and the associated restoration effort. This capability also allows
the utility to understand precisely where
momentary and sustained outages are
occurring in the system, providing them
with the focus to more effectively improve
their reliability efforts. These capabilities
can have significant improvements on a
utility’s overall reliability index ratings.
With the adoption of advanced meter-
ing infrastructure, utilities now have sec-
ondary voltage-sensing capabilities at each
techniques, Itron’s scientists have devel-
oped and patented algorithms to accu-
rately determine phase connectivity and
also identify which meters are connect-
ed to which distribution transformers.
These methods use interval voltage measurements as the basis of their analysis.
The benefits of having this information
includes energy balancing for loss evaluation and phase balancing. With energy
balancing, the total energy at the feeder
head is compared to aggregated measurements at all locations downstream on the
feeder. The difference is a measurement
of equipment losses, line losses and theft.
Phase balancing matches the load on
each phase of a three-phase distribution
circuit, which is critical to safe and efficient energy delivery.
CONNECTIVITY ANALYSIS AND
Soon after new service installation, the
utility may start with a fairly accurate
meter-to-transformer association. Over
time, intermittent unscheduled power
outages may require utilities to rewire
specific meters to different transformers.
Not all changes find their way into utility databases. As time progresses, actual
meter-to-transformer association tends
to drift from what is encoded in utility
records. In some cases, services may have
been installed many years ago prior to
the utility adopting a formal process that
tracks the meter-to-transformer association. Consequences of connectivity errors
are faulty transformer load management,
inaccurate outage locations and faulty
CAIDI and SAIDI calculations due to
mis-associated meters or missing transformers that may be shown in a GIS map,
but are not physically installed in the field.
Itron has developed a new