Electric Energy T&D - Index

Electric Energy T&D - EE Magazine March / April - Index

Data Refresh: Breathing New Life
into a GIS Database
Geographic Information Systems (GIS), a
component of what is known as “spatial
technology”, has origins in simpler systems
such as Computer Aided Design (CAD) and
Automated Mapping/Facility Management
(AM/FM) systems. However, in order to
fully reap the benefits of spatial technology,
many utilities and other organizations find
it necessary to augment and increase the
quality of their existing data; in other words,
to refresh their GIS data.
A History of Spatial Data
Acquisition
In its infancy, from 1950 to the early 1970’s,
spatial technology addressed cartographic
applications such as mapping and charting
of land, water and demographic data. By
the late 1970’s and early 1980’s, spatial
technology had begun to mature, and
utility companies were amongst the first
organizations to adopt CAD or AM/FM. At the
time, these systems were at the leading, and
often bleeding, edge in the utility industry.
Primary applications included mapping,
facility inventory, map-book production and
sometimes construction print production. In
these early systems, spatial technology was
usually a departmental solution, addressing
only a limited set of needs. Spatial
technology matured in the late 1980’s and
early 1990’s, fueled by the proliferation of
personal computers, client/server technology
and scalable architecture. The late 1990’s
saw the growth of more sophisticated spatial
applications, and the technology became
known as “GIS” to emphasize the geographic
focus, and saw the promotion of increased
enterprise use.
Data Refresh: Breathing New
Life into a GIS Database
By Ruth Craven and Dr. Will Shepard,
Enspiria Solutions
Utilities that adopted spatial technology in
the early years were challenged by the data
resources they had – or didn’t have – to
populate the system:
• Existing maps: How accurate were the
maps? Were the maps maintained? What
was the map coverage?
• facilities data sources: What data was
available? Was it available digitally? Was
the data consistent across the enterprise?
How complete was the available data?
• land data: Was commercial land data
available?
AM/FM systems were usually populated by
digitizing source paper maps, performing
field inventories and incorporating other
digital data sources, such as transformer
databases. Not unlike today, the quality
of the resulting AM/FM data was directly
proportional to the quality and completeness
of the source data or field inventory, the
ability to associate various facilities data
and the scope of the data conversion. For
example, attribution from source maps often
could not be related to nearby facilities and
hence was converted as annotation, instead
of attribution. In addition, connectivity was
not a priority, since it was not necessary for
map production.
Given that the value of spatial data for
applications was often not understood during
initial data conversions, current GIS data
holdings often do not support advanced use
of the data. If the scope of the facilities
attribute population encompassed only what
was needed to support mapping and facilities
management, then the data may not have
included all of the facilities, attribution and
50 I March-April 2008 Issue
connectivity required for advanced applications
such as outage management, asset investment,
gas distribution integrity, advanced metering,
dashboard applications or integration with an
enterprise asset repository.
Refreshing GIS Data
Today, GIS is a mainstream enterprise
system that is recognized as an enabling
technology for other operational and energy
delivery systems. Utilities recognize the
enterprise value of spatial data and are eager
for advanced applications and integrations.
However, lacking data or poor quality from
initial conversion efforts will hamper moving
forward with these initiatives. Successful
implementation of these initiatives will
require refreshing GIS data through additional
collection and reconciliation of existing
data problems. Advanced applications and
integrations, with their supplemental data
requirements, include:
• GIS often owns the relationship between
a customer’s premise and the feeding
transformer. Applications such as outage
management systems (OMS), transformer
load management (TLM), and network
analysis require the premise-transformer
relationship, circuit connectivity and
integrated customer data.
• Applications receiving network/circuit
connectivity from GIS require high data
quality. For example, OMS requires that
the nominal state of the network accurately
reflects the field conditions. If it doesn’t,
outage projections and statistics will not
be useful.