Reliability and Asset Management
Tony Villocino
Salt River Project
1600 N. Priest Drive
Tempe Arizona 85281
Abstract
The Salt River Project is an established electrical utility in Phoenix, Arizona. The GIS
Services group of the SRP developed and implemented a GIS for several work groups to
assess the condition and predict failure of various electrical system components. The
result was an integrated workflow process and GIS application called RAMS (Reliability
and Asset Management System).
Discussion will address developing and implementing GIS to address the following; labor
cost, capital resources, outage costs, costs of reducing risk, prioritizing customers,
prioritizing equipment replacement and scheduling inspections. RAMS is an evolving,
growing, integrated set of applications providing a spatial view of the existing and
planned work. RAMS facilitates the inspection of power system components such as
wood poles and overhead lines. Using non-destructive strength evaluation and infrared
technology in the field, inspection results are captured in the GIS. RAMS also provides
predictive analysis and prioritization of cable using several inter-related predictive
algorithms. RAMS interfaces with two work order systems, multiple GIS databases, and
utilizes an intranet web interface. All of these components together have created a detail
work-management strategy that has real world impacts of what gets inspected when, who
has already worked on what, and what equipment is going to be replaced before it fails.
Functional Overview
The basic requirement of Reliability Planning Analysis is to prioritize geographic areas
for preventive inspections based on a cost benefit model. Cost benefit can be determined
per circuit by the represented type of KW load (residential/commercial/critical circuits).
The circuit can then be queried for the specific geographic areas it crosses and the density
of load points of a type within those areas.
The query is executed through a GIS application. The application requires an extract of
customer data containing specifics about customer type and KW load. This customer
data is keyed to the Circuit database through the transformer 40-acre codes, producing
information about the customers and demand types for individual transformers/circuits.
The circuits can be queried for the geographic areas they fall upon and the load types
represented by each geographic area. A prioritization can occur for the geographic areas
based on the highest priority circuit occupying the area (Wood Pole and PM Line
analysis).
Figure 1
The query returns results based on the type of equipment analysis being executed (Wood
Pole, PM Line, and Cable Replacement). This is differentiated so that the facilities that
are interesting to the specific analysis type can influence prioritization of the geographic
areas.
