Reliability and Asset Management
Direct Buried Cable Replacement Prioritization
Much of the electric system that serves SRP’s more than 730,000 customers is buried
underground. SRP has increased funding to its underground cable replacement program,
allotting $100 million over six years to replace damaged cable.
Underground electric systems offer many advantages because they eliminate power poles
and overhead electric lines in residential areas and therefore they are popular with
customers. However, one drawback has always been in the area of repair and
replacement. Over time, underground cable will fail for a variety of reasons: moisture,
electric load, over-voltage, and physical damage. Until recently, to solve most residential
cable problems it required excavation or trenching. This procedure is costly, disrupts
landscaping and pavement, and is not popular with customers.
Consequently, SRP has been concentrating on fixing the cable installed in the 70’s, and in
selected areas, has an alternative to trenching that involves a process called cable cure.
In the SRP’s service territory, direct buried cable installed in the 1970’s is failing sooner
than anticipated. Annual budget for replacing direct buried cable with cable in conduit
does not provide for all cable to be replaced before it fails. Therefore, it was necessary to
determine where the utility will get the most when rationing which cable to replace?
It was determined that in order to provide the best return in terms of reliability, the GIS
would calculate the predictive customer interruption cost for all direct buried primary
conductors in the electrical distribution network. The prioritization of cable replacement
activity is based on outage cost, failure rate, probability of failure and the return on
investment. Extensive research performed by the line maintenance-engineering group of
the SRP determined the constructs of these predictive algorithms. ( J. T. Crozier, Power
Quality and Reliability Index based on Customer Interruption Costs. IEEE Power
Engineering Review, April 1999. )
Menu driven tools developed in the GIS application allow the end user to pre-process the
values generated by the predictive algorithms. These values are assigned to a new object,
which shadows the object of a “primary conductor”. The primary conductor is
represented spatially on screen as a conductor route. The end user then has a reporting
tool which allows them to query these results and sort the values as they determine what
is appropriate to their analysis.
Work order diriven work flow processes.
Once predicative or preventive prioritization has been performed it is time to put the GIS
to work. Using menu driven interfaces the GIS technician, interfaces with a work order
system and creates a work order. This “inspection” work order is homogenous to other
types of work orders, except its “facility” is the map quarter section itself. The GIS then
spatially determines all the candidate equipment that is physically within that quarter
section. The GIS creates a relationship between the work order and all equipment. The
GIS then identifies all other open work orders in the quarter section allowing the
discretion of the GIS technician to pull equipment from the inspection punch list. This
coordination of workflow between GIS and work order eliminates the duplication of
inspection and other facilities related activities. For example, an inspection does not have
to take place on a piece of equipment that is schedule to be replaced. The GIS then
automates a mapping process to produce a large-scale printed map for the inspectors to
use in the field. The inspector uses this map as he performs his work in the field.
The results of the field inspections (e.g. problems found or not found, type of problem,
suggested remedy) are input to the GIS in one or two ways depending on the type of
inspection being carried out. For instance, inspection data is recorded on a hand-held
device when contract personnel complete a wood pole examination. Data must be
uploaded to the GIS via a CSV dump from this device. Whereas, for an infrared
inspection work order, inspectors mark field findings on a map product. Data is then
entered into the GIS by a custom Web application. Other users of the system may query
the data for ‘exceptions’, i.e. inspections where problems were found and some action
needs to be taken. These inspections may then be related to one or more maintenance
work orders. The exceptions are the by-product of an automated validation process that
looks for completeness of data, duplication of data, and mismatched data (data for
facilities not related to the work order). As a by-product to these activities, paper maps
and field verification process allows a feedback mechanism for GIS data integrity to be
checked.
The inspector finally uses a web based tool for entering the inspection results back into
the GIS, at which time the GIS technician uses these results to create additional
equipment based work orders. This process identifies the problems with equipment in the
field, checks the integrity of the GIS data and put the work orders in place the problems
fixed. The inspection results also captures activities that may have been performed on
the spot by the inspector to fix a problem. The inspector will submit a redlined version of
the paper map to mapping technician to correct inside the GIS.
In conclusion, integrated GIS with work order connectivity has been deemed a success
with the working groups at Salt River Project.
