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ransmission & Distribution
A Time and Space Framework for Overhead Grid Maintenance Optimisation
a report by
Francisco Azevedo
1 2
and João Gomes-Mota
1. CENTRIA, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa; 2. Albatroz Engineering
This article introduces a framework for the optimisation of high-voltage aggregates data from all information systems to compute the most
grid maintenance combining data from projects, asset management, complex models. The first step is to estimate the effects of single and
inspections, remedial actions and audits. This framework is based on combined issues in a single OHL; the second step is to compute the
geo-referenced and time-changing databases and probabilistic models aggregated risk across the grid, taking all potential risks into account.
for asset condition and risk management. All solutions found for this task involve past empirical statistics or
educated heuristics.
Motivation
Electrical grid operators have been struggling in recent years to deploy The prioritisation of maintenance (seven o’clock) is based on
new lines to meet demands for more energy and a higher quality of criticality reports, cost of maintenance and distance between
service. Regardless of their success in that endeavour, every grid operator neighbouring issues computed from GIS. Some practical approaches
is now asked to push the use of existing lines up to the limits of safety. are commonly found, but a rich framework allows optimal solutions
to the multivariable ‘travelling salesman problem’. Field maintenance
Grid maintenance is a cycle of processes that keeps the electrical grid is the next, universal step (eight o’clock); however, enhancing it with
running, including inspection, quality and condition audits and geo-referenced data increases process efficiency and reporting. The
remedial actions. The proposed framework to optimise this cycle audit of the maintenance action (nine o’clock) is sometimes
features an architecture and a tool set to aggregate data and methods simultaneous with maintenance, depending on local practices and
from different sources into a consistent model for grid maintenance. the nature of the problems repaired. Returning to the office, asset
Figure 1 shows one model of the cycle with 12 main tasks, organised managers conclude their role by updating the grid condition after
as a clock dial, where the green background represents field tasks and maintenance on their information systems as well as on GIS (10
the pink background represents office tasks. o’clock) and their net asset value and remaining lifetime. This task is
homologous to the condition assessment at four o’clock. Half of the
Entering the cycle at one o’clock, there is the overhead line (OHL) cycle (from five to 10 o’clock) is dedicated to the optimisation of
inspection. Asset management data are used to highlight previous remedies (maintenance), while the other half is dedicated to the
known issues and features of each element that are relevant for optimisation of diagnostics (inspection).
inspection, while geographical information systems (GIS) help
inspectors find the right lines to inspect and plan optimal routes. Finally, it is necessary to update the grid topology as new lines enter
service and others are uprated (11 o’clock). Defining an optimal route
At two o’clock, there is data recording with space and time stamps, and and scheduling the next round of inspections is the last task (12
the option of realtime problem detection. The latter is used to help o’clock). The information infrastructure supporting this cycle involves
inspectors optimise the procedures according to the perceived condition other departments (not shown), summarised by the thick pink arrow
of the line, triggering a thorough review of any candidate issue.
1
uniting GIS and asset management.
Moreover, realtime problem detection allows critical issues to be
reported just after the inspection (three o’clock), which is decisive for Architecture
contingency operations. Our architecture consists of a server with connections to GIS and asset
management systems running modular applications, with access to
Back at the office, experts perform a detailed analysis (four o’clock), relational databases implemented over PostgreSQL and with http-
comparing faulty elements with similar ones from asset data and third- based communication.
party sources to estimate the current condition. The next step (five
o’clock) is quite innovative and not yet implemented in many utilities. Inspection reports, as well as tower co-ordinates or characteristics of
It involves assessing the risk associated with each issue as a function of the electrical lines, may thus be provided to external authorised users,
the degree of non-compliance. Since risk encompasses many aspects such as service providers. It is also possible to validate reports and
(performance, reputation, safety, sales, etc.), for each type of issue upload new ones.
there is a function of risk. A human-expert-based approach, termed
condition-based risk management,
2
was introduced for mechanical and There should be two databases with information supporting the
wear issues by EA Technology, while the authors favour an automatic desired applications and possible future ones: a database containing
approach to risk vegetation management.
3
the electrical grid topology, with all its relevant components and
features,and a ‘lower-level’ database containing the raw data produced
Converting risk into probability of failure and estimating the by line inspections, such as vegetation management, equipment faults,
consequences of failure is the most novel task (six o’clock). This stage navigation systems data, and so on.
© TOUCH BRIEFINGS 2010
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