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A Time and Space Framework for Overhead Grid Maintenance Optimisation
Figure 2: Database Schema
detected by thermography are monitored so that evolution timelinesModularity
The tools should follow the modular structure of the database so that can be projected and the optimal time and scope of remedial actions
every function or set of functions can be changed without modifying determined. Post-maintenance audits and fault reports benchmark the
related data. timelines against reality, and remaining value/life estimates are refined
as a consequence.
Quantitative, Probabilistic Outputs
Although many of the available inputs and desired outputs are tacit or Difference Detection (Inspection, one o’clock;
qualitative, an effort should be made to express all of these in Condition, four o’clock; Risk, five o’clock)
numerical forms, using stochastic variables where appropriate, so that Let us assume a given issue has been detected and no remedial action
different modules can be compared and merged or grafted onto occurred. If the next inspection fails to detect the issue, this difference
different sections of the grid model. opens two lines of reasoning: either inspectors failed to use the best
Independence
The functions or procedures associated with each tool should be kept
Given the wide span of issues
autonomous of the underlying data to the maximum possible extent.
This allows competitive tool development and benchmarking and
found on overhead lines, it is
incremental innovation on the tools. Independence also promotes
important to formalise a common
better and more thorough tool specifications.
set of features all tools should
Traceability and Benchmarking share to keep them consistent.
It should be possible to ‘trace back’ every result and every operation to
each method used to benchmark results, correct errors, analyse the
sensitivity of the tools to parameters or data variations and, ultimately, methods, thus inspection should be audited and enhanced, or some
refine methods. missing element concealed or destroyed the issue – the pattern
matching analysis should detect such candidates, and risk assessment
The most innovative tools being developed focus on the tasks depicted will consider their influence. In either reasoning, it is useful for inspectors
at four to seven and 12 o’clock in Figure 1. Below we briefly outline in the field to have access to asset status to ensure known issues are not
some of them to illustrate the practical aspects of the framework. missed.
4
If maintenance has occurred, inspection acts as an ad hoc
audit: missing issues validate maintenance, while resilient issues denote
Pattern Matching (Condition, four o’clock) underlying causes that were not tackled by remedial actions.
Once the time and space database contains every issue found with links
to asset management and maintenance audits, it is possible to search Condition-based Risk Estimation
for patterns in the whole set of issues recorded. Matches in different (Advance from four’clock to five o’clock)
fields (e.g. manufacturer, time of day, pollution, line load) can then be Most companies are seasoned in condition estimation of all their assets.
detected by data crunching, highlighting common factors that were However, estimating the risk associated with each condition issue is a
hitherto unnoticed. rarer task, sometimes performed on after-fault diagnosis or laboratory
trials performed in samples of the equipments. Depending on the issues,
Timeline (Condition, four o’clock; Risk, five o’clock; it may involve the quantification of tacit knowledge of linemen,
Remaining Value/Life, 10 o’clock) environment modelling, weather statistics, etc. Extending this knowledge
Some issues progress over time and are noticed long before remedial to a whole grid involves wrapping each asset subject to each sort of fault
action is taken. For instance, vegetation growth and mechanical faults with a model of the environment that is as rich and detailed as possible.
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