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operational expenditure reflected in their bills, but those bills rarely get lower in the wake of disaster – repairs must be paid for, and FEMA’s funds are running low.
Mind over muscle
A Herculean task requires Herculean muscle – more inspection teams, more miles, more money. That, or it requires a more intelligent approach.
That starts with a more accurate base of information. Those outdated and incomplete maps of assets must be brought up to date and made more useful. Ask any lineman on the job and they’ll tell you which circuits don’t just need the initial work, but rather, orienteering and investigating just to find out where to do the work. In 2023, that means using sensor- equipped helicopters, trucks or fixed wing aircraft to perform data collection missions which will produce accurate and extensive 3D models of the scope of project, including its surroundings, such as vegetation and housing. At a glance, just by having this accurate information, resources can be saved by no longer having crews deployed to the wrong location, or unprepared for the assets they will find on site.
But, much, much more can be done. This virtual environment, built for the purpose of storing and managing the geo-spatial content which goes into building a living digital twin (LDT), can be analysed by human operators backed up by AI algorithms to identify hotspots for likely asset damage or vegetation encroachment. Rolling inspection regimes can then be more targeted, and more intelligently prioritise efforts to minimise both cost and risk.
Above: Vegetation encroachment analysis. Trained AI/ML models can identify asset and vegetation maintenance needs based on changes over time
We can then go a step further: using the LDT, automated and piloted drones can then fly inspection missions to update the LDT data. Trained AI/ML models can then identify asset and vegetation maintenance needs based on changes over time. Done this way, utilities can inspect many more miles per day at a fraction of the cost when compared with dispatching crews to walk the line, while increasing their ability to catch risks early. They are also less likely to find themselves paying overtime hours. Equipped in this way, utilities can save on the significant operating costs associated with asset and vegetation inspection and management. These savings alone will likely recoup the investment made. Moreover, the AI-powered LDT can be integrated with other departments
and data streams to derive even more value in future.
Most importantly, the utility will be better able to reduce wildfire risk caused by suboptimal asset and vegetation inspection and maintenance. Not only will this reduce risk to life and property, but it will also reduce business risk over time, leaving utilities less open to regulatory fines or hits to the share price. And when wildfires do happen, as the risk can never be reduced to zero, utilities will have a more accurate view of their network to plan immediate response and repairs.
Ultimately, wildfire risk is business risk, and utilities must do whatever they can to mitigate it. Shareholders, ratepayers and – crucially – the communities affected deserve nothing less.
Above: Vegetation management. The AI-powered living digital twin can be integrated with other departments and data streams to derive even more value in future
24 | November/December 2023|
www.modernpowersystems.com
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