If not in California, then in Oregon; if not in Louisiana, then in Hawaii. Each year, the US is subject to a fresh wave of devastating wildfires with little respite. While responsibility for wildfire prevention and protection rests with a wide range of stakeholders, utilities are near top of the list. History has taught us hard lessons about how powerline infrastructure can spark or contribute to a blaze.
Make no mistake: utilities take these risks very seriously. However, given the threat to life and property, it is imperative that they continue to look for ways to improve preparedness and reduce risk. If they don’t, not only are people and communities at risk, but the utilities themselves may be imperiled – shares in Hawaiian Electric Industries fell 40% to their lowest level in more than a decade in the wake of recent fires.
The good news is that there are powerful AI-powered technologies that can improve asset maintenance, vegetation management and reduce wildfire risk while also delivering commercial benefits simultaneously today. The bad news is that utilities may not have the luxury of a ‘calm’ period to focus on the future. Any improvements must be made in parallel with responding to current threats.
A Herculean Task
First, in the context of wildfires, what exactly are the responsibilities of utilities? We know that downed powerlines have been ignition sources for previous fires when they come into contact with, for example, dry vegetation. That critical moment has two sides to the equation: the asset and the surrounding environment. Utilities have responsibilities in regard to both.
In terms of the assets themselves, utilities are responsible for ensuring they are fit for purpose and well maintained. A split wooden utility pole is more likely to come down in high winds; a pole-mounted transformer that has worked loose from its fixings could fall.
In terms of the surrounding environment, utilities spend vast resources on vegetation management – cutting back encroaching foliage that could pose an ignition risk if it comes into contact with the line, or that could damage assets if downed in high winds. For context, this job has never been easy, but today it is more difficult than ever. Scientists have calculated that 90% of Hawaii is getting less rainfall than it did a century ago, creating an environment that is inherently riskier for utilities. Climate change and changing weather patterns make what was already a difficult task into a much more complex one.
What does this mean? In practice, it means that utilities must dispatch teams to manually inspect their assets for signs of wear and weakness. If they find issues that must be rectified, they will then report back, and a workorder will be issued for a repair team to go out and fix the issue based on urgency and severity.
In parallel, if there are concerns over vegetation encroachment, an arborist team will be sent out to inspect, then report back with a quote to cut back to specifications. That initial pre-inspection can cost as much as $800 per mile, not even factoring in the cost for the actual work order.
So, that is two sets of specialist teams sent to perform manual inspections on the assets themselves and the vegetation that surrounds them; followed by separate follow-ups to rectify any issues identified.
That is a lot of work, and a lot of expense. And that’s not all – this is compounded by the fact that utility maps of their assets are frequently wildly inaccurate. We have seen areas where utilities have underestimated the number of poles they have in an area, and have mapped their locations dozens, if not hundreds of yards out of sync with reality.
This isn’t as surprising as it may seem, though. Remember that some of these assets date back to the 1800s, that paper records get lost, and that it’s very easy for discrepancies of any size between designs and as-built to creep into any project.
This introduces huge inefficiencies into the process of inspecting and maintaining the network effectively. There are instances where work crews are dispatched to the wrong location or find the job very different to their scope of work once they get there. In the worst-case scenario, assets that have fallen off the map may be under-inspected and maintained.
Now, consider that there are more than 200,000 miles of high-voltage transmission lines across the US. It is a truly herculean task to stay on top of, and utility resources are not infinite: they must strike a balance between responsible operations, profitability, and respect for the ratepayer.
Any tension between these stakeholders evaporates when the worst comes to pass. Shareholders and executives who have an incentive to prefer lower operational expenditure are not well-served by hits to the share price and regulatory fines. Ratepayers also don’t want high 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 analyzed 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 prioritize efforts to minimize both cost and risk.
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.
By James Conlin, Product Manager at Sharper Shape
