Summary
- Digitalization and increased investment are coming to electricity grids to support the energy transition
- Grid inspection is rapidly changing with the introduction of drones and artificial intelligence (AI) to reduce costs
- AI for grid inspections is still fairly basic but capabilities are expected to improve significantly
Why focus on the grid now?
When it comes to the energy transition, the focus is often on the (previously) novel technologies like solar PV, lithium-ion batteries and electrolyzers that directly change the way we produce and consume electricity. But power grids, which have not experienced as significant technological advancement recently, are also critical to enabling the energy transition and greater electrification. Apricum estimates that there will be a total of 8.2m km of overhead lines and 120m transmission towers in North America[1] and Europe[2] by 2034, a massive amount of infrastructure that must be inspected.
To meet national climate targets, the IEA projects global investment in grid infrastructure must double from $300bn annually to $600bn annually by 2030, [1] including investment in modernization of current infrastructure. In North America and Europe, ~50% of total transmission and distribution line length is over 20 years old, which requires more frequent inspection and maintenance as components age. More severe climate change induced weather conditions also require increased diligence and proactivity from grid operators to prevent failures that can lead to blackouts and wildfires. [2,3] These factors, combined with an aging workforce and desire to reduce inspection costs, are driving grid operators to find innovative solutions.
Why drones are becoming the inspection method of choice
Grid inspections for overground infrastructure have traditionally been performed manually, with linesmen climbing transmission and distribution towers to personally inspect their condition. Helicopters are now used extensively to perform inspections on overhead lines and towers, allowing grid operators to perform high-level inspections much more quickly and at lower cost than with climbing linesmen. Using drones is the next frontier of inspection cost saving and most major grid operators in North America and Europe have started pilot or full-fledged drone programs. Drones provide several advantages over helicopters for grid inspection: they are much less expensive to operate and have a lower carbon footprint, it is easier to learn and be licensed to pilot drones, they can fly closer to lines and towers and at multiple angles to capture more and higher quality images and drones are much safer for both infrastructure and operators. Drones also can be used to inspect underground lines and other infrastructure grid operators may have (for example, some utilities also use drones to inspect thermal power plants), which greatly improves worker safety by eliminating confined space hazards.
Along with technological improvements to inspection methods, more varieties of image capture are now used for grid inspections. RGB, infrared, UV, LiDAR and satellite imaging can all be used to help grid operators get a complete view of their infrastructure. RGB imaging is mostly used for physical defects (for example, loose bolts and corrosion), infrared and UV for electrical defects (for example, to detect coronas or resistive heating from electrical defects), and LiDAR and satellite for vegetation encroachment and wildfire risk mitigation (e.g., to detect where vegetation is growing into the right of way).
Despite these advantages, drone inspection is not yet universally cheaper than helicopters due to regulatory and payload restrictions. Drones are currently limited to VLOS[3] operation (unless granted exemptions, which must be applied for and granted case by case), which significantly limits their operational range (and therefore reduces inspection speed and increases cost). Regulators are slowly warming up to BVLOS[4] operation, especially in Canada and the UK, which would greatly reduce regulatory barriers to drone viability. Drones also currently lack the payload capabilities to perform all data captures in the same flight. Carrying and operating RGB, infrared and LiDAR image capture devices can significantly reduce drone range or even be too heavy for many drones used for grid inspection. As batteries improve and image capture devices get lighter, this problem is likely to become a nonfactor and VLOS regulations will be the primary barrier to drone adoption.
Why inspections are getting digitalized
As grid inspections become more advanced and more inspection data is captured by helicopters and drones, image processing and analysis are now becoming part of the inspection workflow. “Virtual” inspections are becoming more common in the industry, where linesmen analyze grid inspection images taken in the field from an office. This enables grid operators to utilize their resources better, as it is much more cost effective to send drone pilots (who can be inhouse or outsourced) to the field while linesmen focus on analyzing images.
Central image analysis and processing also provides the potential for artificial intelligence (AI) and digitization to speed up and streamline the grid inspection process. Both prescriptive and predictive AI models (for background on different AI classifications and their relevance to the energy transition, see Apricum’s article on Breaking down the AI boom) are applicable for grid operators. Prescriptive AI models for grid inspection are already quite advanced and help grid operators organize captured inspection images by associating images with their respective infrastructure in a GIS or digital twin and removing duplicate and redundant images.
Predictive AI models are the next frontier for development. Once mature, these models will be able to identify potential faults from inspection images and create an optimized preventative maintenance plan across a grid operators entire infrastructure portfolio. Current predictive models are improving rapidly but still lack the accuracy to be used without human supervision and can only detect the most common faults, limiting their benefit to grid operators. Long term inspections data will be integrated into digital twins that will use predictive AI models to predict aging digitally.
Players to watch
Most players providing AI-based grid inspection services are startups, with a few industrial digitalization specialists such as Siemens Energy and Hitachi active as well. Players primarily differentiate based on their service offering and AI performance. Startups like Arkion, eSmart Systems, Hepta and Sharper Shape specialize in AI for grid inspections, which allows them to provide inspection services as well as software and be a one-stop shop for grid operators looking to improve their inspection processes. Other, more general AI image processing startups such as Alteia and LandingAI use more general image tagging and processing AI algorithms that can be used for multiple different applications, but don’t provide inspection services due to their wider industry scope. AI accuracy and fault detection scope are the primary drivers for cost saving by reducing the amount of linesmen resources per inspection, the first players that can collect enough training data to expand fault detection scope and accuracy significantly are likely to win the market in the long run.
How Apricum can help
Apricum can help investors, grid operators and digital energy players to best position themselves in this new convergence. We support on growth strategy (strategy review, business model design, go-to-market strategy), commercial due diligence (buy- and sell-side) and financial advisory (capital raise, sell- and buy-side M&A). We have worked with some of the largest and most pioneering players in North America and Europe. If you would like to learn more about how we can support your company in entering or expanding your activities in the digital grid inspection space, please contact the head of our digital energy practice, Partner Florian Mayr.
Visit our Digital Energy page for more information about our advisory services in the space.
[1] The USA and Canada
[2] The EU, Norway, Switzerland and the United Kingdom
[3] Visual line of sight
[4] Beyond visual line of sight
