In EU alone total length of overhead electricity lines reaches staggering 5.3 million km. That is more than 5 million km of potential fail points, that need to be inspected and maintained in order to ensure the reliability of electricity supply. Currently, these inspections are carried out by helicopters or walking inspection crews. However, both of these practices carry significant drawbacks.
Walking inspector crews are very slow (can cover 7-10 km per day). We estimate in EU these inspections require 3.1 million man-hours each year. Also, these inspections are not accurate – the inspector is visually inspecting electricity grid from the ground, hence some defects are difficult or even impossible to spot. Furthermore, this type of inspection is focused on reactive maintenance – identifying faults that are already there, instead of preventing faults from happening in the first place. Research shows that 64% of the outages are weather related or caused by faults in electricity grid elements, which could have been prevented by proactive maintenance practices.
Meanwhile helicopters can be equipped with advanced sensors (like LiDAR, thermal or high-resolution photo cameras), but are very expensive, carry high risk of loss of life (in case of flying into the electricity lines, survival rate is very low), the data quality suffers due to strong vibrations, while the engine consumes fuel at 60 l/h.
Despite all of this environmental damage, time and money put into ensuring reliability of the grid, the outages are still prevalent across EU. For example, in 2016 there were more than 10 thousand forced electricity outages in EU transmission grid alone. We estimate that power outages in EU result in around 7,2-9.3 billion euros in economic damages per year.
The societal challenge – reducing vast economic losses due to electricity supply interruptions, while simultaneously reducing inspection cost and environmental impact.
Our proposed solution – substituting helicopters and walking crews with our new generation unmanned aerial vehicles (UAVs) equipped with LiDAR , RGB, multispectral and thermal cameras, combined with artificial intelligence (AI) and machine learning (ML) powered analytics, that can quickly and accurately identify defects and faults in electricity grid elements.
