Remote drones could save one-third of powerline inspection costs

A beyond visual line of sight (BVLOS) drone with vertical take-off and landing could save 34% of powerline inspection costs according to research from PricewaterhouseCoopers (PwC).

Commissioned by UK Research & Innovation, PwC’s use case focused on the annual inspection of the Beauly to Denny powerline in Scotland, which links 615 transmission towers over a distance of 220km.

PwC’s business-as-usual case assumes a two-man team (camera operator and drone operator) travels from their base to the first site, where the drone operator pilots the visual line of sight drone on an agreed flight plan, enabling the camera operator to capture the necessary images of tower components. The team drives and walks between each tower (circa 500m apart), and the process is repeated.

The images are uploaded and reviewed by an inspection engineer using processing software, and each component is graded against the defect standard.

The results are then uploaded to a visual asset management platform for the client to review.

The cost of this operation is nearly £194,000, the vast bulk of which is operational cost.

With the remote drone, the overall cost drops to just shy of £128,000, with operational costs nearly halved – more than compensating for an increase in capital expenditure (due to the acquisition of a more advanced and therefore more expensive drone).

PwC assumes that the BVLOS drone is piloted by an operator in Edinburgh to the towers and carries out automated capture of the necessary images.

A second crew member in the field is responsible for charging batteries periodically at predefined locations, which are selected for their ease of access.

The rest of the process is the same as the business-as-usual case.

As well as the significant cost savings, the remote drone method leads to a 40-day time-saving and improves health and safety as there is no need for personnel to get close to the transmission towers.

Read the full report, Future Flight Challenge, Socio-economic study:

Image: 191910152 © Antondmitriev |

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