Maintenance and recovery of high voltage electricity transport systems

The SharperSat project was dedicated to design, develop and validate integrated solutions for transmission system operators (TSOs) and distribution system operators (DSOs) aimed at significantly improving the maintenance and recovery of their overhead assets and reducing related operational costs. This involved the need for rapid recognition of damages after a storm, clearance need detection and prioritisation of areas, supervision of vegetation clearance, and analysis of the cost efficiency of new methods.

To meet these user needs SharperSat used satellite EO supported by remote sensing and airborne data gathered by remotely piloted aircraft systems (RPAS) and its own software solutions to provide a new level of accuracy and faster time-to-results. Software automatically analysed data and identified the need for corrective actions in the field. The service was integrated within the end users processes and the analysis resulted in a maintenance plan with economic optimisation of the actions related to detected issues. No single data gathering method could solve all the needs of end users. Therefore the solution of power line inspection problems was combined with several inspection methods that complement each other in such a way that the inspection results met the needs of the customer in a cost-efficient manner.

The primary market was European TSOs/DSOs, secondary market was Northern American TSOs/DSOs including USA and Canada. The overall logic behind the service concept was to provide OPEX cost reduction to end users. This was achieved through always using the most economic method for analysis and to determine accurately where more expensive and accurate inspection methods should be used in order to minimise unnecessary cost of inspection and maintenance work.

The proposed integrated solution included two relevant space assets, namely satellite Earth observation and Global Navigation Satellite System. SatEO is is able to deliver wide coverage, low cost data over the power line network and related vegetation frequently. This enables optimising the timing and frequency for inspections and potentially replacing partially traditional inspection methods. Therefore, costs for maintenance inspections can be sufficiently reduced. The dominating remote sensing method used relied on unmanned aerial vehicles (UAVs), based on the satellite positioning system GNSS, due to its cost-efficiency, availability and support for both LiDAR and visual imaging.