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Projects: Projects for Investigator
Reference Number NIA_SPEN_0063
Title Virtual OHL Inspections: Combining Statutory Inspection & Condition Based Assessment (CBA)
Status Completed
Energy Categories Other Cross-Cutting Technologies or Research 50%;
Other Power and Storage Technologies(Electricity transmission and distribution) 50%;
Research Types Applied Research and Development 100%
Science and Technology Fields ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 100%
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Project Contact
No email address given
SPEN - SP Distribution Plc
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 October 2021
End Date 31 January 2022
Duration ENA months
Total Grant Value £110,000
Industrial Sectors Power
Region Scotland
Programme Network Innovation Allowance
Investigators Principal Investigator Project Contact , SPEN - SP Distribution Plc (100.000%)
  Industrial Collaborator Project Contact , SP Energy Networks (0.000%)
Web Site https://smarter.energynetworks.org/projects/NIA_SPEN_0063
Objectives Update asset model Gather historical images for missing danger plates Agree trial area image capture guidelines & plan flights Set-up environment Initiate missing danger plate AI Carry out image capture (drone) flights Install Grid Vision & fine tune AI Grid Vision training Carry out virtual inspection and gather feedback. Test missing danger plate AI model Fine tune business case Present final report Defect detection on test areas of network via virtual inspection including the following artificial intelligence modules:Broken insulatorContaminated insulatorCracked poleConductor strand damageFlashed insulatorWoodpecker damageMissing danger plate (new)Full report on OPEX savings, artificial intelligence detection of above and role of digitized defect data in predictive maintenance. Report demonstrating optimal approach to combine statutory & condition based assessment inspections via virtual inspections. To include detailed approach to optimise OPEX savings and utilise digital condition data (including identified from artificial intelligence) in future network planning. 
Abstract This p[roject will assess and trial the use of drones to carry out condition-based monitoring on the OHL network.
Publications (none)
Final Report (none)
Added to Database 02/11/22