Estimating the impact of drone-based inspection on the Levelised Cost of electricity for offshore wind farms

被引:30
|
作者
Poleo, Khristopher Kabbabe [1 ]
Crowther, William J. [1 ]
Barnes, Mike [2 ]
机构
[1] Univ Manchester, Dept Mech Aerosp & Civil Engn, Manchester M13 9PL, Lancs, England
[2] Univ Manchester, Dept Elect & Elect Engn, Manchester M13 9PL, Lancs, England
基金
英国工程与自然科学研究理事会;
关键词
LCOE; Offshore wind; Unmanned aerial vehicles; Cost benefit analysis; Visual inspection; SYSTEMS; ENERGY;
D O I
10.1016/j.rineng.2021.100201
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Using drones for infrastructure inspection is becoming routine, driven by the benefit of reducing risk and costs. In this paper, the business case for drone-based inspection is examined from the perspective of the wind farm operator and the Drone Service Provider (DSP). A physical and financial model of an offshore wind farm is built using techno-economic analysis and activity-based costing, and data from the open literature. Drone operational models are developed based on domain specific knowledge of operation practices and the predicted physical environment. Rope-access inspection is used as a baseline and accounts for 0.7% of the wind farm operational expenditure. Replacing rope-access inspection with drones reduces costs by up to 70% and decreases revenue lost due to down-time by up to 90%. Increasing autonomy of drones increases the speed at which inspections can be performed but increases costs and complexity. For wind farm operator there is marginal economic benefit (2% reduction in inspection costs) in moving towards a fully autonomous drone-based inspection system from the current visual line of sight operation of single drone. However, from the point of view of the DSP, fully autonomous operations allow greater scalability of the business and enables higher utilisation of the fleet.
引用
收藏
页数:11
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