Wind energy is a fast-growing industry that accounts for ten percent [1] of the US electricity supply. At the end of 2023, there were 73,352 turbines [2] in the United States with a rated wind capacity of 141 Gigawatts (GW). Conservative estimates predict 3,000 turbines will be added annually with the Department of Energy forecasting that by 2030, the total wind capacity in the US will grow to 224.07 GW; a 62% increase.
Wind farms are located in remote areas. The harsh and often extreme weather and environmental conditions they encounter, such as hail, lightning, and dust, can cause significant blade damage that directly impacts the performance and shortens the turbine's usable life. Decreased turbine efficiency can result in up to a 25% decrease in a wind turbine's Annual Energy Production (AEP).
In the absence of preventative care, maintenance can cost a company upwards of $50,000 per turbine per year. Between the decrease in a turbine's AEP, and the risk of high maintenance costs, wind farm operators are turning to drones, imagery, and machine learning to prioritize maintenance efforts quickly and proactively.