Lifetime prediction of turbine blades using global precipitation products from satellites

Abstract. The growing size of wind turbines leads to extremely high tip speeds when the blades are rotating. prone leading edge erosion raindrops hit at such speeds, and blade damage will eventually affect power production until repair or replacement is performed. Since these actions come with a cost, it relevant estimate lifetime for given farm site prior construction. Modeling tools prediction require input time series rainfall intensities in addition turbine-specific speed curve. In this paper, we investigate suitability satellite-based precipitation data from Global Precipitation Measurement (GPM) mission context prediction. We first evaluate Integrated Multi-Satellite Retrievals GPM (IMERG) final product against situ observations 18 weather stations located Germany, Denmark, Portugal. then use satellite as model prediction, together measured stations. find that lifetimes estimated satellites good agreement despite very different nature observation methods fact IMERG products have 30 min temporal resolution, whereas deliver 10 accumulated intensities. Our results indicate has large impact on lifetimes. Inland show significantly longer than coastal stations, which more exposed mean speeds. One station mountainous terrain shows differences between based observations. known limited accuracy terrain. analyses also confirm overestimates light underestimates heavy rainfall. Given networks gaps over oceans, there potential utilizing map This useful installed offshore including floating installations far coast.