A categorisation scheme for energy losses and noise increase due to leading edge roughness

A framework for estimating annual energy production (AEP) losses on a wind turbine due to leading edge roughness (LER) on the blades using a novel developed categorisation scheme is presented. It shows how to link inspection data to sectional aerodynamic and aeroacoustic losses through the categorisation scheme and modify the original aerodynamic data to account for losses due to LER, which enables the estimation of the AEP losses. This allows the determination of the optimal time of repair based on a data-driven and objective workflow, reducing the maintenance cost due to LER on wind turbine blades. A key outcome of the present study is that the categorisation scheme is openly available and developed transparently in co-operation between four of the world-leading wind turbine blade manufacturers (Vestas, LM, SiemensGamesa, and Suzlon) and an independent service provider (PowerCurve), with DTU as the overall project manager. The categorisation scheme is based on wind tunnel measurements of different wind turbine aerofoils including high-resolution LER topographies obtained from scans of wind turbine blades. Using the developed categorisation scheme to predict an AEP loss for a modelled and representative LER distribution on the IEA 22MW reference turbine shows a decrease in AEP up to 1.5% dependent on the wind climate.