Silverman et al (2023). Mass determination and model prediction of retired blades from wind turbine repowering or dismantling using a GIS database

A G Silverman, Y Henao, L C Bank, and T R Gentry. (2023) Mass determination and model prediction of retired blades from wind turbine repowering or dismantling using a GIS database. In the 43rd Risø International Symposium on Materials Science -Composite for wind energy: Manufacturing, operation and end-of-life, 4-7 September 2023, IOP Conf. Series: Materials Science and Engineering (2023), https://iopscience.iop.org/article/10.1088/1757-899X/1293/1/012030

Abstract

Existing estimations of waste from wind energy infrastructure that is headed for, flowing through, or having reached the terminus of various post-processing pathways have primarily relied on reported capacity to extrapolate the material weight of turbine components. This data can be used to project future streams of composite blade material coming from wind farm repowering and decommissioning and inform policies to optimize or improve certain blade End of Life (EoL) options. However, rated capacity alone is insufficient to quantify or characterize the dynamics of US wind fleet retirement, since turbines are often repowered with new blades but their capacity remains the same. This research demonstrates an alternative method, comparing various mass estimation techniques and identifying blade models that have been retired or are soon to enter waste pathways due to turbine repowering by spatiotemporal comparison of periodic versions of the United States Geological Survey (USGS) Wind Turbine Database (USWTDB). These analyses are used to compile a list of turbine and blade models that will be at the forefront of national repowering and decommissioning movements in the near future. Mass of future waste flows are totalled and can help inform protocols and frameworks for blade material EoL processes.