Analysis of the systematic errors of energy yield assessment in the context of wind farm repowering

Abstract

Abstract The repowering of wind farms is a rapidly developing area of research and is expected to represent 40 GW of wind projects by 2030 in the European Union. This has led to the emergence of energy yield assessment methods that incorporate operational data from existing farms with the aim of surpassing traditional methods that rely solely on physical modelling and onsite measurements. The current literature on repowering relies upon the assumption that learning from operational farm data applies to the future farm. Indeed, calibration and adjustment methods assume that physics-driven models (PDMs) have spatially and temporally correlated errors. This study investigates this assumption by analysing PDM errors for 25 pairs of nearby wind projects. A statistically significant correlation is observed. We discuss whether it is reasonable to utilise operational data from existing farms, which possess different characteristics, to improve the long-term production prediction of a repowered farm.