The perils of automated fitting of datasets: The case of a wind turbine cost model

Examples and Counterexamples

Katharina Gruber¹  Claude Klöckl²  Peter Regner³  Johannes Schmidt³  Sebastian Wehrle³ 

[1] Institute for Sustainable Economic Development, University of Natural Resources and Life Sciences, Feistmantelstraße 4, 1180 Vienna, Austria;Corresponding author.;Institute for Sustainable Economic Development, University of Natural Resources and Life Sciences, Feistmantelstraße 4, 1180 Vienna, Austria;

关键词: Renewable energy;    Wind turbine;    Cost models;    Regression models;    Wind turbine cost;    LCOE;   

DOI  :  

来源: DOAJ

【 摘 要 】

Rinne et al. (2018) conduct a detailed analysis of the impact of wind turbine technology and land-use on wind power potentials, which allows important insights into each factor’s contribution to overall potentials. The paper presents a detailed and very valuable model of site-specific wind turbine investment cost (i.e. road- and grid access costs), complemented by a model used to estimate site-independent costs.However, the site-independent cost model is flawed in our opinion. This flaw most likely does not impact the results on cost supply-curves of wind power presented in the paper. However, we expect a considerable generalization error. Thus the application of the wind turbine cost model in other contexts may lead to unreasonable results. More generally, the derivation of the wind turbine cost model serves as an example of how applications of automated regression analysis can go wrong.

【 授权许可】

Unknown