The perils of automated fitting of datasets: the case of a wind turbine cost model
For researchers using automated regression in energy cost modeling, this paper highlights pitfalls that can lead to unreliable models.
The authors critique a wind turbine cost model, arguing that its site-independent component is flawed due to improper automated regression, which may cause generalization errors in other contexts.
Rinne et al. conduct an interesting analysis of the impact of wind turbine technology and land-use on wind power potentials, which allows profound insights into each factors contribution to overall potentials. The paper presents a detailed 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. We believe that propose a cutting edge model of site-specific investment costs. However, the site-independent cost model is flawed in our opinion. This flaw most likely does not impact the results presented in the paper, although 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.