Articles | Volume 7, issue 3
Wind Energ. Sci., 7, 1153–1169, 2022
https://doi.org/10.5194/wes-7-1153-2022
Wind Energ. Sci., 7, 1153–1169, 2022
https://doi.org/10.5194/wes-7-1153-2022
Research article
02 Jun 2022
Research article | 02 Jun 2022

Evaluation of obstacle modelling approaches for resource assessment and small wind turbine siting: case study in the northern Netherlands

Caleb Phillips et al.

Model code and software

DW-TAP API D. Duplyakin, S. Zisman, C. Phillips, and H. Tinnesand https://dw-tap.nrel.gov

DW TAP Computational Framework [Computer software] C. Phillips, D. Duplyakin, S. Zisman, and USDOE Office of Energy Efficiency and Renewable Energy https://doi.org/10.11578/dc.20200925.11

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Short summary
Adoption of distributed wind turbines for energy generation is hindered by challenges associated with siting and accurate estimation of the wind resource. This study evaluates classic and commonly used methods alongside new state-of-the-art models derived from simulations and machine learning approaches using a large dataset from the Netherlands. We find that data-driven methods are most effective at predicting production at real sites and new models reliably outperform classic methods.