energies Article Advancing Wind Resource Assessment in Complex Terrain with Scanning Lidar Measurements Julia Gottschall 1, * , Alkistis Papetta 1 , Hassan Kassem 1 , Paul Julian Meyer 1 , Linda Schrempf 2 , Christian Wetzel 2 and Johannes Becker 2   Citation: Gottschall, J.; Papetta, A.; Kassem, H.; Meyer, P.J.; Schrempf, L.; Wetzel, C.; Becker, J. Advancing Wind Resource Assessment in Complex Terrain with Scanning Lidar Measurements. Energies 2021, 14, 3280. https://doi.org/10.3390/ en14113280 Academic Editors: Sukanta Basu and Javier Sanz Rodrigo Received: 15 February 2021 Accepted: 28 May 2021 Published: 3 June 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1 Fraunhofer Institute for Wind Energy Systems IWES, 27572 Bremerhaven, Germany; alkistis.papetta@gmail.com (A.P.); hassan.kassem@iwes.fraunhofer.de (H.K.); paul.meyer@iwes.fraunhofer.de (P.J.M.) 2 GEO-NET Umweltconsulting GmbH, 30161 Hanover, Germany; schrempf@geo-net.de (L.S.); wetzel@geo-net.de (C.W.); becker@geo-net.de (J.B.) * Correspondence: julia.gottschall@iwes.fraunhofer.de Abstract: The planning and realization of wind energy projects requires an as accurate and precise wind resource estimation as possible. Standard procedures combine shorter on-site measurements with the application of numerical models. The uncertainties of the numerical data generated from these models are, particularly in complex onshore terrain, not just rather high but typically not well quantified. In this article we propose a methodology for using a single scanning Doppler wind lidar device to calibrate the output data of a numerical flow model and with this not just quantify but potentially also reduce the uncertainties of the final wind resource estimate. The scanning lidar is configured to perform Plan Position Indicator (PPI) scans and the numerical flow data are projected onto this geometry. Deviations of the derived from the recorded line-of-sight wind speeds are used to identify deficiencies of the model and as starting point for an improvement and tuning. The developed methodology is demonstrated based on a study for a site in moderately complex terrain in central Germany and using two rather different types of numerical flow models. The findings suggest that the use of the methodology and the introduced scanning wind lidar technology offers a promising opportunity to control the uncertainty of the applied flow models, which can otherwise only be estimated very roughly. Keywords: wind resource assessment; scanning lidar; flow model calibration 1. Introduction An as accurate and precise as possible estimation of the wind resource, and the calculation of the prospective energy yield based on it, are important prerequisites for the successful design of a wind farm. The difficulty of the task increases with the complexity of the site under consideration, but also with the advancing point in time within the project life cycle at which the estimation takes place. While an initial rough estimate is sufficient at an early stage of the project development, the final realization and financing of the project requires maximum accuracy and, in particular, the lowest possible uncertainty of the forecast values of the expected energy yield. For the German onshore wind market, as an example, this demand increased even more when in 2017—with the EEG-2017 [1]—an auction model was introduced for the remuneration of electricity generated from wind power. Following this, bidders must submit their bid based on their expected energy yield at the time when the auction takes place. As a parallel development, the complexity of the sites that are planned and awarded within the auctions is increasing, as simple sites in flat terrain with comparatively high average wind speeds are already occupied and thus less available. This leaves onshore sites that are characterized by hilly or forested terrain, for example, both of which pose a significant challenge to the estimation of the site-specific Energies 2021, 14, 3280. https://doi.org/10.3390/en14113280 https://www.mdpi.com/journal/energies