FarmConners wind farm flow control benchmark - Part 1 : blind test results

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Göçmen, Tuhfe and Campagnolo, Filippo and Duc, Thomas and Eguinoa, Irene and Andersen, Søren Juhl and Petrović, Vlaho and Imširović, Lejla and Braunbehrens, Robert and Feng, Ju and Liew, Jaime and Baungaard, Mads and van der Laan, Maarten Paul and Qian, Guowei and Aparicio-Sanchez, Maria and González-Lope, Rubén and Dighe, Vinit and Becker, Marcus and van den Broek, Maarten and van Wingerden, Jan-Willem and Stock, Adam and Cole, Matthew and Ruisi, Renzo and Bossanyi, Ervin and Requate, Niklas and Strnad, Simon and Schmidt, Jonas and Vollmer, Lukas and Blondel, Frédéric and Sood, Ishaan and Meyers, Johan (2022) FarmConners wind farm flow control benchmark - Part 1 : blind test results. Wind Energy Science, 7 (5). pp. 1791-1825. ISSN 2366-7451 (https://doi.org/10.5194/wes-2022-5)

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Abstract

Wind farm flow control (WFFC) is a topic of interest at several research institutes, industry and certification agencies world-wide. For reliable performance assessment of the technology, the efficiency and the capability of the models applied to WFFC should be carefully evaluated. To address that, FarmConners consortium has launched a common benchmark for code comparison under controlled operation to demonstrate its potential benefits such as increased power production. The benchmark builds on available data sets from previous field campaigns, wind tunnel experiments and high-fidelity simulations. Within that database, 4 blind tests are defined and 13 participants in total have submitted results for the analysis of single and multiple wake under WFFC. Some participants took part in several blind tests and some participants have implemented several models. The observations and/or the model outcomes are evaluated via direct power comparisons at the upstream and downstream turbine(s), as well as the power gain at the wind farm level under wake steering control strategy. Additionally, wake loss reduction is also analysed to support the power performance comparison, where relevant. Majority of the participating models show good agreement with the observations or the reference high-fidelity simulations, especially for lower degrees of upstream misalignment and narrow wake sector. However, the benchmark clearly highlights the importance of the calibration procedure for control-oriented models. The potential effects of limited controlled operation data in calibration is particularly visible via frequent model mismatch for highly deflected wakes, as well as the power loss at the controlled turbine(s). In addition to the flow modelling, sensitivity of the predicted WFFC benefits to the turbine representation and the implementation of the controller is also underlined. FarmConners benchmark is the first of its kind to bring a wide variety of data sets, control settings and model complexities for the (initial) assessment of farm flow control benefits. It forms an important basis for more detailed benchmarks in the future with extended control objectives to assess the true value of WFFC.

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