Received: 14 Jan 2022 – Discussion started: 15 Feb 2022
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.
The labels of the following figures is too small!!! 3, 4, 6, 7, 9, 11, 12, 13, 16, 18, 19, 27, 30, 31, 32, A1, A2, A3, B1, B2, B3, B4, C1, C2
Table 1: Instead of "x" put "name of the research institute / name of Code" Table 3: where is the difference between P4 and P5? Maybe write in the "Wake Model" line "Calibration1" and "Calibration2" Figure 3: Include SMV5 in the caption Figure 4: Include SMV7 in the caption Figure 3, Figure 4: what do the empty black circles represent? Figure 5a: diagramm "WS", caption "delta_WS": correct one of them. Table 6: Describe the parameters "alpha", "beta", ...,"n". Best, if also in the text! Figure 9: Distinguish blue dot from green line (not both measurement)! And orange dot from red line! Figure 10: Lines too thick, not clearly visible! Make lines (symbols) smaller Line 408: Why are the wind direction bins in the text +-2.5° and in Figure 12 the labels are by 2°? Figure 12 left: Colours not always easy to distinguish, put symbols Figure 12: Why line plot (left) and bar diagramm (red)? No added value! Same for Figure 13: Rewrite Lines 405 - 422 because concept is quite complex and not described enough. Especially rename term "P_i_Test" because the naming is confusing! Give table with weights and explain concept much more detailed. Line 1000: give equivalent number of revolutions for 3600s simulation time Table 10: line for partner description Figure 30: Labels too small Line 1089: make clear what is meant by subset! WT32,WT28 and WT29, WT25 or different? All turbines in the parc? Line 1123,1124: 8-turbine subset have to be horizontal lines! WT32, WT25,..., WT1 are not in a row!
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 wind farm flow control benefits. Here we present the analysis of the benchmark results under 4 blind tests with 13 participants and 16 models in total, via the direct power comparisons at the turbines, as well as the observed or estimated power gain at the wind farm level under wake steering control strategy.
FarmConners benchmark is the first of its kind to bring a wide variety of data sets, control...