Launch of the FarmConners Wind Farm Control benchmark for code comparison

Göçmen, Tuhfe; Kölle, Konstanze; Andersen, Søren Juhl; Eguinoa, Irene; Duc, Thomas; Campagnolo, Filippo; Iribas-Latour, Mikel; Astrain, D.; Bottasso, Carlo L.; Meyers, Johan; Wingerden, Jan‐Willem van; Giebel, Gregor

doi:10.1088/1742-6596/1618/2/022040

Cited by 6 publications

(4 citation statements)

References 17 publications

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“…As a result, the technological approach for collaborated wind farm control is presently under advancement in multiple research institutions and industries. In particular, the FarmConners environment was introduced recently for the purpose of producing datasets as the basis for the evaluation of different control models in aiming to alleviate the barriers for wind farm control acceptance (Göcmen et al, 2020). In addition, the project was started by FarmConners to eliminate the challenges associated with the commercial application of wind farm control by collaborating a genuine assessment of the state-of-the-art of wind farm control in the FarmConners environment.…”

Section: Recent Challenges and Future Prospects Of Research Studies O...mentioning

confidence: 99%

Wind energy-harvesting technologies and recent research progresses in wind farm control models

et al. 2023

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In order to sustain the overall competitiveness of the wind power industry, unrelenting focus is required on working toward the advancement of enabling technologies and research studies that are associated with wind farm systems. First, wind farm technologies that include various turbine generator systems coupled with different power transmission configurations have enormous impact in determining the quality of wind power production. In addition, modern wind farms are expected to implement robust power control algorithms to meet more advanced requirements of electricity generation. Accordingly, this study explores the statuses of wind energy harvesting technologies and wind farm control strategies by discussing their recent and future impact on transforming the wind power industry. Doubly fed induction generator (DFIG)-based wind energy harvesting technology is well-matured and has exhibited an excellent track-record in past and recent experiences, but its capability of being further scalable for large-scale power production is limited as it is largely incompatible with high-voltage power transmission networks. On the other hand, permanent magnet synchronous generator (PMSG)-based technology is making significant advancements to attain the maximum possible efficiency level in greatly facilitating larger scale power generation, although the construction of bulky and costly power transmission systems is required. In this regard, future technological advances in the wind farm industry are expected to reasonably optimize the design and cost of high-voltage power transmission systems. Similarly, an increasing number of research studies are introducing a number of power optimization-based control models to create an ideal integration of the aforementioned wind farm technologies so as to ultimately enhance the reliability of electricity production by maintaining the systems’ safety. Yet, additional work is still expected to be undertaken in the future for a more extended evaluation of the performances of many different control models under a similar environment.

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Section: Recent Challenges and Future Prospects Of Research Studies O...mentioning

confidence: 99%

Wind energy-harvesting technologies and recent research progresses in wind farm control models

et al. 2023

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“… Quantification of the impact of wind farm control strategies on the wind turbine loads would be highly advantageous in moving wind farm control strategies forward towards widespread implementation and industry acceptance. Wind farm power maximisation is designed and evaluated on many different models, which makes the evaluation of the performance of different control approaches difficult. The FarmConners benchmark was launched recently to provide data sets on which control models can be evaluated [241]. While in simulations it was shown that the power production of wind farms can be increased with a cooperative control strategy, the proof‐of‐concept on a real wind farm is still missing.…”

Section: Discussionmentioning

confidence: 99%

Wind farm control ‐ Part I: A review on control system concepts and structures

Andersson

Anaya‐Lara

Tande

et al. 2021

IET Renewable Power Gen

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Wind farm control design is a recently new area of research that has rapidly become a key enabler for the development of large wind farm projects and their safe and efficient connection to the power grid. A comprehensive review of the intense research conducted in this area over the last 10 years is presented. Part I reviews control system concepts and structures and classifies them depending on their main objective (i.e. to maximise power production or to provide grid services. The work and key findings in each paper are discussed in detail with particular emphasis on the turbine side. Additionally, the review contributes to the existing reviews on the area by providing an elegant classification between model testing and control approaches. Areas where significant work is still needed are also discussed. In Part II, a thorough review on aerodynamic wind farm models for control design purposes is provided.

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“…The FarmConners benchmark is launched in TORQUE 2020 (Göçmen et al, 2020a), and in the end, 13 participants have submitted the results from their models, taking part in different blind tests. The overview of participants among the benchmark blind tests is presented in Table 1, and it should be noted that some participants have provided results from several models.…”

Section: Introductionmentioning

confidence: 99%

FarmConners wind farm flow control benchmark – Part 1: Blind test results

Göçmen

Campagnolo²,

Duc³

et al. 2022

Wind Energ. Sci.

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Abstract. Wind farm flow control (WFFC) is a topic of interest at several research institutes and industry and certification agencies worldwide. 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, the 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, four blind tests are defined and 13 participants in total have submitted results for the analysis of single and multiple wakes under WFFC. Here, we present Part I of the FarmConners benchmark results, focusing on the blind tests with large-scale rotors. 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. The 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 are 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, the sensitivity of the predicted WFFC benefits to the turbine representation and the implementation of the controller is also underlined. The 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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Launch of the FarmConners Wind Farm Control benchmark for code comparison

Cited by 6 publications

References 17 publications

Wind energy-harvesting technologies and recent research progresses in wind farm control models

Wind energy-harvesting technologies and recent research progresses in wind farm control models

Wind farm control ‐ Part I: A review on control system concepts and structures

FarmConners wind farm flow control benchmark – Part 1: Blind test results

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