Review of wake management techniques for wind turbines

Houck, Daniel

doi:10.1002/we.2668

Cited by 58 publications

(39 citation statements)

References 192 publications

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“…Wake steering by yaw, but also derating 1 of the upstream turbines can be used, to increase the overall power production of a wind farm. In addition to increasing the power production, the influence on the loads and lifetime of the wind turbines of such methods are also examined (Andersson et al, 2021;Nash et al, 2021;Meyers et al, 2022;Houck, 2022). At first, the focus is not to increase the loads above the limits of certification, but the use of wind farm control for active load reduction is also examined in several studies (Bossanyi, 2018;Kanev et al, 2018Kanev et al, , 2020Harrison et al, 2020).…”

Section: State Of the Artmentioning

confidence: 99%

“…The derating of the turbine is a setpoint to the wind turbine's real-time controller. The implementation of the derating method by parameters within the real-time controller thus depends on the objective and also on the individual dynamic behaviour of each turbine (Meyers et al, 2022;Houck, 2022). Even reducing damage from heavy rain on the leading edge of the blades might be a possible objective for rotor speed reduction, besides the more common fatigue damage (Bech et al, 2018).…”

Section: State Of the Artmentioning

confidence: 99%

“…There are several studies which investigate derating methods with respect to their influence on various objectives like power regulation for the grid (ancillary services), wake reduction (power maximization) or loads. In Houck (2022), several studies on derating (or axial-induction control) are summarized and sorted into the mentioned categories.…”

Section: 2mentioning

confidence: 99%

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From wind conditions to operational strategy: Optimal planning of wind turbine damage progression over its lifetime

Requate

Meyer²,

Hofmann³

2022

Preprint

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Abstract. Renewable energies have an entirely different cost structure than fossil fuel-based electricity generation. This is mainly due to the operation at zero marginal cost, whereas for fossil fuel plants, the fuel itself is a major driver of the entire cost of energy. For a wind turbine, most of the materials and resources are spent up front. Over its lifetime, this initial capital and material investment is converted into usable energy. Therefore, it is desirable to gain the maximum benefit from the utilized materials for each individual turbine over its entire operating lifetime. Material usage is closely linked to individual damage progression of various turbine components and their respective failure modes. Within this work, we present a novel approach for an optimal long-term planning of the operation of wind energy systems over their entire lifetime. It is based on a process for setting up a mathematical optimization problem that optimally distributes the available damage budget of a given failure mode over the entire lifetime. The complete process ranges from an adaptation of real-time wind turbine control to the evaluation of long-term goals and requirements. During this process, relevant deterministic external conditions and real-time controller setpoints influence the damage progression with equal importance. Finally, the selection of optimal planning strategies is based on an economic evaluation. The method is applied to an example for demonstration. It shows the high potential of the approach for an effective damage reduction on different use cases. The focus of the example is to effectively reduce power of a turbine under conditions where high loads are induced from wake-induced turbulence of neighbouring turbines. Through the optimization approach, the damage budget can be saved or spent under conditions where it pays off most in the long-term perspective. This way, it is possible to gain more energy from a given system and thus to reduce cost and ecological impact by a better usage of materials.

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Section: State Of the Artmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

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From wind conditions to operational strategy: Optimal planning of wind turbine damage progression over its lifetime

Requate

Meyer²,

Hofmann³

2022

Preprint

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“…The volume of published research on the topic is extensive, and discussion of all the nuances is beyond the scope of this work. A review article by Houk 13 serves as a helpful summary and index of prior work.…”

Section: Introductionmentioning

confidence: 99%

Loads assessment of a fixed‐bottom offshore wind farm with wake steering

et al. 2022

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Wake steering via deliberate yaw offset is an emerging wind farm control technique that has the potential to mitigate wake losses and further increase wind farm energy yield. The loads impact of this technique has been studied, but there is limited insight into wind‐farm‐wide impacts of wake steering. Understanding such impacts is crucial to determining the feasibility of using wake steering in commercial wind farms. To that end, this work investigates the impacts of wake steering on the loads of all turbine components across all turbines in a wind farm operating under a broad set of inflow conditions, including inflow velocity, shear exponent, turbulence class, and inflow angle. This was done by performing FAST.Farm simulations of a 12‐turbine wind farm array, excerpted from a larger hypothetical wind farm. The International Energy Agency Wind 15‐MW reference wind turbine was modeled atop a monopile substructure, an open‐source model that closely approximates the properties of similar commercial options. Wake steering was included via yaw offsets that were computed using an offline optimization with the National Renewable Energy Laboratory tool FLORIS. For each inflow case, the 12‐turbine array was simulated with and without wake steering. Results were compared in terms of time‐averaged means, standard deviations, ultimate loads, and damage‐equivalent loads. The findings show that because wake steering is generally applied at rated wind speeds and below, it is unlikely to drive ultimate loads. For fatigue loads, wake steering does increase the overall fatigue accumulation for some load channels, such as blade‐root and shaft bending. This is to be expected when overall power yield increases but may cause the damage accumulation to be more uniform throughout the array. The significance of the added fatigue loading is dependent on how frequent wake steering is utilized in the overall set of inflow conditions across the wind rose.

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“…In addition to turbine siting, there has been very promising research into coordinating turbine controls within a wind farm to maximize its total power. These methods have been recently and well-reviewed in Houck (2021) and Kheirabadi and Nagamune (2019). Axial induction control (AIC) is one method that has been heavily researched, and it involves derating upstream turbines for the benefit of downstream turbines.…”

Section: Introductionmentioning

confidence: 99%

Mid-fidelity simulations and comparisons of five techniques for axial induction control of a wind turbine

Houck

Maniaci

Kelley

2021

Preprint

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Abstract. As wind turbines are more frequently placed in arrays, the need to understand and mitigate problems arising from their wakes has increased. When downstream turbines are in the wakes of upstream ones, the downstream turbines produce less power, require more maintenance, and have shorter lifetimes. One wake mitigation technique is known as axial induction control (AIC) and it involves derating (operating suboptimally) upstream turbines such that more energy remains in their wakes for downstream turbines to harvest. While there has been considerable research on this technique, much of it has suffered from a misunderstanding of the most important parameters in optimizing AIC. As such, the research has been largely inconclusive. Herein, we seek to rectify several perceived shortcomings of previous work by using mid-fidelity simulations to compare five different techniques for AIC at three different derate percentages against a baseline case and examining the recovery of the wake. We find that only the case with the lowest derate, 10 %, and using maximum thrust exceeds the baseline when estimating the combined power of the simulated turbine and a virtual turbine five diameters downstream and that it produced 10 % more power. Furthermore, these results help to validate previous work that concluded that the excess energy that is in the wake of a derated turbine will be at the edges of the wake unless the wake can sufficiently recover before the next downstream turbine. Finally, all together this suggests that the precise combination of derate percentage and the method used to derate turbines (i.e., the precise combination of pitch and torque controls), as well as the spacing and arrangement of turbines, must all be considered when optimizing AIC, and that substantial power gains may be possible.

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Review of wake management techniques for wind turbines

Cited by 58 publications

References 192 publications

From wind conditions to operational strategy: Optimal planning of wind turbine damage progression over its lifetime

From wind conditions to operational strategy: Optimal planning of wind turbine damage progression over its lifetime

Loads assessment of a fixed‐bottom offshore wind farm with wake steering

Mid-fidelity simulations and comparisons of five techniques for axial induction control of a wind turbine

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