Abstract. The flexible-membrane kite employed by some airborne wind energy systems uses a suspended control unit, which experiences a characteristic swinging motion relative to the top of the kite during sharp turning manoeuvres. This paper assesses the accuracy of a two-point kite model in resolving this swinging motion using two different approaches: approximating the motion as a transition through steady-rotation states and solving the motion dynamically. The kite is modelled with two rigidly linked point masses representing the control unit and wing, which conveniently extend a discretised tether model. The tether-kite motion is solved by prescribing the trajectory of the wing point mass to replicate a figure-eight manoeuvre from the flight data of an existing prototype. The computed pitch and roll of the kite are compared against the attitude measurements of two sensors mounted to the wing. The two approaches compute similar pitch and roll angles during the straight sections of the figure-eight manoeuvre and match measurements within 3°. However, during the turns, the dynamically solved pitch and roll angles show systematic differences compared to the steady-rotation solution. As a two-point kite model resolves the roll, the lift force may tilt along with the kite, which is identified as the driving mechanism for turning flexible kites. Moreover, the two-point kite model complements the aerodynamic model as it allows for computing the angle of attack of the wing by resolving the pitch. These characteristics improve the generalisation of the kite model compared to a single-point model with little additional computational effort.
{"title":"Swinging motion of a kite with suspended control unit flying turning manoeuvres","authors":"M. Schelbergen, R. Schmehl","doi":"10.5194/wes-9-1323-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1323-2024","url":null,"abstract":"Abstract. The flexible-membrane kite employed by some airborne wind energy systems uses a suspended control unit, which experiences a characteristic swinging motion relative to the top of the kite during sharp turning manoeuvres. This paper assesses the accuracy of a two-point kite model in resolving this swinging motion using two different approaches: approximating the motion as a transition through steady-rotation states and solving the motion dynamically. The kite is modelled with two rigidly linked point masses representing the control unit and wing, which conveniently extend a discretised tether model. The tether-kite motion is solved by prescribing the trajectory of the wing point mass to replicate a figure-eight manoeuvre from the flight data of an existing prototype. The computed pitch and roll of the kite are compared against the attitude measurements of two sensors mounted to the wing. The two approaches compute similar pitch and roll angles during the straight sections of the figure-eight manoeuvre and match measurements within 3°. However, during the turns, the dynamically solved pitch and roll angles show systematic differences compared to the steady-rotation solution. As a two-point kite model resolves the roll, the lift force may tilt along with the kite, which is identified as the driving mechanism for turning flexible kites. Moreover, the two-point kite model complements the aerodynamic model as it allows for computing the angle of attack of the wing by resolving the pitch. These characteristics improve the generalisation of the kite model compared to a single-point model with little additional computational effort.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141338567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammad Mehdi Mohammadi, H. Olivares-Espinosa, G. P. Navarro Diaz, S. Ivanell
Abstract. This paper investigates different actuator sector model implementation alternatives and how they compare to actuator line results. The velocity sampling method, tip/smearing correction, and time step are considered. A good agreement is seen between the line and sector model in the rotor plane and the wake flow. Using the sector model, it was possible to reduce the computational time by 75 % compared to the actuator line model as it is possible to run the simulations with a larger time step without compromising the accuracy considerably. The results suggest that the proposed velocity sampling method produces the closest results to the line model with different tip speed ratios. Moreover, the vortex-based smearing correction applied to the sector model results in the lowest error values, among the considered methods, to correct the radial load distributions. Also, it is seen that reducing the time step compared to the one used for the actuator disc/sector does not provide an advantage considering the increased computational time.
{"title":"An actuator sector model for wind power applications: a parametric study","authors":"Mohammad Mehdi Mohammadi, H. Olivares-Espinosa, G. P. Navarro Diaz, S. Ivanell","doi":"10.5194/wes-9-1305-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1305-2024","url":null,"abstract":"Abstract. This paper investigates different actuator sector model implementation alternatives and how they compare to actuator line results. The velocity sampling method, tip/smearing correction, and time step are considered. A good agreement is seen between the line and sector model in the rotor plane and the wake flow. Using the sector model, it was possible to reduce the computational time by 75 % compared to the actuator line model as it is possible to run the simulations with a larger time step without compromising the accuracy considerably. The results suggest that the proposed velocity sampling method produces the closest results to the line model with different tip speed ratios. Moreover, the vortex-based smearing correction applied to the sector model results in the lowest error values, among the considered methods, to correct the radial load distributions. Also, it is seen that reducing the time step compared to the one used for the actuator disc/sector does not provide an advantage considering the increased computational time.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141363766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Control co-design is a promising approach for wind turbine design due to the importance of the controller in power production, stability, load alleviation, and the resulting coupled effects on the sizing of the turbine components. However, the high computational effort required to solve optimization problems with added control design variables is a major obstacle to quantifying the benefit of this approach. In this work, we propose a methodology to identify if a design problem can benefit from control co-design. The estimation method, based on post-optimum sensitivity analysis, quantifies how the optimal objective value varies with a change in control tuning. The performance of the method is evaluated on a tower design optimization problem, where fatigue load constraints are a major driver, and using a linear quadratic regulator targeting fatigue load alleviation. We use the gradient-based multi-disciplinary optimization framework Cp-max. Fatigue damage is evaluated with time-domain simulations corresponding to the certification standards. The estimation method applied to the optimal tower mass and optimal cost of energy show good agreement with the results of the control co-design optimization while using only a fraction of the computational effort. Our results additionally show that there may be little benefit to using control co-design in the presence of an active frequency constraint. However, for a soft–soft tower configuration where the resonance can be avoided with active control, using control co-design results in a taller tower with reduced mass.
{"title":"A sensitivity-based estimation method for investigating control co-design relevance","authors":"Jenna Iori, C. Bottasso, M. McWilliam","doi":"10.5194/wes-9-1289-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1289-2024","url":null,"abstract":"Abstract. Control co-design is a promising approach for wind turbine design due to the importance of the controller in power production, stability, load alleviation, and the resulting coupled effects on the sizing of the turbine components. However, the high computational effort required to solve optimization problems with added control design variables is a major obstacle to quantifying the benefit of this approach. In this work, we propose a methodology to identify if a design problem can benefit from control co-design. The estimation method, based on post-optimum sensitivity analysis, quantifies how the optimal objective value varies with a change in control tuning. The performance of the method is evaluated on a tower design optimization problem, where fatigue load constraints are a major driver, and using a linear quadratic regulator targeting fatigue load alleviation. We use the gradient-based multi-disciplinary optimization framework Cp-max. Fatigue damage is evaluated with time-domain simulations corresponding to the certification standards. The estimation method applied to the optimal tower mass and optimal cost of energy show good agreement with the results of the control co-design optimization while using only a fraction of the computational effort. Our results additionally show that there may be little benefit to using control co-design in the presence of an active frequency constraint. However, for a soft–soft tower configuration where the resonance can be avoided with active control, using control co-design results in a taller tower with reduced mass.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141361076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. L. Ebbehøj, Philippe Couturier, Lars Morten Sørensen, Jon Juel Thomsen
Abstract. Modal properties and especially damping of operational wind turbines can vary over short time periods as a consequence of environmental and operational variability. This study seeks to experimentally test and validate a recently proposed method for short-term damping and natural frequency estimation of structures under the influence of varying environmental and operational conditions from measured vibration responses. The method is based on Gaussian process time-dependent auto-regressive moving average (GP-TARMA) modelling and is tested via two applications: a laboratory three-storey shear frame structure with controllable, time-varying damping and a flutter test of a full-scale 7 MW wind turbine prototype, in which two edgewise modes become unstable. Damping estimates for the shear frame compare well with estimates obtained with stochastic subspace identification (SSI) and standard impact hammer tests. The efficacy of the GP-TARMA approach for short-term damping estimation is illustrated through comparison to short-term SSI estimates. For the full-scale flutter test, GP-TARMA model residuals imply that the model cannot be expected to be entirely accurate. However, the damping estimates are physically meaningful and compare well with a previous study. The study shows that the GP-TARMA approach is an effective method for short-term damping estimation from vibration response measurements, given that there are enough training data and that there is a representative model structure.
{"title":"Experimental validation of a short-term damping estimation method for wind turbines in nonstationary operating conditions","authors":"K. L. Ebbehøj, Philippe Couturier, Lars Morten Sørensen, Jon Juel Thomsen","doi":"10.5194/wes-9-1005-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1005-2024","url":null,"abstract":"Abstract. Modal properties and especially damping of operational wind turbines can vary over short time periods as a consequence of environmental and operational variability. This study seeks to experimentally test and validate a recently proposed method for short-term damping and natural frequency estimation of structures under the influence of varying environmental and operational conditions from measured vibration responses. The method is based on Gaussian process time-dependent auto-regressive moving average (GP-TARMA) modelling and is tested via two applications: a laboratory three-storey shear frame structure with controllable, time-varying damping and a flutter test of a full-scale 7 MW wind turbine prototype, in which two edgewise modes become unstable. Damping estimates for the shear frame compare well with estimates obtained with stochastic subspace identification (SSI) and standard impact hammer tests. The efficacy of the GP-TARMA approach for short-term damping estimation is illustrated through comparison to short-term SSI estimates. For the full-scale flutter test, GP-TARMA model residuals imply that the model cannot be expected to be entirely accurate. However, the damping estimates are physically meaningful and compare well with a previous study. The study shows that the GP-TARMA approach is an effective method for short-term damping estimation from vibration response measurements, given that there are enough training data and that there is a representative model structure.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140664814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Papi, G. Troise, R. Behrens de Luna, J. Saverin, S. Pérez-Becker, David Marten, M. Ducasse, Alessandro Bianchini
Abstract. Floating offshore wind is widely considered to be a promising technology to harvest renewable energy in deep ocean waters and increase clean energy generation offshore. While evolving quickly from a technological point of view, floating offshore wind turbines (FOWTs) are challenging, as their performance and loads are governed by complex dynamics that are a result of the coupled influence of wind, waves, and currents on the structures. Many open challenges therefore still exist, especially from a modeling perspective. This study contributes to the understanding of the impact of modeling differences on FOWT loads by comparing three FOWT simulation codes, QBlade-Ocean, OpenFAST, and DeepLines Wind®, and three substructure designs, a semi-submersible, a spar buoy, and the two-part concept Hexafloat, in realistic environmental conditions. This extensive comparison represents one of the main outcomes of the Horizon 2020 project FLOATECH. In accordance with international standards for FOWT certification, multiple design situations are compared, including operation in normal power production and parked conditions. Results show that the compared codes agree well in the prediction of the system dynamics, regardless of the fidelity of the underlying modeling theories. However, some differences between the codes emerged in the analysis of fatigue loads, where, contrary to extreme loads, specific trends can be noted. With respect to QBlade-Ocean, OpenFAST was found to overestimate lifetime damage equivalent loads by up to 14 %. DeepLines Wind®, on the other hand, underestimated lifetime fatigue loads by up to 13.5 %. However, regardless of the model and FOWT design, differences in fatigue loads are larger for tower base loads than for blade root loads due to the larger influence substructure dynamics have on these loads.
{"title":"Quantifying the impact of modeling fidelity on different substructure concepts – Part 2: Code-to-code comparison in realistic environmental conditions","authors":"F. Papi, G. Troise, R. Behrens de Luna, J. Saverin, S. Pérez-Becker, David Marten, M. Ducasse, Alessandro Bianchini","doi":"10.5194/wes-9-981-2024","DOIUrl":"https://doi.org/10.5194/wes-9-981-2024","url":null,"abstract":"Abstract. Floating offshore wind is widely considered to be a promising technology to harvest renewable energy in deep ocean waters and increase clean energy generation offshore. While evolving quickly from a technological point of view, floating offshore wind turbines (FOWTs) are challenging, as their performance and loads are governed by complex dynamics that are a result of the coupled influence of wind, waves, and currents on the structures. Many open challenges therefore still exist, especially from a modeling perspective. This study contributes to the understanding of the impact of modeling differences on FOWT loads by comparing three FOWT simulation codes, QBlade-Ocean, OpenFAST, and DeepLines Wind®, and three substructure designs, a semi-submersible, a spar buoy, and the two-part concept Hexafloat, in realistic environmental conditions. This extensive comparison represents one of the main outcomes of the Horizon 2020 project FLOATECH. In accordance with international standards for FOWT certification, multiple design situations are compared, including operation in normal power production and parked conditions. Results show that the compared codes agree well in the prediction of the system dynamics, regardless of the fidelity of the underlying modeling theories. However, some differences between the codes emerged in the analysis of fatigue loads, where, contrary to extreme loads, specific trends can be noted. With respect to QBlade-Ocean, OpenFAST was found to overestimate lifetime damage equivalent loads by up to 14 %. DeepLines Wind®, on the other hand, underestimated lifetime fatigue loads by up to 13.5 %. However, regardless of the model and FOWT design, differences in fatigue loads are larger for tower base loads than for blade root loads due to the larger influence substructure dynamics have on these loads.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140674202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
O. García-Santiago, A. Hahmann, J. Badger, Alfredo Peña
Abstract. Wind farm parameterizations (WFPs) are used in mesoscale models for predicting wind farm power production and its impact on wind resources while considering the variability of the regional wind climate. However, the performance of WFPs is influenced by various factors including atmospheric stability. In this study, we compared two widely used WFPs in the Weather Research and Forecasting (WRF) model to large-eddy simulations (LES) of turbine wakes performed with the same model. The Fitch WFP and the explicit wake parameterization were evaluated for their ability to represent wind speed and turbulent kinetic energy (TKE) in a two-turbine wind farm layout under neutral, unstable, and stable atmospheric stability conditions. To ensure a fair comparison, the inflow conditions were kept as close as possible between the LES and mesoscale simulations for each type of stability condition, and the LES results were spatially aggregated to align with the mesoscale grid spacing. Our findings indicate that the performance of WFPs varies depending on the specific variable (wind speed or TKE) and the area of interest downwind of the turbine when compared to the LES reference. The WFPs can accurately depict the vertical profiles of the wind speed deficit for either the grid cell containing the wind turbines or the grid cells in the far wake, but not both simultaneously. The WFPs with an explicit source of TKE overestimate TKE values at the first grid cell containing the wind turbine; however, for downwind grid cells, agreement improves. On the other hand, WFPs without a TKE source underestimate TKE in all downwind grid cells. These agreement patterns between the WFPs and the LES reference are consistent under the three atmospheric stability conditions. However, the WFPs resemble less the wind speed and TKE from the LES reference under stable conditions than that under neutral or unstable conditions.
摘要风电场参数化（WFPs）用于中尺度模型，以预测风电场发电量及其对风资源的影响，同时考虑区域风气候的变化。然而，风场参数化的性能受到包括大气稳定性在内的各种因素的影响。在本研究中，我们比较了天气研究与预报（WRF）模型中两种广泛使用的 WFP 与使用同一模型对涡轮机风浪进行的大涡度模拟（LES）。在中性、不稳定和稳定大气稳定条件下，评估了 Fitch WFP 和显式激波参数化在双涡轮风电场布局中表示风速和湍流动能（TKE）的能力。为确保公平比较，在每种稳定条件下，LES 和中尺度模拟的流入条件都尽可能接近，并且 LES 结果在空间上进行了聚合，以与中尺度网格间距保持一致。我们的研究结果表明，与 LES 参考结果相比，WFP 的性能因具体变量（风速或 TKE）和风机下风相关区域而异。WFP 可以准确描绘包含风力涡轮机的网格单元或远处尾流网格单元的风速赤字垂直剖面，但不能同时描绘两者的风速赤字垂直剖面。带有明确 TKE 源的 WFP 高估了包含风力涡轮机的第一个网格单元的 TKE 值，但对于下风网格单元，一致性有所改善。另一方面，没有 TKE 源的 WFP 低估了所有下风网格单元的 TKE 值。在三种大气稳定性条件下，WFP 与 LES 参考之间的这些一致性模式是一致的。不过，与中性或不稳定条件下的风速和 TKE 相比，稳定条件下的 WFP 与 LES 参考值的相似度较低。
{"title":"Evaluation of wind farm parameterizations in the WRF model under different atmospheric stability conditions with high-resolution wake simulations","authors":"O. García-Santiago, A. Hahmann, J. Badger, Alfredo Peña","doi":"10.5194/wes-9-963-2024","DOIUrl":"https://doi.org/10.5194/wes-9-963-2024","url":null,"abstract":"Abstract. Wind farm parameterizations (WFPs) are used in mesoscale models for predicting wind farm power production and its impact on wind resources while considering the variability of the regional wind climate. However, the performance of WFPs is influenced by various factors including atmospheric stability. In this study, we compared two widely used WFPs in the Weather Research and Forecasting (WRF) model to large-eddy simulations (LES) of turbine wakes performed with the same model. The Fitch WFP and the explicit wake parameterization were evaluated for their ability to represent wind speed and turbulent kinetic energy (TKE) in a two-turbine wind farm layout under neutral, unstable, and stable atmospheric stability conditions. To ensure a fair comparison, the inflow conditions were kept as close as possible between the LES and mesoscale simulations for each type of stability condition, and the LES results were spatially aggregated to align with the mesoscale grid spacing. Our findings indicate that the performance of WFPs varies depending on the specific variable (wind speed or TKE) and the area of interest downwind of the turbine when compared to the LES reference. The WFPs can accurately depict the vertical profiles of the wind speed deficit for either the grid cell containing the wind turbines or the grid cells in the far wake, but not both simultaneously. The WFPs with an explicit source of TKE overestimate TKE values at the first grid cell containing the wind turbine; however, for downwind grid cells, agreement improves. On the other hand, WFPs without a TKE source underestimate TKE in all downwind grid cells. These agreement patterns between the WFPs and the LES reference are consistent under the three atmospheric stability conditions. However, the WFPs resemble less the wind speed and TKE from the LES reference under stable conditions than that under neutral or unstable conditions.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140686403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. This study comprehensively investigates the near-wake development of a model wind turbine operating at a low tip-speed ratio in stalled conditions. In the present paper, part 1, different ways of representing the turbine, which include a full geometrical representation and modeling by means of the actuator line method, and different approaches for the modeling of turbulence are assessed. The simulation results are compared with particle image velocimetry (PIV) measurements from the MEXICO and New MEXICO experiments. A highly resolved numerical setup was created and a higher-order numerical scheme was applied to target an optimal resolution of the tip vortex development and the wakes of the blades. Besides the classical unsteady Reynolds-averaged methodology, a recently developed variant of the detached-eddy simulation (DES) was employed, which features robust shielding capabilities of the boundary layers and enhanced transition to a fully developed large-eddy simulation (LES) state. Two actuator line simulations were performed in which the aerodynamic forces were either evaluated by means of tabulated data or imposed from the averaged blade loads of the simulation with full blade geometry. The purpose is to distinguish between the effects of the force projection and the force calculation in the underlying blade-element method on the blade wake development. With the hybrid Reynolds-averaged Navier–Stokes (RANS)–LES approach and the geometrically fully resolved rotor blade, the details of the flow of the detached blade wake could be resolved. The prediction of the wake deficit also agreed very well with the experimental data. Furthermore, the strength and size of the blade tip vortices were correctly predicted. With the linear unsteady Reynolds-averaged Navier–Stokes (URANS) model, the wake deficit could also be described correctly, yet the size of the tip vortices was massively overestimated. The actuator line method, when fed with forces from the fully resolved simulation, provides very similar results in terms of wake deficit and tip vortices to its fully resolved parent simulation. However, using uncorrected two-dimensional polars shows significant deviations in the wake topology of the inner blade region. This shows that the application in such flow conditions requires models for rotational augmentation. In part 2 of the study, to be published in another paper, the development and the dynamics of the early tip vortex formation are detailed.
摘要本研究全面探讨了在失速条件下，以低风尖速比运行的风力涡轮机模型的近翼发展情况。本文第 1 部分评估了表示涡轮机的不同方法，包括全几何表示法和推杆线法建模，以及湍流建模的不同方法。模拟结果与 MEXICO 和 New MEXICO 实验的粒子图像测速仪（PIV）测量结果进行了比较。创建了一个高分辨率的数值设置，并采用了一种高阶数值方案，以获得叶尖涡流发展和叶片湍流的最佳分辨率。除了经典的非稳态雷诺平均方法外，还采用了最近开发的分离涡模拟（DES）变体，其特点是边界层具有强大的屏蔽能力，并增强了向完全开发的大涡模拟（LES）状态的过渡。进行了两次推杆线模拟，其中气动力要么通过表格数据进行评估，要么通过完整叶片几何形状模拟的平均叶片载荷进行评估。这样做的目的是为了区分叶片基本元素方法中的力预测和力计算对叶片尾流发展的影响。利用雷诺平均纳维-斯托克斯（RANS）-LES 混合方法和几何上完全解析的转子叶片，可以解析分离叶片尾流的流动细节。对尾流赤字的预测也与实验数据非常吻合。此外，叶尖涡流的强度和大小也得到了正确预测。使用线性非稳态雷诺平均纳维-斯托克斯（URANS）模型，也能正确描述尾流赤字，但对叶尖涡流的大小估计过高。当采用完全解析模拟的力时，致动器线方法在尾流赤字和尖端涡流方面提供的结果与其完全解析的父模拟非常相似。然而，使用未校正的二维极点时，叶片内侧区域的尾流拓扑结构会出现明显偏差。这表明在这种流动条件下的应用需要旋转增强模型。研究的第二部分将在另一篇论文中发表，详细介绍早期叶尖涡流形成的发展和动态。
{"title":"The near-wake development of a wind turbine operating in stalled conditions – Part 1: Assessment of numerical models","authors":"P. Weihing, M. Cormier, T. Lutz, E. Krämer","doi":"10.5194/wes-9-933-2024","DOIUrl":"https://doi.org/10.5194/wes-9-933-2024","url":null,"abstract":"Abstract. This study comprehensively investigates the near-wake development of a model wind turbine operating at a low tip-speed ratio in stalled conditions. In the present paper, part 1, different ways of representing the turbine, which include a full geometrical representation and modeling by means of the actuator line method, and different approaches for the modeling of turbulence are assessed. The simulation results are compared with particle image velocimetry (PIV) measurements from the MEXICO and New MEXICO experiments. A highly resolved numerical setup was created and a higher-order numerical scheme was applied to target an optimal resolution of the tip vortex development and the wakes of the blades. Besides the classical unsteady Reynolds-averaged methodology, a recently developed variant of the detached-eddy simulation (DES) was employed, which features robust shielding capabilities of the boundary layers and enhanced transition to a fully developed large-eddy simulation (LES) state. Two actuator line simulations were performed in which the aerodynamic forces were either evaluated by means of tabulated data or imposed from the averaged blade loads of the simulation with full blade geometry. The purpose is to distinguish between the effects of the force projection and the force calculation in the underlying blade-element method on the blade wake development. With the hybrid Reynolds-averaged Navier–Stokes (RANS)–LES approach and the geometrically fully resolved rotor blade, the details of the flow of the detached blade wake could be resolved. The prediction of the wake deficit also agreed very well with the experimental data. Furthermore, the strength and size of the blade tip vortices were correctly predicted. With the linear unsteady Reynolds-averaged Navier–Stokes (URANS) model, the wake deficit could also be described correctly, yet the size of the tip vortices was massively overestimated. The actuator line method, when fed with forces from the fully resolved simulation, provides very similar results in terms of wake deficit and tip vortices to its fully resolved parent simulation. However, using uncorrected two-dimensional polars shows significant deviations in the wake topology of the inner blade region. This shows that the application in such flow conditions requires models for rotational augmentation. In part 2 of the study, to be published in another paper, the development and the dynamics of the early tip vortex formation are detailed.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140692502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Maps showing the mean wind speed only give an inaccurate indication of the quality of locations for future wind power developments. Calculating the capacity factor and plotting that on a map gives a better indication of the expected mean power output, but the outcome depends on the turbine choice. In this article, we introduce a general step-by-step method for improved visualisation of potential wind power locations. First, the mentioned dependency on turbine choice is compensated for by putting the expected mean power output in relation to the expected mean power output of all other wind parks of the region. This relative capacity factor results in comprehensive wind resource maps and can be plotted for the situation today and also for a future scenario. Since the expected income of a potential wind park is the product of mean power output and mean market value, looking at the relative capacity factor only does not give the full picture. The mean market value is influenced by the merit order effect that is mainly driven by covariance with other wind parks and the capacity factor's relation to production at low-wind moments. A market value factor is introduced that captures the expected mean market value relative to other wind parks, based on a simplified power market model. Finally the Renewable Energy Complementarity (RECom) index is defined, combining the relative capacity factor and market value factor into a single index, resulting in RECom maps. This map can comprehensively show the revenue potential of different locations for potential future wind power developments.
{"title":"Renewable Energy Complementarity (RECom) maps – a comprehensive visualisation tool to support spatial diversification","authors":"T. Vrana, Harald G. Svendsen","doi":"10.5194/wes-9-919-2024","DOIUrl":"https://doi.org/10.5194/wes-9-919-2024","url":null,"abstract":"Abstract. Maps showing the mean wind speed only give an inaccurate indication of the quality of locations for future wind power developments. Calculating the capacity factor and plotting that on a map gives a better indication of the expected mean power output, but the outcome depends on the turbine choice. In this article, we introduce a general step-by-step method for improved visualisation of potential wind power locations. First, the mentioned dependency on turbine choice is compensated for by putting the expected mean power output in relation to the expected mean power output of all other wind parks of the region. This relative capacity factor results in comprehensive wind resource maps and can be plotted for the situation today and also for a future scenario. Since the expected income of a potential wind park is the product of mean power output and mean market value, looking at the relative capacity factor only does not give the full picture. The mean market value is influenced by the merit order effect that is mainly driven by covariance with other wind parks and the capacity factor's relation to production at low-wind moments. A market value factor is introduced that captures the expected mean market value relative to other wind parks, based on a simplified power market model. Finally the Renewable Energy Complementarity (RECom) index is defined, combining the relative capacity factor and market value factor into a single index, resulting in RECom maps. This map can comprehensively show the revenue potential of different locations for potential future wind power developments.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140702118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nikolaos Bempedelis, Filippo Gori, Andrew Wynn, Sylvain Laizet, Luca Magri
Abstract. Maximising the power production of large wind farms is key to the transition towards net zero. The overarching goal of this paper is to propose a computational method to maximise the power production of wind farms with two practical design strategies. First, we propose a gradient-free method to optimise the wind farm power production with high-fidelity surrogate models based on large-eddy simulations and a Bayesian framework. Second, we apply the proposed method to maximise wind farm power production by both micro-siting (layout optimisation) and wake steering (yaw angle optimisation). Third, we compare the optimisation results with the optimisation achieved with low-fidelity wake models. Finally, we propose a simple multi-fidelity strategy by combining the inexpensive wake models with the high-fidelity framework. The proposed gradient-free method can effectively maximise wind farm power production. Performance improvements relative to wake-model optimisation strategies can be attained, particularly in scenarios of increased flow complexity, such as in the wake steering problem, in which some of the assumptions in the simplified flow models become less accurate. The optimisation with high-fidelity methods takes into account nonlinear and unsteady fluid mechanical phenomena, which are leveraged by the proposed framework to increase the farm output. This paper opens up opportunities for wind farm optimisation with high-fidelity methods and without adjoint solvers.
{"title":"Data-driven optimisation of wind farm layout and wake steering with large-eddy simulations","authors":"Nikolaos Bempedelis, Filippo Gori, Andrew Wynn, Sylvain Laizet, Luca Magri","doi":"10.5194/wes-9-869-2024","DOIUrl":"https://doi.org/10.5194/wes-9-869-2024","url":null,"abstract":"Abstract. Maximising the power production of large wind farms is key to the transition towards net zero. The overarching goal of this paper is to propose a computational method to maximise the power production of wind farms with two practical design strategies. First, we propose a gradient-free method to optimise the wind farm power production with high-fidelity surrogate models based on large-eddy simulations and a Bayesian framework. Second, we apply the proposed method to maximise wind farm power production by both micro-siting (layout optimisation) and wake steering (yaw angle optimisation). Third, we compare the optimisation results with the optimisation achieved with low-fidelity wake models. Finally, we propose a simple multi-fidelity strategy by combining the inexpensive wake models with the high-fidelity framework. The proposed gradient-free method can effectively maximise wind farm power production. Performance improvements relative to wake-model optimisation strategies can be attained, particularly in scenarios of increased flow complexity, such as in the wake steering problem, in which some of the assumptions in the simplified flow models become less accurate. The optimisation with high-fidelity methods takes into account nonlinear and unsteady fluid mechanical phenomena, which are leveraged by the proposed framework to increase the farm output. This paper opens up opportunities for wind farm optimisation with high-fidelity methods and without adjoint solvers.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140710398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Wind direction variability significantly affects the performance and lifetime of wind turbines and wind farms. Accurately modelling wind direction variability and understanding the effects of yaw misalignment are critical towards designing better wind turbine yaw and wind farm flow controllers. This review focuses on control-oriented modelling of wind direction variability, which is an approach that aims to capture the dynamics of wind direction variability for improving controller performance over a complete set of farm flow scenarios, performing iterative controller development and/or achieving real-time closed-loop model-based feedback control. The review covers various modelling techniques, including large eddy simulations (LESs), data-driven empirical models, and machine learning models, as well as different approaches to data collection and pre-processing. The review also discusses the different challenges in modelling wind direction variability, such as data quality and availability, model uncertainty, and the trade-off between accuracy and computational cost. The review concludes with a discussion of the critical challenges which need to be overcome in control-oriented modelling of wind direction variability, including the use of both high- and low-fidelity models.
{"title":"Control-oriented modelling of wind direction variability","authors":"Scott Dallas, Adam Stock, Edward Hart","doi":"10.5194/wes-9-841-2024","DOIUrl":"https://doi.org/10.5194/wes-9-841-2024","url":null,"abstract":"Abstract. Wind direction variability significantly affects the performance and lifetime of wind turbines and wind farms. Accurately modelling wind direction variability and understanding the effects of yaw misalignment are critical towards designing better wind turbine yaw and wind farm flow controllers. This review focuses on control-oriented modelling of wind direction variability, which is an approach that aims to capture the dynamics of wind direction variability for improving controller performance over a complete set of farm flow scenarios, performing iterative controller development and/or achieving real-time closed-loop model-based feedback control. The review covers various modelling techniques, including large eddy simulations (LESs), data-driven empirical models, and machine learning models, as well as different approaches to data collection and pre-processing. The review also discusses the different challenges in modelling wind direction variability, such as data quality and availability, model uncertainty, and the trade-off between accuracy and computational cost. The review concludes with a discussion of the critical challenges which need to be overcome in control-oriented modelling of wind direction variability, including the use of both high- and low-fidelity models.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140716796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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