Abstract. Mesoscale meteorological phenomena, including atmospheric gravity waves (AGWs) and including trapped lee waves (TLWs), can result from flow over topography or coastal transition in the presence of stable atmospheric stratification, particularly with strong capping inversions. Satellite images show that topographically forced TLWs frequently occur around near-coastal offshore wind farms. Yet current understanding of how they interact with individual turbines and whole farm energy output is limited. This parametric study investigates the potential impact of TLWs on a UK near-coastal offshore wind farm, Westermost Rough (WMR), resulting from westerly–southwesterly flow over topography in the southeast of England. Computational fluid dynamics (CFD) modelling (using Ansys CFX) of TLW situations based on real atmospheric conditions at WMR was used to better understand turbine level and whole wind farm performance in this parametric study based on real inflow conditions. These simulations indicated that TLWs have the potential to significantly alter the wind speeds experienced by and the resultant power output of individual turbines and the whole wind farm. The location of the wind farm in the TLW wave cycle was an important factor in determining the magnitude of TLW impacts, given the expected wavelength of the TLW. Where the TLW trough was coincident with the wind farm, the turbine wind speeds and power outputs were more substantially reduced compared with when the TLW peak was coincident with the location of the wind farm. These reductions were mediated by turbine wind speeds and wake losses being superimposed on the TLW. However, the same initial flow conditions interacting with topography under different atmospheric stability settings produce differing near-wind-farm flow. Factors influencing the flow within the wind farm under the different stability conditions include differing, hill and coastal transition recovery, wind farm blockage effects, and wake recovery. Determining how much of the differences in wind speed and power output in the wind farm resulted from the TLW is an area for future development.
{"title":"Modelling the impact of trapped lee waves on offshore wind farm power output","authors":"S. Ollier, S. Watson","doi":"10.5194/wes-8-1179-2023","DOIUrl":"https://doi.org/10.5194/wes-8-1179-2023","url":null,"abstract":"Abstract. Mesoscale meteorological phenomena, including atmospheric\u0000gravity waves (AGWs) and including trapped lee waves (TLWs), can result from\u0000flow over topography or coastal transition in the presence of stable\u0000atmospheric stratification, particularly with strong capping inversions.\u0000Satellite images show that topographically forced TLWs frequently occur\u0000around near-coastal offshore wind farms. Yet current understanding of how\u0000they interact with individual turbines and whole farm energy output is\u0000limited. This parametric study investigates the potential impact of TLWs on\u0000a UK near-coastal offshore wind farm, Westermost Rough (WMR), resulting from\u0000westerly–southwesterly flow over topography in the southeast of England. Computational fluid dynamics (CFD) modelling (using Ansys CFX) of TLW\u0000situations based on real atmospheric conditions at WMR was used to better\u0000understand turbine level and whole wind farm performance in this parametric\u0000study based on real inflow conditions. These simulations indicated that TLWs\u0000have the potential to significantly alter the wind speeds experienced by and\u0000the resultant power output of individual turbines and the whole wind farm.\u0000The location of the wind farm in the TLW wave cycle was an important factor\u0000in determining the magnitude of TLW impacts, given the expected wavelength\u0000of the TLW. Where the TLW trough was coincident with the wind farm, the\u0000turbine wind speeds and power outputs were more substantially reduced\u0000compared with when the TLW peak was coincident with the location of the wind\u0000farm. These reductions were mediated by turbine wind speeds and wake losses\u0000being superimposed on the TLW. However, the same initial flow conditions\u0000interacting with topography under different atmospheric stability settings\u0000produce differing near-wind-farm flow. Factors influencing the flow within\u0000the wind farm under the different stability conditions include differing,\u0000hill and coastal transition recovery, wind farm blockage effects, and wake\u0000recovery. Determining how much of the differences in wind speed and power\u0000output in the wind farm resulted from the TLW is an area for future\u0000development.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48480615","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}
Markus Sommerfeld, M. Dörenkämper, J. De Schutter, C. Crawford
Abstract. This study investigates the performance of pumping-mode ground-generation airborne wind energy systems (AWESs) by determining cyclical, feasible, power-optimal flight trajectories based on realistic vertical wind velocity profiles. These 10 min profiles, derived from mesoscale weather simulations at an offshore and an onshore site in Europe, are incorporated into an optimal control model that maximizes average cycle power by optimizing the trajectory. To reduce the computational cost, representative wind conditions are determined based on k-means clustering. The results describe the influence of wind speed magnitude and profile shape on the power, tether tension, tether reeling speed, and kite trajectory during a pumping cycle. The effect of mesoscale-simulated wind profiles on power curves is illustrated by comparing them to logarithmic wind profiles. Offshore, the results are in good agreement, while onshore power curves differ due to more frequent non-monotonic wind conditions. Results are references against a simplified quasi-steady-state model and wind turbine model. This study investigates how power curves based on mesoscale-simulated wind profiles are affected by the choice of reference height. Our data show that optimal operating heights are generally below 400 m with most AWESs operating at around 200 m.
{"title":"Impact of wind profiles on ground-generation airborne wind energy system performance","authors":"Markus Sommerfeld, M. Dörenkämper, J. De Schutter, C. Crawford","doi":"10.5194/wes-8-1153-2023","DOIUrl":"https://doi.org/10.5194/wes-8-1153-2023","url":null,"abstract":"Abstract. This study investigates the performance of pumping-mode ground-generation airborne wind energy systems (AWESs) by determining cyclical, feasible, power-optimal flight trajectories based on realistic vertical wind velocity profiles. These 10 min profiles, derived from mesoscale weather simulations at an offshore and an onshore site in Europe, are incorporated into an optimal control model that maximizes average cycle power by optimizing the trajectory. To reduce the computational cost, representative wind conditions are determined based on k-means clustering. The results describe the influence of wind speed magnitude and profile shape on the power, tether tension, tether reeling speed, and kite trajectory during a pumping cycle. The effect of mesoscale-simulated wind profiles on power curves is illustrated by comparing them to logarithmic wind profiles.\u0000Offshore, the results are in good agreement, while onshore power curves differ due to more frequent non-monotonic wind conditions. Results are references against a simplified quasi-steady-state model and wind turbine model. This study investigates how power curves based on mesoscale-simulated wind profiles are affected by the choice of reference height. Our data show that optimal operating heights are generally below 400 m with most AWESs operating at around 200 m.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48503603","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}
P. Veers, C. Bottasso, L. Manuel, J. Naughton, L. Pao, J. Paquette, A. Robertson, M. Robinson, S. Ananthan, T. Barlas, A. Bianchini, Henrik Bredmose, S. G. Horcas, J. Keller, H. A. Madsen, J. Manwell, P. Moriarty, S. Nolet, J. Rinker
Abstract. Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push the frontiers in the design of turbine and plant systems. Modern turbine rotors operate through the entire atmospheric boundary layer, outside the bounds of historic design assumptions, which requires reassessing design processes and approaches. Traditional aerodynamics and aeroelastic modeling approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load alleviation potential. Opportunities in co-design can bring controls upstream into design optimization if captured in design-level models of the physical phenomena. It is a research challenge to integrate improved materials into the manufacture of ever-larger components while maintaining quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions needed to continue the progress of wind energy technology toward even lower cost and greater functionality are recommended.
{"title":"Grand challenges in the design, manufacture, and operation of future wind turbine systems","authors":"P. Veers, C. Bottasso, L. Manuel, J. Naughton, L. Pao, J. Paquette, A. Robertson, M. Robinson, S. Ananthan, T. Barlas, A. Bianchini, Henrik Bredmose, S. G. Horcas, J. Keller, H. A. Madsen, J. Manwell, P. Moriarty, S. Nolet, J. Rinker","doi":"10.5194/wes-8-1071-2023","DOIUrl":"https://doi.org/10.5194/wes-8-1071-2023","url":null,"abstract":"Abstract. Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are\u0000articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push\u0000the frontiers in the design of turbine and plant systems. Modern turbine\u0000rotors operate through the entire atmospheric boundary layer, outside the\u0000bounds of historic design assumptions, which requires reassessing design\u0000processes and approaches. Traditional aerodynamics and aeroelastic modeling\u0000approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load\u0000alleviation potential. Opportunities in co-design can bring controls\u0000upstream into design optimization if captured in design-level models of the\u0000physical phenomena. It is a research challenge to integrate improved\u0000materials into the manufacture of ever-larger components while maintaining\u0000quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions\u0000needed to continue the progress of wind energy technology toward even lower\u0000cost and greater functionality are recommended.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43647795","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}
M. Sanchez Gomez, J. Lundquist, J. Mirocha, R. Arthur
Abstract. Wind plants slow down the approaching wind, a phenomenon known as blockage. Wind plant blockage undermines turbine performance for front-row turbines and potentially for turbines deeper into the array. We use large-eddy simulations to characterize blockage upstream of a finite-size wind plant in flat terrain for different atmospheric stability conditions and investigate the physical mechanisms modifying the flow upstream of the turbines. To examine the influence of atmospheric stability, we compare simulations of two stably stratified boundary layers using the Weather Research and Forecasting model in large-eddy simulation mode, representing wind turbines using the generalized actuator disk approach. For a wind plant, a faster cooling rate at the surface, which produces stronger stably stratified flow in the boundary layer, amplifies blockage. As a novelty, we investigate the physical mechanisms amplifying blockage by evaluating the different terms in the momentum conservation equation within the turbine rotor layer. The velocity deceleration upstream of a wind plant is caused by an adverse pressure gradient and momentum advection out of the turbine rotor layer. The cumulative deceleration of the flow upstream of the front-row turbines instigates vertical motions. The horizontal flow is diverted vertically, reducing momentum availability in the turbine rotor layer. Although the adverse pressure gradient upstream of the wind plant remains unchanged with atmospheric stability, vertical advection of horizontal momentum is amplified in the more strongly stable boundary layer, mainly by larger shear of the horizontal velocity, thus increasing the blockage effect.
{"title":"Investigating the physical mechanisms that modify wind plant blockage in stable boundary layers","authors":"M. Sanchez Gomez, J. Lundquist, J. Mirocha, R. Arthur","doi":"10.5194/wes-8-1049-2023","DOIUrl":"https://doi.org/10.5194/wes-8-1049-2023","url":null,"abstract":"Abstract. Wind plants slow down the approaching wind, a phenomenon known as blockage. Wind plant blockage undermines turbine performance for front-row turbines and potentially for turbines deeper into the array. We use large-eddy simulations to characterize blockage upstream of a finite-size wind plant in flat terrain for different atmospheric stability conditions and investigate the physical mechanisms modifying the flow upstream of the turbines. To examine the influence of atmospheric stability, we compare simulations of two stably stratified boundary layers using the Weather Research and Forecasting model in large-eddy simulation mode, representing wind turbines using the generalized actuator disk approach. For a wind plant, a faster cooling rate at the surface, which produces stronger stably stratified flow in the boundary layer, amplifies blockage. As a novelty, we investigate the physical mechanisms amplifying blockage by evaluating the different terms in the momentum conservation equation within the turbine rotor layer. The velocity deceleration upstream of a wind plant is caused by an adverse pressure gradient and momentum advection out of the turbine rotor layer. The cumulative deceleration of the flow upstream of the front-row turbines instigates vertical motions. The horizontal flow is diverted vertically, reducing momentum availability in the turbine rotor layer. Although the adverse pressure gradient upstream of the wind plant remains unchanged with atmospheric stability, vertical advection of horizontal momentum is amplified in the more strongly stable boundary layer, mainly by larger shear of the horizontal velocity, thus increasing the blockage effect.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49320755","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 turbines are designed to minimize the economic cost of energy, a metric aimed at making wind competitive with other energy-producing technologies. However, now that wind energy is competitive, how can we increase its value for the environment and for society? And how much would environmental and societal gains cost other stakeholders, such as investors or consumers? This paper tries to answer these questions, limitedly to climate-related environmental impacts, from the perspective of wind turbine design. Although wind turbines produce green renewable energy, they also have various impacts on the environment, as do all human endeavors. Among all impacts, the present work adopts the environmental effects produced by a turbine over its entire life cycle, expressed in terms of CO2-equivalent emissions. A new approach to design is proposed, whereby Pareto fronts of solutions are computed to define optimal trade-offs between economic and environmental goals. The new proposed methodology is demonstrated on the redesign of a baseline 3 MW wind turbine at two locations in Germany, differing for typical wind speeds but within the same energy market. Among other results, it is found that, in these conditions, a 1 % increase in the cost of energy can buy about a 5 % decrease in the environmental impact of the turbine. Additionally, it is also observed that in the specific case of Germany, very low-specific-power designs are typically favored, because they produce more energy at low wind speeds, where both the economic and environmental values of wind are higher. Furthermore, it is found that the CO2-equivalent emissions displaced by a wind turbine are 1 order of magnitude larger than the produced emissions. Although limited to the sole optimization of wind-generating assets at two different locations, these results suggest the existence of new opportunities for the future development of wind energy where, by shifting the focus slightly away from a purely cost-driven short-term perspective, longer-term benefits for the environment (and, in turn, for society) may be obtained.
{"title":"The eco-conscious wind turbine: design beyond purely economic metrics","authors":"H. Canet, A. Guilloré, C. Bottasso","doi":"10.5194/wes-8-1029-2023","DOIUrl":"https://doi.org/10.5194/wes-8-1029-2023","url":null,"abstract":"Abstract. Wind turbines are designed to minimize the economic cost of energy, a metric aimed at making wind competitive with other energy-producing technologies. However, now that wind energy is competitive, how can we increase its value for the environment and for society? And how much would environmental and societal gains cost other stakeholders, such as investors or consumers? This paper tries to answer these questions, limitedly to climate-related environmental impacts, from the perspective of wind turbine design. Although wind turbines produce green renewable energy, they also have\u0000various impacts on the environment, as do all human endeavors. Among all\u0000impacts, the present work adopts the environmental effects produced by a\u0000turbine over its entire life cycle, expressed in terms of CO2-equivalent\u0000emissions. A new approach to design is proposed, whereby Pareto fronts of\u0000solutions are computed to define optimal trade-offs between economic and\u0000environmental goals. The new proposed methodology is demonstrated on the redesign of a baseline 3 MW wind turbine at two locations in Germany, differing for typical wind speeds but within the same energy market. Among other results, it is found that, in these conditions, a 1 % increase in the cost of energy can buy about a 5 % decrease in the environmental impact of the turbine. Additionally, it is also observed that in the specific case of Germany, very low-specific-power designs are typically favored, because they produce more energy at low wind speeds, where both the economic and environmental values of wind are higher. Furthermore, it is found that the CO2-equivalent emissions displaced by a wind turbine are 1 order of magnitude larger than the produced emissions. Although limited to the sole optimization of wind-generating assets at two\u0000different locations, these results suggest the existence of new\u0000opportunities for the future development of wind energy where, by shifting\u0000the focus slightly away from a purely cost-driven short-term perspective, longer-term benefits for the environment (and, in turn, for society) may be obtained.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46445985","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. A new generalized analytical model for representing body forces in numerical actuator disc models of wind turbines is proposed and compared to results from a blade element momentum (BEM) model. The model is an extension of a previously developed load model, which was based on the rotor disc being subject to a constant circulation, modified for tip and root effects, corresponding to an optimum design case. By adding a parabolic circulation distribution, corresponding to a solid-body approach of the flow in the near wake, it is possible to take into account losses associated with off-design cases, corresponding to pitch regulation at high wind speeds. The advantage of the model is that it does not depend on any detailed knowledge concerning the actual wind turbine being analysed but only requires information about the thrust coefficient and tip-speed ratio. The model is validated for different wind turbines operating under a wide range of operating conditions. The comparisons show generally an excellent agreement with the BEM model even at very small thrust coefficients and tip-speed ratios.
{"title":"Generalized analytical body force model for actuator disc computations of wind turbines","authors":"J. Sørensen","doi":"10.5194/wes-8-1017-2023","DOIUrl":"https://doi.org/10.5194/wes-8-1017-2023","url":null,"abstract":"Abstract. A new generalized analytical model for representing body forces in numerical actuator disc models of wind turbines is proposed and compared to results from a blade element momentum (BEM) model. The model is an extension of a previously developed load model, which was based on the rotor disc being subject to a constant circulation, modified for tip and root effects, corresponding to an optimum design case. By adding a parabolic circulation distribution, corresponding to a solid-body approach of the flow in the near wake, it is possible to take into account losses associated with off-design cases, corresponding to pitch regulation at high wind speeds. The advantage of the model is that it does not depend on any detailed knowledge concerning the actual wind turbine being analysed but only requires information about the thrust coefficient and tip-speed ratio. The model is validated for different wind turbines operating under a wide range of operating conditions. The comparisons show generally an excellent agreement with the BEM model even at very small thrust coefficients and tip-speed ratios.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42228282","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. Understanding and modeling the aerodynamic wake of airborne wind energy systems (AWESs) is crucial for estimating the performance and defining the design of such systems, as tight trajectories increase induced velocities and thus decrease the available power, while unnecessarily large trajectories increase power losses due to the gravitational potential energy exchange. The aerodynamic wake of crosswind AWESs flying circular trajectories is studied here with vortex methods. The velocities induced at the AWES from a generic helicoidal vortex filament, trailed by a position on the AWES wing, are modeled with an expression for the near vortex filament and one for the far vortex filament. The near vortex filament is modeled as the first half rotation of the helicoidal filament, with its axial component being neglected. The induced drag due to the near wake, built up from near vortex filaments, is found to be similar to the induced drag the AWES would have in forward flight. The far wake is modeled as two semi-infinite vortex ring cascades with opposite intensity. An approximate solution for the axial induced velocity at the AWES is given as a function of the radial (known) and axial (unknown) position of the vortex rings. An explicit and an implicit closure model are introduced to link the axial position of the vortex rings with the other quantities of the model. The aerodynamic model, using the implicit closure model for the far wake, is validated with the lifting-line free-vortex wake method implemented in QBlade. The model is suitable to be used in time-marching aero-servo-elastic simulations and in design and optimization studies.
{"title":"Vortex model of the aerodynamic wake of airborne wind energy systems","authors":"Filippo Trevisi, C. Riboldi, A. Croce","doi":"10.5194/wes-8-999-2023","DOIUrl":"https://doi.org/10.5194/wes-8-999-2023","url":null,"abstract":"Abstract. Understanding and modeling the aerodynamic wake of airborne wind energy systems (AWESs) is crucial for estimating the performance and defining the design of such systems, as tight trajectories increase induced velocities and thus decrease the available power, while unnecessarily large trajectories increase power losses due to the gravitational potential energy exchange. The aerodynamic wake of crosswind AWESs flying circular trajectories is studied here with vortex methods. The velocities induced at the AWES from a generic helicoidal vortex filament, trailed by a position on the AWES wing, are modeled with an expression for the near vortex filament and one for the far vortex filament. The near vortex filament is modeled as the first half rotation of the helicoidal filament, with its axial component being neglected. The induced drag due to the near wake, built up from near vortex filaments, is found to be similar to the induced drag the AWES would have in forward flight. The far wake is modeled as two semi-infinite vortex ring cascades with opposite intensity. An approximate solution for the axial induced velocity at the AWES is given as a function of the radial (known) and axial (unknown) position of the vortex rings. An explicit and an implicit closure model are introduced to link the axial position of the vortex rings with the other quantities of the model. The aerodynamic model, using the implicit closure model for the far wake, is validated with the lifting-line free-vortex wake method implemented in QBlade. The model is suitable to be used in time-marching aero-servo-elastic simulations and in design and optimization studies.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44306414","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. In the past several years, wind veer – sometimes called “directional shear” – has begun to attract attention due to its effects on wind turbines and their production, particularly as the length of manufactured turbine blades has increased. Meanwhile, applicable meteorological theory has not progressed significantly beyond idealized cases for decades, though veer's effect on the wind speed profile has been recently revisited. On the other hand the shear exponent (α) is commonly used in wind energy for vertical extrapolation of mean wind speeds, as well as being a key parameter for wind turbine load calculations and design standards. In this work we connect the oft-used shear exponent with veer, both theoretically and for practical use. We derive relations for wind veer from the equations of motion, finding the veer to be composed of separate contributions from shear and vertical gradients of crosswind stress. Following from the theoretical derivations, which are neither limited to the surface layer nor constrained by assumptions about mixing length or turbulent diffusivities, we establish simplified relations between the wind veer and shear exponent for practical use in wind energy. We also elucidate the source of commonly observed stress–shear misalignment and its contribution to veer, noting that our new forms allow for such misalignment. The connection between shear and veer is further explored through analysis of one-dimensional (single-column) Reynolds-averaged Navier–Stokes solutions, where we confirm our theoretical derivations as well as the dependence of mean shear and veer on surface roughness and atmospheric boundary layer depth in terms of respective Rossby numbers. Finally we investigate the observed behavior of shear and veer across different sites and flow regimes (including forested, offshore, and hilly terrain cases) over heights corresponding to multi-megawatt wind turbine rotors, also considering the effects of atmospheric stability. From this we find empirical forms for the probability distribution of veer during high-veer (stable) conditions and for the variability in veer conditioned on wind speed. Analyzing observed joint probability distributions of α and veer, we compare the two simplified forms we derived earlier and adapt them to ultimately arrive at more universally applicable equations to predict the mean veer in terms of observed (i.e., conditioned on) shear exponent; lastly, the limitations, applicability, and behavior of these forms are discussed along with their use and further developments for both meteorology and wind energy.
{"title":"From shear to veer: theory, statistics, and practical application","authors":"M. Kelly, M. P. van der Laan","doi":"10.5194/wes-8-975-2023","DOIUrl":"https://doi.org/10.5194/wes-8-975-2023","url":null,"abstract":"Abstract. In the past several years, wind veer – sometimes called “directional shear” – has begun to attract attention due to its effects on wind turbines and their production, particularly as the length of manufactured turbine blades has increased. Meanwhile, applicable meteorological theory has not progressed significantly beyond idealized cases for decades, though veer's effect on the wind speed profile has been recently revisited.\u0000On the other hand the shear exponent (α) is commonly used in wind energy for vertical extrapolation of mean wind speeds, as well as being a key parameter for wind turbine load calculations and design standards. In this work we connect the oft-used shear exponent with veer, both theoretically and for practical use. We derive relations for wind veer from the equations of motion, finding the veer to be composed of separate contributions from shear and vertical gradients of crosswind stress.\u0000Following from the theoretical derivations, which are neither limited to the surface layer nor constrained by assumptions about mixing length or turbulent diffusivities, we establish simplified relations between the wind veer and shear exponent for practical use in wind energy. We also elucidate the source of commonly observed stress–shear misalignment and its contribution to veer, noting that our new forms allow for such misalignment. The connection between shear and veer is further explored through analysis of one-dimensional (single-column) Reynolds-averaged Navier–Stokes solutions, where we confirm our theoretical derivations as well as the dependence of mean shear and veer on surface roughness and atmospheric boundary layer depth in terms of respective Rossby numbers. Finally we investigate the observed behavior of shear and veer across different sites and flow regimes (including forested, offshore, and hilly terrain cases) over heights corresponding to multi-megawatt wind turbine rotors, also considering the effects of atmospheric stability. From this we find empirical forms for the probability distribution of veer during high-veer (stable) conditions and for the variability in veer conditioned on wind speed. Analyzing observed joint probability distributions of α and veer, we compare the two simplified forms we derived earlier and adapt them to ultimately arrive at more universally applicable equations to predict the mean veer in terms of observed (i.e., conditioned on) shear exponent; lastly, the limitations, applicability, and behavior of these forms are discussed along with their use and further developments for both meteorology and wind energy.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44219466","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}
A. Clifton, S. Barber, Andrew Bray, P. Enevoldsen, Jason M. Fields, A. Sempreviva, Lindy Williams, J. Quick, M. Purdue, Philip Totaro, Yu-Shan Ding
Abstract. The availability of large amounts of data is starting to impact how the wind energy community works. From turbine design to plant layout, construction, commissioning, and maintenance and operations, new processes and business models are springing up. This is the process of digitalisation, and it promises improved efficiency and greater insight, ultimately leading to increased energy capture and significant savings for wind plant operators, thus reducing the levelised cost of energy. Digitalisation is also impacting research, where it is both easing and speeding up collaboration, as well as making research results more accessible. This is the basis for innovations that can be taken up by end users. But digitalisation faces barriers. This paper uses a literature survey and the results from an expert elicitation to identify three common industry-wide barriers to the digitalisation of wind energy. Comparison with other networked industries and past and ongoing initiatives to foster digitalisation show that these barriers can only be overcome by wide-reaching strategic efforts, and so we see these as “grand challenges” in the digitalisation of wind energy. They are, first, creating FAIR data frameworks; secondly, connecting people and data to foster innovation; and finally, enabling collaboration and competition between organisations. The grand challenges in the digitalisation of wind energy thus include a mix of technical, cultural, and business aspects that will need collaboration between businesses, academia, and government to solve. Working to mitigate them is the beginning of a dynamic process that will position wind energy as an essential part of a global clean energy future.
{"title":"Grand challenges in the digitalisation of wind energy","authors":"A. Clifton, S. Barber, Andrew Bray, P. Enevoldsen, Jason M. Fields, A. Sempreviva, Lindy Williams, J. Quick, M. Purdue, Philip Totaro, Yu-Shan Ding","doi":"10.5194/wes-8-947-2023","DOIUrl":"https://doi.org/10.5194/wes-8-947-2023","url":null,"abstract":"Abstract. The availability of large amounts of data is starting to impact how the\u0000wind energy community works. From turbine design to plant layout,\u0000construction, commissioning, and maintenance and operations, new\u0000processes and business models are springing up. This is the process of\u0000digitalisation, and it promises improved efficiency and greater insight,\u0000ultimately leading to increased energy capture and significant savings\u0000for wind plant operators, thus reducing the levelised cost of energy.\u0000Digitalisation is also impacting research, where it is both easing and\u0000speeding up collaboration, as well as making research results more\u0000accessible. This is the basis for innovations that can be taken up by\u0000end users. But digitalisation faces barriers. This paper uses a\u0000literature survey and the results from an expert elicitation to identify\u0000three common industry-wide barriers to the digitalisation of wind\u0000energy. Comparison with other networked industries and past and ongoing\u0000initiatives to foster digitalisation show that these barriers can only\u0000be overcome by wide-reaching strategic efforts, and so we see these as\u0000“grand challenges” in the digitalisation of wind energy. They are,\u0000first, creating FAIR data frameworks; secondly, connecting people and data to foster innovation; and finally, enabling collaboration and competition between organisations. The grand challenges in the digitalisation of wind energy thus include a mix of technical, cultural, and business aspects that\u0000will need collaboration between businesses, academia, and government to\u0000solve. Working to mitigate them is the beginning of a dynamic process\u0000that will position wind energy as an essential part of a global clean\u0000energy future.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48964756","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}
Moritz Gräfe, Vasilis Pettas, J. Gottschall, P. Cheng
Abstract. Inflow wind field measurements from nacelle-based lidar systems offer great potential for different applications including turbine control, load validation, and power performance measurements. On floating wind turbines nacelle-based lidar measurements are affected by the dynamic behavior of the floating foundations. Therefore, the effects on lidar wind speed measurements induced by floater dynamics must be understood. In this work, we investigate the influence of floater motions on wind speed measurements from forward-looking nacelle-based lidar systems mounted on floating offshore wind turbines (FOWTs) and suggest approaches for correcting motion-induced effects. We use an analytical model, employing the guide for the expression of uncertainty in measurements (GUM) methodology and a numerical lidar simulation for the quantification of uncertainties. It is found that the uncertainty of lidar wind speed estimates is mainly caused by the fore–aft motion of the lidar, resulting from the pitch displacement of the floater. Therefore, the uncertainty is heavily dependent on the amplitude and the frequency of the pitch motion. The bias of 10 min mean wind speed estimates is mainly influenced by the mean pitch angle of the floater and the pitch amplitude. We correct motion-induced biases in time-averaged lidar wind speed measurements with a model-based approach, employing the developed analytical model for uncertainty and bias quantification. Testing of the approach with simulated dynamics from two different FOWT concepts shows good results with remaining mean errors below 0.1 m s−1. For the correction of motion-induced fluctuation in instantaneous measurements, we use a frequency filter to correct fluctuations caused by floater pitch motions for instantaneous measurements. The correction approach's performance depends on the pitch period and amplitude of the FOWT design.
摘要基于机舱的激光雷达系统的流入风场测量为不同的应用提供了巨大的潜力，包括涡轮机控制、负载验证和功率性能测量。在浮动风力涡轮机上，基于机舱的激光雷达测量受到浮动基础动态行为的影响。因此，必须了解漂浮物动力学对激光雷达风速测量的影响。在这项工作中，我们研究了漂浮物运动对安装在漂浮式离岸风力涡轮机（FOWT）上的基于机舱的前瞻性激光雷达系统风速测量的影响，并提出了校正运动引起的影响的方法。我们使用分析模型，采用测量不确定性表达指南（GUM）方法和激光雷达数值模拟来量化不确定性。研究发现，激光雷达风速估计的不确定性主要是由漂浮物的俯仰位移引起的激光雷达的前后运动引起的。因此，不确定性在很大程度上取决于俯仰运动的幅度和频率。10的偏差 最小平均风速估计主要受浮筒的平均桨距角和桨距振幅的影响。我们使用基于模型的方法校正了时间平均激光雷达风速测量中由运动引起的偏差，采用了所开发的不确定性和偏差量化分析模型。使用来自两个不同FOWT概念的模拟动力学对该方法进行的测试显示出良好的结果，剩余平均误差低于0.1 m s−1.为了校正瞬时测量中的运动引起的波动，我们使用频率滤波器来校正瞬时测量的浮子俯仰运动引起的变化。校正方法的性能取决于FOWT设计的基音周期和幅度。
{"title":"Quantification and correction of motion influence for nacelle-based lidar systems on floating wind turbines","authors":"Moritz Gräfe, Vasilis Pettas, J. Gottschall, P. Cheng","doi":"10.5194/wes-8-925-2023","DOIUrl":"https://doi.org/10.5194/wes-8-925-2023","url":null,"abstract":"Abstract. Inflow wind field measurements from nacelle-based lidar systems offer great potential for different applications including turbine control, load\u0000validation, and power performance measurements. On floating wind turbines nacelle-based lidar measurements are affected by the dynamic behavior of\u0000the floating foundations. Therefore, the effects on lidar wind speed measurements induced by floater dynamics must be understood. In this work, we investigate the influence of floater motions on wind speed measurements from forward-looking nacelle-based lidar systems mounted on floating\u0000offshore wind turbines (FOWTs) and suggest approaches for correcting motion-induced effects. We use an analytical model, employing the guide for the expression of uncertainty in measurements (GUM) methodology and a numerical lidar simulation for the quantification of uncertainties. It is found that the uncertainty of lidar wind speed estimates is mainly caused by the fore–aft motion of the lidar, resulting from the pitch displacement of the floater. Therefore, the uncertainty is heavily dependent on the amplitude and the frequency of the pitch motion. The bias of 10 min mean wind speed estimates is mainly influenced by the mean pitch angle of the floater and the pitch amplitude. We correct motion-induced biases in time-averaged lidar wind speed measurements with a model-based approach, employing the developed analytical model for uncertainty and bias quantification. Testing of the approach with simulated dynamics from two different FOWT concepts shows good results with remaining mean errors below 0.1 m s−1. For the correction of motion-induced fluctuation in instantaneous measurements, we use a frequency filter to correct fluctuations caused by floater pitch motions for instantaneous measurements. The correction approach's performance depends on the pitch period and amplitude of the FOWT design.\u0000","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43949003","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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