Elie Kadoche, Pascal Bianchi, Florence Carton, Philippe Ciblat, Damien Ernst
Abstract. Wake steering is a technique that optimizes the energy production of a wind farm by employing yaw control to misalign upstream turbines with the incoming wind direction. This work highlights the important dependence between wind direction variations and wake steering optimization. The problem is formalized over time as the succession of multiple steady-state yaw control problems interconnected by the rotational constraints of the turbines and the evolution of the wind. Then, this work proposes a reformulation of the yaw optimization problem of each time step by augmenting the objective function by a new heuristic based on a wind prediction. The heuristic acts as a penalization for the optimization, encouraging solutions that will guarantee future energy production. Finally, a synthetic sensitivity analysis of the wind direction variations and wake steering optimization is conducted. Because of the rotational constraints of the turbines, as the magnitude of the wind direction fluctuations increases, the importance of considering wind prediction in a steady-state optimization is empirically demonstrated. The heuristic proposed in this work greatly improves the performance of controllers and significantly reduces the complexity of the original sequential decision problem by decreasing the number of decision variables.
{"title":"On the importance of wind predictions in wake steering optimization","authors":"Elie Kadoche, Pascal Bianchi, Florence Carton, Philippe Ciblat, Damien Ernst","doi":"10.5194/wes-9-1577-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1577-2024","url":null,"abstract":"Abstract. Wake steering is a technique that optimizes the energy production of a wind farm by employing yaw control to misalign upstream turbines with the incoming wind direction. This work highlights the important dependence between wind direction variations and wake steering optimization. The problem is formalized over time as the succession of multiple steady-state yaw control problems interconnected by the rotational constraints of the turbines and the evolution of the wind. Then, this work proposes a reformulation of the yaw optimization problem of each time step by augmenting the objective function by a new heuristic based on a wind prediction. The heuristic acts as a penalization for the optimization, encouraging solutions that will guarantee future energy production. Finally, a synthetic sensitivity analysis of the wind direction variations and wake steering optimization is conducted. Because of the rotational constraints of the turbines, as the magnitude of the wind direction fluctuations increases, the importance of considering wind prediction in a steady-state optimization is empirically demonstrated. The heuristic proposed in this work greatly improves the performance of controllers and significantly reduces the complexity of the original sequential decision problem by decreasing the number of decision variables.\u0000","PeriodicalId":509667,"journal":{"name":"Wind Energy Science","volume":"6 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141808044","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. We present a new model to estimate the performance of a wind turbine operating in misaligned conditions. The model is based on the classic momentum and lifting-line theories, considering a misaligned rotor as a lifting wing of finite span, and accounts for the combined effects of both yaw and uptilt angles. Improving on the classical empirical cosine law in widespread use, the new model reveals the dependency of power not only on the misalignment angle, but also on some rotor design parameters and – crucially – on the way a rotor is governed when it is yawed out of the wind. We show how the model can be readily integrated with arbitrary control laws below, above, and around the rated wind speed. Additionally, the model also shows that a sheared inflow is responsible for the observed lack of symmetry for positive and negative misalignment angles. Notwithstanding its simplicity and insignificant computational cost, the new proposed approach is in excellent agreement with large eddy simulations (LESs) and wind tunnel experiments. Building on the new model, we derive the optimal control strategy for maximizing power on a misaligned rotor. Additionally, we maximize the total power of a cluster of two turbines by wake steering, improving on the solution based on the cosine law.
{"title":"On the power and control of a misaligned rotor – beyond the cosine law","authors":"Simone Tamaro, F. Campagnolo, C. Bottasso","doi":"10.5194/wes-9-1547-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1547-2024","url":null,"abstract":"Abstract. We present a new model to estimate the performance of a wind turbine operating in misaligned conditions. The model is based on the classic momentum and lifting-line theories, considering a misaligned rotor as a lifting wing of finite span, and accounts for the combined effects of both yaw and uptilt angles. Improving on the classical empirical cosine law in widespread use, the new model reveals the dependency of power not only on the misalignment angle, but also on some rotor design parameters and – crucially – on the way a rotor is governed when it is yawed out of the wind. We show how the model can be readily integrated with arbitrary control laws below, above, and around the rated wind speed. Additionally, the model also shows that a sheared inflow is responsible for the observed lack of symmetry for positive and negative misalignment angles. Notwithstanding its simplicity and insignificant computational cost, the new proposed approach is in excellent agreement with large eddy simulations (LESs) and wind tunnel experiments. Building on the new model, we derive the optimal control strategy for maximizing power on a misaligned rotor. Additionally, we maximize the total power of a cluster of two turbines by wake steering, improving on the solution based on the cosine law.\u0000","PeriodicalId":509667,"journal":{"name":"Wind Energy Science","volume":"80 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810170","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. Large direct-drive wind turbines with a multi-megawatt power rating face design challenges, especially concerning tower top mass, due to scaling laws for high-torque generators. This work proposes to extend the design space by moving towards a more system-oriented approach, considering electro-mechanical interactions. This requires an extension of the state-of-the-art wind turbine models with additional degrees of freedom. To limit the computational effort of such models, a profound understanding of possible interaction mechanisms is required. This work aims to identify interactions of an additional degree of freedom in the radial direction of the generator with the wind turbine structure, the aerodynamics, and the wind turbine controller. Therefore, a Simpack model of the IEA 15 MW RWT is implemented and coupled to a quasi-static analytical generator model for electromagnetic forces. The analytical model, sourced from literature, is code-to-code validated against a finite element model of the generator in COMSOL Multiphysics. Electro-mechanical simulation results do not show interactions with the aerodynamics or the controller. However, interactions with the wind turbine structure occur. It is shown that the modelling approach can affect the system's natural frequencies, which can potentially impact the overall system design choices.
{"title":"Identification of electro-mechanical interactions in wind turbines","authors":"F. D. Lüdecke, Martin Schmid, Po Wen Cheng","doi":"10.5194/wes-9-1527-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1527-2024","url":null,"abstract":"Abstract. Large direct-drive wind turbines with a multi-megawatt power rating face design challenges, especially concerning tower top mass, due to scaling laws for high-torque generators. This work proposes to extend the design space by moving towards a more system-oriented approach, considering electro-mechanical interactions. This requires an extension of the state-of-the-art wind turbine models with additional degrees of freedom. To limit the computational effort of such models, a profound understanding of possible interaction mechanisms is required. This work aims to identify interactions of an additional degree of freedom in the radial direction of the generator with the wind turbine structure, the aerodynamics, and the wind turbine controller. Therefore, a Simpack model of the IEA 15 MW RWT is implemented and coupled to a quasi-static analytical generator model for electromagnetic forces. The analytical model, sourced from literature, is code-to-code validated against a finite element model of the generator in COMSOL Multiphysics. Electro-mechanical simulation results do not show interactions with the aerodynamics or the controller. However, interactions with the wind turbine structure occur. It is shown that the modelling approach can affect the system's natural frequencies, which can potentially impact the overall system design choices.\u0000","PeriodicalId":509667,"journal":{"name":"Wind Energy Science","volume":"16 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816521","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}
Diederik van Binsbergen, P. Daems, T. Verstraeten, Amir R. Nejad, J. Helsen
Abstract. This work presents a robust methodology for calibrating analytical wake models, as demonstrated on the velocity deficit parameters of the Gauss–curl hybrid model using 4 years of time series supervisory control and data acquisition (SCADA) data from an offshore wind farm, with a tree-structured Parzen estimator employed as a sampler. Initially, a sensitivity analysis of wake parameters and their linear correlation is conducted. The wake model is used with a turbulence intensity of 0.06, and no blockage model is considered. Results show that the tuning parameters that are multiplied by the turbine-specific turbulence intensity pose higher sensitivity than tuning parameters not giving weight to the turbulence intensity. It is also observed that the optimization converges with a higher residual error when inflow wind conditions are affected by neighbouring wind farms. The significance of this effect becomes apparent when the energy yield of turbines situated in close proximity to nearby wind farms is compared. Sensitive parameters show strong convergence, while parameters with low sensitivity show significant variance after optimization. Additionally, coastal influences are observed to affect the calibrated results, with wind from land leading to faster wake recovery than wind from the sea. Given the assumption of constant turbulence intensity in this work, recalibration is required when more representative site-specific turbulence intensity measurements are used as input to the model. Caution is advised when using these results without considering underlying model assumptions and site-specific characteristics, as these findings may not be generalizable to other locations without further recalibration.
{"title":"Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm","authors":"Diederik van Binsbergen, P. Daems, T. Verstraeten, Amir R. Nejad, J. Helsen","doi":"10.5194/wes-9-1507-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1507-2024","url":null,"abstract":"Abstract. This work presents a robust methodology for calibrating analytical wake models, as demonstrated on the velocity deficit parameters of the Gauss–curl hybrid model using 4 years of time series supervisory control and data acquisition (SCADA) data from an offshore wind farm, with a tree-structured Parzen estimator employed as a sampler. Initially, a sensitivity analysis of wake parameters and their linear correlation is conducted. The wake model is used with a turbulence intensity of 0.06, and no blockage model is considered. Results show that the tuning parameters that are multiplied by the turbine-specific turbulence intensity pose higher sensitivity than tuning parameters not giving weight to the turbulence intensity. It is also observed that the optimization converges with a higher residual error when inflow wind conditions are affected by neighbouring wind farms. The significance of this effect becomes apparent when the energy yield of turbines situated in close proximity to nearby wind farms is compared. Sensitive parameters show strong convergence, while parameters with low sensitivity show significant variance after optimization. Additionally, coastal influences are observed to affect the calibrated results, with wind from land leading to faster wake recovery than wind from the sea. Given the assumption of constant turbulence intensity in this work, recalibration is required when more representative site-specific turbulence intensity measurements are used as input to the model. Caution is advised when using these results without considering underlying model assumptions and site-specific characteristics, as these findings may not be generalizable to other locations without further recalibration.\u0000","PeriodicalId":509667,"journal":{"name":"Wind Energy Science","volume":"51 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141654458","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. P. Kidambi Sekar, P. Hulsman, M. V. van Dooren, Martin Kühn
Abstract. Field measurements of the flow interaction between the near wake of an upstream wind turbine and the induction zone of a downstream turbine are scarce. Measuring and characterising these flow features in wind farms under various operational states can be used to evaluate numerical flow models and design of control systems. In this paper, we present induction zone measurements of a utility-scale 3.5 MW turbine with a rotor diameter of 126 m in a two-turbine wind farm operating under waked and unwaked conditions. The measurements were acquired by two synchronised continuous-wave WindScanner lidars that could resolve longitudinal and lateral velocities by dual-Doppler reconstruction. An error analysis was performed to quantify the uncertainty in measuring complex flow situations with two WindScanners. This is done by performing a large-eddy simulation while using the same measurement layout, modelling the WindScanner sensing characteristics and simulating similar inflow conditions observed in the field. The flow evolution in the induction zone of the downstream turbine was characterised by performing horizontal-plane dual-Doppler scans at hub height. The measurements were conducted for undisturbed, fully waked and partially waked flows. Evaluation of the engineering models of the undisturbed induction zone showed good agreement along the rotor axis. In the full-wake case, the measurements indicated a deceleration of the upstream turbine wake due to the downstream turbine induction zone as a result of the very short turbine spacing. During a wake steering experiment, the interaction between the laterally deflected wake of the upstream turbine and the induction zone of the downstream turbine could be measured for the first time in the field. Additionally, the analyses highlight the affiliated challenges while conducting field measurements with synchronised lidars.
{"title":"Synchronised WindScanner field measurements of the induction zone between two closely spaced wind turbines","authors":"A. P. Kidambi Sekar, P. Hulsman, M. V. van Dooren, Martin Kühn","doi":"10.5194/wes-9-1483-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1483-2024","url":null,"abstract":"Abstract. Field measurements of the flow interaction between the near wake of an upstream wind turbine and the induction zone of a downstream turbine are scarce. Measuring and characterising these flow features in wind farms under various operational states can be used to evaluate numerical flow models and design of control systems. In this paper, we present induction zone measurements of a utility-scale 3.5 MW turbine with a rotor diameter of 126 m in a two-turbine wind farm operating under waked and unwaked conditions. The measurements were acquired by two synchronised continuous-wave WindScanner lidars that could resolve longitudinal and lateral velocities by dual-Doppler reconstruction. An error analysis was performed to quantify the uncertainty in measuring complex flow situations with two WindScanners. This is done by performing a large-eddy simulation while using the same measurement layout, modelling the WindScanner sensing characteristics and simulating similar inflow conditions observed in the field. The flow evolution in the induction zone of the downstream turbine was characterised by performing horizontal-plane dual-Doppler scans at hub height. The measurements were conducted for undisturbed, fully waked and partially waked flows. Evaluation of the engineering models of the undisturbed induction zone showed good agreement along the rotor axis. In the full-wake case, the measurements indicated a deceleration of the upstream turbine wake due to the downstream turbine induction zone as a result of the very short turbine spacing. During a wake steering experiment, the interaction between the laterally deflected wake of the upstream turbine and the induction zone of the downstream turbine could be measured for the first time in the field. Additionally, the analyses highlight the affiliated challenges while conducting field measurements with synchronised lidars.\u0000","PeriodicalId":509667,"journal":{"name":"Wind Energy Science","volume":"116 42","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141665647","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}
Edgar Werthen, Daniel Hardt, C. Balzani, Christian Hühne
Abstract. During the preliminary design phase of wind turbine blades, the evaluation of many design candidates in a short period of time plays an important role. Computationally efficient methods for the structural analysis that correctly predict stiffness matrix entries for beam models including the (bend–twist) coupling terms are thus needed. The present paper provides an extended overview of available approaches and shows their abilities to fulfill the requirements for the composite design of rotor blades with respect to accuracy and computational efficiency. Three cross-sectional theories are selected and implemented to compare the prediction quality of the cross-sectional coupling stiffness terms and the stress distribution based on different multi-cell test cross-sections. The cross-sectional results are compared with the 2D finite element code BECAS and are discussed in the context of accuracy and computational efficiency. The analytical solution performing best shows very small deviations in the stiffness matrix entries compared to BECAS (below 1 % in the majority of test cases). It achieved a better resolution of the stress distribution and a computation time that is more than an order of magnitude smaller using the same spatial discretization. The deviations of the stress distributions are below 10 % for most test cases. The analytical solution can thus be rated as a feasible approach for a beam-based pre-design of wind turbine rotor blades.
{"title":"Comparison of different cross-sectional approaches for the structural design and optimization of composite wind turbine blades based on beam models","authors":"Edgar Werthen, Daniel Hardt, C. Balzani, Christian Hühne","doi":"10.5194/wes-9-1465-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1465-2024","url":null,"abstract":"Abstract. During the preliminary design phase of wind turbine blades, the evaluation of many design candidates in a short period of time plays an important role. Computationally efficient methods for the structural analysis that correctly predict stiffness matrix entries for beam models including the (bend–twist) coupling terms are thus needed. The present paper provides an extended overview of available approaches and shows their abilities to fulfill the requirements for the composite design of rotor blades with respect to accuracy and computational efficiency. Three cross-sectional theories are selected and implemented to compare the prediction quality of the cross-sectional coupling stiffness terms and the stress distribution based on different multi-cell test cross-sections. The cross-sectional results are compared with the 2D finite element code BECAS and are discussed in the context of accuracy and computational efficiency. The analytical solution performing best shows very small deviations in the stiffness matrix entries compared to BECAS (below 1 % in the majority of test cases). It achieved a better resolution of the stress distribution and a computation time that is more than an order of magnitude smaller using the same spatial discretization. The deviations of the stress distributions are below 10 % for most test cases. The analytical solution can thus be rated as a feasible approach for a beam-based pre-design of wind turbine rotor blades.\u0000","PeriodicalId":509667,"journal":{"name":"Wind Energy Science","volume":" 626","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141669284","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. The wind turbine design process requires performing thousands of simulations for a wide range of inflow and control conditions, which necessitates computationally efficient yet time-accurate models, especially when considering wind farm settings. To this end, FAST.Farm is a dynamic-wake-meandering-based mid-fidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. This work is an extension of a study that addressed constructing a diurnal cycle evolution based on experimental data (Quon, 2024). Here, this inflow is used to validate the turbine structural and wake-meandering response between experimental data, FAST.Farm simulation results, and high-fidelity large-eddy simulation results from the coupled Simulator fOr Wind Farm Applications (SOWFA)–OpenFAST tool. The validation occurs within the nocturnal stable boundary layer when corresponding meteorological and turbine data are available. To this end, we compared the load results from FAST.Farm and SOWFA–OpenFAST to multi-turbine measurements from a subset of a full-scale wind farm. Computational predictions of blade-root and tower-base bending loads are compared to 10 min statistics of strain gauge measurements during 3.5 h of the evolving stable boundary layer, generally with good agreement. This time period coincided with an active wake-steering campaign of an upstream turbine, resulting in time-varying yaw positions of all turbines. Wake meandering was also compared between the computational solutions, generally with excellent agreement. Simulations were based on a high-fidelity precursor constructed from inflow measurements and using state-of-the-art mesoscale-to-microscale coupling.
{"title":"Wind farm structural response and wake dynamics for an evolving stable boundary layer: computational and experimental comparisons","authors":"K. Shaler, E. Quon, Hristo Ivanov, J. Jonkman","doi":"10.5194/wes-9-1451-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1451-2024","url":null,"abstract":"Abstract. The wind turbine design process requires performing thousands of simulations for a wide range of inflow and control conditions, which necessitates computationally efficient yet time-accurate models, especially when considering wind farm settings. To this end, FAST.Farm is a dynamic-wake-meandering-based mid-fidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. This work is an extension of a study that addressed constructing a diurnal cycle evolution based on experimental data (Quon, 2024). Here, this inflow is used to validate the turbine structural and wake-meandering response between experimental data, FAST.Farm simulation results, and high-fidelity large-eddy simulation results from the coupled Simulator fOr Wind Farm Applications (SOWFA)–OpenFAST tool. The validation occurs within the nocturnal stable boundary layer when corresponding meteorological and turbine data are available. To this end, we compared the load results from FAST.Farm and SOWFA–OpenFAST to multi-turbine measurements from a subset of a full-scale wind farm. Computational predictions of blade-root and tower-base bending loads are compared to 10 min statistics of strain gauge measurements during 3.5 h of the evolving stable boundary layer, generally with good agreement. This time period coincided with an active wake-steering campaign of an upstream turbine, resulting in time-varying yaw positions of all turbines. Wake meandering was also compared between the computational solutions, generally with excellent agreement. Simulations were based on a high-fidelity precursor constructed from inflow measurements and using state-of-the-art mesoscale-to-microscale coupling.\u0000","PeriodicalId":509667,"journal":{"name":"Wind Energy Science","volume":"5 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141686132","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}
Daniel R. Houck, Nathaniel B. de Velder, David C. Maniaci, Brent C. Houchens
Abstract. Experiments offer incredible value to science, but results must always come with an uncertainty quantification to be meaningful. This requires grappling with sources of uncertainty and how to reduce them. In wind energy, field experiments are sometimes conducted with a control and treatment. In this scenario uncertainty due to bias errors can often be neglected as they impact both control and treatment approximately equally. However, uncertainty due to random errors propagates such that the uncertainty in the difference between the control and treatment is always larger than the random uncertainty in the individual measurements if the sources are uncorrelated. As random uncertainties are usually reduced with additional measurements, there is a need to know the minimum duration of an experiment required to reach acceptable levels of uncertainty. We present a general method to simulate a proposed experiment, calculate uncertainties, and determine both the measurement duration and the experiment duration required to produce statistically significant and converged results. The method is then demonstrated as a case study with a virtual experiment that uses real-world wind resource data and several simulated tip extensions to parameterize results by the expected difference in power. With the method demonstrated herein, experiments can be better planned by accounting for specific details such as controller switching schedules, wind statistics, and postprocess binning procedures such that their impacts on uncertainty can be predicted and the measurement duration needed to achieve statistically significant and converged results can be determined before the experiment.
{"title":"Method to predict the minimum measurement and experiment durations needed to achieve converged and significant results in a wind energy field experiment","authors":"Daniel R. Houck, Nathaniel B. de Velder, David C. Maniaci, Brent C. Houchens","doi":"10.5194/wes-9-1189-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1189-2024","url":null,"abstract":"Abstract. Experiments offer incredible value to science, but results must always come with an uncertainty quantification to be meaningful. This requires grappling with sources of uncertainty and how to reduce them. In wind energy, field experiments are sometimes conducted with a control and treatment. In this scenario uncertainty due to bias errors can often be neglected as they impact both control and treatment approximately equally. However, uncertainty due to random errors propagates such that the uncertainty in the difference between the control and treatment is always larger than the random uncertainty in the individual measurements if the sources are uncorrelated. As random uncertainties are usually reduced with additional measurements, there is a need to know the minimum duration of an experiment required to reach acceptable levels of uncertainty. We present a general method to simulate a proposed experiment, calculate uncertainties, and determine both the measurement duration and the experiment duration required to produce statistically significant and converged results. The method is then demonstrated as a case study with a virtual experiment that uses real-world wind resource data and several simulated tip extensions to parameterize results by the expected difference in power. With the method demonstrated herein, experiments can be better planned by accounting for specific details such as controller switching schedules, wind statistics, and postprocess binning procedures such that their impacts on uncertainty can be predicted and the measurement duration needed to achieve statistically significant and converged results can be determined before the experiment.\u0000","PeriodicalId":509667,"journal":{"name":"Wind Energy Science","volume":"28 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140968553","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}
E. Fritz, André F. P. Ribeiro, K. Boorsma, Carlos Ferreira
Abstract. This study presents results from a wind tunnel experiment on a three-bladed horizontal axis wind turbine. The model turbine is a scaled-down version of the IEA 15 MW reference wind turbine, preserving the non-dimensional thrust distribution along the blade. Flow fields were captured around the blade at multiple radial locations using particle image velocimetry. In addition to these flow fields, this comprehensive dataset contains spanwise distributions of bound circulation, inflow conditions and blade forces derived from the velocity field. As such, the three blades' aerodynamics are fully characterised. It is demonstrated that the lift coefficient measured along the span agrees well with the lift polar of the airfoil used in the blade design, thereby validating the experimental approach. This research provides a valuable public experimental dataset for validating low- to high-fidelity numerical models simulating state-of-the-art wind turbines. Furthermore, this article establishes the aerodynamic properties of the newly developed model wind turbine, creating a baseline for future wind tunnel experiments using this model.
{"title":"Aerodynamic characterisation of a thrust-scaled IEA 15 MW wind turbine model: experimental insights using PIV data","authors":"E. Fritz, André F. P. Ribeiro, K. Boorsma, Carlos Ferreira","doi":"10.5194/wes-9-1173-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1173-2024","url":null,"abstract":"Abstract. This study presents results from a wind tunnel experiment on a three-bladed horizontal axis wind turbine. The model turbine is a scaled-down version of the IEA 15 MW reference wind turbine, preserving the non-dimensional thrust distribution along the blade. Flow fields were captured around the blade at multiple radial locations using particle image velocimetry. In addition to these flow fields, this comprehensive dataset contains spanwise distributions of bound circulation, inflow conditions and blade forces derived from the velocity field. As such, the three blades' aerodynamics are fully characterised. It is demonstrated that the lift coefficient measured along the span agrees well with the lift polar of the airfoil used in the blade design, thereby validating the experimental approach. This research provides a valuable public experimental dataset for validating low- to high-fidelity numerical models simulating state-of-the-art wind turbines. Furthermore, this article establishes the aerodynamic properties of the newly developed model wind turbine, creating a baseline for future wind tunnel experiments using this model.\u0000","PeriodicalId":509667,"journal":{"name":"Wind Energy Science","volume":"28 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140975692","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. Mesoscale modeling can be used to analyze key parameters for wind turbine load assessment in a large variety of tropical cyclones. However, the modeled wind structure of tropical cyclones is known to be sensitive to the boundary layer scheme. We analyze modeled wind speed, shear, and wind veer across a wind turbine rotor plane in the eyewall and outer cyclone. We further assess the sensitivity of wind speed, shear, and veer to the boundary layer parametrization. Three model realizations of Typhoon Megi are analyzed over the open ocean using three frequently used boundary layer schemes in the Weather Research and Forecasting (WRF) model. All three typhoon simulations reasonably reproduce the cyclone track and structure. The boundary layer parametrization causes up to 15 % differences in median wind speed at hub height between the simulations. The simulated wind speed variability also depends on the boundary layer scheme. The modeled median wind shear is smaller than or equal to 0.11 used in the current IEC (International Electrotechnical Commission) standard regardless of the boundary layer scheme for the eyewall and outer cyclone region. However, up to 43.6 % of the simulated wind profiles in the eyewall region exceed 0.11. While the surface inflow angle is sensitive to the boundary layer scheme, wind veer in the lowest 400 m of the atmospheric boundary layer is less affected by the boundary layer scheme. Simulated median wind veer reaches values up to 1.7×10-2° m−1 (1.2×10-2° m−1) in the eyewall region (outer cyclone region) and is relatively small compared to moderate-wind-speed regimes. On average, simulated wind speed shear and wind veer are highest in the eyewall region. Yet strong spatial organization of wind shear and veer along the rainbands may increase wind turbine loads due to rapid changes in the wind profile at the turbine location.
{"title":"Tropical cyclone low-level wind speed, shear, and veer: sensitivity to the boundary layer parametrization in the Weather Research and Forecasting model","authors":"Sara Müller, X. Larsén, D. Verelst","doi":"10.5194/wes-9-1153-2024","DOIUrl":"https://doi.org/10.5194/wes-9-1153-2024","url":null,"abstract":"Abstract. Mesoscale modeling can be used to analyze key parameters for wind turbine load assessment in a large variety of tropical cyclones. However, the modeled wind structure of tropical cyclones is known to be sensitive to the boundary layer scheme. We analyze modeled wind speed, shear, and wind veer across a wind turbine rotor plane in the eyewall and outer cyclone. We further assess the sensitivity of wind speed, shear, and veer to the boundary layer parametrization. Three model realizations of Typhoon Megi are analyzed over the open ocean using three frequently used boundary layer schemes in the Weather Research and Forecasting (WRF) model. All three typhoon simulations reasonably reproduce the cyclone track and structure. The boundary layer parametrization causes up to 15 % differences in median wind speed at hub height between the simulations. The simulated wind speed variability also depends on the boundary layer scheme. The modeled median wind shear is smaller than or equal to 0.11 used in the current IEC (International Electrotechnical Commission) standard regardless of the boundary layer scheme for the eyewall and outer cyclone region. However, up to 43.6 % of the simulated wind profiles in the eyewall region exceed 0.11. While the surface inflow angle is sensitive to the boundary layer scheme, wind veer in the lowest 400 m of the atmospheric boundary layer is less affected by the boundary layer scheme. Simulated median wind veer reaches values up to 1.7×10-2° m−1 (1.2×10-2° m−1) in the eyewall region (outer cyclone region) and is relatively small compared to moderate-wind-speed regimes. On average, simulated wind speed shear and wind veer are highest in the eyewall region. Yet strong spatial organization of wind shear and veer along the rainbands may increase wind turbine loads due to rapid changes in the wind profile at the turbine location.\u0000","PeriodicalId":509667,"journal":{"name":"Wind Energy Science","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140982041","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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