Pub Date : 2024-06-01DOI: 10.1088/1742-6596/2767/2/022031
Abhyuday Aditya, D. de Tavernier, F. Schrijer, B. V. van Oudheusden, D. Von Terzi
For the largest wind turbines currently designed, when operating at rated power and at high wind speeds, the tip airfoils can experience large negative angles of attack. For these conditions and in combination with turbulence, the airfoils are at risk of reaching locally supersonic flow, even at low free-stream Mach numbers. The possibility of shock wave formation and its consequences endangers the lifetime of these largest rotating machines ever built. So far only numerical analyses of this challenge have been attempted with significant modelling uncertainty. Here, for the first time, a wind turbine airfoil (the FFA-W3-211, used at the blade tip of the IEA 15MW reference wind turbine) is studied under transonic conditions using experimental techniques. Schlieren visualization and Particle Image Velocimetry were employed for free-stream Mach numbers of 0.5 and 0.6 and various angles of attack. It was shown that calculations based on isentropic flow theory and compressibility corrections were able to predict the situations where supersonic flow occurred. However, they could not predict the frequency of occurrence and whether shock waves were formed. In conclusion, an unsteady characterization of such airfoil behavior in transonic flow seems to be warranted.
{"title":"Experimental investigation of the occurrence of transonic flow effects on the FFA-W3-211 airfoil","authors":"Abhyuday Aditya, D. de Tavernier, F. Schrijer, B. V. van Oudheusden, D. Von Terzi","doi":"10.1088/1742-6596/2767/2/022031","DOIUrl":"https://doi.org/10.1088/1742-6596/2767/2/022031","url":null,"abstract":"For the largest wind turbines currently designed, when operating at rated power and at high wind speeds, the tip airfoils can experience large negative angles of attack. For these conditions and in combination with turbulence, the airfoils are at risk of reaching locally supersonic flow, even at low free-stream Mach numbers. The possibility of shock wave formation and its consequences endangers the lifetime of these largest rotating machines ever built. So far only numerical analyses of this challenge have been attempted with significant modelling uncertainty. Here, for the first time, a wind turbine airfoil (the FFA-W3-211, used at the blade tip of the IEA 15MW reference wind turbine) is studied under transonic conditions using experimental techniques. Schlieren visualization and Particle Image Velocimetry were employed for free-stream Mach numbers of 0.5 and 0.6 and various angles of attack. It was shown that calculations based on isentropic flow theory and compressibility corrections were able to predict the situations where supersonic flow occurred. However, they could not predict the frequency of occurrence and whether shock waves were formed. In conclusion, an unsteady characterization of such airfoil behavior in transonic flow seems to be warranted.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141408467","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}
Pub Date : 2024-06-01DOI: 10.1088/1742-6596/2767/3/032004
S. Cioni, F. Papi, Emanuele Cocchi, A. Bianchini
Stall regulation turbines still represent the preferred solution for small wind turbines. In stall-controlled rotors the controller plays a key role but, differently from pitch-based ones, no open-source controller was available to date. The study presents the UNICO (UNIfi research COntroller) controller, which has been specifically developed for variable speed stall-regulated turbines. The controller has been developed in MATLAB® Simulink® and a dynamic link library (.dll) has been generated, which can be coupled with common simulation codes such as OpenFAST and QBlade using a Bladed-style interface. UNICO includes features that are specifically tailored to variable-speed stall-regulated turbines. For below-rated conditions, the controller employs either the commonly used k-ω2 law or a tracking of the optimal tip speed ratio. For above-rated conditions, a PI controller is used to track a user-imposed reference speed. The reference speed is set to decrease linearly with wind speed, providing a safety margin for turbine operation at higher wind speeds. UNICO has been tested on a 50-kW stall-regulated reference turbine. Preliminary results show how the proposed controller can achieve better overall performance in comparison to the simplified control laws implemented in state-of-the-art codes. Additionally, the rotor speed can be controlled in above-rated conditions, providing an increased run away safety margin.
{"title":"UNICO: an open-source controller optimized for stall-regulated wind turbines","authors":"S. Cioni, F. Papi, Emanuele Cocchi, A. Bianchini","doi":"10.1088/1742-6596/2767/3/032004","DOIUrl":"https://doi.org/10.1088/1742-6596/2767/3/032004","url":null,"abstract":"Stall regulation turbines still represent the preferred solution for small wind turbines. In stall-controlled rotors the controller plays a key role but, differently from pitch-based ones, no open-source controller was available to date. The study presents the UNICO (UNIfi research COntroller) controller, which has been specifically developed for variable speed stall-regulated turbines. The controller has been developed in MATLAB® Simulink® and a dynamic link library (.dll) has been generated, which can be coupled with common simulation codes such as OpenFAST and QBlade using a Bladed-style interface. UNICO includes features that are specifically tailored to variable-speed stall-regulated turbines. For below-rated conditions, the controller employs either the commonly used k-ω2 law or a tracking of the optimal tip speed ratio. For above-rated conditions, a PI controller is used to track a user-imposed reference speed. The reference speed is set to decrease linearly with wind speed, providing a safety margin for turbine operation at higher wind speeds. UNICO has been tested on a 50-kW stall-regulated reference turbine. Preliminary results show how the proposed controller can achieve better overall performance in comparison to the simplified control laws implemented in state-of-the-art codes. Additionally, the rotor speed can be controlled in above-rated conditions, providing an increased run away safety margin.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141410762","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}
Pub Date : 2024-06-01DOI: 10.1088/1742-6596/2767/5/052059
A. Patel, E. Muller, F. Houtin-Mongrolle
During the last two decades, wind turbine wakes have been extensively studied in academia by implementing the Actuator Line method in numerous Large Eddy Simulation solvers tailored for atmospheric flows. However, and while being computationally affordable for ad hoc deep investigations, this approach remains barely used in industry. One of the leading causes is the complexity of the simulation process, which still involves several aspects to be carefully looked at to get valuable results in output. This paper aims to present a workflow that merges and automates the different steps required to conduct aero-servo-elastic Large Eddy Simulations of wind turbines. In particular, a strategy based on an Accurate Conservative Level Set function is used to flag the regions where wakes propagate. This allows to automatically derive refinement zones that cover the wakes at all times. This generic procedure can be seamlessly applied to various farm layouts and inflow conditions. To display the capabilities of the workflow, it is applied to several configurations, including one to seven wind turbines for different inflow conditions. It is observed that lower wind speeds require larger mesh to capture the wake dynamics adequately. Overall, the workflow offers the added advantage of significantly reducing the required human effort while standardizing the process. This is important from an industrial perspective, wherein parametric studies are usually carried out as part of the design process.
{"title":"Towards an automated framework for Aero-Servo-Elastic Large Eddy Simulation of wind turbine wakes","authors":"A. Patel, E. Muller, F. Houtin-Mongrolle","doi":"10.1088/1742-6596/2767/5/052059","DOIUrl":"https://doi.org/10.1088/1742-6596/2767/5/052059","url":null,"abstract":"During the last two decades, wind turbine wakes have been extensively studied in academia by implementing the Actuator Line method in numerous Large Eddy Simulation solvers tailored for atmospheric flows. However, and while being computationally affordable for ad hoc deep investigations, this approach remains barely used in industry. One of the leading causes is the complexity of the simulation process, which still involves several aspects to be carefully looked at to get valuable results in output. This paper aims to present a workflow that merges and automates the different steps required to conduct aero-servo-elastic Large Eddy Simulations of wind turbines. In particular, a strategy based on an Accurate Conservative Level Set function is used to flag the regions where wakes propagate. This allows to automatically derive refinement zones that cover the wakes at all times. This generic procedure can be seamlessly applied to various farm layouts and inflow conditions. To display the capabilities of the workflow, it is applied to several configurations, including one to seven wind turbines for different inflow conditions. It is observed that lower wind speeds require larger mesh to capture the wake dynamics adequately. Overall, the workflow offers the added advantage of significantly reducing the required human effort while standardizing the process. This is important from an industrial perspective, wherein parametric studies are usually carried out as part of the design process.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141390066","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}
Pub Date : 2024-06-01DOI: 10.1088/1742-6596/2767/9/092025
G. Bangga, E. Bossanyi
A new framework “BladedFarmWake” to include the upstream wake effects into a wind turbine design tool Bladed was developed in the present work. The effects of neighboring turbines in a wind farm are extracted from a wind farm flow solver LongSim, which has been developed for designing wind farm controllers and evaluating wind farm performance, taking account of atmospheric conditions and wake effects including the importance of turbine layouts and individual turbine or wind farm control strategies. These wind farm effects are incorporated into Bladed simulations to obtain time accurate load analyses. BladedFarmWake is designed to work with less human interaction as much as possible, allowing the tool to be adopted in large scale load analyses within the wind turbine design load cases (DLCs). It is demonstrated that the timeseries of the wind flow field and the wake meandering effects are successfully modelled in the framework. The effects of velocity deficit and the wake added turbulence are well captured in the generated turbulent data. As a consequence of the velocity deficit from the upstream turbine, the hub load changes considerably due to the wake meandering effects. The newly developed integrated framework will be of value for wind turbine engineers to incorporate wind farm effects in the design process.
{"title":"BladedFarmWake: A framework for evaluating the influence of upstream wakes on turbine loads using Bladed","authors":"G. Bangga, E. Bossanyi","doi":"10.1088/1742-6596/2767/9/092025","DOIUrl":"https://doi.org/10.1088/1742-6596/2767/9/092025","url":null,"abstract":"A new framework “BladedFarmWake” to include the upstream wake effects into a wind turbine design tool Bladed was developed in the present work. The effects of neighboring turbines in a wind farm are extracted from a wind farm flow solver LongSim, which has been developed for designing wind farm controllers and evaluating wind farm performance, taking account of atmospheric conditions and wake effects including the importance of turbine layouts and individual turbine or wind farm control strategies. These wind farm effects are incorporated into Bladed simulations to obtain time accurate load analyses. BladedFarmWake is designed to work with less human interaction as much as possible, allowing the tool to be adopted in large scale load analyses within the wind turbine design load cases (DLCs). It is demonstrated that the timeseries of the wind flow field and the wake meandering effects are successfully modelled in the framework. The effects of velocity deficit and the wake added turbulence are well captured in the generated turbulent data. As a consequence of the velocity deficit from the upstream turbine, the hub load changes considerably due to the wake meandering effects. The newly developed integrated framework will be of value for wind turbine engineers to incorporate wind farm effects in the design process.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141390366","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}
Pub Date : 2024-06-01DOI: 10.1088/1742-6596/2781/1/012008
Ge-wei Zhuang, Zhen Gu, He Qing, Jing-yue Zhang, Hong-hong Zhang, Lei Zhou
For a long time, abnormal metering of electricity meters has caused huge economic losses to power grid companies. Abnormal diagnosis of power metering is an important means to ensure the normal operation of electricity meters and power automation operation and maintenance systems and is a hot topic of research for power workers. This article proposes a known measurement anomaly diagnosis model based on small sample learning to address the problem of insufficient labeled samples in power measurement anomaly diagnosis. The embedded network maps samples from the original sample space to the embedded space adjusts the embedded network structure, and improves the loss function. The experimental results show that the improved classification network has a higher recognition accuracy for known anomalies than the original network and other small sample learning models.
{"title":"Research on abnormal diagnosis model of electric power measurement based on small sample learning","authors":"Ge-wei Zhuang, Zhen Gu, He Qing, Jing-yue Zhang, Hong-hong Zhang, Lei Zhou","doi":"10.1088/1742-6596/2781/1/012008","DOIUrl":"https://doi.org/10.1088/1742-6596/2781/1/012008","url":null,"abstract":"For a long time, abnormal metering of electricity meters has caused huge economic losses to power grid companies. Abnormal diagnosis of power metering is an important means to ensure the normal operation of electricity meters and power automation operation and maintenance systems and is a hot topic of research for power workers. This article proposes a known measurement anomaly diagnosis model based on small sample learning to address the problem of insufficient labeled samples in power measurement anomaly diagnosis. The embedded network maps samples from the original sample space to the embedded space adjusts the embedded network structure, and improves the loss function. The experimental results show that the improved classification network has a higher recognition accuracy for known anomalies than the original network and other small sample learning models.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141392756","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}
Pub Date : 2024-06-01DOI: 10.1088/1742-6596/2767/3/032007
Sarah Barber, Yuriy Marykovskiy, Imad Abdallah
A lack of data sharing in the wind energy sector presents a large barrier to increasing the value of wind energy through innovation. One way of improving data sharing is to make it “FAIR”: findable, accessible, interoperable and reusable. The FAIR Data Maturity Model is a tool developed by the Research Data Alliance that can be used to assess and improve the “FAIRness” of data, by quantifying the extent of its findability, accessibility, interoperability and reusability. In this work, we investigate how the FAIR Data Maturity Model could be applied to improve data sharing in the wind energy sector, via a structural health monitoring (SHM) case study. This case study is created as part of a WeDoWind challenge, and was chosen due to the high potential of SHM in reducing the costs of energy through predictive maintenance. WeDoWind is a framework for creating mutually beneficial collaborations, and the WeDoWind wind energy ecosystem is a growing ecosystem of diverse people all over the world sharing and exchanging knowledge and data. It is found that the FAIRness of the provided data set is limited due to the lack of community standards, and the absence of public data sharing services catering specifically to the wind energy context. However, the FAIR Data Maturity Model is successfully applied to improve the FAIRness of the data sets in the case study. A participant survey shows that this made data sharing easier in the context of a WeDoWind data sharing project. Finally, the project results in a set of recommendations for helping the wind energy community to improve the FAIRness of data.
{"title":"Improving data sharing in wind energy - structural health monitoring case study","authors":"Sarah Barber, Yuriy Marykovskiy, Imad Abdallah","doi":"10.1088/1742-6596/2767/3/032007","DOIUrl":"https://doi.org/10.1088/1742-6596/2767/3/032007","url":null,"abstract":"A lack of data sharing in the wind energy sector presents a large barrier to increasing the value of wind energy through innovation. One way of improving data sharing is to make it “FAIR”: findable, accessible, interoperable and reusable. The FAIR Data Maturity Model is a tool developed by the Research Data Alliance that can be used to assess and improve the “FAIRness” of data, by quantifying the extent of its findability, accessibility, interoperability and reusability. In this work, we investigate how the FAIR Data Maturity Model could be applied to improve data sharing in the wind energy sector, via a structural health monitoring (SHM) case study. This case study is created as part of a WeDoWind challenge, and was chosen due to the high potential of SHM in reducing the costs of energy through predictive maintenance. WeDoWind is a framework for creating mutually beneficial collaborations, and the WeDoWind wind energy ecosystem is a growing ecosystem of diverse people all over the world sharing and exchanging knowledge and data. It is found that the FAIRness of the provided data set is limited due to the lack of community standards, and the absence of public data sharing services catering specifically to the wind energy context. However, the FAIR Data Maturity Model is successfully applied to improve the FAIRness of the data sets in the case study. A participant survey shows that this made data sharing easier in the context of a WeDoWind data sharing project. Finally, the project results in a set of recommendations for helping the wind energy community to improve the FAIRness of data.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141404150","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}
Pub Date : 2024-06-01DOI: 10.1088/1742-6596/2767/9/092078
Alexandros Palatos-Plexidas, Simone Gremmo, S. Porchetta, J. van Beeck, Lesley De Cruz, W. Munters
The rapid expansion of wind farms in the North Sea requires a better understanding of the wind turbines’ wake effects. In this study, the classification of wake patterns under different atmospheric boundary layer stability conditions is investigated. For this purpose, the Weather Research and Forecast model is utilized to calculate wind farm wake effects over the southern North Sea for a year-long period. The atmospheric stability is characterized by the value of Monin-Obukhov length, and seven different classes are considered. The results have shown that the predominance of the stability condition depends on seasonality. In autumn and winter months very unstable conditions prevail, while in spring and summer periods near-neutral and stable events occur more frequently. The different atmospheric stability conditions have distinct effects on the averaged wind-speed deficits. Specifically, in near-neutral and stable stratification, wakes propagate further downwind of the wind turbines affecting neighboring wind farms, while in the case of unstable conditions, these effects are weaker.
{"title":"A numerical analysis of wind farm wake characteristics in the southern part of the North Sea","authors":"Alexandros Palatos-Plexidas, Simone Gremmo, S. Porchetta, J. van Beeck, Lesley De Cruz, W. Munters","doi":"10.1088/1742-6596/2767/9/092078","DOIUrl":"https://doi.org/10.1088/1742-6596/2767/9/092078","url":null,"abstract":"The rapid expansion of wind farms in the North Sea requires a better understanding of the wind turbines’ wake effects. In this study, the classification of wake patterns under different atmospheric boundary layer stability conditions is investigated. For this purpose, the Weather Research and Forecast model is utilized to calculate wind farm wake effects over the southern North Sea for a year-long period. The atmospheric stability is characterized by the value of Monin-Obukhov length, and seven different classes are considered. The results have shown that the predominance of the stability condition depends on seasonality. In autumn and winter months very unstable conditions prevail, while in spring and summer periods near-neutral and stable events occur more frequently. The different atmospheric stability conditions have distinct effects on the averaged wind-speed deficits. Specifically, in near-neutral and stable stratification, wakes propagate further downwind of the wind turbines affecting neighboring wind farms, while in the case of unstable conditions, these effects are weaker.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141397722","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}
This study focuses on the intricate interplay between large wind turbines and their wake effects on neighboring turbines. We specifically investigate the influence in power production and aerodynamic loads when a turbine operates under the influence of upstream turbine wakes. The analysis has been performed by means of Computational Fluid Dynamic simulations using OpenFOAM, while wind turbines are modelled with an Actuator Line Model approach. Two large IEA 15 MW reference wind turbines, with one turbine partially affected by the other’s wake, are analyzed. The research assesses the influence of turbine spacing on aerodynamic torque and blade loads. The study shows that the CP may suffer oscillations 2 orders of magnitude greater than the ones observed at the reference cases. For the most affected case, the torque experiences oscillations of a 5.46 % w.r.t. to the averaged torque over the last ten revolutions. The influence of operating in partial wake conditions is specially relevant on the blade root loads that are found to suffer an increase of ∼ 20 % and a decrease of ∼ 30 % over one revolution as the blade is affected by the highly sheared flow resulting from the upstream wake.
{"title":"Wind turbine power extraction under partial wake operations, a CFD study using ALM.","authors":"Guillén Campaña-Alonso, Esteban Ferrer, Beatriz Méndez-López","doi":"10.1088/1742-6596/2767/9/092097","DOIUrl":"https://doi.org/10.1088/1742-6596/2767/9/092097","url":null,"abstract":"This study focuses on the intricate interplay between large wind turbines and their wake effects on neighboring turbines. We specifically investigate the influence in power production and aerodynamic loads when a turbine operates under the influence of upstream turbine wakes. The analysis has been performed by means of Computational Fluid Dynamic simulations using OpenFOAM, while wind turbines are modelled with an Actuator Line Model approach. Two large IEA 15 MW reference wind turbines, with one turbine partially affected by the other’s wake, are analyzed. The research assesses the influence of turbine spacing on aerodynamic torque and blade loads. The study shows that the CP may suffer oscillations 2 orders of magnitude greater than the ones observed at the reference cases. For the most affected case, the torque experiences oscillations of a 5.46 % w.r.t. to the averaged torque over the last ten revolutions. The influence of operating in partial wake conditions is specially relevant on the blade root loads that are found to suffer an increase of ∼ 20 % and a decrease of ∼ 30 % over one revolution as the blade is affected by the highly sheared flow resulting from the upstream wake.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141390824","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}
Pub Date : 2024-06-01DOI: 10.1088/1742-6596/2767/9/092099
David Bretos, Guillén Campaña-Alonso, Beatriz Méndez-López, Elena Cantero-Nouqueret
Massive deployment of wind energy is critical to achieving the renewable energy production targets. This requires the development and improvement of models and tools for the optimal exploitation of high altitude and complex terrain sites for wind energy installations. Predicting the wind resource assessment of these sites is very challenging, as is predicting the interaction of wind farms in complex terrain with neighbouring installations, which is necessary to maximise the efficiency of wind energy. To address these challenges, the use of high-fidelity Computational Fluid Dynamics (CFD) models is recommended. In this study, the wind resource at the complex terrain site of the CENER experimental wind farm (Alaiz) is evaluated using steady-state RANS CFD simulations performed with OpenFOAM v2212, taking into account the effects of terrain topography and vegetation. Furthermore, a virtual wind farm located at Alaiz is modelled with the Actuator Disk (AD) method to analyse the effect of topography on the the wake evolution.
{"title":"CFD wind farm evaluation in complex terrain under free and wake induced flow conditions","authors":"David Bretos, Guillén Campaña-Alonso, Beatriz Méndez-López, Elena Cantero-Nouqueret","doi":"10.1088/1742-6596/2767/9/092099","DOIUrl":"https://doi.org/10.1088/1742-6596/2767/9/092099","url":null,"abstract":"Massive deployment of wind energy is critical to achieving the renewable energy production targets. This requires the development and improvement of models and tools for the optimal exploitation of high altitude and complex terrain sites for wind energy installations. Predicting the wind resource assessment of these sites is very challenging, as is predicting the interaction of wind farms in complex terrain with neighbouring installations, which is necessary to maximise the efficiency of wind energy. To address these challenges, the use of high-fidelity Computational Fluid Dynamics (CFD) models is recommended. In this study, the wind resource at the complex terrain site of the CENER experimental wind farm (Alaiz) is evaluated using steady-state RANS CFD simulations performed with OpenFOAM v2212, taking into account the effects of terrain topography and vegetation. Furthermore, a virtual wind farm located at Alaiz is modelled with the Actuator Disk (AD) method to analyse the effect of topography on the the wake evolution.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141391382","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}
Pub Date : 2024-06-01DOI: 10.1088/1742-6596/2767/7/072019
Jis Hummel, Tsc Pollack, D. Eijkelhof, E. Van Kampen, R. Schmehl
Airborne wind energy is an emerging technology that uses tethered flying devices to capture stronger and more steady winds at higher altitudes. Compared to smaller systems, megawatt-scale systems are substantially affected by gravity during flight operation, resulting in power fluctuations. MegAWES, a 3 MW reference model, experiences power fluctuations between -5.8 MW and +20.5 MW every 12.5 seconds during the traction phase when using its baseline controller at a wind speed of 22 m/s. The baseline controller does not have a power limit, leading to high peak power, and aims to keep the tether force constant, causing it to consume power when the kite is flying upwards. In this paper, we implement an optimal torque controller in the MegAWES framework and show that this eliminates the power consumption during the traction phase. Furthermore, we propose a kite tether force controller that allows setting a power limit when combined with the 2-phase reeling strategy, which decreases the peak power. Our new architecture reduces the power output range by 75% to between +3.7 MW and +9.4 MW in strong wind conditions.
{"title":"Power smoothing by kite tether force control for megawatt-scale airborne wind energy systems","authors":"Jis Hummel, Tsc Pollack, D. Eijkelhof, E. Van Kampen, R. Schmehl","doi":"10.1088/1742-6596/2767/7/072019","DOIUrl":"https://doi.org/10.1088/1742-6596/2767/7/072019","url":null,"abstract":"Airborne wind energy is an emerging technology that uses tethered flying devices to capture stronger and more steady winds at higher altitudes. Compared to smaller systems, megawatt-scale systems are substantially affected by gravity during flight operation, resulting in power fluctuations. MegAWES, a 3 MW reference model, experiences power fluctuations between -5.8 MW and +20.5 MW every 12.5 seconds during the traction phase when using its baseline controller at a wind speed of 22 m/s. The baseline controller does not have a power limit, leading to high peak power, and aims to keep the tether force constant, causing it to consume power when the kite is flying upwards. In this paper, we implement an optimal torque controller in the MegAWES framework and show that this eliminates the power consumption during the traction phase. Furthermore, we propose a kite tether force controller that allows setting a power limit when combined with the 2-phase reeling strategy, which decreases the peak power. Our new architecture reduces the power output range by 75% to between +3.7 MW and +9.4 MW in strong wind conditions.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141393202","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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