Wind Flow Conditions in Offshore Wind Farms: Validation and Application of a CFD Wake Model

Green ◽  
2013 ◽  
Vol 3 (1) ◽  
Author(s):  
Annette Westerhellweg ◽  
Beatriz Cañadillas ◽  
Friederike Kinder ◽  
Thomas Neumann
Keyword(s):  
Wind Farm ◽  
Atmospheric Stability ◽  
Wind Farms ◽  
Offshore Wind ◽  
Wind Flow ◽  
Flow Conditions ◽  
Offshore Wind Farms ◽  
Speed Reduction ◽  
Wake Model ◽  
The Impact

AbstractSince August 2009, the first German offshore wind farm ‘alpha ventus’ is operating close to the wind measurement platform FINO1. Within the research project RAVE-OWEA the wind flow conditions in ‘alpha ventus’ were assessed in detail, simulated with a CFD wake model and compared with the measurements. Wind data measured at FINO1 have been evaluated for wind speed reduction and turbulence increase in the wake. Additionally operational data were evaluated for the farm efficiency. The atmospheric stability has been evaluated by temperature measurements of air and water and the impact of atmospheric stability on the wind conditions in the wake has been assessed. As an application of CFD models the generation of power matrices is introduced. Power matrices can be used for the continual monitoring of the single wind turbines in the wind farm. A power matrix based on CFD simulations has been created for ‘alpha ventus’ and tested against the measured data.

Wind Flow Conditions in Offshore Wind Farms: Validation and Application of a CFD Wake Model

ENERGYO ◽  
2018 ◽  
Author(s):  
Annette Westerhellweg ◽  
Beatriz Cañadillas ◽  
Friederike Kinder ◽  
Thomas Neumann
Keyword(s):  
Wind Farms ◽  
Offshore Wind ◽  
Wind Flow ◽  
Flow Conditions ◽  
Offshore Wind Farms ◽  
Wake Model

An ecosystem approach for studying the impact of offshore wind farms: a French case study

2018 ◽  
Vol 77 (3) ◽  
pp. 1238-1246 ◽  
Author(s):  
Jean-Philippe Pezy ◽  
Aurore Raoux ◽  
Jean-Claude Dauvin
Keyword(s):  
Network Analysis ◽  
Wind Farm ◽  
Wind Farms ◽  
Sampling Strategy ◽  
Ecosystem Approach ◽  
Offshore Wind ◽  
Ecosystem Structure ◽  
Offshore Wind Farms ◽  
Ecopath Model ◽  
The Impact

Abstract The French government is planning the construction of offshore wind farms (OWF) in the next decade (around 2900 MW). Following the European Environmental Impact Assessment Directive 85/337/EEC, several studies have been undertaken to identify the environmental conditions and ecosystem functioning at selected sites prior to OWF construction. However, these studies are generally focused on the conservation of some species and there is no holistic approach for analysing the effects arising from OWF construction and operation. The objective of this article is to promote a sampling strategy to collect data on the different ecosystem compartments of the future Dieppe-Le Tréport (DLT) wind farm site, adopting an ecosystem approach, which could be applied to other OWFs for the implementation of a trophic network analysis. For that purpose, an Ecopath model is used here to derive indices from Ecological Network Analysis (ENA) to investigate the ecosystem structure and functioning. The results show that the ecosystem is most likely detritus-based, associated with a biomass dominated by bivalves, which could act as a dead end for a classic trophic food web since their consumption by top predators is low in comparison to their biomass. The systemic approach developed for DLT OWF site should be applied for other French and European installations of Offshore Wind Farm.

scholarly journals Theory and Verification of a new 3D RANS Wake Model

2020 ◽  
Author(s):  
Philip Bradstock ◽  
Wolfgang Schlez
Keyword(s):  
Wind Farm ◽  
Three Dimensional ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Ambient Flow ◽  
Turbulence Decay ◽  
Local Shear ◽  
Time Lagged ◽  
Wake Model

Abstract. This paper details the background to the WakeBlaster model: a purpose built, parabolic three-dimensional RANS solver, developed by ProPlanEn. WakeBlaster is a field model, rather than a single turbine model; it therefore eliminates the need for an empirical wake superposition model. It belongs to a class of very fast (a few core seconds, per flow case) mid-fidelity models, which are designed for industrial application in wind farm design, operation and control. The domain is a three-dimensional structured grid, with approximately 80 nodes covering the rotor disk, by default. WakeBlaster uses eddy viscosity turbulence closure, which is parameterized by the local shear, time-lagged turbulence development, and stability corrections for ambient shear and turbulence decay. The model prescribes a profile at the end of the near-wake, and the spatial variation of ambient flow, by using output from an external flow model. The WakeBlaster model is verified, calibrated and validated using a large volume of data from multiple onshore and offshore wind farms. This paper presents example simulations for one offshore wind farm.

scholarly journals Coastal protection of the Romanian nearshore throughout hybrid wave and offshore wind farms

2018 ◽  
Vol 51 ◽  
pp. 01004
Author(s):  
Alina Raileanu ◽  
Florin Onea ◽  
Liliana Rusu
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Wave Model ◽  
Reference Points ◽  
Offshore Wind ◽  
Wave Transformation ◽  
The Black Sea ◽  
Coastal Protection ◽  
Offshore Wind Farms ◽  
The Impact

The objective of the present work is to estimate the influence of several hybrid wind and wave farm configurations on the wave conditions reported in the vicinity of the Saint George coastal area, in the Romanian nearshore of the Black Sea. Based on the wave data coming from a climatological database (ERA20C) and also on in situ measurements, it was possible to identify the most relevant wave patterns, which will be further considered for assessment. The numerical simulations were carried out with the SWAN (Simulating Waves Nearshore) wave model, which may provide a comprehensive picture of the wave transformation in the presence of the marine farms. Although the impact of the wind farm is not visible from the spatial maps, from the analysis of the values corresponding to the reference points, it was noticed that a maximum variation of 2% may occur for several wave parameters.

scholarly journals COASTAL BATHYMETRY FROM SATELLITE AND ITS USE ON COASTAL MODELLING

2018 ◽  
pp. 98
Author(s):  
Rodolfo Bolaños ◽  
Lars Boye Hansen ◽  
Mikkel Lydholm Rasmussen ◽  
Maziar Golestani ◽  
Jesper Sandvig Mariegaard ◽  
...  
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Wave Model ◽  
Added Value ◽  
Offshore Wind ◽  
Irregular Waves ◽  
Offshore Wind Farms ◽  
High Resolution Satellite Images ◽  
Sentinel 2A ◽  
The Impact

Offshore wind farms around the world are being developed with the objective of increasing the contribution of renewable energy to the global energy consumption. Bathymetric features at the wind farm sites have a strong influence on waves and currents, controlling the propagation and dissipation of flows during normal and extreme conditions. In this work we use a state-of-the-art cost-effective method for bathymetric mapping based on high resolution satellite images to characterize a coastal wind farm region and assess the added value of such data when performing wave modelling. The study area is characterized by the presence of offshore wind farms and a complex bathymetry that feature sand bars and channels. For this study, a satellite derived bathymetry (SDB) was produced using imagery from the Sentinel-2A satellite. The Sentinel-2a data allows for more detailed SDB retrieval than is available in the existing accessible bathymetric datasets. The data is then used in a spectral wave model (MIKE21SW) with different resolutions outlining the impact of large bedforms on surface waves, mainly due to wave breaking. The bathymetry data is also used in a phase-resolving model (MIKE3waveFM) where regular and irregular waves are simulated, outlining the impact of bedforms on individual wave dissipation. Discussion on the satellite derived bathymetry and wave models results are presented in this paper.

scholarly journals Simulation Based Investigation of the Impact of Information Sharing on the Offshore Wind Farm Installation Process

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Moritz Quandt ◽  
Thies Beinke ◽  
Abderrahim Ait-Alla ◽  
Michael Freitag
Keyword(s):  
Resource Availability ◽  
Information Acquisition ◽  
Wind Farm ◽  
Wind Farms ◽  
Limited Resource ◽  
Energy Generation ◽  
Green Energy ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
The Impact

In the recent decades, the introduction of a sustainable and green energy infrastructure, and, by this, the reduction of emissions caused by fossil energy generation, has been focused on by industry-oriented nations worldwide. Among the technologies of renewable energy generation, wind energy has the highest deployment rate, due to the high wind resource availability and the high technology maturity reached mainly by the onshore installation of wind turbines. However, the planning and the installation of offshore wind farms are a challenging task, because of harsh weather conditions and limited resource availability. Due to the current practice of decentralised information acquisition by the supply chain partners, we investigate the impact of sharing information on the installation process of offshore wind farms by means of a simulation model. Therefore, relevant information items will be identified in order to improve the installation process.

scholarly journals The Methodology for Assessing the Impact of Offshore Wind Farms on Navigation, Based on the Automatic Identification System Historical Data

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6559
Author(s):  
Krzysztof Naus ◽  
Katarzyna Banaszak ◽  
Piotr Szymak
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Offshore Wind ◽  
Automatic Identification ◽  
Identification System ◽  
Large Set ◽  
Data Set ◽  
Offshore Wind Farms ◽  
Automatic Identification System ◽  
The Impact

Mounting offshore renewable energy installations often involves extra risk regarding the safety of navigation, especially for areas with high traffic intensity. The decision-makers planning such projects need to anticipate and plan appropriate solutions in order to manage navigation risks. This process is referred to as “environmental impact assessment”. In what way can these threats be reduced using the available Automatic Identification System (AIS) tool? This paper presents a study of the concept for the methodology of an a posteriori vessel traffic description in the form of quantitative and qualitative characteristics created based on a large set of historical AIS data (big data). The research was oriented primarily towards the practical application and verification of the methodology used when assessing the impact of the planned Offshore Wind Farm (OWF) Baltic II on the safety of ships in Polish Marine Areas, and on the effectiveness of navigation, taking into account the existing shipping routes and customary and traffic separation systems. The research results (e.g., a significant distance of the Baltic II from the nearest customary shipping route equal to 3 Nm, a small number of vessels in its area in 2017 amounting to only 930) obtained on the basis of the annual AIS data set allowed for an unambiguous and reliable assessment of the impact of OWFs on shipping, thus confirming the suitability of the methodology for MREI spatial planning.

scholarly journals Coastal protection of the Romanian nearshore throughout hybrid wave and offshore wind farms

2018 ◽  
Vol 51 ◽  
pp. 01004
Author(s):  
Alina Raileanu ◽  
Florin Onea ◽  
Liliana Rusu
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Wave Model ◽  
Reference Points ◽  
Offshore Wind ◽  
Wave Transformation ◽  
The Black Sea ◽  
Coastal Protection ◽  
Offshore Wind Farms ◽  
The Impact

The objective of the present work is to estimate the influence of several hybrid wind and wave farm configurations on the wave conditions reported in the vicinity of the Saint George coastal area, in the Romanian nearshore of the Black Sea. Based on the wave data coming from a climatological database (ERA20C) and also on in situ measurements, it was possible to identify the most relevant wave patterns, which will be further considered for assessment. The numerical simulations were carried out with the SWAN (Simulating Waves Nearshore) wave model, which may provide a comprehensive picture of the wave transformation in the presence of the marine farms. Although the impact of the wind farm is not visible from the spatial maps, from the analysis of the values corresponding to the reference points, it was noticed that a maximum variation of 2% may occur for several wave parameters.

scholarly journals Observed and simulated turbulent kinetic energy (WRF 3.8.1) overlarge offshore wind farms

2019 ◽  
Author(s):  
Simon K. Siedersleben ◽  
Andreas Platis ◽  
Julie K. Lundquist ◽  
Bughsin Djath ◽  
Astrid Lampert ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Wind Farm ◽  
Wind Farms ◽  
Horizontal Resolution ◽  
Offshore Wind ◽  
Vertical Resolution ◽  
Offshore Wind Farms ◽  
The Impact ◽  
Simulated Wind

Abstract. Because wind farms affect local weather and microclimates, parameterizations of their effects have been developed for numerical weather prediction models. While most wind farm parameterizations (WFP) include drag effects of wind farms, models differ on whether or not an additional turbulent kinetic energy (TKE) source should be included in these parameterizations to simulate the impact of wind farms on the boundary layer. Therefore, we use aircraft measurements above large offshore wind farms in stable conditions to evaluate WFP choices. Of the three case studies we examine, we find the simulated ambient background flow to agree with observations of temperature stratification and winds. This agreement allowing us to explore the sensitivity of simulated wind farm effects with respect to modeling choices such as whether or not to include a TKE source, horizontal resolution, vertical resolution, and advection of TKE. For a stably stratified marine atmospheric boundary layer (MABL), a TKE source and a horizontal resolution in the order of 5 km or finer are necessary to represent the impact of offshore wind farms on the MABL. Additionally, TKE advection results in excessively reduced TKE over the wind farms, which in turn causes an underestimation of the wind speed above the wind farm. Furthermore, using fine vertical resolution increases the agreement of the simulated wind speed with satellite observations of surface wind speed.

scholarly journals An analysis of offshore wind farm SCADA measurements to identify key parameters influencing the magnitude of wake effects

2017 ◽  
Vol 2 (2) ◽  
pp. 477-490 ◽  
Author(s):  
Niko Mittelmeier ◽  
Julian Allin ◽  
Tomas Blodau ◽  
Davide Trabucchi ◽  
Gerald Steinfeld ◽  
...  
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Average Power ◽  
Atmospheric Stability ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Offshore Wind Farms ◽  
Partial Load ◽  
Wake Effects

Abstract. For offshore wind farms, wake effects are among the largest sources of losses in energy production. At the same time, wake modelling is still associated with very high uncertainties. Therefore current research focusses on improving wake model predictions. It is known that atmospheric conditions, especially atmospheric stability, crucially influence the magnitude of those wake effects. The classification of atmospheric stability is usually based on measurements from met masts, buoys or lidar (light detection and ranging). In offshore conditions these measurements are expensive and scarce. However, every wind farm permanently produces SCADA (supervisory control and data acquisition) measurements. The objective of this study is to establish a classification for the magnitude of wake effects based on SCADA data. This delivers a basis to fit engineering wake models better to the ambient conditions in an offshore wind farm. The method is established with data from two offshore wind farms which each have a met mast nearby. A correlation is established between the stability classification from the met mast and signals within the SCADA data from the wind farm. The significance of these new signals on power production is demonstrated with data from two wind farms with met mast and long-range lidar measurements. Additionally, the method is validated with data from another wind farm without a met mast. The proposed signal consists of a good correlation between the standard deviation of active power divided by the average power of wind turbines in free flow with the ambient turbulence intensity (TI) when the wind turbines were operating in partial load. It allows us to distinguish between conditions with different magnitudes of wake effects. The proposed signal is very sensitive to increased turbulence induced by neighbouring turbines and wind farms, even at a distance of more than 38 rotor diameters.

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