scholarly journals Model for evaluation of technical and economic indicators of offshore wind farms

Author(s):  
D. Y. Davydov ◽  
S. G. Obukhov

THE PURPOSE. An urgent problem in the development of offshore wind energy is the high cost of generating electricity, which is due to large capital investments. The solution to this problem is possible by increasing efficiency while reducing costs as much as possible, which requires optimal design of offshore wind farms.GOAL. Development of model for the technical and economic indicators of offshore wind farms based on configuration data, taking into account the factors of climatic conditions and the topography of the seabed at the site of the planned wind farm location.METHODS. Mathematical modeling using Matlab software environment.RESULTS. The model evaluates the impact of wake and electrical losses in the main components of the electrical system on the operation of an offshore wind farm, and also allows to take into account the influence of the seabed relief on the economic characteristics of wind turbine foundations. The model was tested on the example of calculating two existing offshore wind farms «Horns Rev 1» and «Horn Rev 2» by comparing the calculated indicators of the average annual electricity generation, capacity factor, capital expenditures and normalized cost of electricity with the actual indicators obtained during their operation. The comparison results show slight deviations within 5% of the actual values.CONCLUSION. The model for assessing the technical and economic indicators of offshore wind farms was developed and tested on the basis of data on the wind farm configuration and layout, as well as factors of climatic conditions and terrain. Evaluation of the computational speed showed a sufficiently high efficiency of the algorithm, which allows the model to be applied to optimize large offshore wind farms.

2018 ◽  
Vol 77 (3) ◽  
pp. 1238-1246 ◽  
Author(s):  
Jean-Philippe Pezy ◽  
Aurore Raoux ◽  
Jean-Claude Dauvin

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.


2018 ◽  
Vol 51 ◽  
pp. 01004
Author(s):  
Alina Raileanu ◽  
Florin Onea ◽  
Liliana Rusu

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.


Green ◽  
2013 ◽  
Vol 3 (1) ◽  
Author(s):  
Annette Westerhellweg ◽  
Beatriz Cañadillas ◽  
Friederike Kinder ◽  
Thomas Neumann

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.


Author(s):  
Rodolfo Bolaños ◽  
Lars Boye Hansen ◽  
Mikkel Lydholm Rasmussen ◽  
Maziar Golestani ◽  
Jesper Sandvig Mariegaard ◽  
...  

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.


2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Moritz Quandt ◽  
Thies Beinke ◽  
Abderrahim Ait-Alla ◽  
Michael Freitag

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.


Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6559
Author(s):  
Krzysztof Naus ◽  
Katarzyna Banaszak ◽  
Piotr Szymak

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.


2018 ◽  
Vol 51 ◽  
pp. 01004
Author(s):  
Alina Raileanu ◽  
Florin Onea ◽  
Liliana Rusu

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.


2019 ◽  
Author(s):  
Simon K. Siedersleben ◽  
Andreas Platis ◽  
Julie K. Lundquist ◽  
Bughsin Djath ◽  
Astrid Lampert ◽  
...  

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.


2020 ◽  
Vol 13 (1) ◽  
pp. 249-268 ◽  
Author(s):  
Simon K. Siedersleben ◽  
Andreas Platis ◽  
Julie K. Lundquist ◽  
Bughsin Djath ◽  
Astrid Lampert ◽  
...  

Abstract. Wind farms affect local weather and microclimates; hence, parameterizations of their effects have been developed for numerical weather prediction models. While most wind farm parameterizations (WFPs) 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 allows 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 on 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 deficit above the wind farm. Furthermore, using fine vertical resolution increases the agreement of the simulated wind speed with satellite observations of surface wind speed.


2010 ◽  
Vol 27 (8) ◽  
pp. 1302-1317 ◽  
Author(s):  
R. J. Barthelmie ◽  
S. C. Pryor ◽  
S. T. Frandsen ◽  
K. S. Hansen ◽  
J. G. Schepers ◽  
...  

Abstract There is an urgent need to develop and optimize tools for designing large wind farm arrays for deployment offshore. This research is focused on improving the understanding of, and modeling of, wind turbine wakes in order to make more accurate power output predictions for large offshore wind farms. Detailed data ensembles of power losses due to wakes at the large wind farms at Nysted and Horns Rev are presented and analyzed. Differences in turbine spacing (10.5 versus 7 rotor diameters) are not differentiable in wake-related power losses from the two wind farms. This is partly due to the high variability in the data despite careful data screening. A number of ensemble averages are simulated with a range of wind farm and computational fluid dynamics models and compared to observed wake losses. All models were able to capture wake width to some degree, and some models also captured the decrease of power output moving through the wind farm. Root-mean-square errors indicate a generally better model performance for higher wind speeds (10 rather than 6 m s−1) and for direct down the row flow than for oblique angles. Despite this progress, wake modeling of large wind farms is still subject to an unacceptably high degree of uncertainty.


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