Ten Years of Meteorological Measurements for Offshore Wind Farms

2005 ◽  
Vol 127 (2) ◽  
pp. 170-176 ◽  
Author(s):  
Rebecca Barthelmie ◽  
Ole Frost Hansen ◽  
Karen Enevoldsen ◽  
Jørgen Højstrup ◽  
Sten Frandsen ◽  
...  
Keyword(s):  
Wind Speed ◽  
Power Output ◽  
Wind Farms ◽  
Offshore Wind ◽  
Short Term ◽  
Offshore Wind Farms ◽  
Monitoring Strategies ◽  
Wind Resource ◽  
Wind Resources

Risø has been monitoring wind resources and power output from offshore wind farms since 1993. A considerable degree of expertise has been developed in optimizing measurements and in using these databases to develop and validate models for offshore environments. This paper describes the evolution of monitoring strategies to a fully automated satellite based retrieval that provides near-real time access to offshore data, even at remote stand-alone masts. An overview of wind speed and turbulence at offshore sites in Denmark is given. Finally, three methods of generating long-term wind resource estimates from short-term measurements are outlined.

scholarly journals Assessing Boundary Condition and Parametric Uncertainty in Numerical-Weather-Prediction-Modeled, Long-Term Offshore Wind Speed Through Machine Learning and Analog Ensemble

2021 ◽  
Author(s):  
Nicola Bodini ◽  
Weiming Hu ◽  
Mike Optis ◽  
Guido Cervone ◽  
Stefano Alessandrini
Keyword(s):  
Boundary Condition ◽  
Wind Speed ◽  
Weather Prediction ◽  
Parametric Uncertainty ◽  
Offshore Wind ◽  
Gradient Boosting ◽  
Single Model ◽  
Short Term ◽  
Wind Resource

Abstract. To accurately plan and manage wind power plants, not only does the time-varying wind resource at the site of interest need to be assessed, but also the uncertainty connected to this estimate. Numerical weather prediction (NWP) models at the mesoscale represent a valuable way to characterize the wind resource offshore, given the challenges connected with measuring hub height wind speed. The boundary condition and parametric uncertainty associated with modeled wind speed is often estimated by running a model ensemble. However, creating an NWP ensemble of long-term wind resource data over a large region represents a computational challenge. Here, we propose two approaches to temporally extrapolate wind speed boundary condition and parametric uncertainty using a more convenient setup where a mesoscale ensemble is run over a short-term period (1 year), and only a single model covers the desired long-term period (20 year). We quantify hub-height wind speed boundary condition and parametric uncertainty from the short-term model ensemble as its normalized across-ensemble standard deviation. Then, we develop and apply a gradient-boosting model and an analog ensemble approach to temporally extrapolate such uncertainty to the full 20-year period, where only a single model run is available. As a test case, we consider offshore wind resource characterization in the California Outer Continental Shelf. Both the proposed approaches provide accurate estimates of the long-term wind speed boundary condition and parametric uncertainty across the region (R2 > 0.75), with the gradient-boosting model slightly outperforming the analog ensemble in terms of bias and centered root-mean-square error. At the three offshore wind energy lease areas in the region, we find a long-term median hourly uncertainty between 10 % and 14 % of the mean hub-height wind speed values. Finally, we assess the physical variability of the uncertainty estimates. In general, we find that the wind speed uncertainty increases closer to land. Also, neutral conditions have smaller uncertainty than the stable and unstable cases, and the modeled wind speed in winter has less boundary condition and parametric sensitivity than summer.

Long-term effects of wakes from offshore wind farms on the wind conditions at FINO1

2020 ◽  
Author(s):  
Marcos Ortensi ◽  
Richard Fruehmann ◽  
Thomas Neumann
Keyword(s):  
Wind Speed ◽  
Turbulence Intensity ◽  
Wind Farms ◽  
Offshore Wind ◽  
Wind Flow ◽  
Long Term Effects ◽  
Offshore Wind Farms ◽  
Clear Effect ◽  
Research Platform

<p>Investigation on how the wind conditions at the FINO1 research platform have changed through the construction of new wind farms in the vicinity. The long measurement recorded at FINO1 opens the opportunity to analyze how the progressive construction of wind farms influences the downwind wind conditions over a range of distances. In previous publications it has been shown that the wakes from the nearby wind farms Alpha Ventus, Borkum Riffgrund 1 and Trianel Windpark Borkum I have a clear effect on the wind flow, causing a reduction in wind speed and an increase in turbulence intensity.</p>

A Probabilistic Model for Simulating Long-Term Wind-Power Output

2003 ◽  
Vol 27 (3) ◽  
pp. 167-181 ◽  
Author(s):  
Scott Kennedy ◽  
Peter Rogers
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Wind Power ◽  
Power Output ◽  
Energy Resource ◽  
Autoregressive Process ◽  
Resource Planning ◽  
Offshore Wind ◽  
Arbitrary Length

This paper describes a chronological wind-plant simulation model for use in long-term energy resource planning. The model generates wind-power time series of arbitrary length that accurately reproduce short-term (hourly) to long-term (yearly) statistical behaviour. The modelling objective and methodology differ from forecasting models, which focus on minimizing prediction error. In the present analysis, periodic cycles are isolated from historical wind-speed data from a known local site and combined with a first-order autoregressive process to produce a wind-speed time series model. Corrections for negative wind-speed values and spatial smoothing for geographically disperse wind turbines are discussed. The resulting model is used to simulate the output from a hypothetical offshore wind-plant south of Long Island, New York. Modelled differences of power output between individual turbines result from wind speed variability; wake effects are not considered in this analysis.

scholarly journals Development of offshore wind energy of Ukraine in the Sea of Azov: the geographical aspect

2021 ◽  
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbines ◽  
Wind Farms ◽  
Offshore Wind ◽  
Limiting Factors ◽  
Sea Of Azov ◽  
Energy Potential ◽  
Offshore Wind Farms ◽  
The Sea Of Azov

Formulation of the problem. Ukraine's energy sector is import-dependent, and one of the country’s sustainable development goals until 2030 is to ensure access to affordable, reliable, sustainable and modern energy sources. The wind potential of the mainland of our country has been thoroughly studied, so the focus of our interest is water areas, which are promising for the development of offshore wind energy. Offshore wind farms in Ukraine could improve the environmental situation and considerably contribute to the decarbonization of domestic energy. That is why the study considers the opportunity of offshore wind farms installation in the Sea of Azov. Methods. The analysis of literary and cartographic sources has been carried out. Mathematical methods have been used to calculate energy indicators. Using geoinformation modeling, taking into account limiting factors, suitable for the installation of offshore wind farms areas have been identified in the Sea of Azov. The purpose of the article is to geographically analyze the wind energy potential of the Sea of Azov with further assessment of the suitability of areas for the offshore wind farms location. Results. Our research has shown that the installation of offshore wind farms is appropriate in the Sea of Azov, because many areas are characterized by average annual wind speed above 6 meters per second. The most promising areas are the northern and northeastern coasts, where wind speed at different altitudes ranges from 8 to 9.3 meters per second. At altitudes of 50, 100 and 200 m, under the action of limiting factors, the most promising for offshore wind turbines areas are reduced by 8–22%. As considered limiting factors (territorial waters, nature protection objects, settlements and airports) have identical influence regardless of height, it is more effective to install wind turbines with a tower height of more than 100 m in the waters of the Sea of Azov. Interdisciplinary research is needed for the final answer on the effectiveness of offshore wind turbines in the Sea of Azov. Scientific novelty and practical significance. The results of the analysis of the wind energy potential of the Sea of Azov have been given, the tendency of its growth from the west to the east has been revealed. Attention has been paid to the method of geoinformation modeling of the location of offshore wind farms taking into account limiting factors. Maps of wind speed, potential of electricity generated by a single wind turbine and suitability of areas of the Sea of Azov for the location of offshore wind farms at an altitude of 200 m above sea level have been presented. These data can be used by designers of wind energy facilities as a basis for determining the optimal power of wind turbines and the type of energy for a particular area of the Sea of Azov.

scholarly journals Exploitation of the far-offshore wind energy resource by fleets of energy ships – Part 2: Updated ship design and cost of energy estimate

2021 ◽  
Author(s):  
Aurélien Babarit ◽  
Félix Gorintin ◽  
Pierrick de Belizal ◽  
Antoine Neau ◽  
Giovanni Bordogna ◽  
...  
Keyword(s):  
Wind Energy ◽  
Energy Resource ◽  
Wind Farms ◽  
Energy Performance ◽  
Ship Design ◽  
Offshore Wind ◽  
Offshore Wind Energy ◽  
Ocean Engineering ◽  
Offshore Wind Farms

Abstract. This paper deals with a new concept for the conversion of far-offshore wind energy into sustainable fuel. It relies on autonomous sailing energy ships and manned support tankers. Energy ships are wind-propelled ships that generate electricity using water turbines attached underneath their hull. Since energy ships are not grid-connected, they include onboard power-to-X plants for storage of the produced energy. In the present work, the energy vector X is methanol. In the first part of this study (Babarit et al., 2020), an energy ship design has been proposed and its energy performance has been assessed. In this second part, the aim is to estimate the energy and economic performance of such system. In collaboration with ocean engineering, marine renewable energy and wind-assisted propulsion’s experts, the energy ship design of the first part has been revised and updated. Based on this new design, a complete FARWIND energy system is proposed, and its costs (CAPEX and OPEX) are estimated. Results of the models show (i) that this FARWIND system could produce approximately 70,000 tonnes of methanol per annum (approximately 400 GWh per annum of chemical energy) at a cost in the range 1.2 to 3.6 €/kg, (ii) that this cost may be comparable to that of methanol produced by offshore wind farms in the long term, and (iii) that FARWIND-produced methanol (and offshore wind farms-produced methanol) could compete with gasoline on the EU transportation fuel market in the long term.

scholarly journals Floating Offshore Wind Farms in Italy beyond 2030 and beyond 2060: Preliminary Results of a Techno-Economic Assessment

2020 ◽  
Vol 10 (24) ◽  
pp. 8899
Author(s):  
Laura Serri ◽  
Lisa Colle ◽  
Bruno Vitali ◽  
Tullia Bonomi
Keyword(s):  
Wind Turbines ◽  
Weighted Average ◽  
Wind Farms ◽  
Economic Assessment ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Cost Of Energy ◽  
Cost Reductions ◽  
Marine Areas ◽  
Wind Resource

At the end of 2019, 10.5 GW of wind capacity was installed in Italy, all onshore. The National Integrated Climate and Energy Plan sets a target of 18.4 GW of onshore wind capacity and 0.9 GW of offshore wind capacity by 2030. Significant exploitation of offshore wind resources in Italy is expected after 2030, using floating wind turbines, suitable for water depths greater than 50 m. This technology is at the demonstration phase at present. Results of a preliminary techno-economic assessment of floating wind plants in Italian marine areas in a medium (2030) and long-term (2060) scenario are presented. In 2030, a reference park with 10 MW wind turbines will be defined, and parametric costs, depending on distance from shore, were assessed. In 2060, possible wind resource variations due to climate change, and cost reductions due to large diffusion of the technology were considered in three case studies. The economic model used was the simple Levelized Cost of Energy (sLCoE). Different values of Weighted Average Cost of Capital (WACC) were considered too. The results show LCoEs comparable to the ones expected for the sector in 2030. In 2060, even in the more pessimistic scenario, wind resource decreases will be abundantly compensated by expected cost reductions.

Sign in / Sign up

Export Citation Format

Share Document