A dynamical downscaling of ERA‐Interim in the North Sea using WRF with a 3 km grid—for wind resource applications

Large offshore wind energy projects are being planned and installed in the North Sea, and there is an urgent demand for high‐resolution atmospheric statistics to assess potential power production and revenue. Meteorological observations are too sparse to obtain those statistics, and global reanalyses like ERA‐Interim have a resolution too coarse in space and time to capture important small‐scale and terrain‐driven features of the atmospheric flow. We therefore dynamically downscale ERA‐Interim with the mesoscale model Weather Research and Forecasting to a 3 km grid to capture those unresolved features, for the period 1999–2008. The large‐scale flow is conditioned by spectral nudging, and we make use of observation nudging towards QuikSCAT near‐surface winds. The downscaling results in 100 m wind‐speed distributions and mean wind speeds, which are closer to the observations than ERA‐Interim, while the accuracy in terms of root‐mean‐square error decreases. The observation nudging partially counteracts this latter effect, improving the root‐mean‐square error of wind speed and direction by 0.5 m s^?1 and ~10°, respectively. We also introduce the power skill score, specifically designed to evaluate model performance within wind resource mapping. The power skill score confirms that the dynamical downscaling improves the distribution of wind speed in ranges where high accuracy is important for wind resource assessment. Copyright © 2016 John Wiley & Sons, Ltd.     

A numerical approach for planning offshore wind farms from regional to local scales over the Mediterranean

Renewable energy resources, such as wind, are available worldwide. Locating areas with high and continual wind sources are crucial in pre-planning of wind farms. Vast offshore areas are characterized by higher and more reliable wind resources in comparison with continental areas. However, offshore wind energy production is in a quite preliminary phase. Elaborating the potential productivity of wind farms over such areas is challenging due to sparse in situ observations. The Mediterranean basin is not an exception. In this study we are proposing numerical simulations of near-surface wind fields from regional climate models (RCMs) in order to obtain and fill the gaps in observations over the Mediterranean basin. Four simulations produced with two regional climate models are examined here. Remote sensing observations (QuikSCAT satellite) are used to assess the skill of the simulated fields. A technique for estimating the potential energy from the wind fields over the region is introduced. The wind energy potential atlas and the map of a wind turbine's functional range are presented, locating the potentially interesting sub-regions for wind farms. The ability of models to reproduce the annual cycle and the probability density function of wind speed anomalies are detailed for specified sub-regions.     

Feasibility study of offshore wind turbine installation in Iran compared with the world

Renewable energies have potential for supplying of relatively clean and mostly local energy. Wind energy generation is expected to increase in the near future and has experienced dramatic growth over the past decade in many countries. Offshore winds are generally stronger and more constant than onshore winds in many areas. The economic feasibility for utilization of offshore wind energy depends on the favorable wind conditions in the area. The present paper analyses offshore wind speed in global scale and also studies feasibility of introducing this technology for harnessing wind in Persian Gulf, Caspian Sea, Urmia Lake and Gulf of Oman. Wind speed data were collected from different sources. The ocean surface winds at a 10 m height from satellite passes as processed by NOAA/NESDIS, from near real-time data collected by NASA/JPL's Sea Winds Scatterometer aboard the QuikSCAT. Development of renewable energy is one of priority research goals in Iran. There are many installed wind turbines in suitable regions like Manjil and Binalood, but there has not been any offshore wind installation yet in Iran. It is suggested that policy makers to invest and pay more attentions toward harnessing renewable energy sources like offshore wind in Persian Gulf and Gulf of Oman in southern parts of Iran.     

Effectiveness of WRF wind direction for retrieving coastal sea surface wind from synthetic aperture radar

Wind direction is required as input to the geophysical model function (GMF) for the retrieval of sea surface wind speed from a synthetic aperture radar (SAR) images. The present study verifies the effectiveness of using the wind direction obtained from the weather research and forecasting model (WMF) as input to the GMF to retrieve accurate wind fields in coastal waters adjacent to complex onshore terrain. The wind speeds retrieved from 42 ENVISAT ASAR images are validated based on in situ measurements at an offshore platform in Japan. Accuracies are also compared with cases using wind directions: the meso‐analysis of the Japan Meteorological Agency (MANAL), the SeaWinds microwave scatterometer on QuikSCAT and the National Center for Environmental Prediction final operational global analysis data (NCEP FNL). In comparison with the errors of the SAR‐retrieved wind speeds obtained using the WRF, MANAL, QuikSCAT and NCEP FNL wind directions, the magnitudes of the errors do not appear to be correlated with the errors of the wind directions themselves. In addition to wind direction, terrain factors are considered to be a main source of error other than wind direction. Focusing on onshore winds (blowing from the sea to land), the root mean square errors on wind speed are found to be 0.75 m s ^{? 1} (in situ), 0.96 m s ^{? 1} (WRF), 1.75 m s ^{? 1} (MANAL), 1.58 m s ^{? 1} (QuikSCAT) and 2.00 m s ^{? 1} (NCEP FNL), respectively, but the uncertainty is of the same order of magnitude because of the low number of cases. These results indicate that although the effectiveness of using the accurate WRF wind direction for the wind retrieval is partly confirmed, further efforts to remove the error due to factors other than wind direction are necessary for more accurate wind retrieval in coastal waters. Copyright © 2012 John Wiley & Sons, Ltd.     

Accessibility assessment for operation and maintenance of offshore wind farms in the North Sea

Focused on offshore wind energy operation and maintenance applications, this work presents a detailed accessibility analysis of the North Sea. After a review of existing normative dedicated to inspection and access of offshore wind turbines, a rigorous mathematical formulation of relevant accessibility parameters is given by means of the set theory. Long‐term and high‐resolution metocean data are extracted from reanalysis databases and used to evaluate spatial and temporal variability of such parameters. Respectively restricted by significant wave height and mean wind speed, access by workboat and helicopter is evaluated. Being affected by both wave height and wind speed. Access by offshore crane is also analyzed. It resulted that the UK coast and the southern region of the North Sea are highly accessible, while the coast of Denmark and Norway undergoes more severe metocean conditions. This is, however, balanced by a higher wind resource. Moreover, a strong seasonality is ascertained, together with a drastic reduction of accessibility during daytime in a vast part of the basin. Accessibility during daytime in winter and autumn is very difficult for the whole North Sea. Among the studied farms, Dogger Bank is by far the one with the highest resource and lowest accessibility, while Thorntonbank III the one with the lowest resource and highest accessibility. In addition, accessibility is non‐linearly related to wind speed and wave height limits chosen for the access strategies covered. Copyright © 2016 John Wiley & Sons, Ltd.     

基于MM5的沿海风资源数值模拟方法研究

提出通过历史观测资料和中尺度大气模式相融合的方法为沿海区域风能资源的分析评估提供一定时空分辨率的风场数值分析产品。主要探讨了将海洋站逐时测风资料、卫星微波遥感散射计风场反演资料计人中尺度大气模式MM5的同化方法，并对广东沿海区域天气个例进行了模拟试验，将不同模拟试验结果与实测值进行了统计对比分析。分析结果表明，时空分辨率较高的经过质量控制的观测资料的同化对风场模拟结果具有一定的改善作用。     

Using airborne and satellite SAR for wake mapping offshore

Offshore wind energy is progressing rapidly around Europe. One of the latest initiatives is the installation of multiple wind farms in clusters to share cables and maintenance costs and to fully exploit premium wind resource sites. For siting of multiple nearby wind farms, the wind turbine wake effect must be considered. Synthetic aperture radar (SAR) is an imaging remote sensing technique which offers a unique opportunity to describe spatial variations of wind speed offshore. For the first time an airborne SAR instrument was used for data acquisition over a large offshore wind farm. The aim was to identify the turbine wake effect from SAR‐derived wind speed maps as a downstream region of reduced wind speed. The aircraft SAR campaign was conducted on 12 October 2003 over the wind farm at Horns Rev in the North Sea. Nearly simultaneous measurements were acquired over the area by the SAR on board the ERS‐2 satellite. In addition, meteorological data were collected. Both aircraft and satellite SAR‐derived wind speed maps showed significant velocity deficits downstream of the wind farm. Wind speed maps retrieved from aircraft SAR suggested deficits of up to 20% downstream of the last turbine, whereas satellite SAR‐derived maps showed deficits of the order of 10%. The difference originated partly from the two different reference methods used for normalization of measured wind speeds. The detected region of reduced wind speed had the same width as the wind turbine array, indicating a low degree of horizontal wake dispersion. The downstream wake extent was approximately 10 km, which corresponds well with results from previous studies and with wake model predictions. Copyright © 2006 John Wiley & Sons, Ltd.     

Eight years of wind measurements from scatterometer for wind resource mapping in the Mediterranean Sea

Eight years of wind observations from the SeaWinds scatterometer instrument on the National Aeronautics and Space Administration QuikScat satellite and in situ data from 11 locations in the Mediterranean have been considered. The data have been co‐located in time and space, and it is shown that the scatterometer is able to provide similar long‐term statistics as available from buoy data, such as annual and monthly wind indexes. Such statistics is useful to give an overview of the climatology in the different areas. The correlation between QuikScat and in situ observations is degraded towards the coast, giving indication of how well the scatterometer can represent the coastal winds. The degradation is stronger in areas with strong spatial variability. The QuikScat winds are gridded into a 0.25° by 0.25° grid to produce seasonal and annual means of the offshore wind conditions over the Mediterranean. Copyright © 2010 John Wiley & Sons, Ltd.     

The creation of a comprehensive metocean data set for offshore wind turbine simulations

A database of meteorological and ocean conditions is presented for use in offshore wind energy research and design. The original data are from 23 ocean sites around the USA and were obtained from the National Data Buoy Center run by the National Oceanic and Atmospheric Administration. The data are presented in a processed form that includes the variables of interest for offshore wind energy design: wind speed, significant wave height, wave peak‐spectral period, wind direction and wave direction. For each site, a binning process is conducted to create conditional probability functions for each of these variables. The sites are then grouped according to geographic location and combined to create three representative sites, including a West Coast site, an East Coast site and a Gulf of Mexico site. Both the processed data and the probability distribution parameters for the individual and representative sites are being hosted on a publicly available domain by the National Renewable Energy Laboratory, with the intent of providing a standard basis of comparison for meteorological and ocean conditions for offshore wind energy research worldwide. Copyright © 2015 John Wiley & Sons, Ltd.     

Offshore wind resource estimation from satellite SAR wind field maps

A wind resource estimation study based on a series of 62 satellite wind field maps is presented. The maps were retrieved from imaging synthetic aperture radar (SAR) data. The wind field maps were used as input to the software RWT, which calculates the offshore wind resource based on spatial averaging (footprint modelling) of the wind statistic in each satellite image. The calculated statistics can then be input to the program WA^sP and used in lieu of in‐situ observations by meteorological instruments. A regional wind climate map based on satellite SAR images delineates significant spatial wind speed variations. The site of investigation was Horns Rev in the North Sea, where a meteorological time series is used for comparison. The advantages and limitations of these new techniques, which seem particularly useful for mapping of the regional wind climate, are discussed. Copyright © 2005 John Wiley & Sons, Ltd.     

海上相邻风电场间的“尾流效应”实例分析

  目的  研究海上相邻风电场间的“尾流效应”对发电损失的影响。  方法  利用海上风电场实际运行SCADA数据结合激光雷达同期实测测风数据,基于不同的风向扇区范围和风电场实际排布进行尾流效应场景分类,开展实际运行相邻风电场间（20D以上间距）的真实尾流电量损失分析工作。  结果  结果表明:对于规则排布的海上大型风电场,基于实际运行SCADA数据,对各机组发电量进行归一化,可以较好地反映海上风能资源分布特征及各机组发电能力的差异;高度集中的单一扇区条件下,处于下风向的相邻风电场受上风向相邻场区的“尾流效应”影响明显,发电产能较自由流降幅明显;相邻风场间随着缓冲带距离的增加,下风向场区机组尾流电量衰减比随之降低,缓冲带需达到一定的距离,对于风速的恢复有明显的作用,发电产能才能够有所提升;本案例不同场景下,缓冲带距离在23D～44D之间,尾流损失电量降幅在27%～4%之间。  结论  基于相邻风电场实际运行数据开展尾流分析可为后续海上大型风电基地规划设计和机组排布优化设计提供指导。     

Spatial and temporal characteristics of wind and wind power off the coasts of Brittany

The main objective of this paper is to thoroughly examine the remotely sensed wind characteristics around the coasts of Brittany as well as some more specific areas. The offshore wind power potential is then assessed. To achieve this objective, information on wind speed and direction with sufficient spatial and temporal sampling under all weather conditions and during day and night is required. This study uses more than 12 years (December 1999–December 2012) of consistent remotely sensed data retrieved from the ASCAT and QuikSCAT scatterometers to estimate the conventional moments and associated wind distribution parameters. The latter are comparable to wind observations from meteorological stations. Furthermore, combining in-situ and scatterometer wind information enables an improved assessment of the spatial and temporal wind structures at specific locations of interest to be made. The wind statistical results are used to study the spatial and temporal patterns of the wind power. Although the main parameters characterizing wind power potential such as mean, variability, maximum energy, wind speed and intra-annual exhibit seasonal features, significant inter-annual variability is also depicted. Furthermore, differences are found between the wind power estimated for northern and for southern Brittany.     

ENDOW (efficient development of offshore wind farms): modelling wake and boundary layer interactions

While experience gained through the offshore wind energy projects currently operating is valuable, a major uncertainty in estimating power production lies in the prediction of the dynamic links between the atmosphere and wind turbines in offshore regimes. The objective of the ENDOW project was to evaluate, enhance and interface wake and boundary layer models for utilization offshore. The project resulted in a significant advance in the state of the art in both wake and marine boundary layer models, leading to improved prediction of wind speed and turbulence profiles within large offshore wind farms. Use of new databases from existing offshore wind farms and detailed wake profiles collected using sodar provided a unique opportunity to undertake the first comprehensive evaluation of wake models in the offshore environment. The results of wake model performance in different wind speed, stability and roughness conditions relative to observations provided criteria for their improvement. Mesoscale model simulations were used to evaluate the impact of thermal flows, roughness and topography on offshore wind speeds. The model hierarchy developed under ENDOW forms the basis of design tools for use by wind energy developers and turbine manufacturers to optimize power output from offshore wind farms through minimized wake effects and optimal grid connections. The design tools are being built onto existing regional‐scale models and wind farm design software which was developed with EU funding and is in use currently by wind energy developers. Copyright © 2004 John Wiley & Sons, Ltd.     

Evaluation of wind farm efficiency and wind turbine wakes at the Nysted offshore wind farm

Here, we quantify relationships between wind farm efficiency and wind speed, direction, turbulence and atmospheric stability using power output from the large offshore wind farm at Nysted in Denmark. Wake losses are, as expected, most strongly related to wind speed variations through the turbine thrust coefficient; with direction, atmospheric stability and turbulence as important second order effects. While the wind farm efficiency is highly dependent on the distribution of wind speeds and wind direction, it is shown that the impact of turbine spacing on wake losses and turbine efficiency can be quantified, albeit with relatively large uncertainty due to stochastic effects in the data. There is evidence of the ‘deep array effect’ in that wake losses in the centre of the wind farm are under‐estimated by the wind farm model WAsP, although overall efficiency of the wind farm is well predicted due to compensating edge effects. Copyright © 2010 John Wiley & Sons, Ltd.     

A comparison between Advanced Scatterometer and Weather Research and Forecasting wind speeds for the Japanese offshore wind resource map

This paper investigates the validity of the method used in the Japanese offshore wind map (NeoWins) to seamlessly connecting satellite‐derived wind speed for open oceans to mesoscale model‐simulated wind speed for coastal waters. In the NeoWins, the former was obtained from the satellite‐borne Advanced Scatterometer (ASCAT), and the latter was obtained from numerical simulations using the Weather Research and Forecasting (WRF) model. In this study, the consistency of the ASCAT and WRF 10‐m height wind speeds is examined in their overwrapping areas. The comparison between ASCAT and WRF model reveals that their differences in annual mean wind speed are mostly within ±5% and that the ASCAT annual mean wind speed is, as a whole, slightly higher than the WRF annual mean wind speed. The results indicate that there are no large wind speed gaps between WRF and ASCAT in most parts of the Japanese offshore areas. It is moreover found that the discrepancies between the two wind speeds are due to two factors: one is the existence of winter sea ice in the ASCAT observation in the Sea of Okhotsk in ASCAT observation and the other is that the accuracy of the WRF wind speed depends on atmospheric stability.     

Combining meteorological stations and satellite data to evaluate the offshore wind power resource of Southeastern Brazil

Wind is strong and steady over the ocean, but on-site marine meteorological data are sparse for evaluation of oceanic wind power. Here, we draw on meteorological station, satellite data (QuikSCAT), and both theoretical and practical measures of wind turbine performance. The meteorological stations measure directly at high time resolution but low spacial resolution, and provide validation and adjustment of the satellite data. The satellite data provide near-complete spacial coverage at lower time resolution. For the southern coast of Brazil, we use both data sets to evaluate the location, seasonal timing, and availability of the wind power resource. Then, using bathymetry and the properties of current wind-electric technology, we develop maps of wind speed, wind power density, and practical turbine output in power units (MW). In the shallower waters of south Brazil, the most favorable conditions are along the coast between 28°S and 33°S. In just this one coastal area, we find a total resource of 102 GW average electrical production, approximately equal to the electric demand of the entire country.     

Wind energy resources in the Ionian Sea

The wind speed and direction as well as the availability, the duration and the diurnal variation of two offshore sites, Zakinthos and Pylos (BZK and BPY) in the Ionian Sea were assessed. For an analysis period of two years, the mean wind speed at 10 m was determined as 5.7 ± 0.1 m s^?1 and 5.8 ± 0.1 m s^?1 for the BZK and BPY sites, respectively. The wind speed variations over the hours of the day were quite small. The monthly variation in the average wind speeds was between 4.3 (May) and 7.5 m s^?1 (December) for the BZK site and 4.4 (August) and 7.3 m s^?1 (December) for the BPY site. Moreover, QuikSCAT satellite mean values for the grids of the two buoy regions were systematically overestimated in comparison to the buoy data with differences in the range from 8 to 13%. Statistical analysis revealed the high QuikSCAT data uncertainty for wind speeds less than 5 m s^?1 as the major factor of the observed mean value differences. The mean wind power densities were calculated with the buoy wind speed measurements and were found more than 250 W m^?2 at 10 m, suggesting the suitability of the sites for offshore wind energy applications. Capacity factors of up to 48% for energy production were calculated with the existing offshore turbines technology at a hub height of 100 m. Furthermore, the energy yield for different wind turbines and a service life of 20 years were determined from 6.5 to 8.7 and the energy pay-back periods from 2.8 to 2.1 years, respectively. The maximum avoided greenhouse emissions were 140 kt CO₂-e for an offshore turbine generator of 5 MW and a period of 20 years.     

Offshore wind energy prospects

In last two years offshore wind energy is becoming a focal point of national and non national organizations particularly after the limitations of fossil fuel consumption, adopted by many developed countries after Kyoto conference at the end of 1997 on global climate change. North Europe is particularly interested in offshore for the limited land areas still available, due to the intensive use of its territory and its today high wind capacity. Really the total wind capacity in Europe could increase from the 1997 value of 4450 MW up to 40 000 MW within 2010, according the White Paper 1997 of the European Commission; a significant percentage (25%) could be sited offshore up to 10 000 MW, because of close saturation of the land sites at that time. World wind capacity could increase from the 1997 value of 7200 MW up to 60 000 MW within 2010 with a good percentage (20%) offshore 12 000 MW. In last seven years wind capacity is shallow waters of coastal areas has reached 34 MW. Five wind farms are functioning in the internal seas of Netherlands, Denmark, Sweden; however such siting is mostly to be considered as semi-offshore condition. Wind farms in real offshore sites, open seas with waves and water depth over 10 m, are now proposed in North Sea at 10–20 km off the coasts of Netherland, Denmark using large size wind turbine (1–2 MW). In 1997 an offshore proposal was supported in Netherland by Greenpeace after the OWEMES '97 seminar, held in Italy on offshore wind in the spring 1997. A review is presented in the paper of the European offshore wind programs with trends in technology, economics and siting effects.     

An evaluation of the predictive accuracy of wake effects models for offshore wind farms

Wake losses are perceived as one of the largest uncertainties in energy production estimates (EPEs) for new offshore wind projects. In recent years, significant effort has been invested to improve the accuracy of wake models. However, it is still common for a standard wake loss uncertainty of 50% to be assumed in EPEs for new offshore wind farms. This paper presents a body of evidence to support reducing that assumed uncertainty. It benchmarks the performance of four commonly used wake models against production data from five offshore wind farms. Three levels of evidence are presented to substantiate the performance of the models:

• Case studies, i.e. efficiencies of specific turbines under specific wind conditions;
• Array efficiencies for the wind farm as a whole for relatively large bins of wind speed and direction; and
• Validation wake loss, which corresponds to the overall wake loss within the proportion of the annual energy production where validation is possible.

The most important result for predicting annual energy production is the validation wake loss. The other levels of evidence demonstrate that this result is not unduly reliant on cancellation of errors between wind speed and/or wind direction bins. All of the root‐mean‐squared errors in validation wake loss are substantially lower than the 50% uncertainty commonly assumed in EPEs; indeed, even the maximum errors are below 25%. It is therefore concluded that there is a good body of evidence to support reducing this assumed uncertainty substantially, to a proposed level of 25%. Copyright © 2015 John Wiley & Sons, Ltd.     

A simple analytical wind park model considering atmospheric stability

The analytical top‐down wind park model by Emeis and Frandsen 1 is enhanced by consistently making both the downward momentum flux and the momentum loss at the rough surface dependent on atmospheric stability. Specifying the surface roughness underneath the turbines in a wind farm in the model gives the opportunity to investigate principal differences between onshore and offshore wind parks, because the roughness length of the sea surface is two to three orders of magnitude lower than the roughness length of land surfaces. Implications for the necessary distance between single turbines in offshore wind farms and the distance between neighbouring wind parks are computed. It turns out from the model simulations that over smooth surfaces offshore the wind speed reduction at hub height in a wind farm is larger than over rough onshore surfaces given the same density of turbines within the park. Mean wind profiles within the park are also calculated from this model. Offshore wind farms must have a larger distance between each other in order to avoid shadowing effects of the upstream farm. Copyright © 2009 John Wiley & Sons, Ltd.