The influence of non‐logarithmic wind speed profiles on potential power output at Danish offshore sites

Detailed knowledge of mean wind speed profiles is essential for properly assessing the power output of a potential wind farm. Since atmospheric stratification plays a crucial role in affecting wind speed profiles, obtaining a detailed picture of the climatology of stability conditions at a given site is very important. In the present study, long time series from offshore measurement sites around Denmark are analysed, with the aim of quantifying the role of atmospheric stability in wind speed profiles and in our ability to model them. A simple method for evaluating stability is applied, and the resulting statistics of the atmospheric stratification is thoroughly studied. A significant improvement in the mean wind speed profile prediction is obtained by applying a stability correction to the logarithmic profiles suitable for neutral conditions. These results are finally used to estimate power densities at different heights. Copyright © 2004 John Wiley & Sons, Ltd.     

Classifying rotor‐layer wind to reduce offshore available power uncertainty

Rotor‐layer wind resource and turbine available power uncertainties prior to wind farm construction may contribute to significant increases in project risk and costs. Such uncertainties exist in part due to limited offshore wind measurements between 40 and 250 m and the lack of empirical methods to describe wind profiles that deviate from a priori, expected power law conditions. In this article, we introduce a novel wind profile classification algorithm that accounts for nonstandard, unexpected profiles that deviate from near power law conditions. Using this algorithm, offshore Doppler wind lidar measurements in the Mid‐Atlantic Bight are classified based on goodness‐of‐fit to several mathematical expressions and relative speed criteria. Results elucidate the limitations of using power law extrapolation methods to approximate average wind profile shape/shear conditions, as only approximately 18% of profiles fit well with this expression, while most consist of unexpected wind shear. Further, results demonstrate a relationship between classified profile variability and coastal meteorological features, including stability and offshore fetch. Power law profiles persist during unstable conditions and relatively weaker northeasterly flow from water (large fetch), whereas unexpected classified profiles are prevalent during stable conditions and stronger southwesterly flow from land (small fetch). Finally, the magnitude of the discrepancy between hub‐height wind speed and rotor equivalent wind speed available power estimates varies by classified wind‐profile type. During unexpected classified profiles, both a significant overprediction and underprediction of hub‐height wind available power is possible, illustrating the importance of accounting for site‐specific rotor‐layer wind shear when predicting available power.     

Scenarios for offshore wind power production for Central California Call Areas

In response to the growing interest in offshore wind energy development in California, the U.S. Bureau of Ocean Energy Management delineated three Call Areas for potential leasing. This study provides a comprehensive characterization and comparison of offshore wind power potential within the two Central California Call Areas (Diablo Canyon and Morro Bay) using 12- and 15-MW turbines under different inter-turbine spacing and wind farm size scenarios. Our analysis shows similar daily and seasonal patterns of wind power produced within the Call Areas, which peak in spring and during evening hours. Per-turbine power production is higher in the Morro Bay Call Area due to slightly higher hub-height wind speeds, whereas total power production is higher in the Diablo Canyon Call Area due to its larger size. Turbine type had a negligible impact on average power production per-unit-area because while larger turbines produce more power, they require greater inter-turbine spacing. Combined power production from the two fully built out Call Areas could equal nearly a quarter of California's current annual electrical energy production. A commercial-scale wind farm with a realized power output of 960 MW would require a footprint of at least half of the Morro Bay Call Area or at least a quarter of the Diablo Canyon Call Area. These results provide guidance on offshore wind development over the Central California Coast, and the framework demonstrated here could be applied to other wind data sets in other regions.     

Wind model for low frequency power fluctuations in offshore wind farms

This paper investigates the correlation between the frequency components of the wind speed Power Spectral Density. The results extend an already existing power fluctuation model that can simulate power fluctuations of wind power on areas up to several kilometers and for time scales up to a couple of hours, taking into account the spectral correlation between different wind turbines. The modelling is supported by measurements from two large wind farms, namely Nysted and Horns Rev. Measurements from individual wind turbines and meteorological masts are used. Finally, the models are integrated into an aggregated model which is used for estimating some electrical parameters as power ramps and reserves requirements, showing a quite good agreement between simulations and measurement. The comparison with measurements generally show that the inclusion of the correlation between low frequency components is an improvement, but the effect is relatively small. The effect of including the low frequency components in the model is much more significant. Therefore, that aggregated model is useful in the power system planning and operation, e.g. regarding load following and regulation. Copyright © 2009 John Wiley & Sons, Ltd.     

Modelling and measurements of power losses and turbulence intensity in wind turbine wakes at Middelgrunden offshore wind farm

Understanding of power losses and turbulence increase due to wind turbine wake interactions in large offshore wind farms is crucial to optimizing wind farm design. Power losses and turbulence increase due to wakes are quantified based on observations from Middelgrunden and state‐of‐the‐art models. Observed power losses due solely to wakes are approximately 10% on average. These are relatively high for a single line of wind turbines due in part to the close spacing of the wind farm. The wind farm model Wind Analysis and Application Program (WAsP) is shown to capture wake losses despite operating beyond its specifications for turbine spacing. The paper describes two methods of estimating turbulence intensity: one based on the mean and standard deviation (SD) of wind speed from the nacelle anemometer, the other from mean power output and its SD. Observations from the nacelle anemometer indicate turbulence intensity which is around 9% higher in absolute terms than those derived from the power measurements. For comparison, turbulence intensity is also derived from wind speed and SD from a meteorological mast at the same site prior to wind farm construction. Despite differences in the measurement height and period, overall agreement is better between the turbulence intensity derived from power measurements and the meteorological mast than with those derived from data from the nacelle anemometers. The turbulence in wind farm model indicates turbulence increase of the order 20% in absolute terms for flow directly along the row which is in good agreement with the observations. Copyright © 2007 John Wiley & Sons, Ltd.     

Market and regulatory aspects of trans‐national offshore electricity networks for wind power interconnection

Subsea cable connections are an essential part of offshore wind power projects. Apart from direct connections between an offshore wind park to the national grid, several alternatives can be envisaged, including the connection to interconnectors between countries or direct connection to a country outside the jurisdiction where the wind park is based. Besides the technical‐economical constraints of these new types of grid connection, market and regulatory aspects need to be assessed. The paper gives an overview of these trans‐national connection schemes for wind power and considers integration into electricity markets and discusses regulatory implications. The scope of the research is Western Europe. Copyright © 2009 John Wiley & Sons, Ltd.     

Review of recent offshore wind power developments in china

Rapid wind power development in China has attracted worldwide attention. The huge market potential and fast development of wind turbine manufacturing capacity are making China a world leader in wind power development. In 2010, with the newly installed wind power capacity and the cumulative installed capacity, China was ranked first in the world. In 2009, China also constructed and commissioned its first large offshore wind farm near Shanghai. Following earlier papers reviewing the state of China's onshore wind industry, this paper presents a broader perspective and up‐to‐date survey of China's offshore wind power development, making comparisons between the developments in the rest of the world and China, to draw out similarities and differences and lessons for the China offshore wind industry. The paper highlights six important aspects for China's offshore wind development: economics, location, Grid connection, technological development, environmental adaptation and national policies. The authors make recommendations for mitigating some outstanding issues in these six aspects for the future development of China's offshore wind resource. Copyright © 2012 John Wiley & Sons, Ltd.     

新型海上风力发电及其关键技术研究

回顾国外海上风力发电场的发展,针对随着海水深度增加导致海上风力机成本急剧上升的矛盾,引入海上漂浮式风力机概念,并详细介绍其结构和特点,通过系统介绍海上漂浮式风力机组成部分和设计制造中的关键技术,最后得出海上漂浮式风机是一种潜力巨大的新型风力发电技术,值得进一步深入研究。同时,针对我国陆、海资源的具体情况,较为系统地提出了海上漂浮式风力机研究的需要关注的关键问题,指出了该研究所具有的巨大社会经济价值。     

我国海上风电的发展与技术现状分析

对国内外海上风电发展现状进行了对比分析,介绍了我国发展海上风电的优势和面临的困难,并针对海上风电场在设计、施工和运行等阶段可能出现的问题进行了思考和探讨.     

Simulating offshore hydrogen production via PEM electrolysis using real power production data from a 2.3 MW floating offshore wind turbine

This work presents simulation results from a system where offshore wind power is used to produce hydrogen via electrolysis. Real-world data from a 2.3 MW floating offshore wind turbine and electricity price data from Nord Pool were used as input to a novel electrolyzer model. Data from five 31-day periods were combined with six system designs, and hydrogen production, system efficiency, and production cost were estimated. A comparison of the overall system performance shows that the hydrogen production and cost can vary by up to a factor of three between the cases. This illustrates the uncertainty related to the hydrogen production and profitability of these systems. The highest hydrogen production achieved in a 31-day period was 17 242 kg using a 1.852 MW electrolyzer (i.e., utilization factor of approximately 68%), the lowest hydrogen production cost was 4.53 $/kg H₂, and the system efficiency was in the range 56.1–56.9% in all cases.     

Hydrogen production from offshore wind power in South China

Wind power hydrogen production is the direct conversion of electricity generated by wind power into hydrogen through water electrolysis hydrogen production equipment, which produces hydrogen for convenient long-term storage through water electrolysis. With the development of offshore wind power from offshore projects, construction costs continue to rise. Turning power transmission into hydrogen transmission will help reduce the cost of offshore wind power construction. This paper analyses the methods of producing hydrogen from offshore wind power, including alkaline water electrolysis, proton exchange membrane electrolysis of water, and solid oxide electrolysis of water. In addition, this paper outlines economic and cost analyses of hydrogen production from offshore wind power. In the future, with the development and advancement of water electrolysis hydrogen production technology, hydrogen production from offshore wind power could be more economical and practical.     

A modular series connected converter structure suitable for a high‐voltage direct current transformerless offshore wind turbine

A modular generator/converter system suitable for a 100 kV transformerless HVDC offshore wind turbine is analyzed in this paper. The large diameter generator combined with mechanical tolerances may result in substantial parameter deviations. Therefore, the impact of such parameter variations is analyzed. A steady‐state model relating these variations to the imbalances between module DC voltages has been developed. Additionally, the impact of different control strategies was assessed through simulations in EMTDC/PSCAD. Finally, experimental verification of the system performed on a 45 kW laboratory prototype is presented. The theory is developed with the transformerless wind turbine concept in mind but is also applicable to other similar series connected converter topologies.Copyright © 2013 John Wiley & Sons, Ltd.     

Estimation of offshore extreme wind from wind‐wave coupled modeling

A coupledwind‐wave modeling system is used to simulate 23 years of storms and estimate offshore extreme wind statistics. In this system, the atmospheric Weather Research and Forecasting (WRF) model and Spectral Wave model for Near shore (SWAN) are coupled, through a wave boundary layer model (WBLM) that is implemented in SWAN. The WBLM calculates momentum and turbulence kinetic energy budgets, using them to transfer wave‐induced stress to the atmospheric modeling. While such coupling has a trivial impact on the wind modeling for 10‐m wind speeds less than 20 ms^?1, the effect becomes appreciable for stronger winds—both compared with uncoupled WRF modeling and with standard parameterization schemes for roughness length. The coupled modeling output is shown to be satisfactory compared with measurements, in terms of the distribution of surface‐drag coefficient with wind speed. The coupling is also shown to be important for estimation of extreme winds offshore, where the WBLM‐coupled results match observations better than results from noncoupled modeling, as supported by measurements from a number of stations.     

Service reliability of offshore wind turbines

A probabilistic formulation is proposed to assess the performance of the support structure of offshore wind turbines based on their probability and expected time of exceeding specified drift thresholds. To this end, novel probabilistic models are developed to predict the mean and standard deviation of the drift ratio response of wind turbine support structures operating under day-to-day loads as a function of the wind turbine geometry and material properties, and loading conditions. The proposed models are assessed using a database of virtual experiments generated using detailed three-dimensional (3D) nonlinear finite element (FE) models of a set of representative wind turbine configurations. The developed models are then used in a random vibration formulation to estimate the probability and expected time of exceeding specified drift thresholds. As an example, the probability and expected time of exceeding specified drift thresholds are estimated for a typical offshore wind turbine at different wind speeds. A comparison is made between the results obtained based on the proposed models, those obtained using simulators commonly used in practice and detailed 3D nonlinear FE analyses.     

Met‐ocean conditions influence on floating offshore wind farms power production

Met‐ocean conditions may affect the performance of a floating wind turbine, since a harsh climate could lead the system to exceed its operating thresholds and thus to force the machine shutdown. In this paper, it is a proposed methodology to evaluate the effect of met‐ocean conditions on the long‐term dynamic behaviour, and energy production, of a floating wind farm. For a sample of 500 MW farm located off the coast of Aberdeen (Scotland), 20 years of met‐ocean data are generated by means of meteorological reanalysis techniques. A subset of 1000 hourly conditions is selected, by means of a maximum dissimilarity algorithm, and input to a dynamic floating wind turbine model. Numerical results are then interpolated for the whole set of met‐ocean data, using radial basis functions. This approach allows to dramatically reduce the global computation time. Tower inclination and hub acceleration are chosen as relevant operating parameters: the former mainly depends on mean wind speed and direction, being largest at rated wind speed. The latter is also affected by significant wave height, and reaches its highest values when wind and waves are aligned. For each simulation, any machine exceeding the selected safety threshold is considered to be shut down. Assuming continuous operation, the average lifespan capacity factor of the farm is 50.2%; more restrictive tolerances result in a non‐linear reduction of the energy production. This approach may help both at the design and the operational stage, in determining the best trade‐off between energy production and safe operation. Copyright © 2015 John Wiley & Sons, Ltd.     

Evaluation of the wind direction uncertainty and its impact on wake modeling at the Horns Rev offshore wind farm

Accurately quantifying wind turbine wakes is a key aspect of wind farm economics in large wind farms. This paper introduces a new simulation post‐processing method to address the wind direction uncertainty present in the measurements of the Horns Rev offshore wind farm. This new technique replaces the traditional simulations performed with the 10 min average wind direction by a weighted average of several simulations covering a wide span of directions. The weights are based on a normal distribution to account for the uncertainty from the yaw misalignment of the reference turbine, the spatial variability of the wind direction inside the wind farm and the variability of the wind direction within the averaging period. The results show that the technique corrects the predictions of the models when the simulations and data are averaged over narrow wind direction sectors. In addition, the agreement of the shape of the power deficit in a single wake situation is improved. The robustness of the method is verified using the Jensen model, the Larsen model and Fuga, which are three different engineering wake models. The results indicate that the discrepancies between the traditional numerical simulations and power production data for narrow wind direction sectors are not caused by an inherent inaccuracy of the current wake models, but rather by the large wind direction uncertainty included in the dataset. The technique can potentially improve wind farm control algorithms and layout optimization because both applications require accurate wake predictions for narrow wind direction sectors. © 2013 The Authors. Wind Energy published by John Wiley & Sons, Ltd.     

Probabilistic maximum‐value wind prediction for offshore environments

High wind speeds can pose a great risk to structures and operations conducted in offshore environments. When forecasting wind speeds, most models focus on the average wind speeds over a given period, but this value alone represents only a small part of the true wind conditions. We present statistical models to predict the full distribution of the maximum‐value wind speeds in a 3 h interval. We take a detailed look at the performance of linear models, generalized additive models and multivariate adaptive regression splines models using meteorological covariates such as gust speed, wind speed, convective available potential energy, Charnock, mean sea‐level pressure and temperature, as given by the European Center for Medium‐Range Weather Forecasts forecasts. The models are trained to predict the mean value of maximum wind speed, and the residuals from training the models are used to develop the full probabilistic distribution of maximum wind speed. Knowledge of the maximum wind speed for an offshore location within a given period can inform decision‐making regarding turbine operations, planned maintenance operations and power grid scheduling in order to improve safety and reliability, and probabilistic forecasts result in greater value to the end‐user. The models outperform traditional baseline forecast methods and achieve low predictive errors on the order of 1–2 m s^?1. We show the results of their predictive accuracy for different lead times and different training methodologies. Copyright © 2014 John Wiley & Sons, Ltd.     

Experimental verification of computational predictions in power generation variation with layout of offshore wind farms

The optimization of wind farms with respect to spatial layout is addressed experimentally. Wake effects within wind turbine farms are well known to be deleterious in terms of power generation and structural loading, which is corroborated in this study. Computational models are the predominant tools in the prediction of turbine‐induced flow fields. However, for wind farms comprising hundreds of turbines, reliability of the obtained numerical data becomes a growing concern with potentially costly consequences. This study pursues a systematic complementary theoretical, experimental and numerical study of variations in generated power with turbine layout of an 80 turbine large wind farm. Wake effects within offshore wind turbine arrays are emulated using porous discs mounted on a flat plate in a wind tunnel. The adopted approach to reproduce experimentally individual turbine wake characteristics is presented, and drag measurements are argued to correctly capture the variation in power generation with turbine layout. Experimental data are juxtaposed with power predictions using ANSYS WindModeller simulation suite. Although comparison with available wind farm power output data has been limited, it is demonstrated nonetheless that this approach has potential for the validation of numerical models of power loss due to wake effects or even to make a direct physical prediction. The approach has even indicated useful data for the improvement of the physics within numerical models. Copyright © 2014 John Wiley & Sons, Ltd.     

US East Coast offshore wind energy resources and their relationship to peak‐time electricity demand

This study characterized the annual mean US East Coast (USEC) offshore wind energy (OWE) resource on the basis of 5 years of high‐resolution mesoscale model (Weather Research and Forecasting–Advanced Research Weather Research and Forecasting) results at 90 m height. Model output was evaluated against 23 buoys and nine offshore towers. Peak‐time electrical demand was analyzed to determine if OWE resources were coincident with the increased grid load. The most suitable locations for large‐scale development of OWE were prescribed, on the basis of the wind resource, bathymetry, hurricane risk and peak‐time generation potential. The offshore region from Virginia to Maine was found to have the most exceptional overall resource with annual turbine capacity factors (CF) between 40% and 50%, shallow water and low hurricane risk. The best summer resource during peak time, in water of ≤ 50 m depth, is found between Long Island, New York and Cape Cod, Massachusetts, due in part to regional upwelling, which often strengthens the sea breeze. In the South US region, the waters off North Carolina have adequate wind resource and shallow bathymetry but high hurricane risk. Overall, the resource from Florida to Maine out to 200 m depth, with the use of turbine CF cutoffs of 45% and 40%, is 965–1372 TWh (110–157 GW average). About one‐third of US or all of Florida to Maine electric demand can technically be provided with the use of USEC OWE. With the exception of summer, all peak‐time demand for Virginia to Maine can be satisfied with OWE in the waters off those states. Copyright © 2012 John Wiley & Sons, Ltd.     

Performance improvement study of an integrated photovoltaic system for offshore power production

Sustainable energy is one of the main options for resolving energy problems and climate change issues. Solar energy is one of the main promising renewable energy sources, which can be captured and converted to electrical energy through photovoltaic (PV) panels. In the open literature, it is shown that having two PV panels integrated into a back‐to‐back configuration placed on naturally reflective surfaces provides the potential of doubling the total power produced by a single‐faced PV panel with the appropriate location and orientation. This paper presents a case study of two‐PV panel systems for offshore power production. The relevance to offshore has the water surface as the reflective surface to produce power from the back facing panel. The city of Ottawa in Canada is selected as the location for a case study. Various conditions and operating parameters are considered in assessing the performance of the proposed system, including solar radiation intensity, system orientation, time of year in terms of months, and the variations in parameters throughout the day. The assessment of the proposed system is carried out through modeling and simulating the proposed double PV panels in the COMSOL Multiphysics software. It is found that the minimum improvement in the total power production over the single face conventional PV is 38% in January for the east‐facing PV front face. For the two PV systems, the optimal overall power production for the various time conditions and orientations, at the specified location, is found to be the north orientation of the PV panel. In this case, the power it produces is 89% of that of the east orientation. A similar trend is observed for the single‐faced PV panel, where the north‐facing PV provides 62% of what it could produce in the east‐facing orientation.