Meteorological Wind Data Research Articles

CFD Prediction for Wind Power Generation by a Small Vertical Axis Wind Turbine: A Case Study for a University Campus

The accuracy of wind power generation predicted by computational fluid dynamics (CFD) simulations combined with meteorological wind data was validated based on comparisons with directly measured data for a small vertical axis wind turbine system installed on a university campus. The CFD simulations were performed in accordance with established guidelines and frameworks for the prediction of urban wind environments. At the rooftop location, where small wind turbines are typically installed, the deviations in wind velocity from the measurements are quite large. However, in the present study, the prediction accuracy for the wind turbine site, which was 4 m above the ground, was acceptable. The total power generation estimated using the assumed power curve based on the rated output of the turbine was 56% larger than that directly measured by the power generator. However, using the power curves obtained from the measurements, the total power generation could be predicted with a high degree of accuracy and with an error of approximately 3%. It is suggested that not only the accuracy of the wind velocity but also that of the power curve is very important because they are directly related to that of the predicted power generation.

Cluster-based ensemble learning for wind power modeling from meteorological wind data

Reliable and efficient power modeling from meteorological wind data is vital for optimal implementation and monitoring of wind energy, and it is important for understanding turbine control, farm operational optimization, and grid load balance. Based on the idea that similar wind conditions lead to similar wind powers; this paper constructs a modeling scheme that orderly integrates three types of ensemble learning algorithms—bagging, boosting, and stacking—and clustering approaches to achieve wind power modeling from multiple wind-based meteorological factors in a wind farm. The paper also investigates the applications of different clustering algorithms and methodologies to determine cluster numbers in the modeling. The results reveal that all ensemble models with clustering exploit the intrinsic information in wind data and thus outperform models without clustering by approximately 15% on average in modeling wind power. The model with the best-performing Farthest First clustering is computationally rapid and with an improvement of around 30% compared with the baselines. Given the diversity introduced by clustering algorithms, the power modeling performance is further boosted by about 5% by introducing stacking that fuses ensembles with varying clusters. The proposed modeling framework thus demonstrates promise by delivering efficient and robust performance on the targeted problem.

Numerical investigation of the wind environment around tall buildings in a central business district

The wind environment around tall buildings in a central business district (CBD) was numerically investigated. The district covers an area of ~4.0 km2 and features a high density of tall buildings. In this study, only buildings taller than 20 m were considered, resulting in 173 tall buildings in the analysis. The numerical investigation was realized using the commercial computational fluid dynamics code FLUENT with the realizable k - e turbulence model. Special efforts were made to maintain inflow boundary conditions throughout the computational domain. The reliability of the numerical method was validated using results from an experimental investigation conducted in the core area of the CBD (~1.5 km2). Experimental and numerical investigations of wind speed ratios at the center of the three tallest buildings in the CBD agree within an uncertainty factor of 2.0. Both the experimental and numerical results show that wind speed ratios in the wind field with exposure category D are higher than those from the wind field with exposure category B. Based on the above validation work, the wind environment around tall buildings in the whole CBD was then investigated by numerical simulation. Common flow phenomena and patterns, such as stagnation points, shielding effects, separation flow, and channeling flow, were identified around the tall buildings. The pedestrian-level wind environment around tall buildings in the CBD was further evaluated using nearby meteorological wind data. The evaluation results show that some pedestrian activities, such as sitting at the center of the three tallest buildings, are unadvisable when the wind blows from the south-east.

Wind power potential assessment of roof mounted wind turbines in cities

A new methodology to evaluate performance and energy output of roof mounted wind turbines in cities is presented. The methodology combines Computational Fluid Dynamics (CFD) and meteorological data related to a city to assess the energy production of turbine placement on the roof of a building located in a city. The interaction between a Darrieus turbine and a building when the turbine is placed on the roof-top is analysed based on CFD and an accurate power curve is generated. Afterwards, energy yield calculations of this Darrieus turbine placed at each of the 4 corners of a building are performed for both a low and high density urban environments. The energy yield calculations are based on modelling actual regions of a city, followed by simulation of the wind for 8 directions and coupling CFD results with meteorological wind data to obtain an accurate estimate of the energy output. Simulation results indicate that energy production in high density urban environments is significantly reduced due to local wind behaviour.

Influence of the ENSO and Monsoonal Season on Long-Term Wind Energy Potential in Malaysia

This paper assesses the long-term wind energy potential at three selected sites, namely Mersing and Kijal on the east coast of peninsular Malaysia and Kudat in Sabah. The influence of the El Niño-Southern Oscillation on reanalysis and meteorological wind data was assessed using the dimensionless median absolute deviation and wavelet coherency analysis. It was found that the wind strength increases during La Niña events and decreases during El Niño events. Linear sectoral regression was used to predict the long-term wind speed based on the 35 years of extended Climate Forecast System Reanalysis data and 10 years of meteorological wind data. The long-term monthly energy production was computed based on the 1.5 MW Goldwind wind turbine power curve. The measured wind data were extrapolated to the selected wind turbine default hub height (70 m.a.s.l) by using the site-specific power law indexed. The results showed that the capacity factor is higher during the Northeast monsoon (21.32%) compared to the Southwest monsoon season (3.71%) in Mersing. Moreover, the capacity factor in Kijal is also higher during the Northeast monsoon (10.66%) than during the Southwest monsoon (5.19%). However, in Kudat the capacity factor during the Southwest monsoon (36.42%) is higher compared to the Northeast monsoon (24.61%). This is due to the tail-effect of tropical storms that occur during this season in the South China Sea and Pacific Ocean.

Atmospheric processes affecting the separation of volcanic ash and SO<sub>2</sub> in volcanic eruptions: inferences from the May 2011 Grímsvötn eruption

Abstract. The separation of volcanic ash and sulfur dioxide (SO2) gas is sometimes observed during volcanic eruptions. The exact conditions under which separation occurs are not fully understood but the phenomenon is of importance because of the effects volcanic emissions have on aviation, on the environment, and on the earth's radiation balance. The eruption of Grímsvötn, a subglacial volcano under the Vatnajökull glacier in Iceland during 21–28 May 2011 produced one of the most spectacular examples of ash and SO2 separation, which led to errors in the forecasting of ash in the atmosphere over northern Europe. Satellite data from several sources coupled with meteorological wind data and photographic evidence suggest that the eruption column was unable to sustain itself, resulting in a large deposition of ash, which left a low-level ash-rich atmospheric plume moving southwards and then eastwards towards the southern Scandinavian coast and a high-level predominantly SO2 plume travelling northwards and then spreading eastwards and westwards. Here we provide observational and modelling perspectives on the separation of ash and SO2 and present quantitative estimates of the masses of ash and SO2 that erupted, the directions of transport, and the likely impacts. We hypothesise that a partial column collapse or sloughing fed with ash from pyroclastic density currents (PDCs) occurred during the early stage of the eruption, leading to an ash-laden gravity intrusion that was swept southwards, separated from the main column. Our model suggests that water-mediated aggregation caused enhanced ash removal because of the plentiful supply of source water from melted glacial ice and from entrained atmospheric water. The analysis also suggests that ash and SO2 should be treated with separate source terms, leading to improvements in forecasting the movement of both types of emissions.

Performance assessment of tall building-integrated wind turbines for power generation

In response to the gradual degradation of the natural environment, there is a growing interest to advance the development of sustainable buildings, in which renewable energy technologies are often incorporated to strategically minimize the carbon footprint of buildings. Pearl River Tower, a 71-storey tall building in Guangzhou, China, was designed to be the most energy efficient tall building in the world. In addition to a series of energy-efficient measures, the most eye-catching innovation in the design of Pearl River Tower is the deployment of four wind turbines installed in four openings in the tall building for power generation. This study aims to provide a performance assessment of these tall building-integrated wind turbines. At the first step, a 1:150 scaled wind tunnel testing is carried out to experimentally assess the wind speed amplification effects inside the four openings. Comparative analysis and discussions corresponding to four different cases are presented. At the second step, the results from the wind tunnel testing, in conjunction with the statistical analysis results of long-term meteorological wind data recorded in Guangzhou, are applied for the performance assessment of these wind turbines for power generation. The outcomes of this study are expected to provide useful information for architects and engineers involved in the design of sustainable tall buildings.

A study into the accuracy of using meteorological wind data to estimate turbine generation output

Meteorological (met) station data is used as the basis for a number of influential studies into the impacts of the variability of renewable resources. Real turbine output data is not often easy to acquire, whereas meteorological wind data, supplied at a standardised height of 10 m, is widely available. This data can be extrapolated to a standard turbine height using the wind profile power law and used to simulate the hypothetical power output of a turbine. Utilising a number of met sites in such a manner can develop a model of future wind generation output. However, the accuracy of this extrapolation is strongly dependent on the choice of the wind shear exponent α. This paper investigates the accuracy of the simulated generation output compared to reality using a wind farm in North Rhins, Scotland and a nearby met station in West Freugh. The results show that while a single annual average value for α may be selected to accurately represent the long term energy generation from a simulated wind farm, there are significant differences between simulation and reality on an hourly power generation basis, with implications for understanding the impact of variability of renewables on short timescales, particularly system balancing and the way that conventional generation may be asked to respond to a high level of variable renewable generation on the grid in the future.

A new windstorm proxy from lake sediments: A comparison of geological and meteorological data from western Germany for the period 1965–2001

The feasibility of detecting windstorm layers in lake sediments is explored by comparing quartz grain size data from a freeze core obtained from the Schalkenmehrener Maar (Eifel region, western Germany) to recent meteorological wind data. The Schalkenmehrener Maar is appropriate for such a calibration study because the morphological settings of the lake allow the conservation of windstorm layers (in particular, there is no fluvial sediment inflow) and long‐term wind measurements are available from nearby stations. The age model for the uppermost 30 cm of the sediment core is based on measurements of 137Cs and 210Pb concentrations. An ultra‐high‐resolution grain size analysis is performed digitally on thin sections and reveals distinct 1‐mm‐thick layers with increased quartz grain content and sharp Gaussian grain size distributions, which are shifted to larger grain sizes compared to the normal lake sediment. In order to compare the occurrence of these layers with meteorological wind data, a windstorm index is developed, combining data from meteorological stations in the Eifel region and reanalyses from the European Centre for Medium‐range Weather forecast. A statistical evaluation of matches between the windstorm index and the core's silt fraction data indicates that the sediment layers very likely coincide with the major windstorm events in the Eifel region during the last decades (six historical storm are identified). This pilot study identifies the main requirements and proposes a novel methodological approach for using sediment data from lakes with similar settings as the Schalkenmehrener Maar as a new proxy to reconstruct the windstorm record of the geological past.

Estimation of Sand Transportation Rate for Fixed and Semi-Fixed Dunes Using Meteorological Wind Data

Taibus County, Inner Mongolia, China, lies in a farming-pastoral ecotone, where severe wind erosion and various aeolian sand hazards are prevalent and fixed and semi-fixed sand dunes occur frequently. This study was conducted to investigate the relationships between sand transportation rate and wind speed for the fixed and semi-fixed sand dunes based on field measurements. The annual quantity of soil erosion by wind was estimated using meteorological wind data. The results indicated that the sand transportation rate in Taibus County in 2000 was 57.38 kg cm −1 year −1 for the semi-fixed dunes and 4.56 kg cm −1 year −1 for the fixed dunes. The total duration of erosive winds covered 12.5% of the time of the year, and spring posed the highest potential of sand transportation. Wind with low speed (≤ 17 m s −1) and high frequency plays a dominant role in sand transportation, while strong wind (≥ 17 m s −1) with low frequency significantly enhanced the sand transportation. Erosive wind speed, directions, and frequency were three crucial dynamic factors influencing sand hazards in the farming-pastoral ecotone. The dominant factors intensifying sand and dust storms in Taibus County might be related to the favorable wind condition in combination with the durable drought, which led to land desertification and vegetation degradation.

Validation and Operation of a Wake Vortex/Shear Interaction Model

A vortex method model developed previously for studying the mechanisms in vortex/shear-layer interactions has been validated with large-eddy turbulence simulations by Proctor et al. (Proctor, F. H., Hinton, D. A., Han, J., Schowalter, D. G., and Lin, Y. L.) and field measurement data. A shear-detection algorithm used to incorporate meteorological wind data is developed. Operational issues are also explored. The shear-thickness effects and the wind measurement resolution requirement and its sensitivity to the prediction algorithm are discussed. The objective of this work is to develop a computational method that is both accurate enough for the intended purpose and rapid enough to be of use in an operational setting at airports

Utilizing microcomputer-based models to simulate changes in the nearshore environment

This paper demonstrates that changes in the dynamic nearshore environment could be successfully simulated by utilizing a combination of appropriate wave and sediment models. With the use of two microcomputer-based simulation models (WAVE and NSCWIS), nearshore sedimentary fluxes, and eventual beach and nearshore changes have been simulated. The ‘WAVE’ model was modified by the Canada Center for Inland Waters, and the ‘NSCWIS’ model was put forward by the US Army Engineer Waterways Experiment Station, Coastal Engineering Research Center. The ‘WAVE’ model is a parametric-type numerical wave prediction model, and uses as input a standard bathymetric grid and meteorological wind data. When initialized with input wind data the ‘WAVE’ FORTRAN '77 program calculates the wave advection terms at user-specified grid locations. The outputs from the ‘WAVE’ model are used as inputs into the ‘NSCWIS’ model in order to simulate shallow water wave and current conditions, and volumetric sediment transport rate. The ‘NSCWIS’ FORTRAN '77 program provides results on volumetric sediment transport rates. The immersed weight sediment transport rates have been calculated after obtaining estimates of the volumetric sediment transport rate. The model results have been compared with data collected from the Northeast, Northwest and East Beaches of Point Pelee, the southernmost promontory of Canada, on the north shore of Lake Erie. Total sediment flux data were collected each October from 1984–1987 at the East and Northwest Beaches, and from 1982–1989 along the Northeast Beach. To compare the actual total sediment flux data obtained from the study beaches with the simulated immersed transport rate, simulation runs were executed for both models (WAVE and NSCWIS). The simulated net annual immersed sediment flow outputs were then compared to the annual total sediment flux observed in the topographic bathymetric surveys using standard regression methods. Approximately 85.0% of the total sediment flux variations could be accounted for by variations in the estimated net annual immersed sediment flow associated with longshore currents.

Lidar Observations of Dust from the Soufrière Volcanic Eruptions of April 1979

Abstract Lidar observations of the stratosphere were made at Kingston, Jamaica (18.0°N, 76.8°W) following the eruptions of the Soufriere volcano of St. Vincent (13.2°N, 61.2°W) between 13 and 23 April 1979. Anomalous optical scattering was observed, at a height of ∼16 km, between 1 and 5 May 1979. This is discussed in relation to the relevant meteorological wind data and is interpreted as being due to volcanic dust which has been carried eastward once round the earth in the strong, upper tropospheric, zonal winds.