An enormous and urgent energy demand is predicted due to the growing global population, increase in power intensive industries, higher living standards, electrification of remote areas, and globalisation (transportation). Moreover, the global consciousness about the harmful effects of traditional methods of power generation on the environment. That, in turn, has created a need to strategically plan and develop renewable and sustainable energy generation systems. This study presents a wind resource assessment of seven locations proximate to the largest industrial hub in the Middle East, Jubail Industrial City, Kingdom of Saudi Arabia, and a Geographic Information System, GIS based model considering a multi-criteria wind farm site suitability approach for the entire Kingdom of Saudi Arabia and elsewhere. The hourly mean wind speed data at 10, 50 and 90 m above the ground level (AGL) over a period of five years was used for a meteorological station at the Industrial Area (Central) of Jubail. At the remaining six sites, the meteorological data were recorded at 10 m AGL only. Five years of wind data were used for five sites and three years of data were available for the remaining one site. At the Industrial Area (East), the mean wind speeds were found to be 3.34, 4.79 and 5.35 m/s at 10, 50 and 90 m AGL, respectively. At 50 and 90 m AGL, the availability of wind speed above 3.5 m/s was more than 75%. The local wind shear exponent, calculated using measured wind speed values at three heights, was found to be 0.217. The mean wind power density values at measurement heights were 50.92, 116.03 and 168.46 W/m2, respectively. After the assessment and comparison of wind characteristics of all seven sites, the highest annual mean wind speed of 4.52 m/s was observed at Industrial Area (East) and the lowest of 2.52 m/s at the Pearl Beach with standard deviations of 2.52 and 1.1 m/s, respectively. In general, at all sites, the highest monthly mean wind speed was observed in February/June and the lowest in September/October. The period of higher wind availability coincides with a high power demand period in the region attributable to the air conditioning load. The wind rose plots show that the prevailing wind direction for all sites was from the north-west. Weibull parameters for all sites were estimated using maximum likelihood, least-squares regression method (LSRM), and WAsP algorithm. In general, at all sites, the Weibull parameter, c, was the highest in the months of February/June and the lowest in the month of October. The most probable and maximum energy carrying wind speed was determined by all three methods. The highest value of most probable wind speed was found to be in the range of 3.2 m/s to 3.6 m/s at Industrial Area (East) and the highest value of maximum energy carrying wind speed was found to be in the range 8.6 m/s to 9.0 m/s at Industrial Area 2 (South) by three estimation methods. The correlation coefficient (R2), root mean square error (RMSE), mean bias error (MBE), and mean bias absolute error (MAE) showed that all three methods represent wind data at all sites accurately. However, the maximum likelihood method is slightly better than LSRM, followed by WAsP algorithm. The wind power output at all seven sites, from five commercially available wind turbines of rated power ranging from 1.8 to 3.3 MW, showed that Industrial Area (East) is most promising for wind farm development. At all sites, based on percentage plant capacity factor, PCF, the 1.8 MW wind turbine was found to be the most efficient. At Industrial Area (East), this wind turbine was found to have a maximum PCF of 41.8%, producing 6,589 MWh/year energy output. The second best wind turbine was 3 MW at all locations except the Al-Bahar Desalination Plant and Pearl Beach. At both of these locations, 3.3 MW was the next best option. The energy output from the 3 MW wind turbine at Industrial Area (East) was found to be 11,136 MWh/year with a PCF of 41.3%. The maximum duration of rated power output from all selected wind turbines was observed to be between 8 to 16.6% at Industrial Area 2 (South). The minimum duration of rated power output, less than 0.3% for all wind turbines, was observed at Pearl Beach. The maximum duration of zero power output of between 35 to 60% was also observed at Pearl Beach. / Thesis (PhD)--University of Pretoria, 2017. / Mechanical and Aeronautical Engineering / PhD / Unrestricted

This report analyses accuracy of wind speed predictions using wind atlases for the application of wind farm project development. The report aims to compare publicly available New European Wind Atlas (NEWA) mesoscale model data with the NEWA microscale model data. Later, NEWA microscale predictions are checked with manual WindPro WAsP calculations, which use real wind statistics. 9 locations (3 surface roughness types and 3 distances to Baltic coast) are examined. The results show three key-findings: first, the NEWA mesoscale and microscale models are most consistent in coastal open-field locations. Second, NEWA microscale model is most consistent with WindPro WAsP calculations in coastal and mid-coastal forested areas. Lastly, WindPro WAsP calculations significantly reduced wind speed estimates for in-land locations.

Hazardous winds, such as tornadoes and hurricanes, have a great impact on civil engineering structures and cause significant social and economic disturbances. The wind speed and pressure tested in the conventional wind tunnel experiments are much smaller than the actual wind speed and pressure measured in the field. Therefore, the Wind-induced Damage Simulator (WDS) was constructed at the University of Ottawa to overcome the wind speed limitations of wind tunnels and to simulate different types of wind speed profiles. WDS is an isolated cubic box with dimensions 3.65m x3.65 m and 3.0 m height, with multiple inlets on the side faces of the testing chamber and an outlet on the top side. This unique equipment creates a controlled environment for studying wind speed profiles in a confined space, by regulating the air flow with the aid of an attached industrial blower. To measure the simulated wind velocities inside the WDS and to obtain the wind speed profile in the testing chamber, Aeroprobe (12- Hole Probe) sensor was used for different combinations of opened inlets and at four different locations. The data collected from the Aeroprobe was processed by the use of the Aeroflow 2.7.5.7346 software, to get the velocity of wind in three different directions (u, v and w) and the mean velocity at a single point. After determining the mean velocity at different heights and RPM values at all four positions, Matlab software was used to determine the wind profile and the spectra of the turbulence intensities and these were compared for different heights at the four investigated locations and for various rotations per minute (RPM) values (400 to 800 RPM) for controlling the blower. Once the flow characterization was completed, the wind-induced pressure for three models of the Silsoe Cube were measured as a part of the second phase of the test. The current experiment employed 3 different scales of Silsoe cube: 1:40, 1:30 and 1:20, while the pressure coefficients were determined at 16 different points along a vertical line crossing the faces of the cube. A pressure taps system with 16 channels and a Scanivale pressure scanner were used to measure the pressure at 16 different positions on the cube. Matlab software was used to determine the pressure coefficients from the data measured by pressure taps. The pressure coefficienst for the Silsoe Cube were plotted and compared for the three different scales. Also, for determining the best scale to be used in future experiments. The pressure coefficients of the 3 different scaled model of Silsoe Cubes was compared with full-scale data reported in the literature for the same structure. Based on the results obtained from the experiments, recommendations for the best location in the testing chamber for the future experiments employing the WDS were formulated.

The UK has an abundant offshore wind resource with offshore wind farming set to grow rapidly over the coming years. Optimisation of energy production is of the utmost importance and accurate estimates of wind speed distributions are critical for the planning process. Synthetic aperture radar (SAR) data can provide synoptic, wide area wind field estimates at resolutions of a few kilometres and has great potential for wind resource assessment. This thesis addresses the key challenges for the operational implementation of SAR in this context; namely the accuracy of SAR wind retrievals and the ability of SAR to characterise the mean wind speed and wind power density. We consider the main stages of SAR wind retrieval; the retrieval algorithm; sources of a priori information; the optimal configuration of the retrieval system; and the challenges for and accuracy of SAR wind resource estimation. This study was conducted for the eastern Irish Sea in the UK, a region undergoing significant offshore wind energy development. A new wind retrieval algorithm was developed that implements a maximum a posterior probability (MAP) method drawn from Bayesian statistics. MAP was demonstrated to be less sensitive to input errors than the standard direction-based wind speed algorithm (DWSA) and provides a simple retrieval quality check via the error reduction ratio. Retrieval accuracy is strongly influenced by the quality of a priori information. The accuracy of two operationally viable a priori sources, mesoscale numerical weather prediction (NWP) data and WISAR image directions, was evaluated by comparison against in-situ wind observations and WERA coastal data. Results show that NWP wind speeds produce good wind speed and direction estimates with standard deviations of ¬±2 ms-1 and ±16o respectively. WISAR directions were less accurate producing standard deviations ranging from ±20o to ±29o, but were preferable when strong differences between NWP timesteps were observed. The accuracy of SAR wind retrievals was evaluated by comparison against in-situ wind observations. The MAP algorithm was found to provide modest improvements in retrieval accuracy over DWSA. Highest quality retrievals achieved using the CMOD5 forward model, producing wind speeds with a RMSE of 1.83 ms-1. Regarding the ability of SAR to estimate offshore wind resources, dataset density was found to be a controlling parameter. With 103 scenes available mean wind speeds were well characterised by comparison against in-situ observations and Wind Atlas results, while wind power density showed considerable errors. The accuracy of wind speed maps was further improved by accounting for wind direction and fetch effects upon the SAR wind distribution. A key strength of the SAR wind fields is their ability to identify the effect of mesoscale structures upon the surface wind field with atmospheric gravity waves observed in 30% of the images. These structures are shown to introduce wind speed fluctuations of up to ±2 ms-1 at scales of 5 to 10 km and may have significant implications for wind power prediction. These findings show that SAR may provide an important source of wide area wind speed observations as a complement to existing wind resource estimation techniques. SAR may be of particular use in coastal areas where complex wind fields are observed.

The present thesis deals with the influnence of moisture flux and variables, it is derived from, on rainfall in Europe. Sources of this thesis are the NCAR/NCEP and the ERA-40 reanalysis and the GPCC and the ECA&D rainfall databases. A western moisture flux prevails on studied 850 hPa isobaric level, it reaches the highest intensities over the Atlantic around 55th parallel of latitude. There is the highest correlation between moisture flux magnitude and monthly rainfall in winter on the western coast of Europe and it decreases in summer and eastwards. The correlation is very weak or none in some parts of Europe, especially in the eastern Mediterranean. Extremely wet months are related with different intensive moisture flux directions in different parts of Europe, for example there is the highest correlation of monthly rainfall with the northern moisture flux in the Czech Republic. Several selected heavy precipitation episodes in Europe are presented in this thesis - during them the moisture flux anomaly is observed, but it differs in orientation and intensity. A high wind speed causes this anomaly more frequently than a humidity. This does not apply to every event, furher research is needed to draw general patterns of moisture flux during high precipitation events.

A teoria dos valores extremos é um tópico da probabilidade que descreve a distribuição assintótica das estatísticas de ordem, tais como máximos ou mínimos, de uma seqüência de variáveis aleatórias que seguem uma função de distribuição F normalmente desconhecida. Descreve, ainda, a distribuição assintótica dos excessos acima de um valor limiar de um ou mais termos dessa seqüência. Dessa forma, as metodologias padrões utilizada neste contexto consistem no ajuste da distribuição generalizada dos valores extremos a uma série de máximos anuais ou no ajuste da distribuição generalizada de Pareto a uma série de dados compostas somente de observações excedentes de um valor limiar. No entanto, segundo Coles et al. (2003), há uma crescente insatisfação com o desempenho destes modelos padrões para predição de eventos extremos causada, possivelmente, por pressuposições não atendidas como a de independência das observações ou pelo fato de que os mesmos não sejam recomendados para serem utilizados em algumas situações específicas como por exemplo e quando observações de máximos anuais compostas por duas ou mais populações independentes de eventos extremos sendo que a primeira descreve eventos menos freqüentes e de maior magnitude e a segunda descreve eventos mais freqüentes e de menor magnitude. Então, os dois artigos que compõem este trabalho tem como objetivo apresentar alternativas de análise de valores extremos para estas situações em que o ajuste dos modelos padrões não são adequados. No primeiro, foram ajustadas as distribuições generalizada de Pareto e exponencial, caso particular da GP, aos dados de vazão média diária do Posto de Artemis, Piracicaba, SP, Brasil, conjuntamente com a técnica do desagrupamento, (declustering), e comparadas as estimativas dos níveis de retorno para períodos de 5, 10, 50 e 100 anos. Conclui-se que as estimativas intervalares dos níveis de retorno obtidas por meio do ajuste da distribuição exponencial são mais precisas do que as obtidas com o ajuste da distribuição generalizada de Pareto. No segundo artigo, por sua vez, foi apresentada uma metodologia para o ajuste da distribuição de Gumbel e de misturas de duas distribuições de Gumbel aos dados de velocidades de ventos mensais de Piracicaba, SP. Selecionou-se a distribuição que melhor ajustou-se aos dados por meio de testes de hipóteses bootstrap paramétrico e critérios de seleção AIC e BIC. E concluiu-se que a mistura de duas distribuições de Gumbel é a distribuição que melhor se ajustou-se aos dados de velocidades máxima de ventos dos meses de abril e maio, enquanto que o ajuste da distribuição de Gumbel foi o melhor para os meses de agosto e setembro. / The extreme value theory is a probability topics that describes the asymtoptic distribution of order statistics such as maximum or minimum of random variables sequence that follow a distribution function F normaly unknown. Describes still, the excess asymtoptic distribution over threshold of this sequence. So, the standard methodologies of extremes values analysis are the fitting of generalized extreme value distribution to yearly maximum series or the fitting of generalized Pareto distribution to partial duration series. However, according to Coles et al. (2003), there is a growing dissatisfaction with the use this standard models for the prediction of extremes events and one of possible causes this fact may be a false assumptions about a sequence of observed data as a independence assumptions or because the standards models must not used in some specific situations like for example when maximum sample arise from two or more independents populations, where the first population describes more frequents and low intense events and the second population describes less frequents and more intense events. In this way, the two articles this work has a objective show alternatives about extreme values analysis for this situations that the standards models doesn´t recommended. In the first article, the generalized distribution Pareto and exponencial distribution, particular case of GP, together with to declustering methods was applied to mean daily flow of the Piracicaba river, Artemis station, Piracicaba, SP, and the estimates the return levels of 5, 10, 50 and 100 years were compared. We conclude that the interval estimates of the 50 and 100 year return levels obtained using the fitting the exponencial distribution are more precise than those obtained using the generalized Pareto distribution. In the second article, we propose the fit of Gumbel distribution and the Gumbel mixture to data maximum speed wind in Piracicaba, SP. We select the best model using bootstrap test of hypotheses and the AIC and BIC selection criteria We conclude that the mixture Gumbel is the best model to analyze the maximum wind speed data for months of april e may and otherside the fit of Gumbel distributions was the best fit to months of august e september.

The temporal and spatial variability in wind speed and direction was investigated in a study of the mesoscale wind fields in the Canberra region. The statistical description of the winds was based on twelve months of three-hourly data at seventeen sites obtained in a joint program carried out by the Division of Land Use Research, CSIRO, the National Capital Development Commission, and the Bureau of Meteorology. The statistical analysis proceeded in stages. The first two stages were concerned with the determination and examination of averages and measures of dipersion. Information on the temporal variability in regional wind, defined as the average of the winds at the seventeen collection sites, provided the first insight into the important determinants of winds in the region. The data were then categorized on the basis of the information thus obtained, and the averages over time for each site were analysed in each category. The variation between sites revealed the extent of the spatial variability in the region. For each category, for each site, there were perturbations around the average state, and in the last stage of the study, the analysis examined how the perturbations were related across sites using correlation coefficients. Generalized Procrustes Analysis was used, followed by the extensive use of cluster analysis. Linear modelling techniques were used at all stages of the study, not only for wind speed, but also for wind direction which is an angular variate and thus required different modelling procedures. The models related the variables of interest to terrain features such as position, elevation and surface roughness. These models allowed an informed judgement to be made on the likelihood of accurately estimating the winds at other locations in the region using interpolation techniques.

A three-dimensional (3D) steady-state electron modulation model based on Parker (1965) transport equation is applied to study the modelling of – 7 MeV galactic and Jovian electrons in the inner heliosphere. The latter is produced within Jupiter's magnetosphere which is situated at - 5 AU in the ecliptic plane. The heliospheric propagation of these particles is mainly described by the heliospheric diffusion tensor. Some elements of the tensor, such as the diffusion coefficient in the azimuthal direction, which were neglected in the previous two-dimensional modulation studies are investigated to account for the three-dimensional transport of Jovian electrons. Different anisotropic solar wind speed profiles that could represent solar minimum conditions were modelled and their effects were illustrated by computing the distribution of 7 MeV Jovian electrons in the equatorial regions. In particular, the electron intensity time-profile along the Ulysses spacecraft trajectory was calculated for these speed profiles and compared to the 3-10 MeV electron flux observed by the Kiel Electron Telescope (KET) on board the Ulysses spacecraft from launch (1990) up to end of its first out-of-ecliptic orbit (2000). It was found that the model solution computed with the solar wind profile previously assumed for typical solar minimum conditions produced good compatibility with observations up to 1998. After 1998 all model solutions deviated completely from the observations. In this study, as a further attempt to model KET observations more realistically, a new relation is established between the latitudinal dependence of the solar wind speed and the perpendicular polar diffusion. Based on this relation, a transition of an average solar wind speed from solar minimum conditions to intermediate solar activity and to solar maximum conditions was modelled based on the assumption of the time-evolution of large polar coronal holes and were correlated to different scenarios of the enhancement of perpendicular polar diffusion. Effects of these scenarios were illustrated, as a series of steady-state solutions, on the computed 7 MeV Jovian and galactic electrons in comparison with the 3-10 MeV electron observed by the KET instrument from the period 1998 up to the end of 2003. Subsequent effects of these scenarios were also shown on electron modulation in general. It was found that this approach improved modelling of the post-1998 discrepancy between the model and KET observations but it also suggested the need for a time-dependent 3D electron modulation model to describe modulation during moderate to extreme solar maximum conditions. / Thesis (M.Sc.)--North-West University, Potchefstroom Campus, 2004.

A three-dimensional (3D) steady-state electron modulation model based on Parker (1965) transport equation is applied to study the modelling of – 7 MeV galactic and Jovian electrons in the inner heliosphere. The latter is produced within Jupiter's magnetosphere which is situated at - 5 AU in the ecliptic plane. The heliospheric propagation of these particles is mainly described by the heliospheric diffusion tensor. Some elements of the tensor, such as the diffusion coefficient in the azimuthal direction, which were neglected in the previous two-dimensional modulation studies are investigated to account for the three-dimensional transport of Jovian electrons. Different anisotropic solar wind speed profiles that could represent solar minimum conditions were modelled and their effects were illustrated by computing the distribution of 7 MeV Jovian electrons in the equatorial regions. In particular, the electron intensity time-profile along the Ulysses spacecraft trajectory was calculated for these speed profiles and compared to the 3-10 MeV electron flux observed by the Kiel Electron Telescope (KET) on board the Ulysses spacecraft from launch (1990) up to end of its first out-of-ecliptic orbit (2000). It was found that the model solution computed with the solar wind profile previously assumed for typical solar minimum conditions produced good compatibility with observations up to 1998. After 1998 all model solutions deviated completely from the observations. In this study, as a further attempt to model KET observations more realistically, a new relation is established between the latitudinal dependence of the solar wind speed and the perpendicular polar diffusion. Based on this relation, a transition of an average solar wind speed from solar minimum conditions to intermediate solar activity and to solar maximum conditions was modelled based on the assumption of the time-evolution of large polar coronal holes and were correlated to different scenarios of the enhancement of perpendicular polar diffusion. Effects of these scenarios were illustrated, as a series of steady-state solutions, on the computed 7 MeV Jovian and galactic electrons in comparison with the 3-10 MeV electron observed by the KET instrument from the period 1998 up to the end of 2003. Subsequent effects of these scenarios were also shown on electron modulation in general. It was found that this approach improved modelling of the post-1998 discrepancy between the model and KET observations but it also suggested the need for a time-dependent 3D electron modulation model to describe modulation during moderate to extreme solar maximum conditions. / Thesis (M.Sc.)--North-West University, Potchefstroom Campus, 2004.

A statistical downscaling approach based on multiple linear-regression is used to investigate the predictability of land surface winds over the Canadian prairies and Ontario. This study's model downscales mid-tropospheric predictors (wind components and speed, temperature, and geopotential height) from reanalysis products to predict historical wind observations at thirty-one airport-based weather surface stations in Canada. The model's performance is assessed as a function of: season; geographic location; averaging timescale of the wind statistics; and wind regime, as defined by how variable the vector wind is relative to its mean amplitude. Despite large differences in predictability characteristics between sites, several systematic results are observed. Consistent with recent studies, a strong anisotropy of predictability for vector quantities is observed, while some components are generally well predicted, others have no predictability. The predictability of mean quantities is greater on shorter averaging timescales. In general, the predictability of the surface wind speeds over the Canadian prairies and Ontario is poor; as is the predictability of sub-averaging timescale variability. These results and the relative predictability of vector and scalar wind quantities are interpreted with theoretically- and empirically-derived wind speed sensitivities to the resolved and unresolved variability in the vector winds. At most sites, and on longer averaging timescales, the scalar wind quantities are found to be highly sensitive to unresolved variability in the vector winds. These results demonstrate limitations to the statistical downscaling of wind speed and suggest that deterministic models which resolve the short-timescale variability may be necessary for successful predictions. / Graduate