Mean Wind Speed Research Articles

Transient surface pressure of a rectangular cylinder subjected to downburst-like winds

Thunderstorm downbursts are transient in nature and have been responsible for a variety of structural damages in recent years. Currently, the researchers have done several works on the characteristics of downburst wind speed. Nonetheless, rare attention has been placed on the structural aerodynamics characteristics subjected to downburst winds. Based on this, an experimental investigation is performed to reproduce downburst-like winds physically and to study the transient surface pressures (SPs) on a 5:1 rectangular cylinder (RC). The experiment is conducted within a multiple-fan active control wind tunnel (MFACWT) and mainly focuses on simulating the transient characteristics of downburst-like flow, including time-varying mean (TVM) wind speed and nonstationary wind fluctuation. The resulting SPs are measured to understand the influence of transient wind on the aerodynamic behavior of bluff bodies. The spatiotemporal characteristics of the SPs are analyzed using wavelet transform and Priestley's classic spectral theory. The results indicate that the transient nature of the downburst-like flow can be physically reproduced by a MFACWT. The instantaneous pressures of a RC are illustrated by both the turbulence parameters of the transient flow and the flow-separation characteristics. The pressure coefficients normalized by the TVM of the downburst-like winds remain constant, which provides a more appropriate way to estimate the transient gust loading in a quasi-steady manner. Interestingly, the phenomenon of the time-varying phase shift and time-varying correlation of chordwise SPs is observed when the turbulent velocity changes dramatically. In addition, the normalized surface pressure can be regarded as a stationary stochastic process, which provides a significant basis for further establishing the theoretical model of nonstationary gust-loading.

Observed Diurnal Cycles of Near‐Surface Shear and Stratification in the Equatorial Atlantic and Their Wind Dependence

AbstractThe diurnal cycles of near‐surface velocity and temperature, also known as diurnal jet and diurnal warm layer (DWL), are ubiquitous in the tropical oceans, affecting the heat and momentum budget of the ocean surface layer, air‐sea interactions, and vertical mixing. Here, we analyze the presence and descent of near‐surface diurnal shear and stratification in the upper 20 m of the equatorial Atlantic as a function of wind speed using ocean current velocity and hydrographic data taken during two trans‐Atlantic cruises along the equator in October 2019 and May 2022, data from three types of surface drifters, and data from Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) moorings along the equator. The observations during two seasons with similar mean wind speeds but varying surface heat fluxes reveal similar diurnal jets with an amplitude of about 0.11 m s−1 and similar DWLs when averaging along the equator. We find that higher wind speeds lead to earlier diurnal peaks, deeper penetration depths, and faster descent rates of DWL and diurnal jet. While the diurnal amplitude of stratification is maximum for minimal wind speeds, the diurnal amplitude of shear is maximum at 6 m depth for moderate wind speeds of about 5 m s−1. The inferred wind dependence of the descent rates of DWL and diurnal jet is consistent with the earlier onset of deep‐cycle turbulence for higher wind speeds. The DWL and the diurnal jet not only trigger deep‐cycle turbulence but are also observed to modify the wind power input and thus the amount of energy available for mixing.

Repeated drone photogrammetry surveys demonstrate that reconstructed canopy heights are sensitive to wind speed but relatively insensitive to illumination conditions

ABSTRACT Unoccupied aerial vehicle (UAV) based structure-from-motion (SfM) photogrammetry surveys are becoming a standard tool for ecologists to measure plant structure and biomass in non-forest ecosystems. The reproducibility of SfM survey results under different operational conditions, namely wind speed, sun elevation, and cloud condition, is poorly understood. It is also unclear to what extent commonly applied point-to-grid interpolation of derived point clouds affects inference of vegetation structure. These knowledge gaps limit the use of these methods for measuring and monitoring detection. We captured 61 UAV SfM surveys at the same study area under a range of wind/sun/cloud conditions over a 24-day period during 2021 and used generalized linear mixed effects models to test how the structural reconstructions varied with environmental conditions. Wind speed significantly influenced the canopy height reconstructions, with greater wind speeds reducing mean canopy height. Different plant species exhibited varying sensitivities to wind that are likely related to leaf attributes (size, structure, and density), growth form of the canopy, and physical properties such as limb flexibility. The movement of plants can reduce canopy height estimates derived from photogrammetric surveys, even under relatively low wind speeds. Reconstructed canopy heights were comparatively insensitive to solar elevation variations. Cloud conditions and illumination by direct sunlight had a weak, non-significant effect on reconstructed canopy height, with sunny conditions (generating shadows) resulting in a measurable but marginal reduction in mean canopy heights. When comparing canopy heights of interpolated and discontinuous derived canopy height models the results highlighted that these were insensitive to interpolation in this specific setting. We recommend measuring mean wind speeds throughout surveys where comparisons are to be made between different drone-based SfM surveys of vegetation over either time or space. Care should be taken to ensure that the effects of wind are controlled for so that inferences are valid.

Statistical Analysis of Wind Resource Assessment for Different Locations in South-Western Thailand

Weibull parameters have been widely used to evaluate wind energy potential. In this work presents wind resource assessment by statistical analysis with a Weibull distribution model for Krabi, Phuket, and Ranong weather stations in south-western Thailand. Ten-minute intervals include wind speed and wind direction of 10m from four-year records obtained by the Thai meteorological department. Four numerical methods, namely empirical method, graphical method, energy pattern factor method and maximum likelihood method are examined to estimate the Weibull parameters. The Weibull distribution obtained from each method is compared with the observed wind speed distribution by the performance tests using root mean square error, mean percentage error, and chi-square error to select a suitable method for the station area. The results revealed that the maximum likelihood method was the most accurate for Krabi and Phuket stations, and the energy pattern factor method was the most accurate for Ranong station. At a hub height of 80m, the highest mean wind speed and mean wind power density found in Krabi station were 3.25 m/s and 44.84 W/m2. The most probable wind speed value in three stations had a range from 1.80 to 2.50 m/s. The maximum wind speed carrying maximum energy found in Krabi station was 5.53 m/s. The operating probability of a wind turbine in Krabi station was 49.61%, followed by Phuket station was 46.80%, and Ranong station was 37.84%, respectively. In conclusion, all three stations had wind power potential classified as wind class 1 and can be sorted as follows: Krabi, Phuket, and Ranong stations.

Effects of turbulence integral length scales on aerodynamic characteristics and displacement responses of a square prism

This paper investigates the influence of the inflow turbulence integral length scales on the aerodynamic forces on a surface-mounted finite-length square prism and its displacement responses by computational fluid dynamics simulations. Four turbulent inflow conditions with the same mean wind speed and turbulence intensity but different longitudinal and transverse turbulence integral length scales are generated for the simulations. First, the wind pressures and forces on a rigid square prism model and the shear layer characteristics are simulated by large eddy simulations. The simulation results show that the mean characteristics of the wind pressures and shear layers are not sensitive to the turbulence integral length scales. However, the root mean square (RMS) wind pressures on side faces and RMS across-wind forces are increased with the longitudinal turbulence integral length scale, and the mechanism is analyzed by the proper orthogonal decomposition. Second, the displacement responses at the mean wind speed of vortex-induced resonance are computed based on an aeroelastic square prism model by fluid–solid interaction simulations. The RMS displacements of the model are observed to be more sensitive to the transverse turbulence integral length scale rather than the longitudinal turbulence integral length scale. Finally, the influence of the turbulence integral length scales on the Reynolds stresses around the square prism is presented and discussed.

Wind resource assessment for turbine class identification in Bayanzhaganxiang, China

Abstract The wind resource assessment has been used effectively to identify the classification of wind turbines at a particular wind farm site. The current study used WAsP software and various statistical methods such as graphical, energy pattern factor, standard deviation, and Rayleigh distribution methods to find the Weibull parameters by evaluating the raw data collected from August 2005 until July 2006 at four (4) different heights of the meteorological mast station in Bayanzhaganxiang, China. The Weibull parameters were utilized to find the annual mean wind speed, probability density, and cumulative distribution functions of wind conditions at the reference heights of 70 m, 50 m, 30 m, and 10 m. The wind shear coefficient was 0.130 with an overall roughness factor of 0.0385 m, suggesting the site vicinity is an open country with no significant structures and vegetation. The results also showed that the post-processed output from WAsP and standard deviation method at the sensor’s height of 70 m have a correlation coefficient and confidence level of 0.99977 and above 95%, respectively. Based on the turbine classification from GL Wind 2003 and IEC 61400-1 Ed.2, it was found that the turbine class ideal for the site is class III wind turbines with an annual mean wind speed of 7.439 m/s at a hub height of 99 m. The measured wind power density at hub height was calculated according to IEC 61400-12-1, which yields 464.36 W/m2. The characteristic wind turbulence at 70 m high is IEC subclass B. Among the selected wind turbines, the net annual energy production with efficiency is 8,059.57 MWh/year using Avantis AV1010, with the highest capacity factor of 40.05%. It has been found that the lowest energy generation cost is US$ 0.0292/kWh for a period of 20 years.

Evolution the Relationship Between Physiologically Equivalent Temperature and Some Meteorological Parameters for Basra City, Iraq

Background: Physiologically equivalent temperatures (PET) is highly efficient in evaluating the thermal component of any given microclimate as a single thermal index. The assist stakeholders in understanding and interpreting existing bioclimatic, allowing them to make any required modifications and become more robust to predicted climate change. Objective: This study assesses the relationship between Physiologically equivalent temperatures (PET) and some Meteorological Parameters. Methods: The data for this study includes observed mean monthly air temperature values, relative humidity, and wind speed for the period (2001-2020). The data was acquired from “Iraqi Meteorological Organization and Seismology (IMOS)” stations for Basra city. The radiation and Human Bioclimatic (RayMan) model were used to simulate bioclimatic indices (SET, UTCI, PET, PMV). Results: The findings revealed that the greatest mean values for PMV (4.3), SET (36.3), PET (45.5), and UTCI (42.1) were seen in July and August. The measurements have a nice thermal sensation of PMV (-0.5 - 1.9), SET (19.2- 29), PET (18.1- 31.8), and UTCI (15.9 - 28.7) is most noticeable in the months of (March, April, and October). The results showed the PET values (cool) and (Slightly cool) between (9- 18.3) for January, February, March, and December. The value of UTCI was between (5.9- 8.5) within classes (Slight cold stress), the values of PMV (-2.6- (-2.1)) within classes (strong cold stress) and (Slight cold stress) and the value of SET was (10.2- 12.4) within classes (Slight cold stress). Conclusions: Correlations between PET and air temperature (0.99), indicating good agreement between PET and air temperature, and relative humidity (0.96). PET and wind speed (R2=0.56). The scattering pattern of PET and other thermal indices shows that all indexes have a significant correlation coefficient, between PET and UTCI (R2=0.99), between PET and SET (R2=0.98), and (R2=0.99) between PET and PMV.

WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model

Abstract. Urban overheating and its ongoing exacerbation due to global warming and urban development lead to increased exposure to urban heat and increased thermal discomfort and heat stress. To quantify thermal stress, specific indices have been proposed that depend on air temperature, mean radiant temperature (MRT), wind speed, and relative humidity. While temperature and humidity vary on scales of hundreds of meters, MRT and wind speed are strongly affected by individual buildings and trees and vary on the meter scale. Therefore, most numerical thermal comfort studies apply microscale models to limited spatial domains (commonly representing urban neighborhoods with building blocks) with resolutions on the order of 1 m and a few hours of simulation. This prevents the analysis of the impact of city-scale adaptation and/or mitigation strategies on thermal stress and comfort. To solve this problem, we develop a methodology to estimate thermal stress indicators and their subgrid variability in mesoscale models – here applied to the multilayer urban canopy parameterization BEP-BEM within the Weather Research and Forecasting (WRF) model. The new scheme (consisting of three main steps) can readily assess intra-neighborhood-scale heat stress distributions across whole cities and for timescales of minutes to years. The first key component of the approach is the estimation of MRT in several locations within streets for different street orientations. Second, mean wind speed and its subgrid variability are downscaled as a function of the local urban morphology based on relations derived from a set of microscale LES and RANS simulations across a wide range of realistic and idealized urban morphologies. Lastly, we compute the distributions of two thermal stress indices for each grid square, combining all the subgrid values of MRT, wind speed, air temperature, and absolute humidity. From these distributions, we quantify the high and low tails of the heat stress distribution in each grid square across the city, representing the thermal diversity experienced in street canyons. In this contribution, we present the core methodology as well as simulation results for Madrid (Spain), which illustrate strong differences between heat stress indices and common heat metrics like air or surface temperature both across the city and over the diurnal cycle.

How heatwaves affect short-term emergency hospital admissions due to bacterial foodborne diseases

The coming decades are likely to see of extreme weather events becoming more intense and frequent across Europe as a whole and around the Mediterranean in particular. The reproduction rate of some microorganisms, including the bacteria that cause foodborne diseases, will also be affected by these events. The aim of this study was thus to ascertain whether there might be a statistically significant relationship between emergency hospital admissions due to the principal bacterial foodborne diseases (BFDs) and the various meteorological variables, including heatwaves.We conducted a time-series study, with daily observations of both the dependent variable (emergency hospital admissions due to BFDs) and the independent variables (meteorological variables and control variables of chemical air pollution) across the period 2013–2018 in the Madrid Region (Spain), using Generalised Linear Models with Poisson regression, in which control and lag variables were included for the purpose of fitting the models. We calculated the threshold value of the maximum daily temperature above which such admissions increased statistically significantly, analysed data for the whole year and for the summer months alone, and estimated the relative and attributable risks.The estimated attributable risk was 3.6 % for every one-degree rise in the maximum daily temperature above 12 °C throughout the year, and 12.21 % for every one degree rise in temperature above the threshold heatwave definition temperature (34 °C) in summer.Furthermore, different meteorological variables displayed a statistically significant association. Whereas hours of sunlight and mean wind speed proved significant in the analyses of both the whole year and summer, the variables “rain” and “relative humidity”, only showed a significant relationship in the analysis for the whole year.High ambient temperature is a risk factor that favours the increase in emergency hospitalisations attributable to the principal BFDs, with a greater impact being observed on days coinciding with heatwave periods. The results yielded by this study could serve as a basis for implementing BFD prevention strategies, especially on heatwave days.

Host vegetation connectivity is decisive for the natural spread of pine wilt disease.

Pine wilt disease has caused significant economic, ecological, and social losses in China, but there is a notable lack of research on the dynamic process of its propagation and diffusion over long timescales. This study revealed the spatial and temporal spread of the natural invasion of pine wilt disease through an analysis of long time series at macroscopic scales. We analysed and verified by simulations the driving mechanisms of host and wind fields in the natural spread of pine wilt disease. The research findings indicate that from 1982 to 2019, the number of counties affected by pine wilt disease in the Yangtze River Delta region of China exhibited a pattern of 'steady increase-fluctuation-outbreak'. The host forest played a decisive role in the natural spread of the disease, while the wind field played a supporting role. The study revealed specific contributions from various factors, where host forest landscape connectivity, host forest area share, mean wind speed, and wind frequency accounted for 31.8%, 28.7%, 22.6%, and 8.8%, respectively. The interaction of increased host forest area and increased wind speed can significantly increase the risk of pine wilt disease transmission. To validate these findings, vectorial metacellular automata simulations of pine nematode transmission in the Yangtze River Delta were conducted, yielding results with an accuracy of 0.803. By quantifying the contribution of host forest connectivity to the natural spread of pine wilt disease, this research offers a scientific foundation and innovative insights for preventing and controlling its dissemination. © 2024 Society of Chemical Industry.

Long-term trend of surface wind speed in the Guangdong-Hong Kong-Macau Greater Bay Area during 1980–2020: Spatiotemporal variation and urbanization effect

Understanding the surface wind speed variations is important for the climate and air quality assessment in the Guangdong-Hong Kong-Macau Greater Bay Area (GBA), known as the world class urban agglomeration in China. This study investigates the spatial and temporal variations of surface mean wind speed (MWS) in the GBA from 1980 to 2020, drawing upon ground observations and reanalysis data. After accounting for station relocations, the observed wind speed demonstrated a fluctuating declining trend of −0.036 m∙s−1 per decade over the examined period in line with reanalysis data. Wind speeds were found stronger during winter and daytime than summer and nighttime. The southern coastal regions exhibited higher MWS compared with northern mountainous areas. The Empirical Orthogonal Function (EOF) revealed the dominant mode of MWS changes was characterized by a cyclical pattern lasting over 20 years, probably influenced by atmospheric circulation. The urbanization reduced the observed wind speeds by 4.71% - 10.11% over the past decade (2011−2020) in urban areas of the GBA based on urban-minus-rural (UMR), observation-minus-reanalysis (OMR), and urban impact factor (UIF) methods. The long-term spatio-temporal analyses of MWS could benefit the climate and air quality studies and provide data support for regional and micro-scale modeling in the GBA.

Effects of irrigation‐induced surface thermodynamics changes on wind speed in the Heihe River basin, Northwest China

AbstractThe Heihe River Basin, located in Northwest China, serves as a major commodity grain base in China due to its state‐of‐the‐art irrigation system. The rapid increase in soil moisture caused by irrigation can alter the land–atmosphere energy fluxes and regulate regional climate. However, the effects and mechanisms of irrigation on wind speed related to thermodynamics remain unclear. Here, we carried out two 10‐year numerical simulations using the Weather Research and Forecast (WRF) model incorporating a real‐time irrigation scheme. By comparing the simulation differences (including and excluding irrigation), we found that irrigation significantly decreased the daily mean and maximum wind speed at 10 m above ground by 0.30 and 0.55 m·s−1, respectively, in the irrigated area during the growth season. Such surface wind slowdown could be explained by irrigation‐induced surface air cooling and, hence, intensifying atmospheric column stability, weakening turbulent momentum transport, as well as opposite‐to‐prevailing winds vector anomaly caused by increased southward pressure gradient. Meanwhile, we also found wind slowdown mainly occurs below 1100 m while acceleration effect above that level. It was highlighted that the surface wind slowdown effect of irrigation substantially improved the performance of the WRF model. Due to the surface wind slowdown effect of irrigation, the positive bias of daily mean and maximum wind speed simulated by the WRF model was reduced by 15.3% and 27.4%, respectively. Our findings implicate the potential importance of irrigation in improving the performance of climate models as well as in explaining the phenomenon of global stilling.

Assessment of Wind over Complex Terrain Considering the Effects of Topography, Atmospheric Stability and Turbine Wakes

This study proposes a microscale flow model to estimate mean wind speed, fluctuating wind speed and wind direction over complex terrain considering the effects of topography, atmospheric stability, and turbine wakes. Firstly, the effect of topography is considered using Computational Fluid Dynamics (CFD). Next, a mesoscale model is presented to account for the effect of atmospheric stability. The effect of turbine wakes on the mean and fluctuating wind speeds are then represented by an advanced wake model. The model is validated using the measurement data of a wind farm located in the North of Japan. The measured wind data by Lidar at a reference height are horizontally extrapolated to a nearby met mast hub height and validated by a cup anemometer. Moreover, a novel averaging method is proposed to calculate a directional equivalent Monin–Obukhov length scale to account for the effect of atmospheric stability. Finally, the measured wind data at the reference height are vertically extrapolated and validated at the lidar location. The predicted mean and fluctuating wind speeds show good agreement with the measurements.

Wind Potential Assessment for Songkhla, Thailand

The analysis and evaluation of wind energy projects are important to understand their economic and environmental suitability for installation and operation. Using wind data from the Meteorological Department, Used WAsP software for calculating, simulating, and analyzing the Annual Energy Production (AEP) and then applied it to calculate the Levelized Cost of Electricity (LCOE) of wind turbines installed in the Songkhla province area. The selected areas are suitable for all three models of wind turbines in the simulation. From the wind data analysis, wind direct was found that in the east sector (sector 4), there is the highest wind frequency at the wind station. The simulation results from Laem son-on area and Hua khao area show suitable mean wind speeds for wind farm installations. In the wind turbine simulation, three models were compared: Bonus 300 kW MkIII, Bonus 1.3 MW, and PowerWind 56 900 kW. At the Songkhla cape area, the positions with the highest AEP were 132.485 MWh, 344.419 MWh, and 332.597 MWh, respectively. Hua Khao area, the positions with the highest AEP were 225.284 MWh, 586.303 MWh, and 540.045 MWh, respectively. In the LCOE calculations for all model of wind turbines, at both Laem Son- On and Hua Khao locations, the most cost-effective wind turbine is the Bonus 300 kW. It has an LCOE of $142.43/MWh and $83.76/MWh, respectively. Therefore, the most cost-effective location is Hua Khao.

Impact of natural urban terrain on the pedestrian wind environment in neighborhoods: A CFD study with both wind and buoyancy-driven scenarios

The impact of topography on airflow has been studied at different scales, however the influence of urban natural terrain on local wind conditions is unclear. In this study, the impact of natural urban terrain on mean wind speed at the pedestrian level is investigated. A numerical study is conducted using a Large Eddy Simulation (LES) model for a high-density residential neighbourhood in Singapore with the natural terrain and a flat surface. The following two wind variations are examined (1) low wind speed and high temperature conditions for which the atmospheric boundary layer exhibits unstable thermal stratification; (2) annually averaged wind conditions with neutral thermal stratification. The results show that the overall impact of natural urban terrain on pedestrian wind speed is pronounced when the wind environment exhibits unstable thermal stratification i.e. buoyancy driven flows, compared with wind driven flows. For both cases, the results indicate a localized effect based on building density and proximity to steep terrain with spatial averages as high as approximately 0.8 m/s. In areas characterized by low density, fewer surrounding buildings, or open spaces, it is advisable to model the topography when it is shallow or steeply sloping. For medium density built areas, natural urban terrain modelling is also recommended. However, it is observed that in a high-density region, pedestrian wind flow is more strongly affected by the surrounding buildings than the terrain. These results are potentially important to balance computational cost and accuracy in urban wind simulations in urban areas with various densities and microclimate scenarios.

Direct measurements of sea spray particle fluxes using a high temporal resolution optical particle counter over the coastal ocean

ABSTRACT Sea spray particles play a key role in transferring momentum, heat, and gas across the atmosphere–ocean interface at high wind speeds and represent an important source of cloud condensation nuclei which affect the genesis, chemistry, and radiative properties of marine clouds. Here, we present direct measurements of sea spray particle fluxes obtained using an eddy covariance technique through the use of a newly developed high temporal resolution optical particle counter. With this instrumentation measurements were made over the coastal ocean during a 5-week field campaign conducted at an observation pier from November to December 2021. Our optical particle counter was capable of measuring size spectra at a rate of 10 Hz in 8 channels covering a range of mean radii between 0.3 and 15. The power spectra of particle number density followed the Kolmogorov −2/3 power law. The shape of the cospectrum of the particle number density flux was basically similar to that of the cospectra of the heat and gas fluxes. The measured sea spray particle fluxes at mean wind speeds of up to 21 m s−1 were dominated by an upward flux, which likely represents aerosol production caused by the bursting of bubbles at the ocean surface.

Comparing annual extreme winds in Iran predicted by numerical weather forecasting and Gram-Charlier statistical model with meteorological observation data

Iran has been experiencing severe dust storms due to strong wind speeds that cause sand erosion. This erosion is particularly pronounced in the semi-arid and arid zones. Wind speed predictions using numerical weather forecasting (NWF) are indispensable; however, the applicability of NWF for predicting extreme annual wind speeds is not well known. To validate the NWF model, this study compared NWF-model-predicted 3-hour averaged wind speeds over one year and those observed at 390 weather stations. In addition, a statistical model was employed to estimate the probability densities of wind speeds for both the observational data and the NWF output. As an NWF model, the mesoscale Weather Research and Forecasting (WRF) model was utilized to simulate wind speeds. The results indicate that the observation data are consistent with the modeled datasets regarding the relationships among the mean, standard deviation, and skewness, whereas the WRF model tends to overestimate the mean wind speeds. In addition, the predictability of annual extreme wind speeds was determined using the peak factor. Moreover, skewness has emerged as an influential parameter for predicting extreme winds. Finally, the Gram-Charlier series model was utilized to estimate probability density functions of the wind speeds, demonstrating its effectiveness in capturing positively skewed distributions. The present analyses broaden the use of both NWF outputs and statistical methods to predict extreme wind speeds in Iran.

Mathematical Differential Analysis of Atlantic Ocean Wind to Electrical Energy Generation in Lekki Peninsular Lagos Nigeria

This article is a pragmatic approach on the evaluation of wind energy production and it’s estimation in the coastal area of Lagos Nigeria. The work focuses on the accessibility of wind energy production in Lagos Nigeria through analyzing wind data in the look up tables using proficient probability function. Here, three approaches are itemized; Analysis of sets of actual time series data, theoretical Weibull probability function using seven numerical methods and the comparison of theory and the analysis. Two important parameters are used in this analysis are the Weibull shape factor “k” and Weibull scale factor “c”. Theory involves the calculation using seven popular methods of moments (MM), standard deviation method (STDM) or empirical method (EM), maximum likelihood method (MLM), modified maximum likelihood method (MMLM), second modified maximum likelihood method (SMMLM), graphical method (GM) or least mean square method (LSM), energy pattern factor method (EPFM). The performance of the numerical methods has been tested by five methods; RMSE, X2, IA, MAPE and RRMSE. The results expatiate on Actual and theoretical technique being used to find out wind energy conversion per 1 km2. In this paper, a differential performance method for accuracy check has been proposed as an error indicator between the wind energy calculated by theoretical Weibull function and the one by actual time-series data. The wind speed data was measured from January 2018 to December 2021 in the Lekki peninsular area of Lagos State. The suitability values for these parametric; shape and scale parameters of Weibull distribution are determined in selecting the best location for the installation the wind turbine generators. The measured annual mean wind speed and mean wind power are 10.11 ms-1 and 10.4 KWm-2, respectively.

Assessment of Wind Energy Potential at Three Prime Locations in Saudi Arabia: Analysis of Sharma, Qurayyat and Sakaka Sites

Purpose: The research aims to assess the wind energy potential at three chosen sites in Saudi Arabia Sharma, Al Qurayyat, and Sakaka over a five-year period from 2019 to 2023. The main goal is to determine the most favorable locations for wind farm development based on wind speed characteristics, Weibull distribution parameters, and wind power density (WPD). Materials and Methods: The wind speed data for the chosen locations was obtained from NASA's wind website and analyzed using the Weibull distribution to determine the shape (k) and scale (c) parameters, which are indicative of wind speed distribution. Critical metrics such as mean wind speed, WPD, and the most probable wind speed were computed to evaluate the wind energy potential. The Vestas V150-4.2 MW turbine was utilized to estimate potential energy output, considering the variability and reliability of wind resources at the specified locations. The study utilized tables, figures, and wind rose diagrams to highlight important wind parameters like mean wind speed, Weibull parameters, WPD, and Vmax for each location. Flowcharts were also used to summarize the methodology and conclusions, ensuring a clear and comprehensive presentation of the data. Findings: The analysis showed that Qurayyat consistently had the highest mean wind speed and WPD, indicating excellent wind energy potential. Sharma and Sakaka also displayed significant wind resources, with high mean wind speeds and substantial WPD values. The Weibull parameters indicated that all three sites have favorable wind characteristics for energy production. The estimated energy output using the Vestas V150-4.2 MW turbine ranged from 12,809 to 17,807 MWh/yr at Site 18, 14,095 to 15,170 MWh/yr at Site 24, and 14,013 to 15,832 MWh/yr at Site 31. Implications to Theory, Practice and Policy: The study presents a thorough evaluation of the wind energy potential in the Al-Jawf and Tabuk regions of Saudi Arabia. It contributes to a deeper understanding of wind resource distribution and its significance for the development of renewable energy. The study provides valuable insights for wind farm developers and policymakers by identifying the most promising locations for investment in wind energy infrastructure. Furthermore, it emphasizes the need for detailed site-specific analyses to optimize wind energy deployment, aligning with Saudi Arabia's broader renewable energy objectives.

Reduced-order modelling of floating offshore wind turbine: Aero-hydro-elastic stability analysis

A reduced-order aero-hydro-elastic analysis tool for performing the stability analysis on floating offshore wind turbines is presented. In this work, a high-order non-linear aero-elastic model initially developed for onshore wind turbines is extended by utilizing a super-element body, which models the floating platform, the mooring system and the hydrodynamic contributions. The turbine structure is modelled by a Finite beam Element Method, and the aerodynamic loads are modelled by the Blade Element Momentum method coupled with a Beddoes-Leishman type dynamic stall model in a state-space formulation. The linearization is performed around steady state equilibrium at any given mean wind speeds, rotor speeds and collective blade pitch angles utilizing Coleman transformation to remove the periodic terms. The order reduction is based on two projections to reduce the number of structural states and aerodynamic states separately using the structural modal project matrix and the aerodynamic shape functions. Concurrently, we investigate the effect of unsteady aerodynamic states on the stability analysis of a floating wind turbine. The results show the low-order aero-hydro-elastic model expands the scope of numerical tools available for conducting structural modal analysis and aero-hydro-elastic stability analysis on floating wind turbines.