Highest Wind Power Density Research Articles

Study and evaluation of wind power density for the use of small wind turbine under Baghdad conditions

The main aim of this research is to analyze the characteristics of the wind speed and wind power density in Baghdad City within micro-scale meteorological conditions at Mustansiriyah University Meteorological Station (MUMS). Temperature, atmospheric pressure and wind speed data were taken for one year (2016) measured at a height of 18 m above the earth's surface. Hourly, monthly, and seasonal changes in wind speed at an altitude of 30 m were estimated using a power law. The mean diurnal and monthly air density was calculated. Different statistical distributions were used, including the Rayleigh, Gamma and Weibull distributions, and the best distribution function was selected to evaluate the wind power density in the study area. The results showed the highest monthly mean of wind speed recorded in June and July. Therefore, these months have the highest wind power density. The lowest monthly mean of wind speed and wind power density was observed in December. The maximum and minimum values of air density were recorded in December, January and July, August, respectively. The monthly variation of the shape parameter (k) ranges between 0.99 - 1.81, while the monthly variation of the scale parameter(c) ranges between 1.07 - 2.3 m s-1. It was also found that the Weibull distribution was more accurate than the Rayleigh and Gamma distributions. The prevailing wind direction is northeast (NE) and east-northeast (ENE) most of the time. The research results showed that the study area is not suitable for using wind energy to generate energy.

A Circular-Linear Probabilistic Model Based on Nonparametric Copula with Applications to Directional Wind Energy Assessment.

The joint probability density function of wind speed and wind direction serves as the mathematical basis for directional wind energy assessment. In this study, a nonparametric joint probability estimation system for wind velocity and direction based on copulas is proposed and empirically investigated in Inner Mongolia, China. Optimal bandwidth algorithms and transformation techniques are used to determine the nonparametric copula method. Various parameter copula models and models without considering dependency relationships are introduced and compared with this approach. The results indicate a significant advantage of employing the nonparametric copula model for fitting joint probability distributions of both wind speed and wind direction, as well as conducting correlation analyses. By utilizing the proposed KDE-COP-CV model, it becomes possible to accurately and reliably analyze how wind power density fluctuates in relation to wind direction. This study reveals the researched region possesses abundant wind resources, with the highest wind power density being highly dependent on wind direction at maximum speeds. Wind resources in selected regions of Inner Mongolia are predominantly concentrated in the northwest and west directions. These findings can contribute to improving the accuracy of micro-siting for wind farms, as well as optimizing the design and capacity of wind turbine generators.

Optimization and Evaluation of the Weather Research and Forecasting (WRF) Model for Wind Energy Resource Assessment and Mapping in Iran

This study aims to optimize the Weather Research and Forecasting (WRF) model regarding the choice of the best planetary boundary layer (PBL) physical scheme and to evaluate the model’s performance for wind energy assessment and mapping over the Iranian territory. In this initiative, five PBL and surface layer parameterization schemes were tested, and their performance was evaluated via comparison with observational wind data. The study used two-way nesting domains with spatial resolutions of 15 km and 5 km to represent atmospheric circulation patterns affecting the study area. Additionally, a seventeen-year simulation (2004–2020) was conducted, producing wind datasets for the entire Iranian territory. The accuracy of the WRF model was assessed by comparing its results with observations from multiple sites and with the high-resolution Global Wind Atlas. Statistical parameters and wind power density were calculated from the simulated data and compared with observations to evaluate wind energy potential at specific sites. The model’s performance was sensitive to the horizontal resolution of the terrain data, with weaker simulations for wind speeds below 3 m/s and above 10 m/s. The results confirm that the WRF model provides reliable wind speed data for realistic wind energy assessment studies in Iran. The model-generated wind resource map identifies areas with high wind (wind speed > 5.6 m/s) potential that are currently without wind farms or Aeolic parks for exploitation of the wind energy potential. The Sistan Basin in eastern Iran was identified as the area with the highest wind power density, while areas west of the Zagros Mountains and in southwest Iran showed high aeolian potential during summer. A novelty of this research is the application of the WRF model in an area characterized by high topographical complexities and specific geographical features. The results provide practical solutions and valuable insights for industry stakeholders, facilitating informed decision making, reducing uncertainties, and promoting the effective utilization of wind energy resources in the region.

Towards urban wind utilization: The spatial characteristics of wind energy in urban areas

Urban wind energy is gaining increasing recognition for its environmentally friendly nature, particularly in the context of energy shortages. Predicting wind speed in urban environments is challenging due to the varying roughness and drag caused by obstacles on the ground. The complexity of urban morphology significantly disrupts the wind field and hampers the utilization of wind energy. This study aimed to investigate the diverse impacts of highly heterogeneous urban environment on the urban wind energy by innovatively establishing spatially varying power law wind profiles. Firstly, long-term LIDAR observations were conducted to measure the vertical wind profile in the study area. Then, a high-resolution LCZ map was created and integrated into the Weather Research and Forecasting (WRF) model to reproduce the urban wind field, which was validated using the observational data. Finally, the spatial characteristics of the urban wind field and wind energy were analyzed based on 3 representative points and the urban LCZ categories. The results show that the average power law exponents of each LCZ classification ranges from 0.29 to 0.75, with the average power law exponent of the high-volume building area being larger than 0.6. The highest wind power density in the study area can reach 343.3W/m2 at 200m height. Further, significant negative correlation coefficients were found between wind power density and building height, as well as building density, with values of approximately −0.6 and −0.35, respectively. Overall, the high-volume-ratio built-up areas with higher roughness had a notable impact on the wind speed by increasing the power law exponents. These spatially varying wind profiles are expected to provide technical support for the utilization of urban wind energy.

Wind power potential over northern South America using ERA5-Land global reanalysis

Abstract The northernmost region of South America has great potential for wind energy production and is a strategic area for the energy transition. We analysed data from ERA5-Land global reanalysis from 1980 to 2020 to determine the wind power potential in this area. Our aim was to identify areas with a high potential for wind energy that could be used to supply energy in case of drought in the region or increases in fuel prices. We compared data from 19 meteorological stations located in Colombia with ERA5-Land reanalysis data to generate reliable information for the feasibility and operation of wind farms. According to our analysis, the Colombian Caribbean and Coastal Plain have monthly average wind speeds at 90 m ranging from 4.85 to 10.34 m/s and 3.79 to 6.62 m/s, respectively. Based on wind power density calculations, these regions have the highest wind power density in our study, with a monthly average of between 250 and 399 W/m2. The Caribbean Region had a 69% increase in wind power density from January to July compared with the annual average. The wind power density in the plains increased from January to March, while the Mountain Region had higher anomalies from May to October. The Alta Guajira and Paraguaná Peninsula have great potential to generate wind energy due to their privileged geographical location. Although ERA5 offers valuable information about wind availability in time and space, it cannot represent the influence of local effects on wind patterns for the Mountain Region.

Future changes in wind energy resources in Egypt under Paris climate agreements’ goals

The Paris climate agreements’ goals ambitiously aim to hold mean global warming below 2.0°C and to pursue efforts to limit the warming to 1.5°C. One of the effective strategies for achieving these goals and reducing greenhouse gas emissions in the energy sector is using wind power. As Egypt is heavily investing in wind farm projects and planning to depend more on wind energy resources in its energy mix, it is important to assess the impact of climate change on its future wind energy production. This study employed eight global climate models of CMIP6 to project the wind power density (WPD) changes under the shared socioeconomic pathways (SSPs) 1–1.9 and 1–2.6 that inform Paris climate agreements and SSP5–8.5 that present the extreme warming scenario. The results showed that the WPD would increase in most Egypt, except in the far southeast. Increases would be pronounced over the far western desert and in Winter compared to other seasons. Nevertheless, Summer and Fall shall have the highest WPD by the end of the century compared to the present. This is favorable because the seasonal WPD pattern is sufficient to meet the local energy need. Unlike the intra-annual variability, few changes were projected in the inter-annual variability of WPD. Furthermore, a shift towards stronger WPDs compared to the historical period was observed. This study’s results can be useful for energy policymakers and planners in managing wind energy production under climate change scenarios.

GIS-assisted modeling of wind farm site selection based on support vector regression

The optimal siting of wind farms is a multi-attribute problem, and different objectives and constraints like economic, environmental, social, and technical should be taken into account. The widely-used category of site selection methods, multi-criteria decision making (MCDM), suffers from local scoring despite its numerous advantages. In this paper, support vector regression (SVR) is implemented to add the global scoring capability to MCDM by using a global-scale span of decision criteria. Here, the weighting of the decision criteria is obtained by the analytic hierarchy process (AHP), and then an SVR is utilized to appoint a score to any candidate site location. The proposed procedure has been used to study potential wind sites in Iran. In this regard, the study was conducted through three scenarios based on the natural and artificial potential of candidate sites. This study reveals that there are several vast areas, especially in eastern Iran, having high wind power density and flat terrain that are ready to be utilized as an endless source of clean energy provided that proper investment is made in power transmission lines and road networks.

Impacts of urban morphology on improving urban wind energy potential for generic high-rise building arrays

Previous findings have indicated better performance attained by modified urban morphologies for wind energy utilization only in single and pair buildings, or medium-dense low-rise building arrays. Hence, the main purpose of this study is to address the research gaps to complete a fundamental understanding of the influences of urban morphology in compact high-rise urban areas on enhancing urban wind energy harvest for sustainable urban development. A comprehensive parametric study is conducted using the computational fluid dynamics tool to analyze the impacts of urban morphologies on the wind energy potential for a 6 × 6 array of generic high-rise buildings, including (i) urban density altered from compact to sparse urban layouts, (ii) building corner shapes of sharp and rounded corners, (iii) urban layouts of in-line and staggered patterns, and (iv) wind directions of 0° and 45°. This investigation implements the three-dimensional steady Reynolds-averaged Navier-Stokes equations with the Reynolds stress model to explore the distributions of wind speed, power density, and turbulence intensity over the building array. The results indicate that decreasing urban plan area density reduces the unacceptable turbulence areas with relatively higher wind power density on the roof. Besides, round corners can produce elevated power densities up to 201% greater than sharp corners beside the building. Even under the oblique wind direction of 45°, the rounded corner still shows better wind energy potentials than the sharp corner. The in-line urban layout demonstrates more significant areas with higher power densities and low turbulence intensities than the staggered urban layout.

Wind potential estimation and proposed energy production in Southern Punjab using Weibull probability density function and surface measured data

Current work focusses on the wind potential assessment in South Punjab. Eleven locations from South Punjab have been analyzed using two-parameter Weibull model (with Energy Pattern Factor Method to estimate Weibull parameters) and five years (2014–2018) hourly wind data measured at 50 m height and collected from Pakistan Meteorological Department. Techno-economic analysis of energy production using six different turbine models was carried out with the purpose of presenting a clear picture about the importance of turbine selection at particular location. The analysis showed that Rahim Yar Khan carries the highest wind speed, highest wind power density, and wind energy density with values 4.40 ms−1, 77.2 W/m2 and 677.76 kWh/m2/year, respectively. On the other extreme, Bahawalnagar observes the least wind speed i.e. 3.60 ms−1 while Layyah observes the minimum wind power density and wind energy density as 38.96 W/m2 and 352.24 kWh/m2/year, respectively. According to National Renewable Energy Laboratory standards, wind potential ranging from 0 to 200 W/m2 is considered poor. Economic assessment was carried out to find feasibility of the location for energy harvesting. Finally, Polar diagrams drawn to show the optimum wind blowing directions shows that optimum wind direction in the region is southwest.

Evaluation of Wind Potential for the Generation of Electricity in Aliero, Kebbi State

One of the major developments in the technology today is the wind turbine that generates electricity and feed it directly to the grid which is used in many part of the world. The main purpose of this work is to determine the wind potential for electricity generation in Aliero, Kebbi state. Five years Data (2014-2018) was collected from the metrological weather station (Campell Scientific Model), the equipment installed at Kebbi State University of Science And Technology Aliero The data was converted to monthly and annual averages, and compared with the threshold average wind speed values that can only generate electricity in both vertical and horizontal wind turbines. The highest average wind speed 2.81 m/s was obtained in the month of January and the minimum average wind speed of 1.20 m/s in the month of October. Mean annual wind speed measured in the study area shows that there has been an increase in the wind speed from 2014 which peaked in 2015 and followed by sudden decrease to a minimum seasonal value in the year 2016. The highest wind direction is obtained from the North North-East (NNE) direction. From the results of wind power density it shows that we have highest wind power density in month of January and December with 0.8635 w/ m2 and 0.8295 w/ m2 respectively, while lowest wind power density in the month of October and September with 0.6780 w/ m2 and 0.6575 w/ m2 respectively. Result of the type Wind Turbine to be selected in the study area shows that the site is not viable for power generation using a horizontal wind turbine but the vertical wind turbine will be suitable for the generation of electricity.

Viability of Airborne Wind Energy in the United Kingdom

Abstract To meet the worldwide requirements of carbon emission reduction, the European Council has set the UK a 15% energy target to come from renewable energy by 2020. The biggest renewable energy sources in the UK are bioenergy, wind, solar, and hydro. The UK is located in prime geography, considered to be the best in Europe, for harvesting, and over the last three decades, the number of wind farms has increased greatly. However, the interaction of wind speed and structural strength has limited the height of platform-based wind turbines to a maximum height of around 100 m. Airborne wind energy (AWE) systems enable the extraction of more energy from the wind at elevated altitudes beyond 150 m using a device termed a kite. A method is required to determine suitable locations for AWE system implementation. In this work, a regional feasibility study has been conducted to establish an ideal suitable location to implement AWE systems. Extensive research has been carried out to assess the electricity costs, energy savings, area availability, as well as regional airborne wind energy power densities at different regions within the UK. A standardized method has been developed to assess the viability of AWE in various geographical locations. It was found that Scotland was the most suitable location for the implementation of AWE systems due to the high wind power density in this region and existing high costs of electricity, thus greater potentials for energy cost savings.

Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria

This study is aimed to investigate wind energy resource on the basis of Weibull and Rayleigh models in north eastern (Bauchi and Maiduguri) and western (Kano and Sokoto) Nigeria, seventeen years (2000-2016) monthly wind speed data were collected from Nigeria meteorological station, Abuja at 10m height. The probability distribution function (pdf) of wind speed is very important tool needed in wind energy resource investigation, since wind power is proportional to the cube of wind speed. The Weibull parameters shape (k) and scale (c) for the four locations were determined and the values obtained for shape factors in Bauchi and Maiduguri range from 6.91 to 7.21 and Sokoto and Kano range from 9.27 to 10.68, while scale factors is in the range of 3.46 to 7.24 and 9.32 to 11.24, respectively. The Weibull model was found to be better fit than the Rayleigh model in analyzing the wind speed data. The north western part of Nigeria was found to have higher wind power density as compared to the north eastern part of the country.

Wind energy assessment for the capital city of Jordan, Amman

In this study, the meteorological statistics recorded of seven-year wind speed data of the capital city of Jordan, Amman at height 10 m is utilized to assess the potential of wind energy. Also, statistical assessment of wind characteristics is evaluated by the two-parameter Weibull function. Monthly and annual wind speed variation is also analyzed. The study shows that Amman city is more suitable for small-scale wind turbine farms with the current wind speeds. The values of the shape Parameter K, and scale Parameter c show a various ranges between (1-1.5) and (1.5 m/s - 3.5 m/s), respectively. It was also noticed that the annual mean wind speed v̅ is between 2.2 and 3.02 m/s. Results also showed that the highest wind power density is in June whereas the lowest is in October. In wind direction estimation, it was found that most of wind direction for the seven-years is between the southwest and the northwest, i.e. (135°-215°).

On wind speed pattern and energy potential in China

To achieve sustainable socioeconomic development as part of the global community, China has set ambitious goals for developing wind power within its national energy security framework. Existing wind power density maps in China present some knowledge gaps (e.g., lack of spatiotemporal resolution/characteristics and estimates at the height of a typical wind turbine). To address them, we combine the advantages of large network of wind speed observations (2430 meteorological stations; 2006–2015) and the grid-based method in order to create the spatiotemporal distributions of wind resource at the hub height. We found that the spatiotemporal variability of wind resources in China is apparent. Nationally, the annual mean wind speed and wind power density are 4.09 m s−1 and 164.1 W m−2, respectively. Spatially, Northeast China has the highest wind potential with annual mean wind speed and power density 4.64 m s−1 and 204 W m−2, while South China has the lowest wind potential annual mean wind speed and power density 3.55 m s−1 and 97.4 W m−2. Temporally, the wind resources over the entire China are higher in the cold season (spring and winter with peaks in April) than those in the warm season (summer and autumn with bottoms in August). Specifically, the wind power output in “Three North” region (including Northeast China, North China and Northwest China) in the cold season is 1.4 times higher than that in the warm season. Some coastal regions in East China have relatively high wind power density (>500 W m−2) and small seasonal variations. These findings should help decision-makers to identify the areas suitable for utilizing wind energy, and optimizing power generation and transmission across the grid for better system performance.

Feasibility of offshore wind energy as an alternative source for the state of Kuwait

The techno economic feasibility of offshore wind energy potential for Kuwait was assessed. The main objective was focused on selecting right locations for commercial wind mill erections. The measured wind speed from Directorate General of Civil Aviation, Kuwait for eight offshore stations during January 2012 to December 2015 was used and the parameters of Weibull distributions and wind power densities are estimated at an extrapolated elevation of 30-m from mean sea level. It is found that the best marine location was Beacon N6, just 3 km south of Boubiyan Island with wind power density of 583.2 W/m2 during summer. It was found that the wind power density near the coastal area peak in summer, which is good, since in summer, the demand for energy is high. The next highest wind power density was at South Dolphin and Ahmadi oil pier area, which is also closer to mainland. The wind power density was also found to be high at offshore locations such as Sea Island Buoy, Umm Al-Maradim, and Beacon M28 during winter. In Kuwait, the wave climate is moderate and the water depths are less than 20 m for most of the sites. Economic analysis is carried for a 50 MW offshore wind mill and is compared with 800 MW thermal power plant. From this analysis, it is found that power production/kWh from offshore wind turbines will be about 30% cheaper compared to the oil based thermal power plant.

Wind speed and power characteristics of Kalasin province, Thailand

This paper presents a wind energy assessment of Kalasin province in the Upper North-Eastern region of Thailand. Four year wind data were recorded continuously from January 2012 to December 2015 at different heights of 60, 90 and 120 m above ground level (AGL). The mean wind speeds were found to be 3.14, 3.63 and 3.94 m/s at 60, 90 and 120 m AGL, respectively. The majority of wind directions for this region are distributed from the East to South directions. The highest wind power density was observed in the summer season, followed by winter and rainy seasons, in order. Four commercial wind turbines were selected to estimate energy yield output using the WAsP 10.0 software application; the results show that VESTAS with rated power of 2.0 MW was estimated to give 2,747 MWh/year with the highest capacity factor of 15.68%.

Wear Resistance Performance of Conventional and Non-Conventional Wind Turbine Blades with TiN Nano-Coating

Efficiency and durability are critical issues that affect widely-adopted aerofoil-power generator as a sustainable source of electrical power. Even though high wind power density can be achieved; installing wind turbines in desert condition has difficulties including thermal variation, high turbulence and sand storms. Sand blasting on turbine blade surface at high velocities causes erosion resulting turbine efficiency drop. Damage-induced erosion phenomena and aeroelastic performance of the blades needed to be investigated. Suitable coating may prevent erosion to a great extent. A numerical investigation of erosion on NACA 4412 wind turbine blade has been performed using commercial computational fluid dynamics software ANSYS FLUENT 14.5 release. Discrete phase model (DPM) has been used for modelling multi-phase flow of air and sand particles over the turbine blade. Governing equations have been solved by finite volume method (FVM). Conventional 30-70% glass fibre resin and non-conventional jute fibre composite have been used as turbine blade material. Sand particles of diameter have been injected from 20, 30, 45, 60 and 90 degree angles at 500C temperature. Erosion rate, wall shear stress and strain rate have been calculated for different wind velocities and impingement angles. Simulation results for higher velocities deviate from the results observed at lower wind velocities. In simulation, erosion rate is highest for impingement angle at low wind velocities, which has been validated by experiment with a mean absolute error (MAE) of 5.56%. Erosion rate and wall shear stress are higher on jute composite fibre than glass fibre resin. Developed shear stress on wind turbine blade surface is highest for impingement angle at all velocities. On the other hand, exerted pressure on turbine blade surface is found highest for 9 angle of attack. Experimental results, with or without Titanium nitride(TiN) nano-coating, also revealed that surface roughness augments with increasing impingement angles. Nano-coating (TiN) by RF sputtering technique reduced the surface roughness significantly as oppose to uncoated samples. Highest roughness has been observed on uncoated blade surface collided with 0.3-0.69 mm diameter brown aluminium oxide particles.

Evaluation of wind resource potential in mountainous region considering morphometric terrain characteristics

In South Korea, where 64% of the national territory is mountainous, good wind resources in inland areas are mostly situated in high mountain regions. To develop a wind farm in a mountain region, the sloping of mountains and their shielding from wind by the surrounding topology should be considered. It is generally most advantageous to install wind turbines along a ridge that is open in all directions. This article presents a methodology for evaluating suitable sites for wind farm development by identifying suitable ridges using morphometric analysis, while excluding the geographical and social environmental exclusion factors and superposing them on the wind resource map to find the area having a specific level or higher wind power density. The result of the proposed suitable site analysis and existing wind farms was assessed to verify the feasibility of the method of analyzing suitable sites on ridges. The wind resource potential in Gangwon Province when calculated using a method based on conventionally suitable site and the method based on ridge analysis was 9 and 5 GW, respectively. The result confirmed that the conventional area-based potential calculation without consideration of the morphometric terrain characteristics overestimated wind resource potential by around 80% compared to the ridge analysis method of calculation presented in this article.

Wind Energy Potentials and Its Trend in the South China Sea

Using a 30year (1976-2005) daily high-resolution reanalysis wind field dataset assimilated from several meteorological data sources, the wind speed and power characteristics of the South China Sea (SCS) were investigated using the Weibull shape and scale parameters. The region in general showed good wind characteristics. This is shown by high annual mean wind speed and power density values which are 5.93 m/s and 273.84 W/m2 respectively. The calculated annual mean wind power resource attributes the region to a relatively high potential site for large- scale grid connected wind turbine applications. The wind power ranged between 96.27 W/m2 in May and 527.03 W/m2 in December. Furthermore, spatio-temporal variations showed that strong trends in wind power exist in Luzon strait in the northern SCS and Xisha, Zhongsha, Luzon, Liyue bank in the central SCS which are evaluated as high wind potential regions and may be rated as locations excellent for installation of large wind turbines for electrical energy generation. Non-significant and negative trends dominate the southern SCS and may therefore, be suitable for small wind applications. The wind power density exhibited a significant increasing trend of 1.4 W/m2 yr-1 in the SCS as a whole throughout the study period. The trend is strongest (2.8 W/m2 yr-1) in winter.

Offshore Wind Energy Analysis of Cyclone Xaver over North Europe

Cyclone Xaver (5 December 2013; North Sea) was an extreme weather event which affected northern Europe, yielding a record of wind power generation. The most striking aspects of this atmospheric phenomenon were the gale-force winds and the upcoming abrupt increase of the wind power over the North Sea. The main objective of the study is the analysis of the impact of Xaver on offshore wind power production. In this way, the WRF numerical model was used to simulate the cyclone in a fine horizontal resolution (5km x 5km). The focus of the simulation is on the extended region of the North Sea and the Baltic Sea. The evaluation of the model outputs against observational data from 3 offshore locations denotes a sufficient agreement (SI≈0.12) and supports a realistic analysis of the wind field. The simulation exposed much higher values for wind speed over the North Sea compared to the neighboring regions during the passage of the cyclone. The wind speed at the 100 m level ranged within 11-25 m/s (rated output wind speed) for 40 hours over the North Sea and 70 hours over the Baltic Sea. On the other hand, the wind speed at 100 m exceeded 25 m/s (cut out wind speed) for ca 30 hours over the North Sea. In addition, comparison of wind power density between two different height levels (100 m and 200 m) is presented. The model results indicate 15% to 20% higher wind power density at 200 m than for 100 m for the largest part of the North Sea. For some regions the difference exceeds 25%.