Annual Mean Wind Research Articles

The making of the New European Wind Atlas – Part 1: Model sensitivity

Abstract. This is the first of two papers that document the creation of the New European Wind Atlas (NEWA). It describes the sensitivity analysis and evaluation procedures that formed the basis for choosing the final setup of the mesoscale model simulations of the wind atlas. The suitable combination of model setup and parameterizations, bound by practical constraints, was found for simulating the climatology of the wind field at turbine-relevant heights with the Weather Research and Forecasting (WRF) model. Initial WRF model sensitivity experiments compared the wind climate generated by using two commonly used planetary boundary layer schemes and were carried out over several regions in Europe. They confirmed that the most significant differences in annual mean wind speed at 100 m a.g.l. (above ground level) mostly coincide with areas of high surface roughness length and not with the location of the domains or maximum wind speed. Then an ensemble of more than 50 simulations with different setups for a single year was carried out for one domain covering northern Europe for which tall mast observations were available. We varied many different parameters across the simulations, e.g. model version, forcing data, various physical parameterizations, and the size of the model domain. These simulations showed that although virtually every parameter change affects the results in some way, significant changes in the wind climate in the boundary layer are mostly due to using different physical parameterizations, especially the planetary boundary layer scheme, the representation of the land surface, and the prescribed surface roughness length. Also, the setup of the simulations, such as the integration length and the domain size, can considerably influence the results. We assessed the degree of similarity between winds simulated by the WRF ensemble members and the observations using a suite of metrics, including the Earth Mover's Distance (EMD), a statistic that measures the distance between two probability distributions. The EMD was used to diagnose the performance of each ensemble member using the full wind speed and direction distribution, which is essential for wind resource assessment. We identified the most realistic ensemble members to determine the most suitable configuration to be used in the final production run, which is fully described and evaluated in the second part of this study (Dörenkämper et al., 2020).

Evaluation of Wind Energy Potential in a Sahelian Zone: A Case Study of Ouahigouya, Burkina Faso

This study investigates the characteristics of the wind energy potential in Ouahigouya, Burkina Faso. For this purpose, eleven-years data (2006-2016) of wind speed (at 10 m above ground level (AGL)) and surface temperature data from Burkina Faso meteorological agency and wind speed (50 m AGL) from the NASA were used. Based on the mean vertical profile of wind speed at monthly and annual scales, the Weibull function was used to characterize the wind speed frequency distribution and to calculate the wind power density. Major results indicate that the peaks of mean wind speeds are estimated at 3.51 m.s-1 (May) and 5.18 m.s-1 (March) for the 20 m and 50 m altitudes respectively. The mean annual wind speed at the 20 m AGL at the site is estimated at 2.87 m.s-1 while at 50 m AGL, a value of 4.33 m.s-1 is recorded. The estimated wind power density reveals that the largest amounts of energy are generally collected during the months corresponding to the dry season with peaks in March or May depending on the height. The amount of energy available at 20 m AGL varies from 32.90 W/m2 (September) to 84.97 W/m2 (May). At 50 m AGL, this value varies respectively from 68.68 W/m2 (August) to 346.47 W/m2 (March). Average annual power density amounts are estimated at 65.92 W/m2 at 20 m and 223.17 W/m2 at 50 m, respectively, for a growth rate of 70.46 %. In view of these results, the Ouahigouya site could be conducive to the installation of small and medium-sized turbines to supply rural communities with electrical energy.

Changes in wind turbine power characteristics and annual energy production due to atmospheric stability, turbulence intensity, and wind shear

The power generation of wind turbines varies depending on external environmental conditions. To present universal correlations between conditions that affect wind speed and wind turbine power, this study analyzed the effects of three atmospheric factors—atmospheric stability, turbulence intensity (TI), and wind shear exponent (WSE)—on the power performance and annual energy production (AEP) of wind turbines. Additionally, the horizontal and vertical speed components of the 3D sonic anemometer were investigated. At two measurement heights, unstable regimes showed an ascending air current, whereas stable regimes simultaneously showed both ascending and descending currents. Power curves calculated for each atmospheric factor regime revealed that atmospheric stability (200 kW–11 m/s) exhibited the greatest difference, followed by TI (91 kW–11 m/s) and WSE (32 kW–10.5 m/s). Finally, AEP was calculated at the annual mean wind speed of the study site and exhibited variations of 1.4–4% according to the factor regime. The AEP difference due to the change in atmospheric stability was greatest, and AEP was highest in moderately unstable atmospheric conditions. Clearer understanding of the effects of atmospheric factors on the power characteristics and AEP of wind turbines is expected to deliver practical benefits for wind-resource assessment and power-production prediction.

Influence of non-Gaussian characteristics of wind load on fatigue damage of wind turbine

Based on translation models, both Gaussian and non-Gaussian wind fields are generated using spectral representation method for investigating the influence of non-Gaussian characteristics and directivity effect of wind load on fatigue damage of wind turbine. Using the blade aerodynamic model and multi-body dynamics, dynamic responses are calculated. Using linear damage accumulation theory and linear crack propagation theory, crack initiation life and crack propagation life are discussed with consideration of the joint probability density distribution of the wind direction and mean wind speed in detail. The result shows that non-Gaussian characteristics of wind load have less influence on fatigue life of wind turbine in the area with smaller annual mean wind speeds. Whereas, the influence becomes significant with the increase of the annual mean wind speed. When the annual mean wind speeds are 7 m/s and 9 m/s at hub height of 90 m, the crack initiation lives under softening non-Gaussian wind decrease by 10% compared with Gaussian wind fields or at higher hub height. The study indicates that the consideration of the influence of softening non-Gaussian characteristics of wind inflows can significantly decrease the fatigue life, and, if neglected, it can result in non-conservative fatigue life estimates for the areas with higher annual mean wind speeds.

Wind energy potential assessment in the Persian Gulf: A spatial and temporal analysis

Despite the high capacity of wind energy in the offshore regions of Iran seas, wind power plants in these parts have not been significantly considered. In this study, the temporal and spatial wind characteristics and wind energy potential of the Persian Gulf are investigated during the years 2000–2017 based on the European Center for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis data set. The spatio-temporal distributions of the annual, seasonal, monthly, and diurnal mean wind characteristics are presented using the 18-year hourly resolution results. Statistical analysis and variability indices of the wind parameters are presented. The Weibull density function is used to assess and analyze the wind characteristics of the region. The Weibull shape k and scale c parameters are calculated using the maximum likelihood estimation (MLE) method. Finally, the wind capacities at the 12 potential locations near the populated or industrial regions around the studied area are derived. Besides, the capacity factor and the potential energy output of two commercial wind turbines are investigated, which are appropriate for the locations at 50 m and 80 m hub heights. The present results can be used to develop of wind energy plans and wind energy potential assessment in the studied area.

Correlation of spatial distribution and habitat factors of Firmiana danxiaensis based on GeoDetector

Firmiana danxiaensis is an endemic species of Danxia landform in China. Identifying the main driving factors of its distribution can provide scientific basis for the conservation of F. danxiaensis and related habitats. With GeoDetector, we analyzed the correlation (measured by q value) between the spatial distribution of F. danxiaens and its habitat factors in F. danxiaens Nature Reserve in Nanxiong City and the Guangdong Danxia Mountain Tourism Scenic Area (core scenic area). Factors measured in this study included geographical elements (geomorphological type, soil subtype, elevation, slope, aspect) and climatic elements (annual precipitation and annual sunshine hours, mean annual relative humidity and mean annual wind speed). Our results showed that the main habitat factors affecting the spatial distribution of F. danxiaensis were soil subtype, annual sunshine hours, and geomorphologic genesis type. The q values of those three factors were higher than the mean values of all factors. In the pairwise combination of habitat factors, the interaction between geomorphologic genesis types ∩ annual sunshine hours and soil subtypes ∩ annual sunshine hours was enhanced by two factors and the q value was greater than the mean value of all combinations, with a strong correlation. Compared with other factors, the q value of soil subtypes, annual sunshine hours and geomorphologic genesis types were significantly different in the ecological detection of spatial distribution correlation of F. danxiaensis. The spatial distribution of F. danxiaensis was significantly correlated with soil subtypes, geomorphologic genesis types and annual sunshine hours, indicating that the GeoDetector is a useful method for vegetation habitat factor analysis and species distribution prediction.

Study on the characteristics of climate change in Changbai Mountain National Natural Reserve from 1958 to 2017

Climate change is an important factor affecting the ecological environment of regions, and the local climate is closely related to the ecological environment. Taking the Changbai Mountain National Natural Reserve as an example, the regional climate change was studied by analyzing the data from the years 1953–2017. It is found that the temperature of Changbai Mountain is on the rise; the maximum monthly mean temperature difference is approximately 35 °C and the annual mean temperature is 2–5 °C. The monthly mean wind speed in this area has a wavy distribution and obvious seasonal variation. The correlation analysis shows that the correlation coefficient of the monthly mean value of cumulative photosynthetically active radiation (PAR) and total solar radiation (TSR), cumulative evaporation and cumulative PAR, cumulative evaporation and TSR, temperature and cumulative PAR, and temperature and cumulative evaporation were more than 0.9, indicating a significant correlation. The annual cumulative precipitation in this area is between 600 and 1000 mm, the annual cumulative evaporation is between 1000 and 1500 mm, the annual cumulative PAR is between 6000 and 10,000 mol m−2 s−1, and the annual TSR is between 4000 and 6000 MJ m−2. The annual cumulative precipitation, annual cumulative evaporation, annual mean wind speed, annual cumulative PAR, and annual TSR show a downward trend. The climate change in this area will not have a greater negative impact on the forest, but it still needs to pay close attention to the further climate change.

Local Climate Zone Classification Scheme Can Also Indicate Local-Scale Urban Ventilation Performance: An Evidence-Based Study

Studies on urban ventilation indicate that urban ventilation performance is highly dependent on urban morphology. Some studies have linked local-scale urban ventilation performance with the local climate zone (LCZ) that is proposed for surface temperature studies. However, there is a lack of evidence-based studies showing LCZ ventilation performance and affirming the reliability of using the LCZ classification scheme to demonstrate local-scale urban ventilation performance. Therefore, this study aims to analyse LCZ ventilation performances in order to understand the suitability of using the LCZ classification scheme to indicate local-scale urban ventilation performance. This study was conducted in Shenyang, China, with wind information at 16 weather stations in 2018. The results indicate that the Shenyang weather station had an annual mean wind speed of 2.07 m/s, while the mean wind speed of the overall 16 stations was much lower, only 1.44 m/s in value. The mean wind speed at Shenyang weather station and the 16 stations varied with seasons, day and night and precipitation conditions. The spring diurnal mean wind was strong with the speeds of 3.56 m/s and 2.21 m/s at Shenyang weather station and the 16 stations, respectively. The wind speed (2.21 m/s at Shenyang weather station) under precipitation conditions was higher than that (1.75 m/s at Shenyang weather station) under no precipitation conditions. Downtown ventilation performance was weaker than the approaching wind background, where the relative mean wind speed in the downtown area was only 0.53, much less than 1.0. The downtown ventilation performance also varied with seasons, day and night and precipitation conditions, where spring diurnal downtown ventilation performance was the weakest and the winter nocturnal downtown ventilation performance was the strongest. Moreover, the annual mean wind speed of the 16 zones decreased from the sparse, open low-rise zones to the compact midrise zones, indicating the suitability of using LCZ classification scheme to indicate local-scale urban ventilation performance. The high spatial correlation coefficients under different seasons, day and night and precipitation conditions, ranging between 0.68 and 0.99, further affirmed that LCZ classification scheme is also suitable to indicate local-scale urban ventilation performance, despite without the consideration of street structure like precinct ventilation zone scheme.

The temporal and spatial relationships between climatic parameters and fire occurrence in northeastern Iran

Fire is a natural disturbance in a wide range of ecosystem types around the world. Although the majority of fires are caused by anthropogenic ignitions, climate and weather are known to influence the risk of fire spread, regardless of ignition source. However, the specific relationships among these factors remain under-studied for many regions of the world. The objective of this study was to investigate the effect of climatic variables on forest and rangeland fire regimes in the Golestan Province of Iran in three recent decades. Specifically, we sought to determine: (a) the quantitative temporal relationships between climatic variables and fire occurrence; and (b) the spatial relationships between climatic variables and fire occurrence. To assess quantitative temporal relationships, we used correlation and regression analyses to identify and describe statistically significant relationships between climatic data (mean annual temperature, mean annual precipitation, mean annual relative humidity, and mean annual wind velocity) and fire data (number of fire and area burned), using climatic data from the Golestan Meteorological Administration and fire statistics from the Golestan Natural Resources Administration (GNRA). To determine the spatial relationships between climatic variables and fire occurrence, we combined geospatial data on climatic variables (mean annual temperature, mean annual rainfall, wind effect, and topographic wetness index (TWI)) obtained from ASTER-GDEM and active fires derived from MODIS fire products in a random forest (RF) model approach to construct a map of fire susceptibility at 30 m spatial resolution. Our results showed that there was a significant temporal relationship between the number of fires and mean annual temperature, mean annual relative humidity, and mean annual wind velocity. There were also significant temporal relationships between area burned and mean annual relative humidity and mean annual wind velocity. Based on the RF model, the mean annual rainfall had the highest relative importance in fire spatial occurrence. Validation of the fire susceptibility map using area under the curve (AUC) indicated that the RF model created an accurate fire susceptibility map (AUC: 0.823), suggesting that the map can be used as a spatio-temporal climatic alarm system for fire occurrence in the different climatic conditions of the Golestan Province. The results from this study will be important for helping perform climate-change analyses for investigating future temporal and spatial patterns of wildfire in the Golestan Province.

Evaluation of the Wind Potential and Optimal Design of a Wind Farm in The Arzew Industrial Zone in Western Algeria

This work presents an assessment of the wind potential and a design methodology for a 10 MW wind farm in the Arzew industrial region, located in northwest Algeria, to improve the quality of service of the electricity grid and increase Algeria's participation in the use of renewable energy. The hourly wind data of 10 years (2005-2015) that correspond to the wind potential of the site were analyzed, such as: dominant wind directions, probability distribution, Weibull parameters, mean wind speed and power potential. The site has a mean annual wind speed of 4.46 m/s at 10m height, and enough space to locate the wind turbines. A comparative study was carried out between four wind turbine technologies to improve the site's efficiency and select the appropriate technology: PowerWind 56/ 900 kW, Nordex N50/800 kW, Vestas V50/850 kW, NEG-Micon 44/750 kW. The estimate of the energy produced using WAsP software and the choice of the optimal architectural configuration for wind turbines installation was confirmed. A techno-economic and environmental study was carried out by HOMER software, to choose the model that produces the maximum annual net energy with a competitive cost in the global wind energy market, $ 0.068/kWh, and that provides clean energy with a reduced emission of polluting gases. Finally, this work provides a good indicator for the construction of a wind farm in Arzew.

Predictive model and assessment of the potential for wind and solar power in Rayak region, Lebanon

With the increasing consumption of fossil fuel, reducing greenhouse gas (GHG) emissions has become a serious issue that has attracted worldwide attention. Therefore, Lebanon is currently interested in utilizing renewable energy technologies to reduce energy dependence on oil reserves and GHG emissions. The present study is focused on solar and wind power potential and the economic viability of wind/solar systems for the Rayak region in Lebanon for the first time. The input data sources for the study including the Meteorological data for wind speed and NASA database for solar energy. In the assessment of wind energy, a two-parameter Weibull distribution function was used to analyze the characteristics of wind speed. Yearly and seasonal Weibull parameters were calculated for 10 m height using the Maximum likelihood method. In addition, yearly and seasonal wind power density values were calculated. The results showed that the mean annual wind speed and wind power density values were 5.884 m/s and 124.534 W/m2, respectively, during the investigation period. It can be concluded that the value of wind power density at the region was classified as marginal wind power potential and high-scale wind turbines can be used to gather wind energy potential in the region. Furthermore, predicting wind speed depends on various atmospheric factors and random variables. Therefore, 63 ANN models are developed by varying the meteorological parameters to predict the daily wind speed in the selected region. All the models with various combinations are validated and the performances of the models are analyzed using root mean squared error. The results demonstrated that the most relevant input variables for predicting the daily wind speed were found to be temperature, pressure, and relative humidity. In the assessment of wind energy, average monthly global solar radiation data were evaluated. It is found that the annual global solar radiation was 1877.41 kWh/m2, which indicates the selected region has high solar resources and is categorized as an excellent potential class. Moreover, this study provides a comprehensive and integrated feasibility analysis of 100 MW grid-connected wind and solar projects economic projects that can be developed in the country to reduce the electricity crisis and GHG emissions. Several different economic and financial indicators were calculated. The results indicate that the wind farm is a more economical option than the solar plant because of the higher values of NPV, BCR, ALCS, and IRR as well as the lower values of EB, SB, and LCOE.

Sakarya Nehri Deltası’nda Uzun Süreli Rüzgar ve Dalga İklimi Değişimleri

Global projections on the concept of climate change mainly indicate global warming, sea level rise and increases in climatic extremes. The main drivers of coast evolution related to climate change are rising sea levels, wave characteristics, storm frequency/intensity, and river floods. Delta plains are densely populated, and large numbers of people are often impacted by external terrestrial influences (e.g., river floods) and/or external marine influences (storm surges, erosion). Estuaries and deltas are widely recognized as highly vulnerable to the impacts of climate change, particularly sea-level rise and changes in runoff. The goal of this study is to evaluate the impact of climate change on wind and wave climate in a deltaic area. Sakarya River Delta system, a vulnerable deltaic area with a shoreline stretching approximately 80 km in Karasu province on the Black Sea coast of Turkey, is selected as a case study. Long-term wind and wave data in the study area were obtained from the NOAA CFSRR database and validated with measurements at different locations over the Black Sea. Annual mean wind speed and significant wave height show long-term decreasing trends (~4% and ~11%, respectively). Maximum wind speed and significant wave height tend to increase by 12% and 6%, respectively. In addition to the storm intensities, storm frequency also increases significantly (up to a 100% increase). The results of this study indicate that long-term changes in wind and wave climate in the study area are broadly consistent with climate change indicators.

Regional Study of Changes in Wind Power in the Indian Shelf Seas over the Last 40 Years

Wind power variations at two heights (the surface level and turbine hub level) were investigated at 20 locations in the shelf seas of India using hourly fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalyses of the global climate (ERA5) data covering the last 40 years (1979 to 2018). The interannual and seasonal variability in wind power was studied. The wind power density, the exceedance probability of power density and the exploitable wind resources were examined. In the Indian shelf seas, the annual mean wind power density at 10 m above mean sea level varies from 82 to 353 W/m2. Wind power density at 110.8 m is 20% to 40% higher than at 10 m above mean sea level. The study shows that the shelf seas have an abundance of wind power, with wind speeds over 3 m/s during 90% of the time at locations 1 to 3, 12 and 13, with a high occurrence of exploitable wind energy above 0.7 × 103 kWh/m2. Among the locations studied, the most power-rich area was location 12, where during ~62% of the time power was greater than 200 W/m2. A significant change (~10–35%) in inter-annual wind power density was detected at a few locations, and these variations were associated with Indian summer monsoon and El Niño–Southern Oscillation events. Trend analysis suggests a decreasing trend in the annual mean wind power density for most of the locations in the Indian shelf seas over the last 40 years. Wind power has considerable directional distribution, and at different locations the annual wind power from the dominant direction is 10% to 79% of the total available power from all directions.

A framework for preliminary large-scale urban wind energy potential assessment: Roof-mounted wind turbines

Urban wind energy can provide a decentralized local source of energy for residential areas and reduce the cost of energy by avoiding the losses/costs of long-distance energy transmission. In this perspective, a preliminary assessment of urban wind energy is highly desired by turbine developers, investors and policy makers. However, given the large number of parameters involved, predictions of the wind energy potential in urban areas are very challenging. The present paper, therefore, intends to present a straightforward framework to provide a preliminary and large-scale assessment of the urban wind energy potential, i.e. at city or country scales, for roof-mounted turbines. The framework is based on four main steps: (i) collecting the building data, i.e. the number of potential candidate high-rise buildings and their height and rooftop surface area; (ii) obtaining the annual mean wind speed statistics at the height of these buildings and sorting the building data based on these statistics; (iii) obtaining the turbine characteristics and determining the average number of turbines per building roof; (iv) calculating the annual energy production (AEP). The application of the framework is then illustrated at the country scale for the Netherlands. In this case, the urban wind energy potential is assessed by considering the installation of 18,156 small wind turbines on the roofs of 1513 existing high-rise buildings in 12 major cities in the Netherlands, yielding an annual energy production of 150.1 GWh.

Prioritization of the effectiveness rate of various climatic variables on the annual yield of rain-fed winter wheat using different statistical models

The annual yield of different plant species is affected by various parameters such as soil and water properties, climatic variables, etc. Due to the importance of the role of climatic variables on the yield of rain-fed winter wheat (as a strategic and effective plant species in the food security of the people of Iran), in this research the influence of climatic variables including the mean annual maximum temperature (MAT), the mean annual minimum temperature (MIT), the mean annual sunshine (SS), the mean annual relative humidity (HU), the mean annual wind speed (W) and the annual rainfall (R) on the annual yield of rain-fed winter wheat (AYWW) were evaluated based on the records of 10 stations from 1967 to 2016 scattered in Iran. To evaluate the impact of climate variables on the AYWW, the backward time series regression (BTSR), the backward logistic generalized estimating equation (BLGEE) and the backward generalized estimating equation (BGEE) statistical methods were used. All the statistical methods showed that W and SS variables were respectively the most and the least effective variables on the AYWW. Effective variables on AYWW in the BTSR were found to be the W, MIT and R (in 5, 4 and 1 stations out of 10), Effective variables on AYWW in the BLGEE were found to be the W, MIT, R and MAT (in 5, 3, 1 and 1 stations out of 10) and effective variables on AYWW in the BGEE were found to be the W, MIT, R and HU (in 5, 3, 1 and 1 stations out of 10).

A comparison between Advanced Scatterometer and Weather Research and Forecasting wind speeds for the Japanese offshore wind resource map

AbstractThis paper investigates the validity of the method used in the Japanese offshore wind map (NeoWins) to seamlessly connecting satellite‐derived wind speed for open oceans to mesoscale model‐simulated wind speed for coastal waters. In the NeoWins, the former was obtained from the satellite‐borne Advanced Scatterometer (ASCAT), and the latter was obtained from numerical simulations using the Weather Research and Forecasting (WRF) model. In this study, the consistency of the ASCAT and WRF 10‐m height wind speeds is examined in their overwrapping areas. The comparison between ASCAT and WRF model reveals that their differences in annual mean wind speed are mostly within ±5% and that the ASCAT annual mean wind speed is, as a whole, slightly higher than the WRF annual mean wind speed. The results indicate that there are no large wind speed gaps between WRF and ASCAT in most parts of the Japanese offshore areas. It is moreover found that the discrepancies between the two wind speeds are due to two factors: one is the existence of winter sea ice in the ASCAT observation in the Sea of Okhotsk in ASCAT observation and the other is that the accuracy of the WRF wind speed depends on atmospheric stability.

Load analysis and structural strength evaluation of semi-submersible platform for wind turbines in Jeju Island sea states using hydrodynamic-structure interaction analysis

The present study conducted an analysis of waves and wind on the west coast of Jeju Island in South Korea to derive the loads for a structural analysis under operational, extreme, and survival conditions and then evaluated the structural strength of the DeepCwind semi-submersible platform of NREL for 5 MW wind turbine. As a floating structure is exposed to wind and wave loads in a highly changeable marine environment and consists of tubular joints with slender-element members, a load analysis is necessary for strength evaluation and design of the structure. The wave scatter diagrams based on KORDI’s 24-year measurements of sea states and the annual mean wind speeds were used as the operational conditions. A sea state with a period that is very likely to cause the resonance of a floating structure was applied as the extreme condition. Another sea state during the Bolaven, a typhoon passing west of Jeju Island in 2000, is adopted as the survival condition. The surface pressure distribution of DeepCwind calculate through hydrodynamic analysis was applied to a structural analysis model based on a hydrodynamic-structure interaction analysis. The evaluation of the structural strength is performed in accordance with the provisions of DNV-OS-C201 and API-2A-WSD under operational, extreme, and survival conditions.

An Ensemble Framework to Investigate Wind Energy Sustainability Considering Climate Change Impacts

Wind power is a key element for future renewable energy resources and plays a vital role in sustainable development. Global warming and future climate conditions are going to impact many atmospheric, oceanic, and earth systems. In this study, impacts of climate change on wind power resources under future climatic conditions are evaluated for the Persian Gulf to explore the sustainability of this kind of energy for present and future developments. To that end, three regional climate models obtained from coordinated regional downscaling experiment (CRODEX), including daily simulations of near-surface wind speeds for a 20-year period in the present and future, were considered. Prior to computing the wind power at turbine hub-height, historical simulations of CORDEX were evaluated versus ERA-Interim wind outputs to determine the accuracy of the regional climate models. An attempt was made to build an ensemble model from available models by assigning weights to the models based on their merits. Subsequently, the wind power at the turbine hub-height was computed for historical and future periods to detect the impacts of climate change. Some points with a relatively high energy potential were selected as energy hotspots for further investigations. The results revealed that the mean annual wind power over the study area changed remarkably, which is of great importance for sustainable developments. Moreover, the results of the directional investigations showed roughly the same directional distribution for the future period as the past.

Association of leaf silicon content with chronic wind exposure across and within herbaceous plant species

AbstractAimHigh foliar silicon (henceforth Si) concentration protects plant tissues against herbivory, but protection against several abiotic stressors has also been proposed, although the adaptive significance of these functions is still being debated. We aimed to explore the potential relationships between foliar Si content and chronic wind exposure across a large scale and multiple species and to analyse an overlooked alternative or complementary function of silicon in leaves: mechanical protection against wind.LocationMainland China.Time periodFrom July to September during 2012–2014.Major taxa studiedTwo hundred and eighty‐two vascular plant species in predominantly herbaceous communities.MethodsWe compiled a dataset for leaf silicon concentration ([Si]) across 27 sites and 153 herbaceous plots within the major climate zones of China. We hypothesized that evolutionary lineages that generally have high [Si] should show positive relationships between leaf [Si] and mean annual wind speed.ResultsWithin major families with generally high [Si] (especially grasses, sedges and composites), leaf [Si] exhibits a consistently positive correlation with mean wind speed among species across China. For the seven widespread monocot species with high leaf [Si], including the globally distributed common reed (Phragmites australis), intraspecific variation in leaf [Si] exhibits the same consistent positive correlation with mean wind speed.Main conclusionsOur findings suggest that high leaf [Si] is likely to have widespread adaptive value for wind exposure of leaves, at least in several very widespread families and species of herbaceous plants. Damage from wind is a danger for plants in many ecosystems, hence these findings are of global significance and indicate that further research into large‐scale variation of leaf Si and mechanical traits in relationship to wind exposure is likely to be illuminating.

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.