scholarly journals Assessment of Wind Energy Potential In Zwara, Libya

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Alhassan A. Teyabeen ◽  
Fathi R. Akkari ◽  
Ali E. Jwaid ◽  
Ashraf Zaghwan ◽  
Rehab Abodelah
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Ground Level ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Wind Power Density ◽  
Wind Energy Potential ◽  
Wind Resource

To assess the wind energy potential at any site, the wind power density should be estimated; it evaluates the wind resource and indicates the amount of available wind energy. The purpose of this study is to estimate the monthly and annual wind power density based on the Weibull distribution using wind speed data collected in Zwara, Libya during 2007. The wind date are measured at the three hub heights of 10m, 30m, and 50m above ground level, and recorded every 10 minutes. The analysis showed that the annual average wind speed are 4.51, 5.86, 6.26 m/s for the respective mentioned heights. The average annual wind power densities at the mentioned heights were 113.71, 204.19, 243.48 , respectively.

scholarly journals Assessment of wind energy potential across varying topographical features of Tamil Nadu, India

2019 ◽  
Vol 38 (1) ◽  
pp. 175-200 ◽  
Author(s):  
Shafiqur Rehman ◽  
Narayanan Natarajan ◽  
Mangottiri Vasudevan ◽  
Luai M Alhems
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Tamil Nadu ◽  
High Energy ◽  
Energy Potential ◽  
Annual Average ◽  
Wind Power Density ◽  
Wind Energy Potential

Wind energy is one of the abundant, cheap and fast-growing renewable energy sources whose intensive extraction potential is still in immature stage in India. This study aims at the determination and evaluation of wind energy potential of three cities located at different elevations in the state of Tamil Nadu, India. The historical records of wind speed, direction, temperature and pressure were collected for three South Indian cities, namely Chennai, Erode and Coimbatore over a period of 38 years (1980-2017). The mean wind power density was observed to be highest at Chennai (129 W/m2) and lowest at Erode (76 W/m2) and the corresponding mean energy content was highest for Chennai (1129 kWh/m2/year) and lowest at Erode (666 kWh/m2/year). Considering the events of high energy-carrying winds at Chennai, Erode and Coimbatore, maximum wind power density were estimated to be 185 W/m2, 190 W/m2 and 234 W/m2, respectively. The annual average net energy yield and annual average net capacity factor were selected as the representative parameters for expressing strategic wind energy potential at geographically distinct locations having significant variation in wind speed distribution. Based on the analysis, Chennai is found to be the most suitable site for wind energy production followed by Coimbatore and Erode.

scholarly journals An Assessment of Wind Energy Potential for the Three Topographic Regions of Eritrea

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1846 ◽  
Author(s):  
Teklebrhan Negash ◽  
Erik Möllerström ◽  
Fredric Ottermo
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Coastal Region ◽  
Energy Potential ◽  
Wind Power Density ◽  
Prevailing Wind Direction ◽  
Central Highland ◽  
Wind Energy Potential

This paper presents the wind energy potential and wind characteristics for 25 wind sites in Eritrea, based on wind data from the years 2000–2005. The studied sites are distributed all over Eritrea, but can roughly be divided into three regions: coastal region, western lowlands, and central highlands. The coastal region sites have the highest potential for wind power. An uncertainty, due to extrapolating the wind speed from the 10-m measurements, should be noted. The year to year variations are typically small and, for the sites deemed as suitable for wind power, the seasonal variations are most prominent in the coastal region with a peak during the period November–March. Moreover, Weibull parameters, prevailing wind direction, and wind power density recalculated for 100 m above ground are presented for all 25 sites. Comparing the results to values from the web-based, large-scale dataset, the Global Wind Atlas (GWA), both mean wind speed and wind power density are typically higher for the measurements. The difference is especially large for the more complex-terrain central highland sites where GWA results are also likely to be more uncertain. The result of this study can be used to make preliminary assessments on possible power production potential at the given sites.

Climate change impacts on wind power density over southeastern Mediterranean

2020 ◽  
Author(s):  
Chris G. Tzanis ◽  
Kostas Philippopoulos ◽  
Constantinos Cartalis ◽  
Konstantinos Granakis ◽  
Anastasios Alimissis ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Energy Production ◽  
Energy Potential ◽  
Wind Power Density ◽  
Climatic Scenarios ◽  
Wind Energy Potential

<p>Energy production from the utilization of wind energy potential depends on the variability of the wind field as determined by the interaction of natural processes on different scales. Global climate change can cause alterations in the surface wind and thus it may affect the geographical distribution and the wind energy potential variability. Wind energy production is sensitive to wind speed changes, especially in the upper percentile of the wind speed distributions, where energy production is more effective. The importance of wind energy production changes is enhanced by the fact that wind energy investments are long-term and are characterized by high initial costs and low operating costs. In the present study, these changes are examined for the southeastern Mediterranean region, based on simulations of the Regional Climate Model ALADIN 5.2 extracted from the Med-CORDEX database for the climatic scenarios RCP4.5 and RCP8.5. The results indicate a wind power density increase over the Aegean Sea, the Ionian Sea, the Dardanelles and the Black Sea, with similar levels of increase for both climatic scenarios. In contrast, during the winter period there is a decline across the southeastern Mediterranean, which is more significant in the case of the RCP8.5 scenario. Finally, for most areas of eastern Greece, there is a reduction in the number of wind speed cases for both below and above cut-in and cut-out wind speeds, while there is an increase in the number of wind speed cases that wind turbines operate at their maximum power. The results are expected to reduce the uncertainty associated with the impact of climate change on wind energy production. </p>

Assessment of wind energy potential and characteristics in Qatar for clean electricity generation

2021 ◽  
pp. 0309524X2110438
Author(s):  
Carlos Méndez ◽  
Yusuf Bicer
Keyword(s):  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Rose ◽  
Energy Potential ◽  
Wind Power Density ◽  
Wind Speeds ◽  
Wind Energy Potential

The present study analyzes the wind energy potential of Qatar, by generating a wind atlas and a Wind Power Density map for the entire country based on ERA-5 data with over 41 years of measurements. Moreover, the wind speeds’ frequency and direction are analyzed using wind recurrence, Weibull, and wind rose plots. Furthermore, the best location to install a wind farm is selected. The results indicate that, at 100 m height, the mean wind speed fluctuates between 5.6054 and 6.5257 m/s. Similarly, the Wind Power Density results reflect values between 149.46 and 335.06 W/m2. Furthermore, a wind farm located in the selected location can generate about 59.7437, 90.4414, and 113.5075 GWh/y electricity by employing Gamesa G97/2000, GE Energy 2.75-120, and Senvion 3.4M140 wind turbines, respectively. Also, these wind farms can save approximately 22,110.80, 17,617.63, and 11,637.84 tons of CO2 emissions annually.

Wind resource assessment and wind farm modeling in Mossobo-Harena area, North Ethiopia

2020 ◽  
pp. 0309524X2092540
Author(s):  
Addisu Dagne Zegeye
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Power Density ◽  
Energy Production ◽  
Wind Farm ◽  
Ground Level ◽  
Energy Potential ◽  
Mean Power ◽  
Wind Energy Potential

Although Ethiopia does not have significant fossil fuel resource, it is endowed with a huge amount of renewable energy resources such as hydro, wind, geothermal, and solar power. However, only a small portion of these resources has been utilized so far and less than 30% of the nation’s population has access to electricity. The wind energy potential of the country is estimated to be up to 10 GW. Yet less than 5% of this potential is developed so far. One of the reasons for this low utilization of wind energy in Ethiopia is the absence of a reliable and accurate wind atlas and resource maps. Development of reliable and accurate wind atlas and resource maps helps to identify candidate sites for wind energy applications and facilitates the planning and implementation of wind energy projects. The main purpose of this research is to assess the wind energy potential and model wind farm in the Mossobo-Harena site of North Ethiopia. In this research, wind data collected for 2 years from Mossobo-Harena site meteorological station were analyzed using different statistical software to evaluate the wind energy potential of the area. Average wind speed and power density, distribution of the wind, prevailing direction, turbulence intensity, and wind shear profile of the site were determined. Wind Atlas Analysis and Application Program was used to generate the generalized wind climate of the area and develop resource maps. Wind farm layout and preliminary turbine micro-sitting were done by taking various factors into consideration. The IEC wind turbine class of the site was determined and an appropriate wind turbine for the study area wind climate was selected and the net annual energy production and capacity factor of the wind farm were determined. The measured data analysis conducted indicates that the mean wind speed at 10 and 40 m above the ground level is 5.12 and 6.41 m/s, respectively, at measuring site. The measuring site’s mean power density was determined to be 138.55 and 276.52 W/m2 at 10 and 40 m above the ground level, respectively. The prevailing wind direction in the site is from east to south east where about 60% of the wind was recorded. The resource grid maps developed by Wind Atlas Analysis and Application Program on a 10 km × 10 km area at 50 m above the ground level indicate that the selected study area has a mean wind speed of 5.58 m/s and a mean power density of 146 W/m2. The average turbulence intensity of the site was found to be 0.136 at 40 m which indicates that the site has a moderate turbulence level. According to the resource assessment done, the area is classified as a wind Class IIIB site. A 2-MW rated power ENERCON E-82 E2 wind turbine which is an IEC Class IIB turbine with 82 m rotor diameter and 98 m hub height was selected for estimation of annual energy production on the proposed wind farm. 88 ENERCON E-82 E2 wind turbines were properly sited in the wind farm with recommended spacing between the turbines so as to reduce the wake loss. The rated power of the wind farm is 180.4 MW and the net annual energy production and capacity factor of the proposed wind farm were determined to be 434.315 GWh and 27.48% after considering various losses in the wind farm.

scholarly journals The Investigation of Wind Energy Potential in Order to Estimate Power Plants in Baladeh Mazandaran, Iran

2012 ◽  
pp. 29-33
Author(s):  
S. Asghar Gholamian ◽  
S. Bagher Soltani ◽  
R. Ilka
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Power Plants ◽  
Weather Station ◽  
Energy Potential ◽  
Wind Power Density ◽  
Synoptic Weather ◽  
Wind Potential

First step for achieving wind energy is to locate points with appropriate wind power density in a country. Wind data which are recorded in a synoptic weather station, are the best way to study the wind potential of an area. In this paper wind speed period of Baladeh synoptic weather station is studied, since it has the maximum average of wind speed among 15 stations of the MAZANDARAN Province. Weibull factors k and c are calculated for 40 months from September 2006 to December 2009 and wind power density is determined based on these data. The total average of factors k and c for a height for 50 m are 1.442 m/s and 5.1256 respectively. By using the average of factors, wind power density in 50 m height will be 147.40 watt/m2 which is categorized as weak potential in wind class. However by monthly investigation it is shown that with a 50 m wind, this station can be put in medium class in hot months of the year.

Wind Energy Potential along the Onshore and Offshore Qatar

2020 ◽  
Author(s):  
Aboobacker Valliyil Mohammed ◽  
Ebrahim M.A.S. Al-Ansari ◽  
Shanas Puthuveetil Razak ◽  
Veerasingam Subramanian ◽  
Vethamony Ponnumony
Keyword(s):  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Time Series Data ◽  
Series Data ◽  
Energy Potential ◽  
Wind Power Density ◽  
Enso Events ◽  
Wind Energy Potential

Wind energy is one among the clean and renewable energy resources. The utilization of nonconventional energies over the conventional sources helps to reduce the carbon emissions significantly. The present study aims at investigating the wind energy potential at select coastal locations of Qatar using ERA5 winds. ERA5 is the updated reanalysis product of the European Centre for Medium-range Weather Forecasts (ECMWF), in which the scatterometer and in situ wind data are assimilated to improve the accuracy of predictions, thus the long-term and shortterm variabilities are reasonably well captured. Compared to the earlier studies, in this work, we have assessed the wind power at inland and offshore areas of Qatar, considering 40-year long (1979-2018) time series data with hourly ERA5 winds at 10-m height. The results show that there is no significant increase or decrease of wind power around Qatar in the last 40 years in most of the locations, while there is a slight decreasing trend in the offshore areas of Al Ruwais. This indicates that the average wind power is consistently available throughout the years. The links of climatic indices, especially the ENSO events with the wind climate of Qatar, are clearly evident in the long-term data. As obvious, the offshore regions of Qatar have relatively high wind power compared to the land areas. Among the selected locations, the highest annual mean wind power density is obtained in the offshore Al Ruwais (152 W/m2), followed by offshore Ras Laffan (134 W/m2) and land area of Al Khor (120 W/m2). The maximum wind power density varies between 1830 and 2120 W/m2 in the land areas, while it is between 1850 and 2410 W/m2 in the offshore areas of Qatar. The highest wind power is consistently available during the prevalence of shamal winds in winter (January-March) as well as summer (June).

scholarly journals Techno-Economic Investigation of Wind Energy Potential in Selected Sites with Uncertainty Factors

2021 ◽  
Vol 13 (4) ◽  
pp. 2182
Author(s):  
Varadharajan Sankaralingam Sriraja Balaguru ◽  
Nesamony Jothi Swaroopan ◽  
Kannadasan Raju ◽  
Mohammed H. Alsharif ◽  
Mun-Kyeom Kim
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Tamil Nadu ◽  
Series Data ◽  
Energy Potential ◽  
Data Set ◽  
Uncertainty Factors ◽  
Wind Energy Potential

This work demonstrates a techno-economical assessment of wind energy potential for four passes of Tamil Nadu (Aralvaimozhi, Shencottah, Palghat, and Cumbum) with uncertainty factors. First, a potential assessment was carried out with time-series data, and the Weibull parameters, such as c (scale) and k (shape), were determined using the modern-era retrospective analysis for research and applications (MEERA) data set. Using these parameters, the mean speed, most probable speed, power density, maximum energy-carrying speed of wind power were determined. From the analysis, it was observed that all four passes had better wind parameters; notably, the Aralvaimozhi pass attained a better range of about 6.563 m/s (mean wind speed), 226 W/m2 (wind power density), 6.403 m/s (most probable wind speed), and 8.699 m/s (max wind speed). Further, uncertainty factors, such as the probability of exceedance (PoE), wind shear co-efficient (WSC), surface roughness, and wake loss effect (WLE), were evaluated. The value of PoE was found to be within the bound for all the locations, i.e., below 15%. In addition, the ranged of WSC showed a good trend between 0.05 and 0.5. Moreover, the surface length of the passes was evaluated and recorded to be 0.0024 m with a 73% energy index. Further, output power, annual energy production (AEP), capacity factor (CF), and cost of wind energy of all four passes were computed using different wind turbine ratings in two cases, i.e., with and without WLE. It was observed that there was a huge profit in loss from all the four locations due to WLE that was estimated to be Rupees (Rs.) 10.07 crores without considering interest components and Rs. 13.66 crores with interest component at a 10% annual rate of interest.

scholarly journals Evaluation of Lebanon’s Offshore-Wind-Energy Potential

2019 ◽  
Vol 7 (10) ◽  
pp. 361 ◽  
Author(s):  
Gabriel Ibarra-Berastegi ◽  
Alain Ulazia ◽  
Jon Saénz ◽  
Santos J. González-Rojí
Keyword(s):  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Dew Point ◽  
Offshore Wind ◽  
Offshore Wind Energy ◽  
Energy Potential ◽  
Wind Power Density ◽  
Air Density ◽  
Wind Energy Potential

The only regional evaluation of Lebanese wind-energy potential (National Wind Atlas) dates back to 2011 and was carried out by a United Nations agency. In this work, data from the most recent reanalysis (ERA5) developed at the European Center for Medium Range Weather Forecast (ECMWF), corresponding to the 2010–2017 period, were used to evaluate Lebanese offshore-wind-energy potential. In the present study, wind power density associated to a SIEMENS 154/6 turbine was calculated with a horizontal resolution of 31 km and 1 hour time steps. This work incorporated the impact of air density changes into the calculations due to the seasonal evolution of pressure, temperature, and humidity. Observed average offshore air density ρ 0 was 1.19 kg / m 3 for the 2010–2017 period, but if instead of ρ 0 , hourly ρ values were used, seasonal oscillations of wind power density ( W P D ) represented differences in percentage terms ranging from −4% in summer to +3% in winter. ERA5 provides hourly wind, temperature, pressure, and dew-point temperature values that allowed us to calculate the hourly evolution of air density during this period and could also be used to accurately evaluate wind power density off the Lebanese coast. There was a significant gradient in wind power density along the shore, with the northern coastal area exhibiting the highest potential and reaching winter values of around 400 W / m 2 . Finally, this study suggests that the initial results provided by the National Wind Atlas overestimated the true offshore-wind-energy potential, thus highlighting the suitability of ERA5 as an accurate tool for similar tasks globally.

Techno-economic analysis of wind energy potential in Kazakhstan

2021 ◽  
pp. 095765092110015
Author(s):  
Hamed H Pourasl ◽  
Vahid M Khojastehnezhad
Keyword(s):  
Wind Speed ◽  
Energy Density ◽  
Wind Energy ◽  
Wind Power ◽  
Energy Production ◽  
Energy Utilization ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Average Wind ◽  
Wind Energy Potential

The use of renewable energy as a future energy source is attracting considerable research interest globally. In particular, there is a significant growth in wind energy utilization during the last few years. This present study through a detailed and systematic literature survey assesses the wind energy potential of Kazakhstan for the first time. Using the Weibull distribution function and hourly wind speed data, the annual power and energy density of the sites are calculated. For the 50 sites considered in this study and at a height of 10 m above the ground, the annual average wind speed, the power density, and energy production of Kazakhstan range from 0.94–5.15 m/s, 4.50–169.34 W/m2 and 39.56–1502.50 kWh/m2/yr, respectively. It was found that Fort Sevcenko, Atbasar, and Akmola are the three best locations for wind turbine installation with wind power densities of 169.34, 135.30, and 111.51 W/m2, respectively. Fort Sevcenko demonstrates the highest potential for wind energy harvesting with an energy density of 1483.46 kWh/m2/yr. For the 15 commercial wind turbines, it was observed that the annual energy production of the selected turbines ranges between 3.8 GWh/yr in Petropavlovsk to 15.4 GWh/yr in Fort Sevcenko among the top six locations. The lowest and highest capacity factors correspond to the same sites with the values of 29.21% and 58.66%, respectively. Overall, it is the intention of this study to constitute a database for the users and developers of wind power in Kazakhstan.

Sign in / Sign up

Export Citation Format

Share Document