Statistical analysis of measured wind speed data’s appealing spreadsheet applications

2021 ◽  
Vol 66 (1) ◽  
pp. 100-108
Author(s):  
Cristian Paul Chioncel ◽  
Nicoleta Gillich ◽  
Gelu-Ovidiu Tirian
Keyword(s):  
Statistical Analysis ◽  
Wind Farm ◽  
Time Series Data ◽  
Series Data ◽  
Energy Yield ◽  
Energy Potential ◽  
Wind Potential ◽  
Weibull Models ◽  
Wind Energy Potential ◽  
Probability Density Distributions

Once the wind data is measured, the values are processed, based on statistic approach, as accurately as possible, to provide a clear over-view of the locations wind potential, being the basis of any wind farm project, representing the go or no-go in further subsequent design steps. The probability density distributions are derived from time-series data, identifying the associated distributional parameters. The wind energy potential of the locations is studied based on the Rayleigh and Weibull models, implemented with the help of Excel computations, and representing tools, to understand the wind characteristics. Based on the statistical analysis of wind conditions presented here, the results of current study can be used to make a sustainable energy yield for any location.

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 Data analysis wind monitoring in the Republic of Tatarstan

2020 ◽  
Vol 21 (6) ◽  
pp. 39-50
Author(s):  
E. V. Nasyrova ◽  
N. F. Timerbayev ◽  
O. V. Leukhina ◽  
I. Yu. Mazarov
Keyword(s):  
Wind Power ◽  
Wind Farm ◽  
Detailed Calculation ◽  
Energy Potential ◽  
Wind Speeds ◽  
Wind Generators ◽  
Direct Measurements ◽  
Wind Potential ◽  
Wind Energy Potential ◽  
The Republic

The paper presents the results of wind monitoring carried out in order to confirm the feasibility of building a wind farm in the Republic of Tatarstan. The task of wind monitoring is to determine and study the dynamics of the average annual wind regime and calculate the wind energy potential at promising sites for placing a wind power plant. On the given sites, after the annual cycle of meteorological parameters measurements, the average annual wind speeds, wind power, preferred directions, wind density, vertical profile of the wind flow and other data necessary for a detailed calculation of the wind power potential of the sites and the selection of specific models of wind generators and their arrangements for operation will be determined at these sites. An important component of the work performed is the development of methods for calculating wind potential at heights other than the heights of direct measurements.

scholarly journals Wind Data Analysis and Wind Flow Simulation Over Large Areas

2014 ◽  
Vol 10 (1) ◽  
pp. 38-45
Author(s):  
Angel Terziev ◽  
Ivan Antonov ◽  
Rositsa Velichkova
Keyword(s):  
Renewable Energy ◽  
Wind Energy ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Wind Flow ◽  
Energy Potential ◽  
Wind Potential ◽  
Wind Energy Potential ◽  
The Impact

Abstract Increasing the share of renewable energy sources is one of the core policies of the European Union. This is because of the fact that this energy is essential in reducing the greenhouse gas emissions and securing energy supplies. Currently, the share of wind energy from all renewable energy sources is relatively low. The choice of location for a certain wind farm installation strongly depends on the wind potential. Therefore the accurate assessment of wind potential is extremely important. In the present paper an analysis is made on the impact of significant possible parameters on the determination of wind energy potential for relatively large areas. In the analysis the type of measurements (short- and long-term on-site measurements), the type of instrumentation and the terrain roughness factor are considered. The study on the impact of turbulence on the wind flow distribution over complex terrain is presented, and it is based on the real on-site data collected by the meteorological tall towers installed in the northern part of Bulgaria. By means of CFD based software a wind map is developed for relatively large areas. Different turbulent models in numerical calculations were tested and recommendations for the usage of the specific models in flows modeling over complex terrains are presented. The role of each parameter in wind map development is made. Different approaches for determination of wind energy potential based on the preliminary developed wind map are presented.

scholarly journals Aerodynamic Performance of the NREL S826 Airfoil in Icing Conditions

2017 ◽  
Author(s):  
Julie Krøgenes ◽  
Lovisa Brandrud ◽  
Richard Hann ◽  
Jan Bartl ◽  
Tania Bracchi ◽  
...  
Keyword(s):  
Wind Farm ◽  
Aerodynamic Performance ◽  
Cold Climate ◽  
Navier Stokes ◽  
Computational Results ◽  
Energy Potential ◽  
Pressure Distributions ◽  
Wind Energy Potential ◽  
Experimental Values ◽  
Lift And Drag

Abstract. The demand for wind power is rapidly increasing, creating opportunities for wind farm installations in more challenging climates. Cold climate areas, where ice accretion can be an issue, are often sparsely populated and have high wind energy potential. Icing may lead to severely reduced aerodynamic performance and thereby reduced power output. To reach a greater understanding of how icing affects the aerodynamics of a wind turbine blade, three representative icing cases; rime ice, glaze ice and a mixed ice, were defined and investigated experimentally and computationally. Experiments at Re = 1.0 × 105–4.0 × 105 were conducted in the low-speed wind tunnel at NTNU on a two dimensional wing with applied 3D-printed ice shapes, determining lift, drag and surface pressure distributions. Computational results, obtained from the Reynolds Averaged Navier–Stokes fluid dynamics code FENSAP, complement the experiments. Measured and predicted data show a reduction in lift for all icing cases. Most severe is the mixed ice case, with a lift reduction of up to 30 % in the linear lift area, compared to a clean reference airfoil. Computational results show an under-prediction in maximum lift of 7–18 % compared to experimental values. Curvature and tendencies for both lift and drag show good agreement between simulations and experiment.

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 Market model analysis and forecasting behavior of watermelon production in Bangladesh

2014 ◽  
Vol 26 (1-2) ◽  
pp. 47-56
Author(s):  
Murshida Khanam ◽  
Umme Hafsa
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
Linear Models ◽  
Time Series Data ◽  
Arima Model ◽  
Model Analysis ◽  
Market Model ◽  
Series Data ◽  
Log Linear

An attempt has been made to study various models regarding watermelon production in Bangladesh and to identify the best model that may be used for forecasting purposes. Here, supply, log linear, ARIMA, MARMA models have been used to do a statistical analysis and forecasting behavior of production of watermelon in Bangladesh by using time series data covering whole Bangladesh. It has been found that, between the supply and log linear models; log linear is the best model. Comparing ARIMA and MARMA models it has been concluded that ARIMA model is the best for forecasting purposes. DOI: http://dx.doi.org/10.3329/bjsr.v26i1-2.20230 Bangladesh J. Sci. Res. 26(1-2): 47-56, December-2013

Investigation on offshore wind energy potential in Benin Republic

2019 ◽  
pp. 0309524X1987276 ◽  
Author(s):  
Maurel R Aza-Gnandji ◽  
François-Xavier Fifatin ◽  
Frédéric Dubas ◽  
Télesphore C Nounangnonhou ◽  
Christophe Espanet ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Wind Energy ◽  
Exclusive Economic Zone ◽  
Offshore Wind ◽  
Offshore Wind Energy ◽  
Energy Potential ◽  
Wind Potential ◽  
Wind Energy Potential ◽  
Economic Zone ◽  
Benin Republic

This article presents a study on offshore wind energy viability in Benin Republic. Weibull law has been used to model the spatial distribution of daily wind speed data in Benin Republic’s Exclusive Economic Zone. The spatial distribution of wind energy potential in Benin’s exclusive economic zone has been obtained at several heights by extrapolating Weibull parameters. Wind resource has then been categorized using National Renewable Energy Laboratory standards. Bathymetric data in the exclusive economic zone are used to determine areas showing good compromise between exploitable wind potential and turbine’s foundation. We have shown that Benin’s offshore resources can reach Class 7 at 100 m height, Class 6, respectively, at 100 and 80 m heights and finally Class 5 at 50 m height. We have also shown that locations close to the shore are the most suitable to offshore wind power generation in Benin’s exclusive economic zone.

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