Average Wind Speed Values Research Articles

The Effect of Varying Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Parameters on Wind Energy Prediction: A Comparative Study

Owing to the development of technology, the majority of nations throughout the world now rely on fossil fuels and nuclear power plants to meet their energy needs. However, as academic research on this subject has shown, it has become clear that alternative energy uses are necessary due to the gradual depletion of these fuels and their significant negative effects on the environment. In order to ensure energy diversity and end the energy shortage, the development of renewable energy sources is crucial. The prediction of wind power is crucial for effectively utilizing the potential of wind energy. In this study, an adaptive neuro-fuzzy inference system (ANFIS) and an artificial neural network (ANN) have been developed for the prediction of wind power. In this study, data sets were created by taking the daily average wind speeds of the selected wind turbine, the daily average power values it produces, and the daily average wind speed values in the Velimese region. By creating single-hidden layer and multi-hidden layer ANN models, the network was trained multiple times with different activation functions and different numbers of neurons, and wind power prediction was performed. In the ANFIS model, the number of membership functions is kept constant, and wind power prediction is performed using different membership functions. With these ANFIS and ANN models developed with different parameter combinations, it is aimed to determine the most efficient model by performing daily average wind power prediction. Parameter combinations were tested to determine the appropriate models, and as a result, the ANN and ANFIS models were compared with each other.

Investigation of the effects of synthetic wind speed parameters and wind speed distribution on system size and cost in hybrid renewable energy system design

The accuracy of wind speed data has an important impact on determining power output from a Hybrid Renewable Energy System including wind turbine. For a better estimation of energy price or payback period, it is crucial to determine both monthly average wind speed values and distribution parameters. Studies evaluating the sensitivity of wind speed distribution parameters concerning the optimal system size are lacking in the literature. This work fills the gap in the literature and for the first time, the effects of wind speed distribution parameters and wind speed distribution on the optimum system are statistically demonstrated. According to this case study, if these parameters are not set correctly, the Cost of Energy may be faulty between −14.024% and +37.804% for the Photovoltaic-Wind-Battery-Inverter system, may be faulty between −19.024% and +97.05% for the Wind-Battery-Inverter system and may be faulty between −56.437% and +65.250% for the Wind-Inverter system. When the default distribution parameters of the HOMER software are used, the errors are −0.609%, −18.30%, −34.215% respectively. This study reveals that in addition to monthly average wind speed values, distribution parameters should be chosen as accurately as possible. The innovative aspect of this work is the statistical presentation of how synthetic wind speed distribution can affect Hybrid Renewable Energy System sizing and at the same time Cost of Energy. Its importance is that it provides more precise results by guiding optimization studies using synthetic meteorological data, which is a popular field of study.

Software-Based Wind Energy Potential Assessment: A Case Study from Western Turkey

In this research, wind energy potential of a specific region in Western Turkey has been analyzed by using WindPRO software. The analyzed site is located in Ayvacık district of Çanakkale province of Turkey. Two types of wind energy turbines with 3 MW power including Enercon E-101/3000 and Nordex N117/3000 have been selected for the analyses. Weibull distribution has been utilized in the wind energy potential assessment. Also, average wind speed values and prevailing wind directions have been calculated for the selected locations in the analyzed region. The prevailing wind direction was determined for Enercon E-101/3000 and Nordex N117/3000 turbines as NNW and SSE, respectively. Estimated electrical energy generation values for Enercon E-101/3000 and Nordex N117/3000 turbines were obtained between 10177-11925 MWh/year and 9283-10954 MWh/year, respectively. Moreover, shape and scale parameters for each wind directions and annual energy generation values of each location have been calculated within the scope of this work.

On the Thermal Environmental Quality of Typical Urban Settlement Configurations

Urban overheating and energy imbalances are severe environmental concerns. The role of urban sprawl patterns in the formation of Heat Island has recently absorbed the researchers’ interest. The research focuses on metropolitan areas with a range of urban typologies. However, there still is a knowledge gap in how UHI responds to different urban typologies. The interaction between urban configurations and heat island characteristics is explored in Sydney. A combination of terrestrial surveys and modelling techniques was implemented, and results were extracted based on simulation results. The Urban Taskforce Australia suggested the applied categorization methods that follow Stewart and Oke’s Local Climate Zones (LCZs) scheme. We assessed eleven urban designs on ambient air temperature, wind characteristics, heat intensity, and outdoor thermal comfort over three summer days. We correlated results to density and the built-up ratio in all configurations and found that the maximum configurational impact on the heat island reached 2.33 °C. Configurations with a built-up ratio between 0.37 to 0.5 present a sharp downward trend in the average wind speed value and indicate a minimum with a built-up ratio of 0.63. Wind maps present an increase in layouts with built-up ratios of 0.23 to 0.37, whereas they decreased with built-up ratios of higher than 0.43. The average temperature decrease in high-rise compact configurations was 1.12 °C per hour. This record is substantially higher than its open counterparts. The study showed the importance of urban configuration on thermal environmental quality. In addition, implementing appropriate urban design parameters is vital to mitigate heat islands and improve environmental thermal comfort in urban areas.

Study and Analysis of Different Absorber Geometry of Compound Parabolic Solar Collector and its Effect on Thermal Efficiency for Heating Water for Sanitary Use

Abstract: This project is focused on carrying out a study of the absorber geometry of the parabolic solar collector compound for heating water for sanitary use, to evaluate the temperature gradient between the inlet and outlet of the water of this concentraDDDtor collector, and the efficiency achieved according to the absorber configuration to later compare it with collectors with a conventional flat absorber surface. The parabola of the reflector of the composite parabolic solar collector was obtained considering the circular absorber, with a concentration ratio of 4 plus 10% of this, to consider a truncation of the reflector, the circular absorber was configured with a small absorber plate of aluminum which has a thermal conductivity of 401 W /mK The values obtained experimentally in the collector were based on the data collected in the field files. It was considered to experience the heating of water on different days with the climatic conditions, cloudy, partially cloudy and sunny, with a totally clear sky. The water heating tests were carried out with two types of geometric configuration of the absorber of the composite parabolic solar collector; circular absorber and configured circular absorber, with which a water outlet temperature of 61 ° C and 76 ° C and a thermal efficiency of 60% respectively were obtained, these results were presented taking into account a climatic condition (sunny day) approximately the same for the two absorber configurations, and with average values of wind speed, ambient temperature and solar radiation.

Software Modeling of Direct Wind to Energy Generator

The Wind Energy is one of the cleanest sources of electrical energy. Commercial wind turbines deliver the promise of being practically realizable with the cost of having an extremely large footprint and being haunted by the Betz Limit. This paper gives an idea of Direct Wind to Energy Conversion which aims to produce electrical energy by harnessing wind’s kinetic energy, devoid of any rotational mechanism. The method in question utilizes the technique of Electro-Hydro-Dynamic Atomization (EHDA) to atomize charged working fluid to deposit its particles on collector electrodes using wind as a carrier. A comparative analysis of several working fluids was conducted to optimize energy production. Simulations on the charged particle trajectory were conducted based on historical average wind speed values to enhance electrode placement which in turn led to design iterations and increased efficiency.

Wind mapping using the mesoscale WRF model in a tropical region of Brazil

This study details an evaluation of the onshore and offshore wind speed field in the state of Bahia, northeastern Brazil, using the WRF (Weather Research and Forecasting) mesoscale model, version 4.0. The simulations were run for a period of five years—between 2015 and 2020—with a horizontal resolution of 3 km, and were compared with data from 41 automatic surface stations for the onshore case. For the offshore case, data from a surface station located in the Abrolhos Archipelago were used. The winter period presents higher values of wind speed for the onshore region (9–14 m/s), and the northern and southwestern regions of the state stand out for the generation of wind energy. In the offshore case, spring presents the highest averages for wind speed (7–8 m/s), followed by the summer season, highlighting the maritime coast in the extreme south of the state (7–10 m/s). Furthermore, the nocturnal wind regime is more intense than the daytime one, indicating a great complementarity with solar energy. The year 2017 had the highest average values of wind speed in the region, being considered one of the warmest years without the influence of the El Nino phenomenon recorded globally since 1850. The hourly averages of onshore and offshore winds for the state of Bahia demonstrated the great wind potential of the region, with high and medium speeds at altitude, which were in accordance with the minimum attractiveness thresholds for investments in wind energy generation.

Wind Distribution Map of Iraq - A Comparative Study

Wind speed data of 10m in height for 11 meteorological station in Iraq has been studied, to understand and determine the distribution of wind speed. Wind speed values is increased when we go toward the southern region of Iraq because the flatness of the ground surface. The sites of Basrah, Nasiriya and Hai were the best with respect to wind speed, especially, at summer. These sites have an annual average values of wind speed of about 5m/s and more. A good similarity obtained when comparing the prepared wind map of the annual average wind speed, with the wind map of Iraq that produced by the National Renewable Energy Centre of Spain (CENER). This similarity demonstrates the reliability of the local data used in this paper, which means it is certified and a good source for the researchers in the site assessment. Also, this data is useful to the decision maker when he decide to install wind turbine or establish wind farm to generate electric power.

Statistical Wind Energy Analysis and Wind Persistence Assessment for Cordoba And Sucre Departments' Weather Stations in The Caribbean Region of Colombia

A statistical analysis is carried out on the behavior of wind speed at meteorological stations located in the Caribbean Region of Colombia, in order to establish and identify the potential available in wind energy to be used as a renewable energy source, this by through the use of rigorous periodic studies, carried out by the Colombian Institute of Environment, Meteorology and Hydrology (IDEAM), to have efficient energy management and encourage the start-up of wind farms, which satisfy the energy demand necessary for the supply of Vulnerable Populations in the Colombian nation, therefore, the meteorological stations and their location are described, a wind analysis is made at different heights and roughness of the study terrain, and wind persistence studies are carried out using the autocorrelation function (ACF), behavioral analyzes are made Hourly and annual wind rate, for the meteorological stations described, in addition, graphs of the wind direction or wind roses are presented, with greater stability in the annual periods. From which an analysis could be established that allows the use of wind energy potential to be viewed by adequately reaching the behavior of the wind for meteorological stations in the departments of Córdoba and Sucre located in the Caribbean Region. The department of Córdoba presents, according to its meteorological stations, an average wind speed value ranging from 1.3 m/s to 1.4 m/s, while in the department of Sucre, values of average wind speed of 0.85 m/s to 1.7 m/s.

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.

A Spliced Gamma-Generalized Pareto Model for Short-Term Extreme Wind Speed Probabilistic Forecasting

Renewable sources of energy such as wind power have become a sustainable alternative to fossil fuel-based energy. However, the uncertainty and fluctuation of the wind speed derived from its intermittent nature bring a great threat to the wind power production stability, and to the wind turbines themselves. Lately, much work has been done on developing models to forecast average wind speed values, yet surprisingly little has focused on proposing models to accurately forecast extreme wind speeds, which can damage the turbines. In this work, we develop a flexible spliced Gamma-Generalized Pareto model to forecast extreme and non-extreme wind speeds simultaneously. Our model belongs to the class of latent Gaussian models, for which inference is conveniently performed based on the integrated nested Laplace approximation method. Considering a flexible additive regression structure, we propose two models for the latent linear predictor to capture the spatio-temporal dynamics of wind speeds. Our models are fast to fit and can describe both the bulk and the tail of the wind speed distribution while producing short-term extreme and non-extreme wind speed probabilistic forecasts. Supplementary materials accompanying this paper appear online.

Wind speed variability and wind power potential over Turkey: Case studies for Çanakkale and İstanbul

In this study, variability of wind speed and its effects on power generation for the 1980–2013 period over Turkey was studied. Hourly wind speed data of 335 stations was obtained from Turkish State Meteorological Service and subjected to quality control. 77 station data was found reliable and used in this work. For the 1980–2013 period, highest hourly average wind speed values equal or larger than 3.80 m/s were found in Gökçeada, Çanakkale and Mardin stations located at Aegean, Marmara and Southeastern regions of Turkey. Monthly average wind speed is observed to be the highest in July with a value of 2.22 m/s. As an Automated Weather Observation System (AWOS), highest average wind speed for the 2007–2013 period was found in Çatalca-Radar, İstanbul with a value of 7.08 m/s. Wind power was analyzed by Weibull distribution and seasonal power density analysis of Çanakkale reveals spring, summer and autumn seasonal average power densities as 49.11 W/m2, 51.12 W/m2 and 50.16 W/m2, together with a winter maximum of 81.68 W/m2. According to results, Çatalca was found as the largest wind energy potential in Turkey, not just having the largest wind speed but also having large rural districts for possible wind farm installment.

Assessment of Wind Potential Energy at Height 100 m in Minna, Niger State, Nigeria

The reliance of a developing nation like Nigeria on hydro-electricity over time has led to power shortage which has hampered her economic and technological advancement because of its seasonal variation. The use of fossil fuel will not also be a better alternative since it is not environmental friendly. However, wind energy is free, clean, cheap and does not contribute to acid rain or global warming. The aim of this research is to carry out an assessment of wind potential in Minna, Niger State, Nigeria for power generation. The characteristics of the wind speed and energy potential in Minna, were examined using daily wind speed and direction data of 2 years, obtained using a metrological instrument; Davis 6162 Wireless Vantage Pro2 positioned at 100 m height. The collected data was analysed statistically and summarised in a simple and concise manner. The results show that the most probable wind speed was 0.4 ms -1 with extractable energy density of 25.04 Whm -2 while the wind speed corresponding to the maximum energy was 10.70 ms -1 delivering 45.96 kWh of energy. The average of the annual wind speed was 10.35 ms -1 which produced energy of 38.03 kWh. Though the average wind speed value revealed that the wind is suitable for wind-electric generation but has a low frequency, hence the power generation will do well for irrigation purposes. The prevailing wind direction was in the North-East direction with 14.84 % of the wind direction frequency. So a wind station will be more efficient if it is stationed in this predominant North-East direction. Keywords: Wind speed, wind direction, energy density, power, electricity DOI : 10.7176/APTA/76-01 Publication date :March 31 st 2019

Модели вертикального профиля ветра по данным ветроизмерительных комплексов полуострова Камчатка

The article describes two wind shear profile (WSP) models constructed in the form of empirical dependencies of the Hellman exponent mean values from the wind speed at the minimal met mast measurement height. The WSP models were developed using the wind speed observation series with 10-min averaging intervals obtained for the minimum and maximum measurement heights from four met masts in the Kamchatka Peninsula, which were then subjected to generalization and putting in a systematic order. The empirical dependencies (WSP models) are applicable for modeling the average wind speed at any height up to 100 m for different source data averaging intervals (month, hour, 10 min) in territories similar to the four met mast sites on the Kamchatka Peninsula in physical and geographical conditions (terrain relief and roughness, and type of water surfaces: river, internal or external sea, etc.). The second model seems to be of special value for further application due to its ability to model the average wind speed for short intervals of time (from 10 min to several hours) to any height, a feature that is of importance in designing wind power plants (WPPs) intended for operation in small local power systems (LPS). In developing this model, the wind turbulence was taken into account in addition to the terrain physical and geographical conditions. To this end, empirical and approximating dependences of the average turbulence intensity from the average wind speed in gradations (at 1 m/s steps) at the minimum measurement height of four met masts were developed. The article describes the methods, verification and approximation criteria, and adopted assumptions based on which the WSP models were developed. The determinacy coefficient R2 was taken as the empirical dependence approximation validity indicator. The developed WSP models were verified in accordance with the criterion of relative deviation of the compared average wind speed values at the met mast maximum measurement height calculated from the actual series of data observed on met masts and using the modeled data, which should not exceed the permissible speed measurement error on the met mast (0.1 m/s) for the considered interval. The effect the selected WSP model has on the design power output produced by a single WPP was analyzed only for one WPP site that coincides with the Ust Kamchatsk met mast site. Investigations for other met mast sites were not performed due to lack of WPP operational data. It is shown that the source data averaging interval should duly be taken into account in choosing the WSP model.

Statistical Analysis of Wind Speed Data with Weibull, Lognormal and Gamma Distributions

In this study, average wind speed data in Bitlis for the years between 2012 and 2016 is analyzed. Average wind speed estimations for these years are obtained with the Weibull, Gamma and Lognormal distributions. Maximum Likelihood method is used in parameter estimation of these distributions. It is aimed that the most fit distribution is determined with Kolmogorov-Smirnov Goodness of Fit test, coefficient of determination and root mean square error criteria. As a result of evaluating the wind speed data with the program written in MATLAB R2009a, it was determined that average wind speed estimations are similar for each distribution, but Gamma distribution has the lowest standard deviation with the average wind speed value in August (0.15 m/s). In modelling of the average wind speed data between 2012 and 2016, it was seen that Gamma distribution had higher coefficient of determination compared to the other distributions. Similarly, the lowest Kolmogorov-Smirnov Goodness of Fit test statistic and root mean square error value are obtained for Gamma distribution. As a result, it is recommended that Gamma distribution is used in modelling the wind speed data of Bitlis between 2012 and 2016.

Universal families of Johnson distributions and their use for analysis of time series of surface wind speed

Introduction. During the last decades in connection with rapid development of numerical methods of weather forecasting insufficient attention is given physical and statistical regularities. Nevertheless, climate change and its implications for the various sectors of the economy requires information about the probability characteristics of meteorological variables and phenomena, including wind anomaly. In the article it was considered experience of application Johnson′s distributions to equalize time series of surface wind speed in the meteorological station of Odessa-port in the central months of the seasons. Were found a number of regularities that take into account not only the seasonal and diurnal variation of parameters this distribution, but also the impact of physical and geographical conditions of the location meteorological station on the formation of surface wind regime.
 The purpose of publication is to substantiation application of Johnson′s law to approximate series of wind speed at the surface on the meteorological station Odessa-port.
 Methods and results. To describe the experimental data in various analytical models of the distribution law increasingly applied the family of Johnson's distributions. Its advantage compared to the distribution of the Pearson consists in the fact, that after some transformations, it leads to a normally distributed random variable. Approximation methods based on universal families of distributions provide flexibility solving the problem of alignment of distributions. The most common approaches to the construction of universal families are approaches based on the method of moments, and the replacement of the original sample the other, the distribution of which is the standard. Statistics wind is presented by following parameters: average values of wind speed, standard deviations, coefficients of asymmetry, excess, coefficient of variation and their error. Conducted alignment time series of surface wind speed using Johnson's distribution for station Odessa-port during a period 1981-1990 y.y., which managed to pick up when ε from -0.51 to -8.00. The parameter λ, which determines the scale of change of the random variable seasonal ranges from 63.56 in January (18 UTC) to 15.77 in October (18 UTC). Estimating shape parameters of wind speed curves η and γ, can reveal some features of the surface wind regime at the st. Odessa port during the year. The less γ, the less slope of the curves. The values of η and γ varies within 0,82-3,54 and 0,24-4,81, respectively. In all cases, λ > 1, indicating that the family of curves belonging SL. The values of Q, which vary from 0.01 to 0.07, confirm the possibility of equalization the series of wind speed at the st. Odessa-port, Johnson's distribution family of SL.
 Conclusion. For unimodal distributions of time series wind speed at the meteorological station Odessa-port in almost all cases, possible to use the universal distribution of the Johnson's family SL. The parameters of this distribution allow to reveal regularities, that take into account impact of physical and geographical conditions of the location stations on the formation of surface wind regime.

Current distribution of wind in Morocco

Information about wind is widely used in many sectors of the economy. Wind also causes many dangerous and extreme weather events. Modern climate changes require a certain revision of weather patterns previously accepted for the area. This article provides information on the current space and time distribution of wind characteristics within the territory of Morocco. During the period of 2005-2014 some monthly average wind speed values and data on repeatability of wind directions by gradations were obtained on the basis of physical and statistical analysis of results of observations of wind speed and directions performed at 26 stations.
 The authors defined the character of distribution of monthly averages of wind speed within the territory and its seasonal changes. Most of the territory is covered by mountains of Morocco which encourages development of local winds. At central and northern regions of Morocco predominance of weak winds due to complex orography of terrain is observed. In the central part of Morocco there is a region with the lowest values of wind speed. Formation of the wind regime at the coastal stations takes place in a developed breeze circulation. Wind speed and direction are significantly different at the nearby stations, such as Larache and Chefchaouen, Meknes and Fez.
 Increase of wind during the warmer half of a year was revealed at all stations. Nature of annual variation of average wind speed at the stations allows us to split the stations into two groups. The first group includes the stations where the average wind speed increases in summer and decreases in winter. The second group includes the stations where the average wind speed increases in spring and decreases in autumn. In the southern part and along the coast, where the terrain is flat, an increase of wind speed is observed. On open plains of the southern part of Atlantic coast during all seasons wind has a direction corresponding to direction of trade winds of the Northern hemisphere. It should be noted that the main factor forming air circulation within the territory of Morocco is represented by trade winds the intensity of which nearly doubles from summer to winter.
 Formation of wind directions at the stations takes place mainly under the influence of terrain of the area. At many stations predominant wind direction in January changes by 180º in comparison to the respective July values. Therefore, characteristics of the wind regime of Morocco in 2005-2014 consist in increase of wind speed in the coastal zone and decrease thereof in mountain areas together with presence of two types of annual variation of wind speed depending on physical and geographical conditions.

Preliminary assessment of the variability of UK offshore wind speed as a function of distance to the coast

In the UK, there is an interest in the expected offshore wind resource given ambitious national plans to expand offshore capacity. There is also an increasing interest in alternative datasets to evaluate wind seasonal and inter-annual cycles which can be very useful in the initial stages of the design of wind farms in order to identify prospective areas where local measurements can then be applied to determine small-scale variations in the marine wind climate. In this paper we analyse both MERRA2 reanalysis data and measured offshore mast data to determine patterns in wind speed variation and how they change as a function of the distance from the coast. We also identify an empirical expression to estimate wind speed based on the distance from the coast. From the analysis, it was found that the variations of the seasonal cycles seem to be almost independent of the distance to the nearest shore and that they are an order of magnitude larger than the variations of the diurnal cycles. It was concluded that the diurnal variations decreased to less than a half for places located more than 100km from the nearest shore and that the data from the MERRA2 reanalysis grid points give an under-prediction of the average values of wind speed for both the diurnal and seasonal cycles. Finally, even though the two offshore masts were almost the same nearest distance from the coast and were geographically relatively close, they exhibited significantly different behaviour in terms of the strength of their diurnal and seasonal cycles which may be due to the distance from the coast for the prevailing wind direction being quite different for the two sites.

A stochastic approach for the wind load effect on steel structures

The Brazilian design load standard still provides a wind speed map developed in 1977. Since then, new data have been collected and new charts have been proposed in literature. The literature not only alerts to changes in short-term wind gust patterns, but it also warns that the wind speed values are higher than observed in the past. Many researchers have suggested that these differences are correlated to climate change effects. Besides the geophysical and societal impacts of climate change, there is a general concern between designers on the impacts of higher wind speeds on structural design. This paper aims to analyze the wind speed as a stochastic variable and its influence on the design of steel structures when changes in wind speed occur. A stochastic approach is used to evaluate expected stress values for a steel beam-column example. A Monte Carlo analysis is performed on a forty-story steel frame to compare the impact of different wind speed scenarios and types of analysis. In the analyses, the wind speed is approached by a Gumbel distribution and future wind scenarios are generated for sensitiveness evaluation. The analytical and Monte Carlo analyses indicate that greater attention shall be given to the consequences of using an average wind speed value instead of a probability distribution function.

An investigation on wind energy potential and small scale wind turbine performance at İncek region – Ankara, Turkey

Renewable energy resources increased their importance in the last decades due to environmental pollution problems. Additionally, the fact that fossil fuels such as oil, coal, and natural gas will be depleted in near future encourages researchers to make investigations on alternative energy resources. Wind energy, which is one of the most used alternative resources, has a great potential. In this study, Weibull parameters at İncek region of Ankara (the capital city of Turkey), where Atılım University campus is located, were determined for four different seasons and for twelve months in order to accomplish wind speed characterization at the region. Wind speed data at 20m and 30m heights were collected from a measurement station installed at Atılım University campus area. The data were taken as 1min average values for a one year period between June 2012 and June 2013. Hourly average wind speed values for each height were derived using the collected wind data. Weibull parameters were calculated with five different methods using the derived hourly average wind speed values. According to root mean square error analyses, the best methods for which Weibull distribution fits the actual wind data were determined as power density and empirical methods. The power and energy density values for the region were also calculated for each season and each month. It was revealed that the maximum power density is encountered in March with about 98 (W/m2). Since this power density indicates that large scale wind turbine use is not a good option at the region, the performances of three different small scale wind turbines were evaluated. According to the results, two of the investigated wind turbines were found to be capable to generate all yearly energy need of an average household in Turkey.