Regional assessment of wind power in western Turkey by the cumulative semivariogram method

Regional patterns of wind energy potential along the western Aegean Sea coastal part of Turkey are evaluated by considering its regional variability through the use of cumulative semivariogram (CSV) models. This innovative technique provides clues about the regional variations along any direction. Since in the western Anatolian coast winds are predominantly northerly or east northerly or west northerly, the regional variability is investigated along the north-south direction. The CSV techniques yielded the radius of influence for wind velocity and Weibull distribution parameters. Dimensionless Standard Regional Dependence (SRD) functions are obtained from the sample CSV. These SRD functions help to make simple regional predictions for the wind energy or wind velocity distribution parameters. The methodology has been applied for predicting the wind velocity in Turkey along the Aegean sea coast. Similar predictions can be achieved for wind energy and Weibull distribution parameters.     

The wind energy potential of western greece

In this study wind data have been used to determine the monthly and annual variations of the wind at 13 meterological stations in west Greece. An analysis of the available wind data for the Ionian Sea islands and the western coasts of Greece is carried out to ascertain its potential for wind energy development. The effect of the limited number of daily observations available on the accuracy of the mean wind speed and annual wind energy estimates is ascertained. The wind speed and direction distributions are represented with Weibull functions. Besides, a mass-consistent numerical mesoscale model has been used to give an overview of the wind prospecting and sitting problem, and an example of its use for Corfu (Kerkira), an island in the Ionian Sea, is given. The comparison of the accuracy of the stimulation results versus measured wind at an available site is quite encouraging even though it cannot be conclusive since only one station is available.     

Wind characteristics and wind energy potential in Morocco

The wind characteristics of 11 sites in the windy regions in Morocco have been analysed. The annual average wind speed for the considered sites ranged from 5 m/s to 10 m/s and the average power density from 100 W/m² to 1000 W/m², which might be suitable for electrical power production by installing wind farms. On an annual scale the observations of the distribution of hourly wind speed are better fitted by the Weibull hybrid distribution in contrast to the Weibull distribution.The wind power is estimated to be 1817 MW, that is to say, the exploitable wind energy is 15198 GWh, which represents theoretically 11% of the total consumed energy in Morocco in 1994.     

Investigation of wind characteristics and wind energy potential in Kirklareli, Turkey

Utilization of wind energy as an energy source has been growing rapidly in the whole world due to environmental pollution, consumption of the limited fossil fuels and global warming. Although Turkey has fairly high wind energy potential, exploitation of the wind energy is still in the crawling level. In the current study, wind characteristics and wind energy potential of Kırklareli province in the Marmara Region, Turkey were analyzed taking into account the wind data measured as hourly time series. The wind data used in the study were taken from Electrical Power Resources Survey and Development Administration (EIEI) for the year 2004. The measured wind data were processed as annual, seasonal and monthly. Weibull and Rayleigh probability density functions of the location are calculated in the light of observed data and Weibull shape parameter k and scale parameter c are found as 1.75 and 5.25 m/s for the year 2004. According to the power calculations done for the site, annual mean power density based on Weibull function is 138.85 W/m². The results indicate that investigated site has fairly wind energy potential for the utilization.     

A survey on the assessment of wind energy potential in Egypt

In this paper, wind data obtained from the Egyptian Meteorological Authority are used to assess monthly and annual wind power and wind energy. The study is based on data from 15 anemometer meteorological stations, distributed all over Egypt and covering a period ranging from 1973 to 1994. For these stations the wind data are summarized. The wind energy potential at the 25 m height was obtained by extrapolation of data at 10 m using a power-law expression. The result presents the mean wind energy density estimates and potential for application in Egypt. The analysis showed that along Red Sea coasts, the annual wind energy flux is found to be high, which indicates that these coastal stations are possible locations for wind energy utilization. On both the Mediterranean coast and in the interior parts of Egypt, some stations are of low available wind energy, while others are found to be rather high. Also, the two Weibull distribution parameters have been estimated from the wind speed data for some meteorological stations and the wind power density is calculated using the values of these parameters.     

Investigation of wind energy potentials in Brunei Darussalam

Conventional power generation mainly depends on natural gas and diesel oil in Brunei Darussalam. The power utility company is now thinking of power generation using natural wind. In this paper, wind energy, being one of the most readily available renewable energy sources, was studied. The wind characteristic, velocity and directions were studied using Weibull distribution based on the measurement of wind speed at two different locations in Brunei Darussalam. These wind speed distributions were modeled using the Wind Power program. The wind rose graph was obtained for the wind direction to analyze the wind power density onshore and offshore. Based on this analysis, it has been found that the wind speed of 3 to 5 m/s has a probability of occurrence of 40%. Besides, the annual energy production at a wind speed of 5 m/s has been found to be in the range between 1000 and 1500 kWh for both the locations in Brunei Darussalam.     

A particle swarm optimization for wind energy control problem

The control problem of a wind turbine involves the determination of rotor speed and tip-speed ratio to maximize power and energy capture from the wind. The problem can be formulated as a nonlinear programming problem with the annual energy generation as the objective function. The wind speed distribution is modeled as the Weibull distribution. The Weibull shape and scale parameters are assigned to be stochastic in response to limited wind data and variability nature of the wind. It is proposed to apply particle swarm optimization to solve for optimum rotor speed under fixed-speed operation and optimum tip-speed ratio under variable-speed operation. The optimum rotor speed varies with the wind speed distribution, while the optimum tip-speed ratio does not depend on the wind speed distribution. It can be concluded from the simulation results that both the wind power and energy are more dependent of the Weibull scale parameter than the Weibull shape parameter. This implies that the wind power and energy are more dependent of the mean wind speed than the speed distribution.     

Wind resource evaluation in six selected high altitude locations in Nigeria

This paper presents an assessment of wind energy potentials of six selected high altitude locations within the North-West and North-East geopolitical regions, Nigeria, by using 36-year (1971–2007) wind speed data subjected to 2-parameter Weibull distribution functions. The results showed that the maximum mean wind speed is obtained in Katsina as 9.839 m/s while the minimum value of 3.397 m/s is got in Kaduna for all the locations considered. The annual wind power density and energy variation based on the Weibull analysis ranged from 368.92 W/m² and 3224.45 kWh/m²/year to 103.14 W/m² and 901.75 kWh/m²/year in Kano and Potiskum for the maximum and minimum values respectively. Furthermore, Katsina and Kano will be suitable for wind turbine installations while Gusau will only be appropriate for wind energy utilization using taller wind turbine towers whereas Kaduna, Bauchi and Potiskum will be considered marginal for wind power development based of their respective annual mean wind speeds and power densities.     

Potential wind power generation in the State of Kuwait

The wind characteristics of six locations in the State of Kuwait have been assessed. The annual average wind speed for the considered sites ranged from 3.7 to 5.5 m/s and a mean wind power density from 80 to 167 W/m² at standard height of 10 m. The Weibull parameters and power density of each station have been determined using Weibull distribution. The wind data at heights 15, 20, 25 and 30 m were obtained by extrapolation of the 10 m data using the Power-Law. The potential wind energy at different heights was estimated using Weibull parameters. Maximum power density is found at 30 m height which varies between 130 and 275 W/m² with 70% increase from the standard height indicating fairly potential wind energy especially in the northern part of the country. The highest potential wind power was found during the summer season which is the peak demand season of electricity in Kuwait.     

Mesoscale interactions on wind energy potential in the northern Aegean region: a case study

Aegean coast and surrounding areas are promising higher wind power potential. In this study the reasons of the higher wind power potential in the region of the northern Aegean coast of Turkey and surrounding islands were discussed. The channel effect, route of cyclones and surface pressure gradients were evaluated over the region. Estimated results of the Weibull parameters illustrate the higher wind power potential in the region.     

Wind resource assessment of an area using short term data correlated to a long term data set

A method of estimating the annual wind energy potential of a selected site using short term measurements related to one year’s recorded wind data at another reference site is presented. The proposed method utilizes the 1-year measured wind speed of one site to extrapolate the annual wind speed at a new site, using an artificial neural network (ANN). In this study, concurrent measurements from target and reference sites over periods of 1-month and 2-month were used to “train” the ANN. Topographical details or other meteorological data are not required for this approach. After derivation of the simulated wind speed time series for the target site, its mean value and its corresponding Weibull distribution parameters are calculated. The derived Weibull distribution of the simulated wind speed is used to make an assessment of the annual wind energy resource in the new area with respect to a particular wind turbine model. Three pairs of measuring stations in the southwest of Ireland were examined, where the wind potential is high and technically exploitable. Analysis of the measurements showed a reasonable cross-correlation coefficient of the wind speed between the sites. Results indicate that with this method, only a short time period of wind data acquisition in a new area might provide the information required for a satisfactory assessment of the annual wind energy resource. To evaluate the accuracy of the method, simulation results of the 1-month and 2-month training periods are compared to the corresponding actual values recorded at the sites. Also, a comparison with the results of a commercial wind energy assessment software package is presented showing similar results.     

Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function

The wind resource is a crucial step in planning a wind energy project and detailed knowledge of the wind characteristic at a site is needed to estimate the performance of a wind energy project. In this paper, with the help of 2-parameter Weibull distribution, the assessment of wind energy potentiality at Kudat and Labuan in 2006-2008 was carried out. “WRPLOT” software has been used to show the wind direction and resultant of the wind speed direction. The monthly and yearly highest mean wind speeds were 4.76 m/s at Kudat and 3.39 m/s at Labuan respectively. The annual highest values of the Weibull shape parameter (k) and scale parameter (c) were 1.86 and 3.81 m/s respectively. The maximum wind power density was found to be 67.40 W/m² at Kudat for the year 2008. The maximum wind energy density was found to be 590.40 kWh/m²/year at Kudat in 2008. The highest most probable wind speed and wind speed carrying maximum energy were estimated 2.44 m/s at Labuan in 2007 and 6.02 m/s at Kudat in 2007. The maximum deviation, at wind speed more than 2 m/s, between observed and Weibull frequency distribution was about 5%. The most probable wind directions (blowing from) were 190° and 269° at Kudat and Labuan through the study years. From this study, it is concluded that these sites are unsuitable for the large-scale wind energy generation. However, small-scale wind energy can be generated at the turbine height of 100 m.     

Use of two-component Weibull mixtures in the analysis of wind speed in the Eastern Mediterranean

The statistical characteristics of wind speed data recorded at nine buoys, located in Ionian and Aegean Sea (Eastern Mediterranean) are analyzed in this paper, in order to present a more accurate method for estimation of wind speed characteristics, according to the suitability of the probability distribution functions (pdf). This article has focussed on wind regimes that present nearly zero percentages of null wind speeds. The selected distributions for examination are the typical two-parameter Weibull wind speed distribution (W-pdf) and the two-component mixture Weibull distribution (WW-pdf), involving five parameters (two shape parameters, two scale parameters, and one proportionality parameter).     

The wind potential impact on the maximum wind energy penetration in autonomous electrical grids

According to long-term wind speed measurements the Aegean Archipelago possesses excellent wind potential, hence properly designed wind energy applications can substantially contribute to fulfill the energy requirements of the island societies. On top of this, in most islands the electricity production cost is extremely high, while significant insufficient power supply problems are often encountered, especially during the summer. Unfortunately, the stochastic behaviour of the wind and the important fluctuations of daily and seasonal electricity load pose a strict penetration limit for the contribution of wind energy in the corresponding load demand. The application of this limit is necessary in order to avoid hazardous electricity grid fluctuations and to protect the existing thermal power units from operating near or below their technical minima. In this context, the main target of the proposed study is to present an integrated methodology able to estimate the maximum wind energy penetration in autonomous electrical grids on the basis of the available wind potential existing in the Aegean Archipelago area. For this purpose a large number of representative wind potential types have been investigated and interesting conclusions have been derived.     

Wind energy potential in Aden-Yemen

The wind energy resource is very large and widely distributed throughout the world as well as in Yemen. Aden possesses a very good potential of wind energy. In this article a number of years data on wind speed in Aden has been studied and presented. A statistical analysis was carried out from which the annual wind speed was found to be 4.5 m/s and most of the time the wind speed is in the range of 3.5–7.5 m/s. The wind speed distributions were represented by Weibull and Rayleigh distributions. It was found that the Rayleigh distribution is suitable to represent the actual probability of wind speed data for Aden. The wind speed data showed that the maximum monthly wind speed occurs in the month of February with the maximum in the month of June. It is concluded that Aden can be explored for wind energy applications.     

Estimation of wind power availability in Tamil Nadu

Eleven years' daily wind speed data at 21 locations in the state of Tamil Nadu, India were analysed to assess the available wind power potential using Weibull distribution under two different methods. The mean wind speed varied from 1.0 to 5.0 m/s dividing the state into four regions. Judged by mean and standard deviation of available wind power, six locations have been identified as possible sites for a wind energy system.     

Evaluation of hydrogen production from harvesting wind energy at high altitudes in Iran by three extrapolating Weibull methods

One of the most appropriate ways for energy storage is producing hydrogen from renewable resources. Wind energy is recognized as one of the widely used renewable energy resources. This paper investigates the use of wind energy for producing hydrogen in Iran. To achieve this, the country is divided into five major regions: center, north, south, east and west. The performance of three large-scale commercial wind turbines, ranging from 1500 kW to 3000 kW at hub height of 80 m and four large-scale wind turbine ranging from 2000 kW to 4500 kW at hub height of 120 m are evaluated for producing hydrogen in 150 wind stations in Iran. All wind data were recorded based on 10-min time intervals for more than one year at different wind mast heights. For estimating Weibull parameters, the Standard Deviation Method (SDM), Empirical Method of Lysen (EML) and Power Density Method (PDM) are used. An extrapolation method is used to determine the shape and the scale parameters of the Weibull distribution at the high attitudes of 80 m and 120 m. Then, power law and surface roughness exponents, capacity factor, annual energy production and annual hydrogen production for the wind sites are determined. The results indicate that rated power is not the only determinative parameter and the highest hydrogen production is from the GW-109/2500 wind turbine at the hub height of 80 m and from E112/4500 at the hub height of 120 m. For better assessment, the amount of hydrogen production is depicted in Geographic Information Science (GIS) maps using power production of the seven wind turbine models. Next by analyzing these GIS maps, it is found that there are significant potentials in north, north-west, east and south of Iran for producing hydrogen from wind energy.     

Potential for wind generation on the Guyana coastlands

Guyanas dependence upon imported petroleum fuels can only be offset by the sustained exploitation of its indigenous resources. With its populated coastlands exposed to the northeast trade winds and a history of small-scale wind energy utilisation wind is one such potential energy source. In this study, the coastal wind regime is analysed and historical data from a coastal weather station are used to estimate the potential for wind generation. It is found that a hybrid Weibull probability density function best describes the annual wind speed frequency distribution at the reference height of 10.67 m. With an annual mean wind speed of 5.8 ms, an energy pattern factor of 1.41, and an annual average power density of 159 Wm², this distribution represents a class-3 wind resource, suitable for most wind turbine applications. Site analysis and observed trends in coastal wind availability suggest the strong likelihood of a greater wind resource in more open locations. In view of its apparent potential for wind farm operation, a comprehensive, wind resource assessment programme is recommended for the Guyana coastlands.     

变桨距风力发电机额定风速的确定方法

根据风速的Weibull分布特性和变桨距风力发电机的发电特性,构建不同额定风速下风力发电机年发电量计算方法.应用美国可再生能源实验室(NREL)对风力发电成本的研究成果,建立了变桨距风力发电机发电的度电成本数学模型,提出了以度电成本最低为目标的额定风速确定方法,为变桨距风力发电机的额定风速最优选择提供了计算依据.     

Wind energy assessment in Turkey

Long-term wind speed measurements from 117 stations in Turkey have been evaluated in order to find prospective sites for building large scale wind-power machines. Based on these measurements, monthly mean isopleth maps as well as an annual mean density map for wind speed have been produced. Using the Weibull distributions, the available annual mean power and the variations with altitude have been computed for the selected stations. Finally the applicability of these systems to this country is discussed.