Feasibility study of harnessing wind energy for turbine installation in province of Yazd in Iran

This paper analyses the wind speed of some major cities in province of Yazd which is located in central part of Iran. Also, the feasibility study of implementing wind turbines to take advantage of wind power is reviewed and then the subject of wind speed and wind potential at different stations is considered. This paper utilized wind speed data over a period of almost 13 years between 1992 and 2005 from 11 stations, to assess the wind power potential at these sites. In this paper, the hourly measured wind speed data at 10 m, 20 m and 40 m height for Yazd province have been statically analyzed to determine the potential of wind power generation. Extrapolation of the 10 m data, using the Power Law, has been used to determine the wind data at heights of 20 m and 40 m. The results showed that most of the stations have annual average wind speed of less than 4.5 m/s which is considered as unacceptable for installation of the wind turbines. City of Herat has higher wind energy potential with annual wind speed average of 5.05 m/s and 6.86 m/s, respectively, at height of 10 m and 40 m above ground level (AGL). This site is a good candidate for remote area wind energy applications. But some more information is required, because the collected data for Herat is only for 2004. Cities of Aghda with 3.96 m/s, Gariz with 3.95 m/s, and Maybod with 3.83 m/s annual wind speed average at height of 10 m above ground level are also able to harness wind by installing small wind turbines. The Tabas and Bafgh sites wind speed data indicated that the two sites have lower annual wind speed averages between 1.56 m/s and 2.22 m/s at 10 m height. The monthly and annual wind speeds at different heights have been studied to ensure optimum selection of wind turbine installation for different stations in Yazd.     

Quantifying sources of uncertainty in reanalysis derived wind speed

Reanalysis data are attractive for wind-power studies because they can offer wind speed data for large areas and long time periods and in locations where historical data are not available. However, reanalysis-predicted wind speeds can have significant uncertainties and biases relative to measured wind speeds. In this work we develop a model of the bias and uncertainty of CFS reanalysis wind speed than can be used to correct the data and identify sources of error. We find the CFS reanalysis data underestimate wind speeds at high elevations, at high measurement heights, and in unstable atmospheric conditions. For example, at a site with an elevation of 500 m and hub height of 80 m, a CFS reanalysis wind speed of 8 m/s is 0.2 m/s higher to 1.3 m/s lower than the measured wind speed. We also find a seasonal bias that correlates with surface roughness length used by the reanalysis model during the spring season. The corrections we propose reduce the average bias of reanalysis wind speed extrapolated to hub height to nearly zero, an improvement of 0.3–0.9 m/s. These corrections also reduce the RMS error by 0.1–0.4 m/s, a small improvement compared to the uncorrected RMS errors of 1.5–2.4 m/s.     

Wind characteristics and wind energy potential in western Nevada

The wind potential in western Nevada was assessed by using wind, temperature, and pressure data over a period of four and half years from four 50 m tall towers. The seasonal wind patterns for all towers show a maximum during the spring season. Diurnal wind speed patterns for all seasons and months showed a minimum during the late morning and a maximum during the late afternoon. The highest values are during the spring season with multi-annual hourly wind speeds at or above 8 m/s and relative frequency of the wind speed in the optimum turbine range (5–25 m/s) of 70% or higher for the Tonopah tower, with lower values for the other three towers. The monthly power law index values are lower than the standard value 0.147 (in general 0.13 or lower). The hourly turbulence intensities were higher at lower elevations, with values of about 0.35 or higher at the 10 m level and at lower wind speed range (5.0 m/s or less). Higher turbulence intensities were found for all towers and heights during the spring and summer seasons and lower values during the rest of the year. The daily gust factor for the 2003–2007 composite data sets shows low probabilities (2% or less) of the wind gusts exceeding 25 m/s.     

A statistical model for estimating electricity produced by wind energy

Potential wind power for a given period (e.g. a day) can be determined from wind speed data measured in certain hours of a period. Obviously, the sum of the cubes of wind speeds measured depends on the number of measurements. This dependence can be reduced in two ways: determining the average and the relative wind energy for a given time within a given period. The method of sliding averages uses both. Applying this method a given hourly average wind speed cube of a day is estimated on the basis of wind speeds measured in that hour of the day. Cubes of the wind speeds are in proportion with the total daily potential and produced wind energy. This model requires long-time series of wind speed data that are available only for weather stations in Hungary, where hourly average winds speeds are registered.For this reason, statistics required for the model were calculated from different subsets of ten-year-long hourly average wind speed time series of three Hungarian weather stations (Szombathely, Budapest-L?rinc and Debrecen). Using the statistics and hourly wind speed data measured in the vicinity of the wind turbines/on the wind turbines themselves, the model is suitable for giving estimations hourly of the potential wind energy for the whole day in a particular season or circulation type group. A software for the model is also presented here. Considering the results the sliding average model (SLIDAV) makes it possible to forecast average daily wind power 6–9 h before the end of the day with an error of 20%. The magnitude of the error of estimation depends on the given season and/or synoptic type group. These results may provide important information for wind turbine owners: daily amount of wind energy can be determined in this way. Thus the owner can decide whether to operate the turbine whole day, or to stop it periodically for maintenance for example.     

Wind power resource in the south-western region of Algeria

In this study, we present a statistical analysis of wind speeds at Tindouf in Algeria using Risoe National Laboratory's Wind Atlas Analysis and Application Program (WAsP). It requires information related to the sheltering obstacles, surface roughness changes and terrain height variations in order to calculate their effects on the wind. Wind data, consisting of hourly wind speed records over a 5-year period, 2002–2006, were obtained from SONELGAZ R&D Office; the average wind speed at a height of 17 m above ground level was found to range from 7.19 to 7.95 m/s. The Weibull distributions parameters (c and k) were found to vary between 8.0 and 8.9 m/s and 2.54–3.23, respectively, with average power density ranging from 318 to 458 W/m². The dominant wind directions and the frequency distributions were also determined.     

Wind energy potential estimation and micrositting on Izmir Institute of Technology Campus, Turkey

The aim of this study was to predict the wind energy content over the campus area of Izmir Institute of Technology. The wind data were collected at 10 and 30 m mast heights for a period of 16 months. Mean wind speeds were 7.03 and 8.14 m/s at 10 and 30 m mast heights, respectively. The ‘WAsP’ and ‘WindPRO’ softwares were used for the wind statistics and energy calculations. Suitable sites were selected according to the created wind power and energy maps. Wind turbines with nominal powers between 600 and 1500 kW were established for annual energy production calculations and best fitted ones were used for the micrositting.     

Airborne wind energy: Optimal locations and variability

This paper explores the global wind power potential of Airborne Wind Energy (AWE), a relatively new branch of renewable energy that utilizes airborne tethered devices to generate electricity from the wind. Unlike wind turbines mounted on towers, AWE systems can be automatically raised and lowered to the height of maximum wind speeds, thereby providing a more temporally consistent power production. Most locations on Earth have significant power production potential above the height of conventional turbines. The ideal candidates for AWE farms, however, are where temporally consistent and high wind speeds are found at the lowest possible altitudes, to minimize the drag induced by the tether. A criterion is introduced to identify and characterize regions with wind speeds in excess of 10 m s⁻¹ occurring at least 15% of the time in each month for heights below 3000 m AGL. These features exhibit a jet-like profile with remarkable temporal constancy in many locations and are termed here “wind speed maxima” to distinguish them from diurnally varying low-level jets. Their properties are investigated using global, 40 km-resolution, hourly reanalyses from the National Center for Atmospheric Research's Climate Four Dimensional Data Assimilation, performed over the 1985–2005 period. These wind speed maxima are more ubiquitous than previously thought and can have extraordinarily high wind power densities (up to 15,000 W m⁻²). Three notable examples are the U.S. Great Plains, the oceanic regions near the descending branches of the Hadley cells, and the Somali jet offshore of the horn of Africa. If an intermediate number of AWE systems per unit of land area could be deployed at all locations exhibiting wind speed maxima, without accounting for possible climatic feedbacks or landuse conflicts, then several terawatts of electric power (1 TW = 10¹² W) could be generated, more than enough to provide electricity to all of humanity.     

Investigation of wind power density at different heights in the Gelibolu peninsula of Turkey

This study aims to determine the wind characteristics and wind power potential of the Gelibolu peninsula in the Çanakkale region of Turkey. For this purpose, hourly average wind data observed at the Gelibolu meteorological station were used. The Weibull probability density functions and Weibull parameters of time-series of wind speed, mean wind speed, and mean wind power potential were determined for different heights as 10, 20, 30, 40, and 50 m. According to the results obtained at 10- and 50-m heights above the ground level, the annual wind speed varied from 6.85 to 8.58 m/s in this region, respectively. The annual wind power potential of the site was determined as 407 and 800 W/m² for 10- and 50-m heights, respectively. These results indicate that the investigated site has a reasonable wind power potential for generating electricity.     

Evaluating the performance of wind turbines in selected locations in Oyo state,Nigeria

The wind speed distribution and wind energy potential are investigated in three selected locations in Oyo state using wind speed data that span between 12 and 20 years measured at 10 m height. In addition, the performance of selected small to medium size wind turbines in these sites were examined. The annual energy output and capacity factor for these turbines were determined. It was found that the monthly mean wind speeds in Oyo state ranges from 2.85 m/s to 5.20 m/s. While the monthly mean power density varies between 27.08 W/m² and 164.48 W/m², while the annual mean power density is in the range of 67.28 W/m² and 106.60 W/m². Based on annual energy output, wind turbines with cut-in wind speed of about 2.5 m/s and moderate rated wind speeds will be best suited for all the sites.     

Evaluation of wind energy potential as a power generation source for electricity production in Binalood,Iran

In this paper, the hourly measured wind speed data for years 2007–2010 at 10 m, 30 m and 40 m height for Binalood region in Iran have been statically analyzed to determine the potential of wind power generation. The study showed that the long-term wind speeds were found to be relatively high. The numerical values of the dimensionless Weibull shape parameter (k) and Weibull scale parameters (c) were also determined. Based on these data, it was found that the numerical values of the shape and scale parameters for Binalood varied over a wide range. The yearly values of k at 40 m elevation range from 2.165 to 2.211 with a mean value of 2.186, while those of c are in the range of 7.683–8.016 with a mean value of 7.834. However, the yearly mean wind speed, mean power density and power density of Binalood at 40 m height are found as 5.923 m/s, 305.514 W/m² and 2676.30 (kWh/m²/year) respectively. The results show that Binalood has available great wind energy potential for grid connection system.     

Wind resource assessment of the Southern Appalachian Ridges in the Southeastern United States

The analysis of wind data collected throughout the Southern Appalachian Mountain region of the Southeastern US is presented. Data were collected at 50 m above ground level on nine ridge top sites between 2002 and 2005. Monthly average wind speeds, power densities, wind sheers, and turbulence intensities, along with monthly maximum gusts, are presented. Measured annual average wind speeds are compared to AWS TrueWind predictions. Diurnal variations in wind speed are also reported. Annual wind roses for each site are presented. Annual wind speeds range from 5.5 to 7.4 m/s with the highest annual average wind speeds found on ridges near the northern TN–NC border. A 20% winter and nighttime enhancement of the wind speed was observed. The prevailing wind is from the westerly directions. The estimated annual energy outputs from a small wind farm consisting of fifteen 1.5 MW GE turbines range from 50 to 75 MkWh, and estimated capacity factors range from 25% to 35%. This analysis suggests that ridges in the region are suitable for utility-scale wind development.     

Wind to power a new city in Oman

This paper proposes the use of wind power as a source of electricity in a new city being developed in the Duqm area of Oman. Recent wind speed measurements taken at the Duqm metrological station are analyzed to obtain the annual and monthly wind probability distribution profiles represented by Weibull parameters. The monthly average mean wind speed ranges between 2.93 m/s in February and 9.76 m/s in July, with an annual average of 5.33 m/s.A techno-economic evaluation of a wind power project is presented to illustrate the project's viability. Given Duqm's wind profile and the power curve characteristics of a V90-1.8 turbine, an annual capacity factor of 0.36 is expected. For the base-case assumptions, the cost of electricity is about $0.05 and $0.08 per kWh for discount rates of 5% and 10%, respectively. These values are higher than that of the existing generation system, due to the subsidized prices of domestically available natural gas. However, given high international natural gas prices, the country's long-term LNG export obligations, and the expansion of natural gas-based industries, investments in wind power in Duqm can be justified. A feed-in tariff and capital cost allowance policies are recommended to facilitate investments in this sector.     

Wind resource assessment of the Jordanian southern region

Wind data in terms of annual, seasonal and diurnal variations at Queira, which is located in the southern part of Jordan was studied and analyzed. For this purpose, long-term wind speed data for a period of 12 years (1990–2001) was used. The analysis showed that the seasonal and diurnal pattern of wind speed matches the electricity load pattern of the location. Higher winds of the order of 6 m/s and more were observed during both the summer months of the year (May–August) and peak hours (1100–1500) of the day. The wind duration availability is discussed as the number of hours during which the wind remained in certain wind speed intervals. The possibility of electricity generation from wind power at Queira was carried out using three different wind energy systems of sizes 100, 22 kW rated power, and a wind farm consisting of 25 small wind turbines; each of 4 kW rated power with hub heights of 20, 30, and 40 m. The energy production analysis showed higher production from the wind farm with a 20 m hub height than the production from the other two wind turbines. Similarly, the cost analysis showed that the lowest generation costs of 1 kWh were obtained for the wind farm compared to the other two wind turbines. The possibility of water pumping using the wind farm was also investigated. The results showed that water pumping using wind turbines is an appropriate alternative for the photovoltaic water pumping in the region.     

Wind shear coefficients and their effect on energy production

This paper provides realistic values of wind shear coefficients calculated using measured values of wind speed at 20, 30 and 40 m above the ground for the first time in Saudi Arabia in particular and, to the best of the authors’ knowledge, in the Gulf region in general. The paper also presents air density values calculated using the measured air temperature and surface pressure and the effects of wind shear factor on energy production from wind machines of different sizes. The measured data used in the study covered a period of almost three years between June 17, 1995 and December 1998. An overall mean value of wind shear coefficient of 0.194 can be used with confidence to calculate the wind speed at different heights if measured values are known at one height. The study showed that the wind shear coefficient is significantly influenced by seasonal and diurnal changes. Hence, for precise estimations of wind speed at a height, both monthly or seasonal and hourly or night time and day time average values of wind shear coefficient must be used. It is suggested that the wind shear coefficients must be calculated either (i) using long term average values of wind speed at different heights or (ii) using those half hourly mean values of wind speed for which the wind shear coefficient lies in the range ⩾0 and ⩽0.51. The air density, calculated using measured temperature and pressure was found to be 1.18 kg/m³. The air density values were also found to vary with the season of the year and hour of the day, and hence, care must be taken when precise calculations are to be made. The air density values, as shown in this paper, have no significant variation with height. The energy production analysis showed that the actual wind shear coefficient presented in this paper produced 6% more energy compared to that obtained using the 1/7 power law. Similarly, higher plant capacity factors were obtained with the wind shear factor of 0.194 compared to that with 0.143.     

Offshore wind power simulation by using WRF in the central coast of Chile

This paper presents the first estimate of offshore wind power potential for the central coast of Chile. For this purpose, wind speed data from in-situ stations and ERA-Interim reanalysis were used to simulate wind fields at regional level by means of the Weather Research and Forecasting (WRF) model. Wind field simulations were performed at different heights (20, 30, 40 and 140 m.a.s.l.) and a spatial resolution of 3 × 3 km for the period from February 1, 2006 to January 31, 2007, which comprised the entire series of in-situ data available. The results show an RMSE and r² of 2.2 m s⁻¹ and 0.55 respectively for the three heights simulated as compared to in-situ data. Based on the simulated wind data, the wind power for the study area was estimated at ∼1000 W m⁻² at a height of 140 m.a.s.l. For a typical wind turbine of 8 MW generator, the estimated capacity factor exceeds 40%, with an average annual generation of ∼30 GWh. Offshore wind power in Chile is an emerging renewable energy source that is as yet still under-developed, these estimates help to fill in some of the gaps in our knowledge about Chile's true renewable energy potential.     

Wind energy assessment and wind farm simulation in Triunfo – Pernambuco,Brazil

This paper presents a wind energy assessment and a wind farm simulation in the city of Triunfo in the state of Pernambuco in the northeast region of Brazil. The wind data were obtained from the SONDA (Sistema de Organização Nacional de Dados Ambientais) project’s meteor station (wind speed, wind direction and temperature) at both heights of 50 m during a period of time of 30 months. The Triunfo wind characterization and wind power potential assessment study shows an average wind speed (V) of 11.27 m/s (predominant Southeast wind direction), an average wind power density (P/A_T) of 1.672 W/m² and Weibull parameters shape (K) and scale (A) respectively equal to 2.0 and 12.7 m/s. Those values demonstrate an important wind potential in this region for future wind farm prospection. The wind farm (TRI) was simulated by using 850 kW wind turbines given a total of 20 MW installed. The simulated results show(s) an AEP (annual energy produced) of 111.4 GWh, a capacity factor (C_f) of 62% and a total of 5.462 h of operation by year (full load hours). The economical simulated results show(s) a Pay-back of 3 years Internal Rate of Return (IRR) of 47% and Net Present Value (NPV) of 85.506 k€ (both in a period of time of 20 years).     

Wind energy resource assessment for five locations in Saudi Arabia

The analysis of recently collected wind data at five sites in Saudi Arabia namely, Dhulum, Arar, Yanbu, Gassim and Dhahran is presented. The five sites represent different geographically and climatologically conditions. The data collected over a period spanned between 1995 and 2002 with different collection periods for each site. Daily, monthly and frequency profiles of the wind speed at the sites showed that Dhulum and Arar sites have higher wind energy potential with annual wind speed average of 5.7 and 5.4 m/s and speeds higher than 5 m/s for 60 and 47% of the time, respectively. The two sites are candidates for remote area wind energy applications. The costal site's, i.e. Yanbu and Dhahran wind speed data indicated that the two sites have lower annual wind speed averages and wind blows at speed higher than 5 m/s during afternoon hours. That makes the two sites candidates for grid connected wind systems for electrical load peak shaving. The data of Gassim site showed that the site has the lowest wind energy potential compared to the others. The annual energy produced by a Nordex N43 wind machine is estimated to be 1080, 990, 730, 454 and 833 MWh for Dhulum, Arar, Yanbu, Gassim and Dhahran, respectively. The analysis showed that the estimated annual energy produced by the machine based on 10 min averaged data is 2.5% higher than the estimated energy based on 30 min averaged data.     

The influence of the Weibull assumption in monthly wind energy estimation

An estimation of the monthly wind energy output for the period 1999–2003 at five wind farms in northeastern Spain was evaluated. The methodology involved the calculation of wind speed histograms and the observed average wind power versus wind relation obtained from hourly data. The energy estimation was based on the cumulated contribution of the wind power from each wind speed interval. The impact of the Weibull distribution assumption as a substitute of the actual histogram in the wind energy estimation was evaluated. Results reveal that the use of a Weibull probability distribution has a moderate impact in the energy calculation as the largest estimation errors are, on average, no larger than 10% of the total monthly energy produced. However, the evaluation of the goodness of fit through the χ² statistics shows that the Weibull assumption is not strictly substantiated for most of the sites. This apparent discrepancy is based on the partial cancellation of the positive and negative departures of the Weibull fitted and the actual wind frequency distributions. Further investigation of the relation between the χ² and the error contribution exposes a tendency of the Weibull distribution to underestimate (overestimate) the observed histograms in the lower and upper (intermediate) wind speed intervals. This fact, together with the larger wind power weight over the highest winds, results in a systematic total wind energy underestimation. Copyright © 2008 John Wiley & Sons, Ltd.     

Wind energy analysis based on turbine and developed site power curves: A case-study of Darling City

The observed wind at a given site varies continuously as a function of time and season, increasing hub heights, topography of the terrain, prevailing weather condition etc. The quality of wind resource is one of the important site factors to be considered when assessing the wind potential of any location for any energy project. In this study, two wind energy analysis techniques are presented: the use of direct technique where the electrical power outputs of the wind turbines at a time t are estimated using the turbine power curve(s) and the use of statistical-based technique where the power outputs are estimated based on the developed site power curve(s). The wind resource assessment at Darling site is conducted using a 5-min time series weather data collected on a 10 m height over a period of 24 months. Because of the non-linearity of the site's wind speed and its corresponding power output, the wind resources are modeled and the developed site power curve(s) are used to estimate the long term energy outputs of the wind turbines for changing weather conditions. Three wind turbines rating of 1.3 MW, 1.3 MW and 1.0 MW were selected for the energy generation based on the gauged wind resource(s) at 50, 60 and 70 m heights, respectively. The energy outputs at 50 m height using the 1.3 MW WT were compared to the energy outputs at 60 m to determine the standard height for utility scale energy generation at this site. An additional energy generation of 190.71 MWh was available by deploying the same rated turbine at a 60 m height. Furthermore, comparisons were made between the use of turbine and site power curve for wind energy analysis at the considered heights. The results show that the analysis of the energy outputs of the WTs based on the site power curve is an accurate technique for wind energy analysis as compared to the turbine power curve. Conclusions are drawn on the suitability of this site for utility scale generation based on the wind resources evaluation at different heights.     

The potential of electricity generation on the east coast of Red Sea in Egypt

Wind characteristics have been analyzed based on long-term measured data of monthly mean wind speed of seven meteorological stations along the east coast of Red Sea in Egypt. It was found that the windiest stations (Region A) namely (Zafarana, Abu Darag, Hurghada and Ras Benas) have annual mean wind speeds (7.3, 7.2, 6.4 and 5.5 m/s) at 10 m height, respectively.Numerical estimations using measured wind speeds and frequencies to calculate the two Weibull parameters were carried out and two methods were applied.The methodical analysis for the corrected monthly wind power density at a height of 10 m above ground level, over roughness class 0 (water), for each station was done. The recommended correlation equation was also stated for Red Sea zone in Egypt. Also the corrected annual wind power density at the heights (50–70) m was obtained for all stations. Moreover, calculations show that the four stations in (Region A) have a huge energy potential available (430–1000 W/m²) at 70 m height, while Quseir and Suez stations (Region B) have good wind power density (170–190 W/m²) at 50 m height.A technical and economic assessment has been made of electricity generation from two turbines machines having capacity of (1000 and 600 kW) considered in Regions A & B, respectively, using WASP program. The yearly energy output, capacity factor and the electrical energy cost of kWh produced by the two different turbines in each region were estimated. The production costs of four stations in Region A was found to be less than 2€ cent/kWh and compared with retail tariff.