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.     

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.     

Evaluation of wind energy potential and electricity generation on the coast of Mediterranean Sea in Egypt

Wind data from 10 coastal meteorological stations along the Mediterranean Sea in Egypt have been used for statistical analysis to determine the wind characteristics. It was found that three stations show annual mean wind speed greater than 5.0 m/s. In order to identify the Weibull parameters for all stations two different methods were applied.The methodical analysis for all stations was done for the corrected monthly and annual mean wind power at a height of 10 m, over roughness class 0 (water). The recommended correlation equation was also stated for Mediterranean Sea zone in Egypt. Also the wind power densities for heights of 30–50 m were calculated for all stations. Three of them are the best locations, namely: Sidi Barrani, Mersa Matruh, and El Dabaa, where these contiguous stations have great abundantly wind energy density.A technical assessment has been made of the electricity generation using WASP program for two commercial turbines (300 kW and 1 MW) considering at the three promising sites. The wind turbine of capacity 1 MW was found to produce an energy output per year of 2718 MW h at El Dabaa station, and the production costs was found 2€ cent/kW h.     

Assessment of wind characteristics and wind turbine characteristics in Taiwan

Wind characteristics and wind turbine characteristics in Taiwan have been thoughtfully analyzed based on a long-term measured data source (1961–1999) of hourly mean wind speed at 25 meteorological stations across Taiwan. A two-stage procedure for estimating wind resource is proposed. The yearly wind speed distribution and wind power density for the entire Taiwan is firstly evaluated to provide annually spatial mean information of wind energy potential. A mathematical formulation using a two-parameter Weibull wind speed distribution is further established to estimate the wind energy generated by an ideal turbine and the monthly actual wind energy generated by a wind turbine operated at cubic relation of power between cut-in and rated wind speed and constant power between rated and cut-out wind speed. Three types of wind turbine characteristics (the availability factor, the capacity factor and the wind turbine efficiency) are emphasized. The monthly wind characteristics and monthly wind turbine characteristics for four meteorological stations with high winds are investigated and compared with each other as well. The results show the general availability of wind energy potential across Taiwan.     

Assessment of windfarm economics in relation to site wind resources applied to sites in Jordan

This paper describes an analytical method for estimation of the economical feasibility of a project for wind energy utilization in Jordan. The method is applied to a windfarm and is based on the wind speed distribution at the site considered and on the financial parameters for the complete plant and its running costs. For this method, equations were derived to calculate the cost of a kWh generated by wind turbines with different characteristics as a function of the capital investment per kW installed capacity. The method was applied to the sites at which Royal Scientific Society performs wind speed measurements, and the results indicate that some of these sites are well suited for cost efficient generation of electricity by wind energy. The results also show that a wind tribine which is designed to have a relatively low rated speed has a wider range of economical operation than a wind turbine with a higher rated speed for the sites investigated assuming that the maximum rated power for all for the wind turbines is held constant.     

Potential wind power generation in South Egypt

Egypt is one of the developing countries. The production of electricity in Egypt is basically on petroleum, natural gas, hydro-power and wind energy. The objective of this work to prove the availability of sufficient wind potential in the wide area of deep south Egypt for the operation of wind turbines there. Nevertheless, it gives in general an approximate profile which is useful to the wind parks design for this area. The data used in the calculation are published and analyzed for the first time. The diagrams of the measured wind data for three meteorological stations over a period of two years (wind speed, frequency, direction), wind shear coefficient, the mean monthly and annual wind speed profile for every location are presented. Monthly Weibull parameters, standard deviation and coefficient of variation have been statistically discussed. A comparison of the rose diagrams shows that the wind speed is more persistent and blow over this region of Egypt in two main sectors N and NNW with long duration of frequencies from 67% to 87% over the year with an average wind speed in the range 6.8-7.9 m/s at the three stations. Evaluation of monthly wind energy density at 10 m height by two different methods was carried out. And the final diagram for every site shows no significant difference between them. The annual natural wind energies at 70 m A.G.L. lie between 333 and 377 W/m² for Dakhla South and Kharga stations, respectively, which is similar to the inland wind potential of Vindeby (Denmark) and some European countries. These results indicate that Kharga and Dakhla South locations are new explored sites for future wind power generation projects.     

Adequacy assessment of generating systems containing wind power considering wind speed correlation

Wind power is an important renewable energy resource. Electrical power generation from wind energy behaves quite differently from that of conventional sources, and maintaining a reliable power supply is an important issue in power systems containing wind energy. In these systems, the wind speeds at different wind sites are correlated to some degree if the distances between the sites are not very large. Genetic algorithm methods are applied here to adjust autoregressive moving-average time series models in order to simulate correlated hourly wind speeds with specified wind speed cross-correlation coefficients of two wind sites. Multi-state wind energy conversion system models are used to incorporate the correlated wind farms in reliability studies of generating systems. A method to generate random numbers with specified correlation coefficients for application in a state-sampling Monte Carlo simulation technique is introduced. It is shown that the proposed method can be used in the adequacy assessment of a generating system incorporating partially dependent wind farms.     

Wind speed and wind energy potential of Jordan

Routine wind data from 11 stations in Jordan have been analysed. Monthly average, and seasonal wind speed and average power density distributions were determined for each station. The monthly average wind speed for the two most potential sites Ras Muneef (RA) and Mafraq (MF) ranged from 3.0 to 7.4 m/sec and the average power density for these two sites ranged from 110 to 370 W/m² at RA and from 105 to 470 W/m² at MF. An application of wind power as supplementary power supply is suggested and cost analysis is given.     

Performance evaluation of pairing between sites and wind turbines

This paper presents a simple method for determination of pairing between sites and wind generators. It requires six parameters to describe the matching between turbine models and site characteristics, and the energy output performance can thus be easily estimated and used as the index of pairing effectiveness. To describe a Weibull model of wind speed distribution, the shape parameter and the scale parameter are necessarily required. Besides, four other parameters are chosen to specify the characteristics of the power curve of a wind generator: the cut-in speed, the rated speed, the cut-off speed and the nominal power. By combining these six parameters, the average power output of some particular wind turbine at a specific site can be practically and quickly approximated as a reference for turbine siting consideration. An example is also shown to demonstrate the utilization of the proposed method to choose between a group of wind sites and a list of commercial wind turbines.     

Correlation of wind speed between neighboring measuring stations

A method for establishing wind speed correlation between neighboring measuring stations is presented in this paper. The aim of this study is to develop a model, in which given the wind speed at a particular site to simulate the wind speed at another, nearby site, in order to estimate the wind power of an area. This method takes into account the evolution of the sample cross correlation function (SCCF) of wind speed in time domain and uses an artificial neural network to perform the wind speed simulation. Four separate pairs of wind data measuring stations at two different regions were examined. Tests showed that the higher the SCCF value between two sites, the better simulation achieved. Also, in a pair of stations under investigation the reference station must be the one that contains more information in its wind speed signal, in order to obtain the optimum simulation performance.     

Spatial and temporal characteristics of wind and wind power off the coasts of Brittany

The main objective of this paper is to thoroughly examine the remotely sensed wind characteristics around the coasts of Brittany as well as some more specific areas. The offshore wind power potential is then assessed. To achieve this objective, information on wind speed and direction with sufficient spatial and temporal sampling under all weather conditions and during day and night is required. This study uses more than 12 years (December 1999–December 2012) of consistent remotely sensed data retrieved from the ASCAT and QuikSCAT scatterometers to estimate the conventional moments and associated wind distribution parameters. The latter are comparable to wind observations from meteorological stations. Furthermore, combining in-situ and scatterometer wind information enables an improved assessment of the spatial and temporal wind structures at specific locations of interest to be made. The wind statistical results are used to study the spatial and temporal patterns of the wind power. Although the main parameters characterizing wind power potential such as mean, variability, maximum energy, wind speed and intra-annual exhibit seasonal features, significant inter-annual variability is also depicted. Furthermore, differences are found between the wind power estimated for northern and for southern Brittany.     

Wind power potential of Baja California Sur, México

This work is an analysis of wind characteristics of Baja California Sur (BCS), México, during the period from February 1997 to February 1998. Fifteen wind stations located in the eastern coastal area recorded the wind speed and wind direction for this region. The wind resources of BCS were recorded and the annual average wind speed, power density, and annual energy density at 10 m above ground level are presented here.We considered the wind data from El Cardón, BCS, as a case study. This location can be considered to be representative of the 15 wind stations that were installed in BCS. Using the Weibull probability density function, we estimated the wind energy output and the capacity factor for two different wind turbines during the year. The capacity factors for both wind turbines were estimated at close to 25%. Considering the wind energy output and the capacity factor, we estimated the levelized production costs for both wind turbines. Taking into account two different discount rates of 7% and 10%, we developed data for the levelized production cost of both wind turbines.     

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.     

Wind resource assessment over Iran using weather station data

This paper investigates the wind energy potential over 42 sites in Iran. Ten years of wind data (1996–2005) were used from weather stations located at these sites. Different criteria were considered, including vertical wind profile, wind power density (WPD), wind frequency distribution, wind sustainability, seasonal variation, turbulence intensity and peak demand matching. Air density and roughness length, which play important role in the calculation of the WPD potential, were derived for each station site. Simple scoring was used to rank the mostly windy sites. It is concluded that Sistan and Bluchistan governorate (Zabol) has the highest potential. Zahedan, Jazireh Kish and Ardebil also have high wind power potential.     

Low wind speed turbines and wind power potential in Minnesota, USA

Wind power development in Minnesota largely has been focused in the “windy” southwestern part of the state. This research evaluates the additional power that potentially could be generated via low wind speed turbines, particularly for areas of the state where there has been comparatively little wind energy investment. Data consist of 3 years (2002–2004) of wind speed measurements at 70–75 m above ground level, at four sites representing the range of wind speed regimes (Classes 2–5) found in Minnesota. Power estimates use three configurations of the General Electric 1.5-MW series turbine that vary in rotor diameter and in cut-in, cut-out, and rated speeds. Results show that lower cut-in, cut-out, and rated speeds, and especially the larger rotor diameters, yield increases of 15–30% in wind power potential at these sites. Gains are largest at low wind speed (Class 2) sites and during the summer months at all four sites. Total annual wind power at each site shows some year-to-year variability, with peaks at some sites partially compensating for lulls at others. Such compensation does not occur equally in all years: when large-scale atmospheric circulation patterns are strong (e.g., 2002), the four sites show similar patterns of above- and below-average wind power, somewhat reducing the ability of geographic dispersion to mitigate the effects of wind speed variability.     

Assessment of wind energy in Iran: A review

In this study, a ten minute period measuring wind speed data for year 2007 at 10 m, 30 m and 40 m heights for different places in Iran, has been statistically analyzed to determine the potential of wind power generation. Sixty eight sites have been studied. The objective is to evaluate the most important characteristics of wind energy in the studied sites. The statistical attitudes permit us to estimate the mean wind speed, the wind speed distribution function, the mean wind power density and the wind rose in the site at three different heights. Some local phenomena are also considered in the characterization of the site.     

Economic viability and production capacity of wind generated renewable hydrogen

Generally, wind to power conversion is calculated by assuming the quality of wind as measured with a Weibull probability distribution at wind speed during power generation. We build on this method by modifying the Weibull distributions to reflect the actual range of wind speeds and wind energy density. This was combined with log law that modifies wind speed based on the height from the ground, to derive the wind power potential at windy sites. The study also provides the Levelized cost of renewable energy and hydrogen conversion capacity at the proposed sites. We have also electrolyzed the wind-generated electricity to measure the production capacity of renewable hydrogen. We found that all the sites considered are commercially viable for hydrogen production from wind-generated electricity. Wind generated electricity cost varies from $0.0844 to $0.0864 kW h, and the supply cost of renewable hydrogen is $5.30 to $ 5.80/kg-H₂. Based on the findings, we propose a policy on renewable hydrogen fueled vehicles so that the consumption of fossil fuels could be reduced. This paper shall serve as a complete feasibility study on renewable hydrogen production and utilization.     

Normalized power curves as a tool for identification of optimumwind turbine generator parameters

This paper presents a novel method of matching wind turbine generators to a site using normalized power and capacity factor curves. The site matching is based on identifying optimum turbine speed parameters from turbine performance index curve, which is obtained from the normalized curves, so as to yield higher energy production at higher capacity factor. The wind speeds are parameterized using cubic mean cuberoot and statistically modeled using Weibull probability density function. An expression for normalized power and capacity factor, expressed entirely in normalized rated speed, is derived. Wind Turbine Performance Index, a new ranking parameter, is defined to optimally match turbines to a potential wind site. The plots of normalized power, capacity factor and turbine performance index versus normalized rated wind speed are drawn for a known value of Weibull shape parameter of a site. Usefulness of these normalized curves for identifying optimum wind turbine generator parameters for a site is presented by means of two illustrative case studies. The generalized curves, if used at the planning and development stages of wind power stations, will serve as useful tool to make a judicious choice of a wind turbine generator that yields higher energy at higher capacity factor     

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.     

Copula-based joint distribution analysis of wind speed and wind direction: Wind energy development for Hong Kong

Accurate and reliable assessment of wind energy potential has important implication to the wind energy industry. Most previous studies on wind energy assessment focused solely on wind speed, whereas the dependence of wind energy on wind direction was much less considered and documented. In this paper, a copula-based method is proposed to better characterize the direction-related wind energy potential at six typical sites in Hong Kong. The joint probability density function (JPDF) of wind speed and wind direction is constructed by a series of copula models. It shows that Frank copula has the best performance to fit the JPDF at hilltop and offshore sites while Gumbel copula outperforms other models at urban sites. The derived JPDFs are applied to estimate the direction-related wind power density at the considered sites. The obtained maximum direction-related wind energy density varies from 41.3 W/m² at an urban site to 507.9 W/m² at a hilltop site. These outcomes are expected to facilitate accurate micro-site selection of wind turbines, thereby improving the economic benefits of wind farms in Hong Kong. Meanwhile, the developed copula-based method provides useful references for further investigations regarding direction-related wind energy assessments at various terrain regions. Notably, the proposed copula-based method can also be applied to characterize the direction-related wind energy potential somewhere other than Hong Kong.