An assessment on seasonal analysis of wind energy characteristics and wind turbine characteristics

This paper presents seasonal variations of the wind characteristics and wind turbine characteristics in the regions around Elazig, namely Maden, Agin and Keban. Mean wind speed data in measured hourly time series format is statistically analyzed for the six year period 1998–2003. The probability density distributions are derived from the time series data and their distributional parameters are identified. Two probability density functions are fitted to the measured probability distributions on a seasonal basis. The wind energy characteristics of all the regions is studied based on the Weibull and Rayleigh distributions. Energy calculations and capacity factors for the wind turbine characteristics were determined for wind machines of different sizes between 300 and 2300 kW. It was found that Maden is the best region, among the regions analyzed, for wind characteristics and wind turbine characteristics.     

对福建省陆地风能资源的评估

对我国福建省福州和厦门2座城市进行了风能开发潜力的评估.基于对该地区近15年的日平均风速的统计分析,计算了各月的风能密度,拟合出了Weibull分布密度函数的特征参数.用Weibull分布密度函数预测了各月的风能密度.并与实测值进行了对比及相关性分析,结果证明了Weibull函数对实测数据有很好的拟合性,同时也表明福建省陆地风力资源的不足,对该地区风力资源的调查重点应放在沿海滩涂及浅海.     

内蒙古地区风资源评估与风场特征风速的推导

对内蒙古二十四个地区的风能资源进行评估,得到风谱图.首先提出了利用WAsP软件对1998年至2008年期间内蒙古二十四地区的风资源资料中的基础进行分析;然后利用风速威布尔分布函数和风力发电机组输出功率的威布尔的概率密度函数,求两个函数的极值,推导出切入风速和额定风速的公式.最后以内蒙古六个地区为例,计算不同风资源条件下的切入风速和额定风速.     

A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey

The electric generating capacity of Turkey must be tripled by 2010 to meet Turkey’s electric power consumption, if the annual 8% growth in electric power consumption continues. Turkey has to make use of its renewable energy resources, such as wind and solar, not only to meet the increasing energy demand, but also for environmental reasons. Studies show that Iskenderun (36°35′N; 36°10′E) located on the Mediterranean coast of Turkey is amongst the possible wind energy generation regions. In the present study, the wind energy potential of the region is statistically analyzed based on 1-year measured hourly time-series wind speed data. The probability density distributions are derived from time-series data and distributional parameters are identified. Two probability density functions are fitted to the measured probability distributions on a monthly basis. The wind energy potential of the location is studied based on the Weibull and the Rayleigh models.     

Wind energy estimation at Quetta

Hourly wind data at Quetta airport (Samungli) for the years 1984–1985, were obtained using a standard anemometer height of 10 m, with a view to work out the feasibility of wind energy utilization. Quetta (lat. 30°11 'N long. 66°57'E) is elevated at 1799 m above sea level. In this paper, we analyse the wind energy data by using the Weibull distribution. Scaling and shaping parameters are determined by using least-squares approximation to a straight line. Actual wind data, weighted Weibull density function and weighted Rayleigh probability density function for regular and continuous periods of 4 weeks up to a year (wind characteristics are being recorded and summarized as diurnal and monthly wind velocity distributions and wind power density roses) are plotted which shows that the Weibull distribution is generally of the right shape to fit low-averaged wind speed frequency curves. However, density function of a normal distribution is also determined. Deviations in wind speed distributions at very low-averaged wind speeds and at comparatively large-averaged wind speeds are found.     

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.     

新疆达坂城风电场风能资源特性分析

对新疆达坂城风电场的风能资源特性进行了详细的研究。基于在达坂城风电场实测的10m和24m高程的10min平均风速数据,分析了原始风速的分布特性。根据地表风速沿高度呈风剪指数分布的特性,计算了在各个轮毂高度上的风速分布。采用最小误差逼近算法原理,计算了风速韦布尔分布的参数以及平均风速和分布方差。通过对韦布尔分布的分析,计算了各个高度上风电场的平均风功率密度、有效平均风功率密度和可利用小时数等风能资源特性参数,为当地的风能开发提供分析基础。     

Wind characterization analysis incorporating genetic algorithm: A case study in Taiwan Strait

In this paper, the genetic algorithm (GA) is originally applied to compute the Weibull parameters for wind characterization analysis, in which an objective function required in GA for searching optimization solution has been first defined as well. Wind data analyzed are observed at a wind farm in the Taiwan Strait from 2006 to 2008. To accurately describe wind speed distribution three kinds of probability density functions are compared, i.e. the Weibull, logistic and lognormal functions. Statistical parameters including the max error in the Kolmogorov-Smirnov test, root mean square error, Chi-square error and relative error of wind power density are considered as judgment criterions. The results show that GA is a useful method, there is about 33% time saving when compared with conventional iteration method. Weibull function describes best the wind distribution, regardless of time periods. Accordingly, wind power density, availability factor and electrical energy output from an ideal turbine are assessed using the Weibull parameters; utilization rate of wind energy for the currently used turbine is discussed. Further the wind energy compensates very well with solar energy; when solar radiation is down in winter and spring, the wind power becomes greater; energy ratios for each month are calculated lastly.     

Wind speed time series characterization by Hilbert transform

Predictions of wind energy potential in a given region are based on on‐location observations. The time series of these observations would later be analysed and modelled either by a probability density function (pdf) such as a Weibull curve to represent the data or recently by soft computing techniques, such as neural networks (NNs). In this paper, discrete Hilbert transform has been applied to characterize the wind sample data measured on ?zmir Institute of Technology campus area which is located in Urla, ?zmir, Turkey, in March 2001 and 2002. By applying discrete Hilbert transform filter, the instantaneous amplitude, phase and frequency are found, and characterization of wind speed is accomplished. Authors have also tried to estimate the hourly wind data using daily sequence by Hilbert transform technique. Results are varying. Copyright © 2005 John Wiley & Sons, Ltd.     

Wind power statistics and an evaluation of wind energy density

In this paper the statistical data of fifty days' wind speed measurements at the MERC-solar site are used to find out the wind energy density and other wind characteristics with the help of the Weibull probability distribution function. It is emphasized that the Weibull and Rayleigh probability functions are useful tools for wind energy density estimation but are not quite appropriate for properly fitting the actual wind data of low mean speed, short-time records. One has to use either the actual wind data (histogram) or look for a better fit by other models of the probability function.     

Implications of seasonal and diurnal variations of wind velocity for power output estimation of a turbine: a case study of Grenada

This case study highlights the importance of taking into consideration diurnal variations of wind velocity for wind energy resources assessment. Previous studies of wind energy distribution that are based on the two-parameter Weibull density function have so far neglected to consider time of day fluctuations in wind speed, instead concentrating primarily on seasonal deviations. However, this has serious implications where such a wind energy model is the underpinning of calculations for the potential power production from a wind turbine and in particular where the timing of the energy output is essential to meet electricity loads. In the case of Grenada the energy output from a wind turbine during the day is approximately two times the output at night thereby fluctuating enormously around the seasonal mean distribution. When this is not taken into account the economic and technological viability of a wind turbine project may be overestimated or not even be identified. This work shows how a wind energy resources assessment based on the Weibull distribution model can be done and how the power output of a horizontal axis turbine is calculated. An analysis of the recorded wind data confirms the application of the Weibull density function as a suitable tool for modelling wind regimes. Copyright © 2003 John Wiley & Sons, Ltd.     

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.     

A comparison between wind speed distributions derived from the maximum entropy principle and Weibull distribution. Case of study; six regions of Algeria

The knowledge of the probability density function of wind speed is of paramount importance in many applications such as wind energy conversion systems and bridges construction. An accurate determination of the probability distribution of wind speed allows an efficient use of wind energy, thus rendering wind energy conversion system more productive. In the present paper, the maximum entropy principle (MEP) is used to derive a family of pre-exponential distributions in order to fit wind speed distributions. Using averaged hourly wind speed of six different regions in Algeria, it has been found that the proposed pre-exponential distributions fit the wind speed distributions better than the conventional Weibull distributions in terms of root mean square error. However, it has been found also that MEP based distributions have shown some practical limitations such as the choice of pre-exponential order and interval of definition.     

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.     

都昌老爷庙风电场风能资源研究

利用都昌气象局对老爷庙风电场所测的数据,对其风能资源中平均风速、平均风能密度、有效风能密度、有效时数等参数进行了详细的计算和分析.利用威布尔双参数曲线拟合风的频率曲线, 对其两个参数k和c的估算用三种不同方法分别加以探讨并进行误差对比,最终得到老爷庙风电场的风能评估结果.     

Wind speed generation for dynamic analysis

A simple model to generate large band wind speed time sequences, especially easy to implement with a very reduced number of parameters, is presented. It is based on the calculation of a low‐frequency and a high‐frequency components. Low‐frequency component with 1 h sample time is obtained from a random process based on a conditional probability density function. Using real data from two different wind farms in two different months of the year, it has been found that Weibull distribution centered in the current hourly mean value seems to represent well the 1 h conditional PDF in all cases, and the standard deviation of this conditional Weibull is more or less in the range 1–1.3 m s^?1 independently of the season of the year or the location. Regarding to high‐frequency component, low‐frequency samples are used as initial and final values and, between them, the turbulence component values are inserted. For that, it has been used a stochastic process based on a Beta probability function and a simple rescaling procedure with two non‐linear parameters, calculated in a recursive way. Unlike the usual modelling procedures presented in the literature, spectral power density functions are not used. This simplifies the implementation significantly. Ten second sample‐time real speed wind data from two different wind farms have been used to validate the proposed high‐frequency model, obtaining excellent results. A thorough revision of the main models found in the literature to produce wind speed time sequences for dynamic analysis is performed in the paper. Copyright © 2017 John Wiley & Sons, Ltd.     

Wind power potential and characteristic analysis of the Pearl River Delta region, China

Wind power potentials of the Pearl River Delta (PRD) region have been statistically analyzed based on the hourly measured wind speed data in four islands. The hourly and monthly wind speed and wind power density are assessed to have remarkable variations, and the Weibull distribution function has been derived from the available data with its two parameters identified. The wind power and operating possibilities of these locations have been studied based on the Weibull function. The wind power potentials of these sites were found to be encouraging; however, the wind power at different site varies significantly, so attention should be paid to the wind conditions as well as the site terrains in choosing the wind farm sites.     

Wind energy potential assessment in Uttara Kannada district of Karnataka, India

Availability of wind energy and its characteristics at Kumta and Sirsi in Uttara Kannada District of Karnataka has been studied based on primary data collected at these sites for a period of 24 months. Wind regimes at Karwar (1952–1989), Honnavar (1939–1989) and Shirali (1974–1989) have also been analysed based on data collected from India Meteorological Department (IMD) of respective meterological observatories. Wind energy conversion systems would be most effective in these taluks during the period May to August. The monthly frequency distributions of wind speed have been analysed for Kumta and Sirsi where hourly wind speed recording is available. It is shown that two parameter Weibull distribution is a good representation of the probability density function for the wind speed. Energy Pattern Factor (EPF) and Power Densities are computed for sites at Kumta and Sirsi. With the knowledge of EPF and mean wind speed, mean power density is computed for Karwar, Honnavar and Shirali. Our analyses show that the coastal taluks such as Karwar and Kumta have good wind potential. This potential, if exploited would help local industries and coconut and areca plantations. Premonsoon availability of wind energy would help in irrigating these orchards and makes the wind energy a desirable alternative.     

Evaluation of monthly capacity factor of WECS using chronological and probabilistic wind speed data: A case study of Taiwan

Monthly energy outputs and capacity factors of an existing median-scale wind power station located in Mailiao, Taiwan, have been analyzed by using the measured half-hourly wind speed data over a period spanned between 2002 and 2005. The wind speed data in the chronological (time-series) format and probabilistic (Weibull) format are used to estimate the monthly capacity factors of Vestas V47–660 KW turbines in Mailiao. The monthly capacity factors calculated from the chronological and probabilistic approaches are compared with and validated by the measured capacity factors obtained in Mailiao. In addition, due to the climatic features of the Asia monsoon, there are two prominent wind periods within a year in Taiwan, i.e., the strong (October–March) and weak (April–September) wind periods. This study also investigates the differences of the measured and calculated capacity factors in the strong and weak wind periods of Mailiao. It is shown that the capacity factors calculated from the time-series approach have better agreement with the actual capacity factors than the Weibull approach. Both approaches have slightly underestimated the capacity factors in the strong wind period, but have significantly overestimated the capacity factors in the weak wind period.     

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.