Wind power potential and time response of wind energy machines

Low-cost digital wind speed histogram recorders were designed to survey the west coast of British Columbia. Results are presented for several shore and island locations in terms of an available power parameter. Additional short term measurements of autocorrelation and cross-correlation functions showed ten-second exponential correlation in velocity fluctuations and gave values for the root mean square fluctuation. A derivation is given of the response time of a Darrieus wind energy converter, which has implications for the sampling time of any wind speed recorder, and for the power fluctuations to be expected from such a converter.     

Wind speed prediction in the mountainous region of India using an artificial neural network model

Measured wind speed data are not available for most sites in the mountainous regions of India. The objective of present study is to predict wind speeds for 11 locations in the Western Himalayan Indian state of Himachal Pradesh to identify possible wind energy applications. An artificial neural network (ANN) model is used to predict wind speeds using measured wind data of Hamirpur location for training and testing. Temperature, air pressure, solar radiation and altitude are taken as inputs for the ANN model to predict daily mean wind speeds. Mean absolute percentage error (MAPE) and correlation coefficient between the predicted and measured wind speeds are found to be 4.55% and 0.98 respectively. Predicted wind speeds are found to range from 1.27 to 3.78 m/s for Bilaspur, Chamba, Kangra, Kinnaur, Kullu, Keylong, Mandi, Shimla, Sirmaur, Solan and Una locations. A micro-wind turbine is used to assess the wind power generated at these locations which is found to vary from 773.61 W to 5329.76 W which is suitable for small lighting applications. Model is validated by predicting wind speeds for Gurgaon city for which measured data are available with MAPE 6.489% and correlation coefficient 0.99 showing high prediction accuracy of the developed ANN Model.     

Spatial estimation of wind speed

This study utilizes Abductory Induction Mechanism to estimate the mean monthly wind speed at some locations in Saudi Arabia based on wind data at other available recording stations in addition to some historical wind speed data at the target site. Wind speed data from 20 meteorological stations over a period of 16 years between 1990 and 2005 was used to accomplish the set objective. To validate the model, data from 19 stations was used to estimate the wind speed at the 20th location. Evaluation was performed for every one of the 20 available locations. Results show good agreement between estimated and measured monthly mean wind speed values. Copyright © 2010 John Wiley & Sons, Ltd.     

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.     

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.     

Wind power distributions: A review of their applications

This paper presents the features of wind power distributions that have been analytically obtained from wind distribution functions. Simple equations establishing a relationship between mean power density and wind speed have been obtained for a given location and wind turbine (WT). Four different concepts relating wind power distribution functions are shown: the power transported by the wind; the theoretical maximum convertible power from it according to the Betz’ law; the maximum convertible power from the wind considering more realistic limits that will be explained; finally an even more approximate limit to the maximum power obtained from a wind turbine, considering its parameters. Similarly, four different equations are obtained establishing relationships between the mean power density and the mean wind speed. These equations are very simple and very useful when discarding locations for wind turbine installation.     

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.     

浅谈变速恒频双馈风力发电机

阐述了双馈风力发电机实现变速恒频的工作原理,讨论了双馈电机的运行状态,推导了双馈电机功率传输方式与转差率的关系,指出了变速恒频风力发电系统的优点是拓宽了风速的可利用范围,对提高风电场发电能力具有重要意义。     

Simulation of hourly wind speed and array wind power

Statistical summaries of wind speed are sufficient to compute many characteristics of turbine-generated power, such as the mean, variance and reliability of various power levels. However, a wind speed time series is necessary to produce a sequence of power values as used for investigating load matching and storage requirements. Since a long historical record of wind speed may not be available at a wind turbine candidate site, it is desirable to be able to generate a simulated numerical sequence of hourly wind speed values. Two such approximate procedures are developed in this paper. One procedure generates sequential wind speed values at a site based on the Weibull parameters of hourly wind speed and the lag-one autocorrelation of hourly wind speed values. Comparison with historical data at a site is made. The second procedure generates sequential hourly wind power values for a regional array of wind turbines. It utilizes the typical site wind characteristics, the spatial and lag-one cross correlation and autocorrelation of hourly wind speed values and an equivalent linearized relationship between array average wind speed and array power. Comparison with results for six different wind turbines in three different regional arrays indicates good agreement for wind power histograms, autocorrelation function and mean persistence.     

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.     

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.     

The wind shear exponent in a Mediterranean island climate

The difficulties in estimating the long term mean wind speed and subsequently wind turbine energy output derive from the fact that more often than not, available data is taken at a level other than machine hub height. The 1/7th power law has been recognised as a handy tool to carry out vertical wind speed extrapolation to the desired hub height. It is also understood that using an exponent of 1/7th could lead to underestimation of the actual long-term mean wind speed aloft. This paper strives to evaluate the power law with respect to wind data taken on a 25 m mast on the central Mediterranean island of Malta. Whilst deriving a site-specific factor affiliated to a typical terrain type, it also strives to determine characteristic variations of the power law exponent over appropriate sampling intervals.     

Assessment of wind energy potential for coastal locations of the Kingdom of Saudi Arabia

This paper presents the wind data analysis for five coastal locations of the Kingdom of Saudi Arabia, namely Dhahran, Yanbo, Al-Wajh, Jeddah, and Gizan. The data analysis utilized hourly mean values of wind speed and wind direction covering a period of almost 14 years between 1970 and 1983. The data were validated in terms of completeness, continuity, erroneous values, etc. The analyses include seasonal and diurnal changes in wind speed values. Energy calculations and capacity factors were also determined for wind machines of different sizes between 150 and 2500 kW. It was found that Yanbo is the best location, among the sites analyzed, for harnessing the power of wind, while Dhahran is the next best location. The other three locations were found to have more or less the same results.     

Probabilistic multi-objective optimal power flow considering correlated wind power and load uncertainties

Increasing penetration of wind power in power systems causes difficulties in system planning due to the uncertainty and non dispatchability of the wind power. The important issue, in addition to uncertain nature of the wind speed, is that the wind speeds in neighbor locations are not independent and are in contrast, highly correlated. For accurate planning, it is necessary to consider this correlation in optimization planning of the power system. With respect to this point, this paper presents a probabilistic multi-objective optimal power flow (MO-OPF) considering the correlation in wind speed and the load. This paper utilizes a point estimate method (PEM) which uses Nataf transformation. In reality, the joint probability density function (PDF) of wind speed related to different places is not available but marginal PDF and the correlation matrix is available in most cases, which satisfy the service condition of Nataf transformation. In this paper biogeography based optimization (BBO) algorithm, which is a powerful optimization algorithm in solving problems including both continuous and discrete variables, is utilized in order to solve probabilistic MO-OPF problem. In order to demonstrate performance of the method, IEEE 30-bus standard test case with integration of two wind farms is examined. Then the obtained results are compared with the Monte Carlo simulation (MCS) results. The comparison indicates high accuracy of the proposed method.     

Modeling of the dynamics of wind to power conversion including high wind speed behavior

This paper proposes and validates an efficient, generic and computationally simple dynamic model for the conversion of the wind speed at hub height into the electrical power by a wind turbine. This proposed wind turbine model was developed as a first step to simulate wind power time series for power system studies. This paper focuses on describing and validating the single wind turbine model, and is therefore neither describing wind speed modeling nor aggregation of contributions from a whole wind farm or a power system area. The state‐of‐the‐art is to use static power curves for the purpose of power system studies, but the idea of the proposed wind turbine model is to include the main dynamic effects in order to have a better representation of the fluctuations in the output power and of the fast power ramping especially because of high wind speed shutdowns of the wind turbine. The high wind speed shutdowns and restarts are represented as on–off switching rules that govern the output of the wind turbine at extreme wind speed conditions. The model uses the concept of equivalent wind speed, estimated from the single point (hub height) wind speed using a second‐order dynamic filter that is derived from an admittance function. The equivalent wind speed is a representation of the averaging of the wind speeds over the wind turbine rotor plane and is used as input to the static power curve to get the output power. The proposed wind turbine model is validated for the whole operating range using measurements available from the DONG Energy offshore wind farm Horns Rev 2. Copyright © 2015 John Wiley & Sons, Ltd.     

Statistical wind direction modeling for the analysis of large scale wind power generation

Understanding the effects of large‐scale wind power generation on the electric power system is growing in importance as the amount of installed generation increases. In addition to wind speed, the direction of the wind is important when considering wind farms, as the aggregate generation of the farm depends on the direction of the wind. This paper introduces the wrapped Gaussian vector autoregressive process for the statistical modeling of wind directions in multiple locations. The model is estimated using measured wind direction data from Finland. The presented methodology can be used to model new locations without wind direction measurements. This capability is tested with two locations that were left out of the estimation procedure. Through long‐term Monte Carlo simulations, the methodology is used to analyze two large‐scale wind power scenarios with different geographical distributions of installed generation. Wind generation data are simulated for each wind farm using wind direction and wind speed simulations and technical wind farm information. It is shown that, compared with only using wind speed data in simulations, the inclusion of simulated wind directions enables a more detailed analysis of the aggregate wind generation probability distribution. Copyright © 2016 John Wiley & Sons, Ltd.     

A methodology to generate statistically dependent wind speed scenarios

Wind power – a renewable energy source increasingly attractive from an economic viewpoint – constitutes an electricity production alternative of growing relevance in current electric energy systems. However, wind power is an intermittent source that cannot be dispatched at the will of the producer. Modeling wind power production requires characterizing wind speed at the sites where the wind farms are located. The wind speed at a particular location can be described through a stochastic process that is spatially correlated with the stochastic processes describing wind speeds at other locations. This paper provides a methodology to characterize the stochastic processes pertaining to wind speed at different geographical locations via scenarios. Each one of these scenarios embodies time dependencies and is spatially dependent of the scenarios describing other wind stochastic processes. The scenarios generated by the proposed methodology are intended to be used within stochastic programming decision models to make informed decisions pertaining to wind power production. The methodology proposed is accurate in reproducing wind speed historical series as well as computationally efficient. A comprehensive case study is used to illustrate the capabilities of the proposed methodology. Appropriate conclusions are finally drawn.     

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 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.     

Demonstrating the effect of vertical and directional shear for resource mapping of wind power

The use of wind energy is growing around the world, and its growth is set to continue into the foreseeable future. Estimates of the wind speed and power are helpful to assess the potential of new sites for development and to facilitate electric grid integration studies. In the present paper, wind speed and power resource mapping analyses are performed. These resource mappings are produced on a 13 km, hourly model grid over the entire continental USA for the years of 2006–2014. The effects of the rotor equivalent wind speed (REWS) along with directional shear are investigated. The total dataset (wind speed and power) contains ≈152,000 model grid points, with each location containing ≈78,000 hourly time steps. The resource mapping and dataset are created from analysis fields, which are output from an advanced weather assimilation model. Two different methods were used to estimate the wind speed over the rotor swept area (with rotor diameter of 100 m). First, using a single wind speed at hub height (80 m) and, second, the REWS with directional shear. The demonstration study shows that in most locations the incorporation of the REWS reduces the average available wind power. In addition, the REWS technique estimates more wind power production at night and less production in the day compared with the hub height technique; potentially critical for siting new wind turbines and plants. However, the wind power estimate differences are dependent on seasonality, diurnal cycle and geographic location. More research is warranted into these effects to determine the level at which these features are observed at actual wind plants.© 2015 The Authors. Wind Energy published by John Wiley & Sons, Ltd.