Site Characterization and the Aerodynamics of an Offshore Wind Power Plant: Statistical, Numerical and Analytical Approaches

2016 ◽  
Author(s):  
J. Agbormbai ◽  
M. Yu ◽  
W. D. Zhu
Keyword(s):  
Wind Speed ◽  
Probability Distribution ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Power ◽  
Historical Data ◽  
Average Wind ◽  
Error Bars ◽  
Wind Resources ◽  
Blade Element

Prior to choosing a site for a wind farm, its wind resources must be known. On-site measurement of wind speed, using an anemometer or any other appropriate measuring device or the use of historical meteorological data for the site (if they exist) enhance the knowledge of the site’s wind resources. Typically, the use of 50-year historical data is recommended by Wind Energy Engineering Standards. For the offshore site in study, only the 24-year historical data from the National Oceanic and Atmospheric Administration (NOAA) data base is available. Wind speed determined from NOAA’s error bars is used to plot Rayleigh probability distribution curves for each month of the year, based on the operational limit of the 5MW NREL reference wind turbine. The site’s average wind speed and gust are determined based on average wind energy capture. A Gumbel probability distribution curve is plotted based on the operational range of the wind turbine in study, using NOAA’s error bars for the 24year historical hourly wind gust for the site. This study uses the estimated mean wind speed and mean gust, to implement BEMT simulations to investigate the aerodynamic forces caused by the wind or gust on the blades of the HAWT rotor. The wind power captured and the power coefficient are estimated for each scenario. Empirical formulae are developed for the estimation of the rotor blade airfoil’s chord length in terms of blade element radius and the axial induction factor for each scenario, in terms of blade element radius.

A case study of climate variability effects on wind resources in South Africa

2014 ◽  
Vol 25 (3) ◽  
pp. 2-10 ◽  
Author(s):  
Lynette Herbst ◽  
Jörg Lalk
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Power ◽  
Energy Production ◽  
Energy Sector ◽  
Speed Increase ◽  
Wind Resources ◽  
Wind Speed Increase

The wind energy sector is one of the most prominent sectors of the renewable energy industry. However, its dependence on meteorological factors subjects it to climate change. Studies analysing the impact of climate change on wind resources usually only model changes in wind speed. Two elements that have to be calculated in addition to wind speed changes are Annual Energy Production (AEP) and Power Density (PD). This is not only because of the inherent variability between wind speed and wind power generated, but also because of the relative magnitudes of change in energy potentially generated at different areas under varied wind climates. In this study, it was assumed that two separate locations would experience a 10% wind speed increase after McInnes et al. (2010). Given the two locations’ different wind speed distributions, a wind speed increase equal in magnitude is not equivalent to similar magnitudes of change in potential energy production in these areas. This paper demonstrates this fact for each of the case studies. It is of general interest to the energy field and is of value since very little literature exists in the Southern African context on climate change- or variability-effects on the (wind) energy sector. Energy output is therefore dependent not only on wind speed, but also wind turbine characteristics. The importance of including wind power curves and wind turbine generator capacity in wind resource analysis is emphasised.

SHAPING OF AN AUTONOMOUS POWER SYSTEM FOR GUARANTEED POWER SUPPLY WITH THE PREDOMINANCE WIND ENERGY

2018 ◽  
pp. 28-50
Author(s):  
S. G. Ignatiev ◽  
S. V. Kiseleva
Keyword(s):  
Energy Storage ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Demand ◽  
Diesel Generator ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Average Wind

Optimization of the autonomous wind-diesel plants composition and of their power for guaranteed energy supply, despite the long history of research, the diversity of approaches and methods, is an urgent problem. In this paper, a detailed analysis of the wind energy characteristics is proposed to shape an autonomous power system for a guaranteed power supply with predominance wind energy. The analysis was carried out on the basis of wind speed measurements in the south of the European part of Russia during 8 months at different heights with a discreteness of 10 minutes. As a result, we have obtained a sequence of average daily wind speeds and the sequences constructed by arbitrary variations in the distribution of average daily wind speeds in this interval. These sequences have been used to calculate energy balances in systems (wind turbines + diesel generator + consumer with constant and limited daily energy demand) and (wind turbines + diesel generator + consumer with constant and limited daily energy demand + energy storage). In order to maximize the use of wind energy, the wind turbine integrally for the period in question is assumed to produce the required amount of energy. For the generality of consideration, we have introduced the relative values of the required energy, relative energy produced by the wind turbine and the diesel generator and relative storage capacity by normalizing them to the swept area of the wind wheel. The paper shows the effect of the average wind speed over the period on the energy characteristics of the system (wind turbine + diesel generator + consumer). It was found that the wind turbine energy produced, wind turbine energy used by the consumer, fuel consumption, and fuel economy depend (close to cubic dependence) upon the specified average wind speed. It was found that, for the same system with a limited amount of required energy and high average wind speed over the period, the wind turbines with lower generator power and smaller wind wheel radius use wind energy more efficiently than the wind turbines with higher generator power and larger wind wheel radius at less average wind speed. For the system (wind turbine + diesel generator + energy storage + consumer) with increasing average speed for a given amount of energy required, which in general is covered by the energy production of wind turbines for the period, the maximum size capacity of the storage device decreases. With decreasing the energy storage capacity, the influence of the random nature of the change in wind speed decreases, and at some values of the relative capacity, it can be neglected.

scholarly journals A Controller for Optimum Electrical Power Extraction from a Small Grid-Interconnected Wind Turbine

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5809
Author(s):  
Tania García-Sánchez ◽  
Arbinda Kumar Mishra ◽  
Elías Hurtado-Pérez ◽  
Rubén Puché-Panadero ◽  
Ana Fernández-Guillamón
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Energy Conversion ◽  
Wind Turbine ◽  
Wind Power ◽  
Maximum Power ◽  
Wind Energy Conversion System ◽  
Wind Energy Conversion ◽  
Conversion System ◽  
Energy Conversion System

Currently, wind power is the fastest-growing means of electricity generation in the world. To obtain the maximum efficiency from the wind energy conversion system, it is important that the control strategy design is carried out in the best possible way. In fact, besides regulating the frequency and output voltage of the electrical signal, these strategies should also extract energy from wind power at the maximum level of efficiency. With advances in micro-controllers and electronic components, the design and implementation of efficient controllers are steadily improving. This paper presents a maximum power point tracking controller scheme for a small wind energy conversion system with a variable speed permanent magnet synchronous generator. With the controller, the system extracts optimum possible power from the wind speed reaching the wind turbine and feeds it to the grid at constant voltage and frequency based on the AC–DC–AC conversion system. A MATLAB/SimPowerSystems environment was used to carry out the simulations of the system. Simulation results were analyzed under variable wind speed and load conditions, exhibiting the performance of the proposed controller. It was observed that the controllers can extract maximum power and regulate the voltage and frequency under such variable conditions. Extensive results are included in the paper.

scholarly journals Wake and Turbulence Analysis for Wind Turbine Layouts in an Island

2018 ◽  
Vol 64 ◽  
pp. 06010
Author(s):  
Bachhal Amrender Singh ◽  
Vogstad Klaus ◽  
Lal Kolhe Mohan ◽  
Chougule Abhijit ◽  
Beyer Hans George
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Production ◽  
Wind Farm ◽  
Full Length Paper ◽  
Turbulence Analysis ◽  
Wake Model ◽  
Wind Resources

There is a big wind energy potential in supplying the power in an island and most of the islands are off-grid. Due to the limited area in island(s), there is need to find appropriate layout / location for wind turbines suited to the local wind conditions. In this paper, we have considered the wind resources data of an island in Trøndelag region of the Northern Norway, situated on the coastal line. The wind resources data of this island have been analysed for wake losses and turbulence on wind turbines for determining appropriate locations of wind turbines in this island. These analyses are very important for understanding the fatigue and mechanical stress on the wind turbines. In this work, semi empirical wake model has been used for wake losses analysis with wind speed and turbine spacings. The Jensen wake model used for the wake loss analysis due to its high degree of accuracy and the Frandsen model for characterizing the turbulent loading. The variations of the losses in the wind energy production of the down-wind turbine relative to the up-wind turbine and, the down-stream turbulence have been analysed for various turbine distances. The special emphasis has been taken for the case of wind turbine spacing, leading to the turbulence conditions for satisfying the IEC 61400-1 conditions to find the wind turbine layout in this island. The energy production of down-wind turbines has been decreased from 2 to 20% due to the lower wind speeds as they are located behind up-wind turbine, resulting in decreasing the overall energy production of the wind farm. Also, the higher wake losses have contributed to the effective turbulence, which has reduced the overall energy production from the wind farm. In this case study, the required distance for wind turbines have been changed to 6 rotor diameters for increasing the energy gain. From the results, it has been estimated that the marginal change in wake losses by moving the down-stream wind turbine by one rotor diameter distance has been in the range of 0.5 to 1% only and it is insignificant. In the full-length paper, the wake effects with wind speed variations and the wind turbine locations will be reported for reducing the wake losses on the down-stream wind turbine. The Frandsen model has been used for analysing turbulence loading on the down-stream wind turbine as per IEC 61400-1 criteria. In larger wind farms, the high turbulence from the up-stream wind turbines increases the fatigues on the turbines of the wind farm. In this work, we have used the effective turbulence criteria at a certain distance between up-stream and down-stream turbines for minimizing the fatigue load level. The sensitivity analysis on wake and turbulence analysis will be reported in the full-length paper. Results from this work will be useful for finding wind farm layouts in an island for utilizing effectively the wind energy resources and electrification using wind power plants.

scholarly journals Evaluation of Wind Potential for the Generation of Electricity in Aliero, Kebbi State

2020 ◽  
pp. 1-7
Author(s):  
A. A. Yahaya ◽  
I. M. Bello ◽  
N. Mudassir ◽  
I. Mohammed ◽  
M. I. Mukhtar
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Power ◽  
Power Density ◽  
Horizontal Wind ◽  
Average Wind Speed ◽  
Wind Power Density ◽  
North East ◽  
Average Wind ◽  
Wind Potential

One of the major developments in the technology today is the wind turbine that generates electricity and feed it directly to the grid which is used in many part of the world. The main purpose of this work is to determine the wind potential for electricity generation in Aliero, Kebbi state. Five years Data (2014-2018) was collected from the metrological weather station (Campell Scientific Model), the equipment installed at Kebbi State University of Science And Technology Aliero The data was converted to monthly and annual averages, and compared with the threshold average wind speed values that can only generate electricity in both vertical and horizontal wind turbines. The highest average wind speed 2.81 m/s was obtained in the month of January and the minimum average wind speed of 1.20 m/s in the month of October. Mean annual wind speed measured in the study area shows that there has been an increase in the wind speed from 2014 which peaked in 2015 and followed by sudden decrease to a minimum seasonal value in the year 2016. The highest wind direction is obtained from the North North-East (NNE) direction. From the results of wind power density it shows that we have highest wind power density in month of January and December with  0.8635 w/ m2 and 0.8295 w/ m2 respectively, while lowest wind power density in the month of October and September with 0.6780 w/ m2 and 0.6575 w/ m2  respectively. Result of the type Wind Turbine to be selected in the study area shows that the site is not viable for power generation using a horizontal wind turbine but the vertical wind turbine will be suitable for the generation of electricity.

Weibull Probability Distribution of Wind Speed for Gaza Strip for 10 Years

2019 ◽  
Vol 892 ◽  
pp. 284-291
Author(s):  
Ahmed S.A. Badawi ◽  
Nurul Fadzlin Hasbullah ◽  
Siti Hajar Yusoff ◽  
Sheroz Khan ◽  
Aisha Hashim ◽  
...  
Keyword(s):  
Wind Speed ◽  
Probability Density Function ◽  
Probability Distribution ◽  
Wind Energy ◽  
Probability Density ◽  
Density Function ◽  
Gaza Strip ◽  
Actual Data ◽  
Average Wind Speed ◽  
Average Wind

The need of clean and renewable energy, as well as the power shortage in Gaza strip with few wind energy studies conducted in Palestine, provide the importance of this paper. Probability density function is commonly used to represent wind speed frequency distributions for the evaluation of wind energy potential in a specific area. This study shows the analysis of the climatology of the wind profile over the State of Palestine; the selections of the suitable probability density function decrease the wind power estimation error percentage. A selection of probability density function is used to model average daily wind speed data recorded at for 10 years in Gaza strip. Weibull probability distribution function has been estimated for Gaza based on average wind speed for 10 years. This assessment is done by analyzing wind data using Weibull probability function to find out the characteristics of wind energy conversion. The wind speed data measured from January 1996 to December 2005 in Gaza is used as a sample of actual data to this study. The main aim is to use the Weibull representative wind data for Gaza strip to show how statistical model for Gaza Strip over ten years. Weibull parameters determine by author depend on the pervious study using seven numerical methods, Weibull shape factor parameter is 1.7848, scale factor parameter is 4.3642 ms-1, average wind speed for Gaza strip based on 10 years actual data is 2.95 ms-1 per a day so the behavior of wind velocity based on probability density function show that we can produce energy in Gaza strip.

Wind Energy Resource Assessment for Wind Farm

2011 ◽  
Vol 130-134 ◽  
pp. 1295-1297
Author(s):  
Hui Qun Ma ◽  
Qi Feng Wang
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Weibull Distribution ◽  
Wind Power ◽  
Wind Farm ◽  
Energy Resource ◽  
Resource Assessment ◽  
Important Process ◽  
Wind Resources ◽  
Resources Assessment

In feasible research of wind farm construction, wind resources assessment is an important process. The grade of wind resources is the crucial qualification in the construction. It determines whether this wind farm is profitable or not. his paper introduces the theory of wind energy resource assessment firstly, including: wind power density, wind speed correction and Weibull distribution. Then take Yishui wind farm as example to calculate the wind energy resource assessment.

Optimization of the Wind Turbine Designs for Areas With Low Wind Speeds

2015 ◽  
Author(s):  
Mohammed S. Mayeed ◽  
Adeel Khalid
Keyword(s):  
Energy Consumption ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Small Scale ◽  
Wind Speeds ◽  
Low Wind Speed ◽  
Average Wind ◽  
The World

Wind energy has been identified as an important source of renewable energy. In this study, several wind turbine designs have been analyzed and optimized designs have been proposed for low wind speed areas around the world mainly for domestic energy consumption. The wind speed range of 4–12 mph is considered, which is selected based on the average wind speeds in the Atlanta, GA and surrounding areas. These areas have relatively low average wind speeds compared to various other parts of the United States. Traditionally wind energy utilization is limited to areas with higher wind speeds. In reality a lot of areas in the world have low average wind speeds and demand high energy consumption. In most cases, wind turbines are installed in remote offshore or away from habitat high wind locations, causing heavy investment in installation and maintenance, and loss of energy transfer over long distance. A few more advantages of small scale wind turbines include reduced visibility, less noise and reduced detrimental environmental effects such as killing of birds, when compared to traditional large turbines. With the latest development in wind turbine technology it is now possible to employ small scale wind turbines that have much smaller foot print and can generate enough energy for small businesses or residential applications. The low speed wind turbines are typically located near residential areas, and are much smaller in sizes compared to the large out of habitat wind turbines. In this study, several designs of vertical and horizontal axes wind turbines are modeled using SolidWorks e.g. no-airfoil theme, airfoil blade, Savonius rotor etc. Virtual aerodynamic analysis is performed using SolidWorks Flow simulation software, and then optimization of the designs is performed based on maximizing the starting rotational torque and ultimate power generation capacity. From flow simulations, forces on the wind turbine blades and structures are calculated, and used in subsequent stress analysis to confirm structural integrity. Critical insight into low wind speed turbines is obtained using various configurations, and optimized designs have been proposed. The study will help in the practical and effective utilization of wind energy for the areas around the globe having low average wind speeds.

Techno-economic analysis of wind energy potential in Kazakhstan

2021 ◽  
pp. 095765092110015
Author(s):  
Hamed H Pourasl ◽  
Vahid M Khojastehnezhad
Keyword(s):  
Wind Speed ◽  
Energy Density ◽  
Wind Energy ◽  
Wind Power ◽  
Energy Production ◽  
Energy Utilization ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Average Wind ◽  
Wind Energy Potential

The use of renewable energy as a future energy source is attracting considerable research interest globally. In particular, there is a significant growth in wind energy utilization during the last few years. This present study through a detailed and systematic literature survey assesses the wind energy potential of Kazakhstan for the first time. Using the Weibull distribution function and hourly wind speed data, the annual power and energy density of the sites are calculated. For the 50 sites considered in this study and at a height of 10 m above the ground, the annual average wind speed, the power density, and energy production of Kazakhstan range from 0.94–5.15 m/s, 4.50–169.34 W/m2 and 39.56–1502.50 kWh/m2/yr, respectively. It was found that Fort Sevcenko, Atbasar, and Akmola are the three best locations for wind turbine installation with wind power densities of 169.34, 135.30, and 111.51 W/m2, respectively. Fort Sevcenko demonstrates the highest potential for wind energy harvesting with an energy density of 1483.46 kWh/m2/yr. For the 15 commercial wind turbines, it was observed that the annual energy production of the selected turbines ranges between 3.8 GWh/yr in Petropavlovsk to 15.4 GWh/yr in Fort Sevcenko among the top six locations. The lowest and highest capacity factors correspond to the same sites with the values of 29.21% and 58.66%, respectively. Overall, it is the intention of this study to constitute a database for the users and developers of wind power in Kazakhstan.

scholarly journals Optimum Method for Determining Weibull Distribution Parameters Used in Wind Energy Estimation

2020 ◽  
pp. 635-648
Author(s):  
Ulku Erisoglu ◽  
Nil Aras ◽  
Hasan Donat Yildizay
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Weibull Distribution ◽  
Wind Power ◽  
Estimation Method ◽  
Energy Potential ◽  
Average Wind ◽  
Distribution Parameters ◽  
Wind Energy Potential ◽  
Two Parameter

One of the well-known methods for the determination of wind energy potential is the two-parameter Weibull distribution. It is clear that the success of the Weibull distribution for wind energy applications depends on the estimation of the parameters which can be determined by using various numerical methods. In the present study, Monte Carlo simulation method is performed by using six parameters estimation method that is used in the estimation of Weibull distribution parameters such as Maximum Likelihood Estimation (MLE), Least Squares Method (LSM), Method of Moments (MOM), Method of Logarithmic Moments (MLM), Percentile Method (PM), and L-Moment Method (LM), and is compared to Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). In this study, the wind energy potential of the Meşelik region in Eskişehir was modeled with two-parameter Weibull distribution. The average wind speed (m/s) data, which are gathered in 10-minute intervals from the measuring device installed 10 meters about the ground in Meşelik Campus of Eskişehir Osmangazi University, is used. As a result of the simulation study, it has been determined that MLE is the best parameter estimation method for two-parameter Weibull distribution in large sample sizes, and LM has the closest performance to MLE. The wind speed (m/h) data of the region has been successfully modeled with two-parameter Weibull distribution and the highest average wind power density has been obtained in July as 49.38295 (W/m2) while the lowest average wind power density has been obtained in October as 19.30044 (W/m2).

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