scholarly journals Wind Speeds at Heights Crucial for Wind Energy: Measurements and Verification of Forecasts

2012 ◽  
Vol 51 (9) ◽  
pp. 1602-1617 ◽  
Author(s):  
Susanne Drechsel ◽  
Georg J. Mayr ◽  
Jakob W. Messner ◽  
Reto Stauffer
Keyword(s):  
Wind Speed ◽  
Low Cost ◽  
Good Choice ◽  
Mountainous Regions ◽  
Wind Speeds ◽  
Relative Contribution ◽  
Site Characteristics ◽  
One Year ◽  
Nwp Model ◽  
Ecmwf Model

AbstractWind speed measurements from one year from meteorological towers and wind turbines at heights between 20 and 250 m for various European sites are analyzed and are compared with operational short-term forecasts of the global ECMWF model. The measurement sites encompass a variety of terrain: offshore, coastal, flat, hilly, and mountainous regions, with low and high vegetation and also urban influences. The strongly differing site characteristics modulate the relative contribution of synoptic-scale and smaller-scale forcing to local wind conditions and thus the performance of the NWP model. The goal of this study was to determine the best-verifying model wind among various standard wind outputs and interpolation methods as well as to reveal its skill relative to the different site characteristics. Highest skill is reached by wind from a neighboring model level, as well as by linearly interpolated wind from neighboring model levels, whereas the frequently applied 10-m wind logarithmically extrapolated to higher elevations yields the largest errors. The logarithmically extrapolated 100-m model wind reaches the best compromise between availability and low cost for data even when the vertical resolution of the model changes. It is a good choice as input for further statistical postprocessing. The amplitude of measured, height-dependent diurnal variations is underestimated by the model. At low levels, the model wind speed is smaller than observed during the day and is higher during the night. At higher elevations, the opposite is the case.

scholarly journals Wind speed modeling based on measurement data to predict future wind speed with modified Rayleigh model

2021 ◽  
Vol 12 (3) ◽  
pp. 1823
Author(s):  
Suwarno Suwarno ◽  
Rohana Rohana
Keyword(s):  
Wind Speed ◽  
Measurement Data ◽  
Rayleigh Distribution ◽  
Scale Factor ◽  
Percentage Error ◽  
Monthly Data ◽  
Wind Speeds ◽  
Wind Characteristics ◽  
One Year ◽  
The Many

The development of modeling wind speed plays a very important in helping to obtain the actual wind speed data for the benefit of the power plant planning in the future. The wind speed in this paper is obtained from a PCE-FWS 20 type measuring instrument with a duration of 30 minutes which is accumulated into monthly data for one year (2019). Despite the many wind speed modeling that has been done by researchers. Modeling wind speeds proposed in this study were obtained from the modified Rayleigh distribution. In this study, the Rayleigh scale factor (<em>C<sub>r</sub></em>) and modified Rayleigh scale factor (<em>C<sub>m</sub></em>) were calculated. The observed wind speed is compared with the predicted wind characteristics. The data fit test used correlation coefficient (R<sup>2</sup>), root means square error (RMSE), and mean absolute percentage error (MAPE). The results of the proposed modified Rayleigh model provide very good results for users.

scholarly journals Scatterometer hurricane wind speed retrievals using cross polarization

2013 ◽  
Vol 6 (4) ◽  
pp. 7945-7984 ◽  
Author(s):  
G.-J. van Zadelhoff ◽  
A. Stoffelen ◽  
P. W. Vachon ◽  
J. Wolfe ◽  
J. Horstmann ◽  
...  
Keyword(s):  
Wind Speed ◽  
Weather Prediction ◽  
Data Sets ◽  
Data Set ◽  
Wind Speeds ◽  
Geophysical Model ◽  
Hurricane Wind ◽  
Geophysical Model Function ◽  
Sar Imagery ◽  
Nwp Model

Abstract. Hurricane-force wind speeds can have a large societal impact and in this paper microwave C-band cross-polarized (VH) signals are investigated to assess if they can be used to derive extreme wind speed conditions. European satellite scatterometers have excellent hurricane penetration capability at C-band, but the vertically (VV) polarized signals become insensitive above 25 m s−1. VV and VH polarized backscatter signals from RADARSAT-2 SAR imagery acquired during severe hurricane events were compared to collocated SFMR wind measurements acquired by NOAA's hurricane-hunter aircraft. From this data set a Geophysical Model Function (GMF) at strong-to-extreme/severe wind speeds (i.e. 20 m s−1 < U10 < 45 m s−1) is derived. Within this wind speed regime, cross-polarized data showed no distinguishable loss of sensitivity and as such, cross-polarized data can be considered a good candidate for the retrieval of strong-to-severe wind speeds from satellite instruments. The upper limit of 45 m s−1 is defined by the currently available collocated data. The validity of the derived relationship between wind speed and VH has been evaluated by comparing the cross polarized signals to two independent wind speed datasets, i.e. short-range ECMWF Numerical Weather Prediction (NWP) model forecast winds and the NOAA best estimate one-minute maximum sustained winds. Analysis of the three comparison data sets confirm that cross-polarized signals from satellites will enable the retrieval of strong-to-severe wind speeds where VV or horizontal (HH) polarization data has saturated. The VH backscatter increases exponentially with respect to wind speed (linear against VH [dB]) and a near real time assessment of maximum sustained wind speed is possible using VH measurements. VH measurements thus would be an extremely valuable complement on next-generation scatterometers for Hurricane forecast warnings and hurricane model initialization.

scholarly journals Evaluation of ERA5, MERRA-2, COSMO-REA6, NEWA and AROME to simulate wind power production over France

2020 ◽  
Vol 17 ◽  
pp. 63-77 ◽  
Author(s):  
Bénédicte Jourdier
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Farm ◽  
Regional Scale ◽  
Power Production ◽  
Local Scale ◽  
Electric System ◽  
Wind Speeds ◽  
Diurnal Cycles ◽  
Nwp Model

Abstract. As variable renewable energies are developing, their impacts on the electric system are growing. To anticipate these impacts, prospective studies may use wind power production simulations in the form of 1 h or 30 min time series that are often based on reanalysis wind-speed data. The purpose of this study is to assess how several wind-speed datasets are performing when used to simulate wind-power production at the local scale, when no observation is available to use bias correction methods. The study evaluates two global reanalysis (MERRA-2 from NASA and ERA5 from ECMWF), two high-resolution models (COSMO-REA6 reanalysis from DWD, AROME NWP model from Météo-France) and the New European Wind Atlas mesoscale data. The study is conducted over continental France. In a first part, wind-speed measurements (between 55 and 100 m above ground) at eight locations are directly compared to modelled wind speeds. In a second part, 30 min wind-power productions are simulated for every wind farm in France and compared to two open datasets of observed production published by the distribution and transmission system operators, either at the local scale in terms of annual bias, or aggregated at the regional scale, in terms of bias, correlations and diurnal cycles. ERA5 is very skilled, despite its low resolution compared to the regional models, but it underestimates wind speeds, especially in mountainous areas. AROME and COSMO-REA6 have better skills in complex areas and have generally low biases. MERRA-2 and NEWA have large biases and overestimate wind speeds especially at night. Several problems affecting diurnal cycles are detected in ERA5 and COSMO-REA6.

Wind resource prospecting: Predicting winds aloft using surface winds and the position of the sun

2020 ◽  
pp. 0309524X2094439
Author(s):  
Marc Arbez
Keyword(s):  
Wind Speed ◽  
Quantitative Research ◽  
Energy Production ◽  
Low Cost ◽  
Surface Wind ◽  
The Sun ◽  
Wind Speeds ◽  
Remote Sites ◽  
Wind Resource ◽  
Production Errors

The sun’s position in the sky appears to strongly influence the vertical wind gradient within the atmospheric boundary layer. This study uses a quantitative research design that combines the position of the sun along with surface wind speeds to estimate the wind gradient. The model applies to uncluttered simple terrain and requires only 10 m wind speed data to extrapolate wind speeds and wind turbine energy production to heights of 60 m or more. The average daytime and nighttime model wind speed errors are 1.7% and 2.4%, respectively. The average daytime and nighttime model turbine energy production errors are 3.8% and 6.1%, respectively. The model offers a practical and low-cost alternative to tall tower systems to assess wind resources, especially for remote sites.

Study of the Flow Over Wind Turbine Blade

2010 ◽  
Author(s):  
R. S. Amano ◽  
R. J. Malloy
Keyword(s):  
Renewable Energy ◽  
Wind Speed ◽  
Wind Energy ◽  
Cross Sections ◽  
Low Cost ◽  
Renewable Energy Sources ◽  
Optimization Technique ◽  
Direct Result ◽  
Wind Speeds ◽  
Computational Fluid Dynamics Cfd

Recently there has been an increase in the demand for the utilization of clean renewable energy sources. This is a direct result of the volatility in oil prices and an increased awareness of human induced climate change. Wind energy has been shown to be one of the most promising sources of renewable energy. With current technology, the low cost of wind energy is competitive with more conventional sources of energy such as coal. Most blades available for commercial grade wind turbines incorporate a straight span-wise profile and airfoil shaped cross sections. These blades are found to be very efficient at lower wind speeds in comparison to the potential energy that can be extracted. However as the oncoming wind speed increases the efficiency of the blades decreases as they approach a stall point. This paper explores the possibility of increasing the efficiency of the blades at higher wind speeds while maintaining efficiency at the lower wind speeds. The design intends to maintain efficiency at lower wind speeds by selecting the appropriate orientation and size of the airfoil cross sections based on a low oncoming wind speed and given constant rotation rate. The blades will be made more efficient at higher wind speeds by implementing a swept blade profile. The torque generated from a blade using only the first optimization technique is compared to that generated from a blade using both techniques as well as that generated by NTK500/41 turbine using LM19.1 blades. Performance will be investigated using the computational fluid dynamics (CFD).

scholarly journals Retrieving hurricane wind speeds using cross-polarization C-band measurements

2014 ◽  
Vol 7 (2) ◽  
pp. 437-449 ◽  
Author(s):  
G.-J. van Zadelhoff ◽  
A. Stoffelen ◽  
P. W. Vachon ◽  
J. Wolfe ◽  
J. Horstmann ◽  
...  
Keyword(s):  
Wind Speed ◽  
Weather Prediction ◽  
Data Sets ◽  
Data Set ◽  
Wind Speeds ◽  
Geophysical Model ◽  
Hurricane Wind ◽  
Geophysical Model Function ◽  
Sar Imagery ◽  
Nwp Model

Abstract. Hurricane-force wind speeds can have a large societal impact and in this paper microwave C-band cross-polarized (VH) signals are investigated to assess if they can be used to derive extreme wind-speed conditions. European satellite scatterometers have excellent hurricane penetration capability at C-band, but the vertically (VV) polarized signals become insensitive above 25 m s−1. VV and VH polarized backscatter signals from RADARSAT-2 SAR imagery acquired during severe hurricane events were compared to collocated SFMR wind measurements acquired by NOAA's hurricane-hunter aircraft. From this data set a geophysical model function (GMF) at strong-to-extreme/severe wind speeds (i.e., 20 m s−1 < U10 < 45 m s−1) is derived. Within this wind speed regime, cross-polarized data showed no distinguishable loss of sensitivity and as such, cross-polarized data can be considered a good candidate for the retrieval of strong-to-severe wind speeds from satellite instruments. The upper limit of 45 m s−1 is defined by the currently available collocated data. The validity of the derived relationship between wind speed and VH backscatter has been evaluated by comparing the cross-polarized signals to two independent wind-speed data sets (i.e., short-range ECMWF numerical weather prediction (NWP) model forecast winds and the NOAA best estimate 1-minute maximum sustained winds). Analysis of the three comparison data sets confirm that cross-polarized signals from satellites will enable the retrieval of strong-to-severe wind speeds where VV or horizontal (HH) polarization data has saturated. The VH backscatter increases exponentially with respect to wind speed (linear against VH [dB]) and a near-real-time assessment of maximum sustained wind speed is possible using VH measurements. VH measurements thus would be an extremely valuable complement on next-generation scatterometers for hurricane forecast warnings and hurricane model initialization.

scholarly journals Investigation on the Performance of a Portable Power Generation System with a Low-Cost Vertical Axis Wind Turbine

2021 ◽  
Vol 11 (6) ◽  
pp. 7809-7813
Author(s):  
M. F. Basar ◽  
A. M. Norazizi ◽  
I. Mustaffa ◽  
C. T. Colin ◽  
S. N. S. Mirin ◽  
...  
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Low Cost ◽  
Public Awareness ◽  
Vertical Axis ◽  
Small Scale ◽  
Vertical Axis Wind Turbine ◽  
Wind Speeds ◽  
Portable Power

The purpose of this project was to develop an innovative, small-scale, and portable vertical axis wind turbine for power generation. The wind turbine was simple in design and economical. Wind speeds ranging from 2.0ms-1 to 7.0ms-1 were tested on the proposed wind turbine. The experiments revealed that the turbine required a minimum wind speed of 3.9ms-1 to operate. According to the results, the proposed turbine achieved its maximum power output of 5.6W at a rotational speed of 65rpm when the wind speed was 7.0m/s. Additionally, voltage and current increased proportionately with increasing wind speed. The proposed system showed an average coefficient factor between 0.10 and 0.12. This portable wind turbine potentially revolutionizes industry while raising public awareness about clean and renewable energy.

On Probabilistic Assessment of Exergy Analysis of a Wind Turbine for Optimum Performance

2021 ◽  
Author(s):  
Mubashir Ali Siddiqui ◽  
Muhammad Uzair Yousuf ◽  
Muhammad Kashan Rashid ◽  
Ahsan Ahmed
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Probability Density ◽  
Wind Farm ◽  
Exergy Efficiency ◽  
Second Law ◽  
Optimum Performance ◽  
Wind Speeds ◽  
One Year ◽  
Performance Conditions

Judgment on the performance of a wind turbine depends upon its first law efficiency as well as its second law efficiency. This paper focuses on the second law efficiency, i.e., the exergy efficiency of a wind turbine. The work introduces a novel technique to determine the optimum performance conditions of a wind turbine. Jhimpir city, Pakistan, has been selected as a case study. The wind speed distribution of the selected area is analyzed using different probability density functions. Three-parameter Weibull Distribution turns out to be the best probability density function fitting the wind speed variation. Probability distribution of total wind exergy is performed, and a one-year variation of wind exergy is plotted, showing maximum exergy around the middle of the year. The exergy efficiency of the turbine using a power curve and wind exergy is determined at different wind speeds. Probabilities of various exergy efficiencies are also determined. Results show that higher exergy efficiency has a high probability but so does low exergy efficiency due to seasonal variations. The proposed method can be extended to any wind farm provided the geographical and meteorological parameters of the site.

A Methodology to Synthesize Gearbox and Control Design for Increased Power Production and Blade Root Stress Mitigation in a Small Wind Turbine1

2017 ◽  
Vol 139 (8) ◽  
Author(s):  
Hamid Khakpour Nejadkhaki ◽  
Amrita Lall ◽  
John F. Hall
Keyword(s):  
Wind Speed ◽  
Low Cost ◽  
Control Design ◽  
Power Production ◽  
Wind Speeds ◽  
Blade Root ◽  
Squirrel Cage Induction Generator ◽  
And Control ◽  
Root Stress ◽  
Selection Of

Large wind turbines typically have variable rotor speed capability that increases power production. However, the cost of this technology is more significant for small turbines, which have the highest cost-per-watt of energy produced. This work presents a low-cost system for applications where cost and reliability are of concern. The configuration utilizes the fixed-speed squirrel cage induction generator. It is combined with a variable ratio gearbox (VRG) that is based on the automated-manual automotive transmission. The design is simple, low cost and implements reliable components. The VRG increases efficiency in lower wind speeds through three discrete rotor speeds. In this study, it is implemented with active blades. The contribution of this work is a methodology that synthesizes the selection of the gearbox ratios with the control design. The design objectives increase the power production while mitigating the blade stress. Top-down dynamic programming reduces the computational expense of evaluating the performance of multiple gearbox combinations. The procedure is customizable to the wind conditions at an installation site. A case study is presented to demonstrate the ability of the strategy. It employs a 300 kW wind turbine drivetrain model that simulates power production. Two sets of wind data representing low and high wind speed installation sites were used as the input. The results suggest a VRG can improve energy production by up to 10% when the system operates below the rated wind speed. This is also accompanied by a slight increase in the blade-root stress. When operating above the rated speed, the stress decreases through the optimal selection of gear combinations.

scholarly journals Statistical post-processing of wind speed forecasts using convolutional neural networks

2020 ◽  
Author(s):  
Maurice Schmeits ◽  
Simon Veldkamp ◽  
Kirien Whan
Keyword(s):  
Neural Networks ◽  
Wind Speed ◽  
Convolutional Neural Networks ◽  
Spatial Information ◽  
Weather Prediction ◽  
Data Sets ◽  
Post Processing ◽  
Wind Speeds ◽  
Recent Developments ◽  
Nwp Model

&lt;p&gt;Current statistical post-processing methods for providing a probabilistic forecast are not capable of using full spatial patterns from the numerical weather prediction (NWP) model output. Recent developments in deep learning (notably convolutional neural networks) have made it possible to use large gridded input data sets. This could potentially be useful in statistical post-processing, since it allows us to use more spatial information.&lt;/p&gt;&lt;p&gt;In this study we consider wind speed forecasts for 48 hours ahead, as provided by KNMI's Harmonie-Arome model. Convolutional neural networks, fully connected neural networks and quantile regression forests are used to obtain probabilistic wind speed forecasts. Comparing these methods shows that convolutional neural networks are more skillful than the other methods, especially for medium to higher wind speeds.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document