scholarly journals Highway wind power energy assessment of Al-Durra highway street in Baghdad, Iraq

2020 ◽  
Vol 11 (4) ◽  
pp. 2055
Author(s):  
Adnan Ahmed Abdul Raheem ◽  
Wadhah Esmaeel Ibraheem
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Power Plants ◽  
The Road ◽  
Wind Speeds ◽  
Road Lighting ◽  
Energy Assessment ◽  
Moving Vehicles ◽  
Time Series Simulation ◽  
Support Time

In certain spots on the planet which have less attainable of utilizing enormous breeze power plants, the expressway wind vitality can be utilized to help little loads in the main grids. Interstates road lighting for instance of that heaps that is expending a great deal of vitality and cost every year. When the vitality that originates from vehicles development along the highway avenues can be taken in thought, this paper has examined the outcomes if moment vehicles wind speed during 24 hours per day. 24 hours, brief interim of vehicles wind speeds have been estimated by utilizing anemometer put in the road. A vertical pivot wind turbine (VAWT) has been proposed to be utilized in this task. All venture regulation has been simulated by utilizing Opendss program; it can support time series simulation. The outcomes demonstrated that the undertaking is possible to be utilized in Al-Durra Highway Street. The normal breeze speed of moving vehicles is 4.7 m/s which can deliver 67.3 watt by the proposed turbine. The got energy saw that it as contributed to be utilized by the maingrid during the day time. All the demonstrated bends of the outcomes speak to the Iraq grid support by diminishing the main demand and operational expenses too.

scholarly journals Optimization of a Small Wind Power Plant for Annual Wind Speed Distribution

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1587
Author(s):  
Krzysztof Wrobel ◽  
Krzysztof Tomczewski ◽  
Artur Sliwinski ◽  
Andrzej Tomczewski
Keyword(s):  
Wind Speed ◽  
Power Plant ◽  
Wind Power ◽  
Power Plants ◽  
Control Method ◽  
Wind Power Plant ◽  
Switched Reluctance ◽  
Wind Speeds ◽  
Wind Speed Distribution ◽  
And Control

This article presents a method to adjust the elements of a small wind power plant to the wind speed characterized by the highest annual level of energy. Tests were carried out on the basis of annual wind distributions at three locations. The standard range of wind speeds was reduced to that resulting from the annual wind speed distributions in these locations. The construction of the generators and the method of their excitation were adapted to the characteristics of the turbines. The results obtained for the designed power plants were compared with those obtained for a power plant with a commercial turbine adapted to a wind speed of 10 mps. The generator structure and control method were optimized using a genetic algorithm in the MATLAB program (Mathworks, Natick, MA, USA); magnetostatic calculations were carried out using the FEMM program; the simulations were conducted using a proprietary simulation program. The simulation results were verified by measurement for a switched reluctance machine of the same voltage, power, and design. Finally, the yields of the designed generators in various locations were determined.

Investigation of the wind speed threshold above which discarded cigarettes are likely to be moved by the wind

2006 ◽  
Vol 15 (4) ◽  
pp. 567 ◽  
Author(s):  
Gavriil Xanthopoulos ◽  
Dany Ghosn ◽  
George Kazakis
Keyword(s):  
Wind Speed ◽  
Road Surface ◽  
Regression Equations ◽  
Compacted Soil ◽  
Asphalt Cement ◽  
The Road ◽  
Wind Speeds ◽  
Cigarette Butts ◽  
Cigarette Butt ◽  
On The Road

Cigarette butts thrown from passing cars often become fire ignition sources. However, this is only possible if a butt ends up on dead and dry fuels on the roadside. The current paper presents two experiments, carried out in a wind tunnel, designed to investigate the wind speed thresholds above which a butt thrown on the road is unlikely to stay on the road surface but will roll with the wind. The work was done for three road surfaces: asphalt, cement, and compacted soil. The experiments demonstrated that a lower wind speed is necessary for cigarette butts to start rolling from a still condition than the wind speed needed for whole cigarettes. Three wind speed thresholds, 0.88 m s–1 for asphalt, 1.63 m s–1 for cement, and 2.33 m s–1 for compacted soil, represent a conservative lower limit below which movement of still butts is highly unlikely. Three logistic regression equations were developed for calculating the probability that a cigarette butt thrown on the road surface under wind will continue to roll. They show that for wind speeds of less than 4.5 m s–1, a cigarette butt thrown on a dirt road is much less likely to be carried by the wind than if it was thrown on an asphalt or cement surface. The wind speed values refer to a height of 5 cm. The present paper provides a discussion of how this value relates to commonly used meteorological wind previsions. It also includes an example of how the findings can be used for fire prevention purposes.

scholarly journals Economic justification for the use of a vertical axis wind power plant in wind conditions of Russia

2021 ◽  
Vol 24 (6) ◽  
pp. 1285-1296
Author(s):  
B. P. Khozyainov ◽  
T. N. Svistunova
Keyword(s):  
Wind Speed ◽  
Power Plant ◽  
Wind Power ◽  
Power Plants ◽  
Vertical Axis ◽  
Wind Power Plant ◽  
Wind Speeds ◽  
Economic Justification ◽  
The Cost ◽  
Natural Wind

The purpose of the study is to provide an economic justification of the application efficiency of vertical axis wind-driven power plants using the principle of differential blade drag under low natural wind speeds from 1 to 15 m/s. The estimated cost is determined by the resource-index method. Calculations are made in two stages: at the first stage a statement is compiled where the consumption of resources for the design volume of work is determined according to the state unit estimate standards collections; at the second stage a local resource estimate is made, and the resource consumption in natural units is converted to cost estimates (in the prices of 2000 year). Local estimates are made using the GRAND-SMETA software package. All costs of construction materials for the wind turbine and supporting structure were assumed at the commercial cost, which was translated to the budget cost of October 2019 using deflators. The transition indices from the prices of 2000 to the prices of 2019 are applied to the cost of materials and machinery operation (without remuneration of engine-drivers) as well as to the amount of labour remuneration for installers and engine-drivers. The cost of the installation set calculated by the strength at 20 m/s natural speed is 1643.591 thousand rubles. This allowed to determine the cost of 1 kWh, which depends on the service life and the average annual wind speed. At a wind speed of 4 m/s the cost is 7.12 rub/kWh; at a wind speed of 8 m/s it is 2.19 rub/kWh. At wind speeds from 5 m/s to 11 m/s with equal exposure time intervals, the average cost of 1 kWh will be within 3.14 rub/kWh. Conducted studies have confirmed the effective use of the proposed vertical axis wind power plant under conditions of low natural wind speeds in Russia. The installation is proved to be competitive in comparison with the traditional methods of energy generation.

scholarly journals A "Global Radiosonde and tracked-balloon Archive on Sixteen Pressure levels" (GRASP) going back to 1905 – Part 2: homogeneity adjustments for pilot balloon and radiosonde wind data

2014 ◽  
Vol 6 (2) ◽  
pp. 297-316 ◽  
Author(s):  
L. Ramella Pralungo ◽  
L. Haimberger
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Wind Direction ◽  
Sampling Bias ◽  
Observation Time ◽  
Early Years ◽  
Wind Speed Data ◽  
Wind Speeds ◽  
Measurement Biases ◽  
The 1960S

Abstract. This paper describes the comprehensive homogenization of the "Global Radiosonde and tracked balloon Archive on Sixteen Pressure levels" (GRASP) wind records. Many of those records suffer from artificial shifts that need to be detected and adjusted before they are suitable for climate studies. Time series of departures between observations and the National Atmospheric and Oceanic Administration 20th-century (NOAA-20CR) surface pressure only reanalysis have been calculated offline by first interpolating the observations to pressure levels and standard synoptic times, if needed, and then interpolating the gridded NOAA-20CR standard pressure level data horizontally to the observation locations. These difference time series are quite sensitive to breaks in the observation time series and can be used for both automatic detection and adjustment of the breaks. Both wind speed and direction show a comparable number of breaks, roughly one break in three stations. More than a hundred artificial shifts in wind direction could be detected at several US stations in the period 1938/1955. From the 1960s onward the wind direction breaks are less frequent. Wind speed data are not affected as much by measurement biases, but one has to be aware of a large fair-weather sampling bias in early years, when high wind speeds were much less likely to be observed than after 1960, when radar tracking was already common practice. This bias has to be taken into account when calculating trends or monthly means from wind speed data. Trends of both wind speed and direction look spatially more homogeneous after adjustment. With the exception of a widespread wind direction bias found in the early US network, no signs of pervasive measurement biases could be found. The adjustments can likely improve observation usage when applied during data assimilation. Alternatively they can serve as a basis for validating variational wind bias adjustment schemes. Certainly, they are expected to improve estimates of global wind trends. All the homogeneity adjustments are available in the PANGAEA archive with associated doi:10.1594/PANGAEA.823617.

German Bight Storminess over the Last Century

2020 ◽  
Author(s):  
Daniel Krieger ◽  
Oliver Krueger ◽  
Frauke Feser ◽  
Ralf Weisse ◽  
Birger Tinz ◽  
...  
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
German Bight ◽  
Geostrophic Wind ◽  
Air Pressure ◽  
Offshore Wind ◽  
Pressure Data ◽  
Storm Activity ◽  
Wind Speeds ◽  
North East

<p>Assessing past storm activity provides valuable knowledge for economic and ecological sectors, such as the renewable energy sector, insurances, or health and safety. However, long time series of wind speed measurements are often not available as they are usually hampered by inhomogeneities due to changes in the surroundings of a measurement site, station relocations, and changes in the instrumentation. On the contrary, air pressure measurements provide mostly homogeneous time series as the air pressure is usually unaffected by such factors.</p><p>Therefore, we perform statistical analyses on historical pressure data measured at several locations within the German Bight (southeastern North Sea) between 1897 and 2018. We calculate geostrophic wind speeds from triplets of mean sea level pressure observations that form triangles over the German Bight. We then investigate the evolution of German Bight storminess from 1897 to 2018 through analyzing upper quantiles of geostrophic wind speeds, which act as a proxy for past storm activity. The derivation of storm activity is achieved by enhancing the established triangle proxy method via combining and merging storminess time series from numerous partially overlapping triangles in an ensemble-like manner. The utilized approach allows for the construction of robust, long-term and subdaily German Bight storminess time series. Further, the method provides insights into the underlying uncertainty of the time series.</p><p>The results show that storm activity over the German Bight is subject to multidecadal variability. The latest decades are characterized by an increase in activity from the 1960s to the 1990s, followed by a decline lasting into the 2000s and below-average activity up until present. The results are backed through a comparison with reanalysis products from four datasets, which provide high-resolution wind and pressure data starting in 1979 and offshore wind speed measurements taken from the FINO-WIND project. This study also finds that German Bight storminess positively correlates with storminess in the North-East Atlantic in general. In certain years, however, notably different levels of storm activity in the two regions can be found, which likely result from shifted large-scale circulation patterns.</p>

scholarly journals Point Downscaling of Surface Wind Speed for Forecast Applications

2018 ◽  
Vol 57 (3) ◽  
pp. 659-674 ◽  
Author(s):  
Brian H. Tang ◽  
Nick P. Bassill
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
High Frequency Component ◽  
Daily Maximum ◽  
Wind Speeds ◽  
Power Spectral

AbstractA statistical downscaling algorithm is introduced to forecast surface wind speed at a location. The downscaling algorithm consists of resolved and unresolved components to yield a time series of synthetic wind speeds at high time resolution. The resolved component is a bias-corrected numerical weather prediction model forecast of the 10-m wind speed at the location. The unresolved component is a simulated time series of the high-frequency component of the wind speed that is trained to match the variance and power spectral density of wind observations at the location. Because of the stochastic nature of the unresolved wind speed, the downscaling algorithm may be repeated to yield an ensemble of synthetic wind speeds. The ensemble may be used to generate probabilistic predictions of the sustained wind speed or wind gusts. Verification of the synthetic winds produced by the downscaling algorithm indicates that it can accurately predict various features of the observed wind, such as the probability distribution function of wind speeds, the power spectral density, daily maximum wind gust, and daily maximum sustained wind speed. Thus, the downscaling algorithm may be broadly applicable to any application that requires a computationally efficient, accurate way of generating probabilistic forecasts of wind speed at various time averages or forecast horizons.

scholarly journals Computational Fluid Dynamics (CFD) Approach to Predict an Actual Wind Speed over Complex Terrain

2018 ◽  
Author(s):  
Takanori Uchida
Keyword(s):  
Fluid Dynamics ◽  
Time Series ◽  
Wind Speed ◽  
Complex Terrain ◽  
Field Observations ◽  
Wind Speeds ◽  
Elevation Data ◽  
Wind Park ◽  
Kagoshima Prefecture ◽  
Computational Fluid Dynamics Cfd

This paper proposes a procedure for predicting the actual wind speed for flow over complex terrain with CFD. It converts a time-series of wind speed data acquired from field observations into a time-series of actual scalar wind speed by using non-dimensional wind speed parameters which are determined beforehand with the use of CFD output. The accuracy and reproducibility of the prediction procedure were examined by simulating the flow with CFD with the use of high resolution (5 m) surface elevation data for the Noma Wind Park in Kagoshima Prefecture, Japan. The errors of the predicted average monthly wind speeds relative to the observed values were less than approximately 20%.

scholarly journals A global radiosonde and tracked balloon archive on 16 pressure levels (GRASP) back to 1905 – Part 2: Homogeneity adjustments for PILOT and radiosonde wind data

2014 ◽  
Vol 7 (1) ◽  
pp. 335-383 ◽  
Author(s):  
L. Ramella Pralungo ◽  
L. Haimberger
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Wind Direction ◽  
Sampling Bias ◽  
Observation Time ◽  
Early Years ◽  
Wind Speed Data ◽  
Wind Speeds ◽  
Measurement Biases ◽  
The 1960S

Abstract. This paper describes the comprehensive homogenization of the GRASP wind records. Many of those records suffer from artificial shifts that need to be detected and adjusted before they are suitable for climate studies. Time series of departures between observations and the National Atmospheric and Oceanic Administration 20th century (NOAA-20CR) surface pressure only reanalysis have been calculated offline by first interpolating the observations to pressure levels and standard synoptic times, if needed, and then interpolating the gridded NOAA-20CR standard pressure level data horizontally to the observation locations. These difference time series are quite sensitive to breaks in the observation time series and can be used for both automatic detection and adjustment of the breaks. Both wind speed and direction show a comparable number of breaks, roughly one break in three stations. More than hundred artificial shifts in wind direction could be detected at several US stations in the period 1938/1955. From the 1960s onward the wind direction breaks are less frequent. Wind speed data are not so much affected by measurement biases but one has to be aware of a large fair weather sampling bias in early years when high wind speeds were much less likely to be observed than after 1960 when RADAR tracking was already common practice. It has to be taken into account when calculating trends or monthly means from wind speed data. Trends of both wind speed and direction look spatially more homogeneous after adjustment. With the exception of a widespread wind direction bias found in the early US network no signs of pervasive measurement biases could be found. The adjustments can likely improve observation usage when applied during data assimilation. Alternatively they can serve as basis for validating variational wind bias adjustment schemes. Certainly they are expected to improve estimates of global wind trends. All the homogeneity adjustments are available in the PANGAEA archive with the associated DOI doi:10.1594/PANGAEA.823617.

scholarly journals A Novel Integration of Hodrick-Prescott Filter and Harmonic Analysis with Machine Learning Methods to Enhance Time Series Prediction Accuracy of Daily and Monthly Wind Speeds

2021 ◽  
Author(s):  
Chigbogu Godwin Ozoegwu
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Wind Speed ◽  
Harmonic Analysis ◽  
Hybrid Algorithm ◽  
Support Vector ◽  
Learning Methods ◽  
Wind Speeds ◽  
Machine Learning Methods ◽  
Tropical Conditions

Abstract In this work, a new hybrid algorithm for modelling time series of daily and monthly wind speed is proposed. The method utilizes Hodrick-Prescott Filter (HPF) to decompose raw wind speed data into trend and cyclic components, and harmonic analysis (HA) is thereafter used to decompose the cyclic component into the periodic and stochastic sub-components. Machine learning (ML) methods are then used to model the time series of both the trend and stochastic components. The predicted wind speeds are finally summed from the individual predictions of the ML methods and harmonic analyses. To highlight the considerably higher predictive accuracy that results from the introduced data pre-treatments with HPF and HA, the proposed hybrid algorithm is compared against the traditional ML methods that are not subjected to the pre-treatments. The proposed hybrid algorithms are highly accurate relative to the traditional ML methods reflecting much higher coefficients of determination and correlation coefficients, and much lower error indices. Artificial neural networks (ANNs), linear regression with interactions (LRI), support vector machine (SVM), rational quadratic Gaussian process regression (RQGPR), fine regression trees (FRTs) and boosted ensembles of trees (BETs) are used as the illustrative machine learning methods. To guarantee both versatility and robustness, the methods are tested on example data drawn from both temperate and tropical conditions.

scholarly journals Modeling Wind Speed Based on Fractional Ornstein-Uhlenbeck Process

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5561
Author(s):  
Sergey Obukhov ◽  
Ahmed Ibrahim ◽  
Denis Y. Davydov ◽  
Talal Alharbi ◽  
Emad M. Ahmed ◽  
...  
Keyword(s):  
Wind Speed ◽  
Power Plants ◽  
Moving Average ◽  
Discrete Models ◽  
Model Parameters ◽  
Observation Data ◽  
Time Step ◽  
Uhlenbeck Process ◽  
Wind Speeds ◽  
Ornstein Uhlenbeck Process

The primary task of the design and feasibility study for the use of wind power plants is to predict changes in wind speeds at the site of power system installation. The stochastic nature of the wind and spatio-temporal variability explains the high complexity of this problem, associated with finding the best mathematical modeling which satisfies the best solution for this problem. In the known discrete models based on Markov chains, the autoregressive-moving average does not allow variance in the time step, which does not allow their use for simulation of operating modes of wind turbines and wind energy systems. The article proposes and tests a SDE-based model for generating synthetic wind speed data using the stochastic differential equation of the fractional Ornstein-Uhlenbeck process with periodic function of long-run mean. The model allows generating wind speed trajectories with a given autocorrelation, required statistical distribution and provides the incorporation of daily and seasonal variations. Compared to the standard Ornstein-Uhlenbeck process driven by ordinary Brownian motion, the fractional model used in this study allows one to generate synthetic wind speed trajectories which autocorrelation function decays according to a power law that more closely matches the hourly autocorrelation of actual data. In order to demonstrate the capabilities of this model, a number of simulations were carried out using model parameters estimated from actual observation data of wind speed collected at 518 weather stations located throughout Russia.

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