Prediction uncertainty of wind-generated noise spectra from wind speed

2021 ◽  
Vol 150 (1) ◽  
pp. 215-224
Author(s):  
Ying Zhang ◽  
Qiulong Yang ◽  
Kunde Yang
Keyword(s):  
Wind Speed ◽  
Prediction Uncertainty ◽  
Noise Spectra

Characterizing the convective heat exchange with plastic shading nets under natural arid conditions

2019 ◽  
pp. 11-20
Author(s):  
Ahmed M Abdel-Ghanya ◽  
Ibrahim M Al-Helal
Keyword(s):  
Wind Speed ◽  
Thermal Radiation ◽  
Convective Heat ◽  
Convective Heat Transfer Coefficient ◽  
Convective Heat Exchange ◽  
Radiative Properties ◽  
Wooden Frame ◽  
Arid Conditions ◽  
Air Temperatures ◽  
Radiation Fluxes

Plastic nets are extensively used for shading purposes in arid regions such as in the Arabian Peninsula. Quantifying the convection exchange with shading net and understanding the mechanisms (free, mixed and forced) of convection are essential for analyzing energy exchange with shading nets. Unlike solar and thermal radiation, the convective energy, convective heat transfer coefficient and the nature of convection have never been theoretically estimated or experimentally measured for plastic nets under arid conditions. In this study, the convected heat exchanges with different plastic nets were quantified based on an energy balance applied to the nets under outdoor natural conditions. Therefore, each net was tacked onto a wooden frame, fixed horizontally at 1.5-m height over the floor. The downward and upward solar and thermal radiation fluxes were measured below and above each net on sunny days; also the wind speed over the net, and the net and air temperatures were measured, simultaneously. Nets with different porosities, colors and texture structures were used for the study. The short and long wave’s radiative properties of the nets were pre-determined in previous studies to be used. Re and Gr numbers were determined and used to characterize the convection mechanism over each net. The results showed that forced and mixed convection are the dominant modes existing over the nets during most of the day and night times. The nature of convection over nets depends mainly on the wind speed, net-air temperature difference and texture shape of the net rather than its color and its porosity.

Monitoring Coastal Wind Speed Using BeiDou GEO Reflected Signals

2016 ◽  
Author(s):  
Qiang Wang ◽  
Dongkai Yang ◽  
Hongxing Gao ◽  
Weiqiang Li ◽  
Yunlong Zhu ◽  
...  
Keyword(s):  
Wind Speed

FORECASTING THE AVERAGE MONTHLY WIND SPEED WITH THE USE OF THE BAYES APPROACH TO FORECASTING

2018 ◽  
Vol 27 (103) ◽  
pp. 151-156
Author(s):  
V. Rosen, ◽  
◽  
A. Chermalykh, ◽  
A. Buchkivskii
Keyword(s):  
Wind Speed ◽  
Bayes Approach

THE INFLUENCE OF THE WIND SPEED PREDICTION ERROR ON THE SIZE OF THE STORAGE CONTROLLED OPERATION ZONE IN THE SYSTEM WITH THE WIND GENERATOR

2020 ◽  
Vol 2020 (57) ◽  
pp. 35-41
Author(s):  
K.S. Klen ◽  
◽  
M.K. Yaremenko ◽  
V.Ya. Zhuykov ◽  
◽  
...  
Keyword(s):  
Wind Speed ◽  
Prediction Error ◽  
Average Energy ◽  
Interpolation Formula ◽  
Wind Speed Prediction ◽  
Wind Generator ◽  
Prediction Horizon ◽  
Speed Prediction ◽  
Using Data ◽  
Predictor Corrector

The article analyzes the influence of wind speed prediction error on the size of the controlled operation zone of the storage. The equation for calculating the power at the output of the wind generator according to the known values of wind speed is given. It is shown that when the wind speed prediction error reaches a value of 20%, the controlled operation zone of the storage disappears. The necessity of comparing prediction methods with different data discreteness to ensure the minimum possible prediction error and determining the influence of data discreteness on the error is substantiated. The equations of the "predictor-corrector" scheme for the Adams, Heming, and Milne methods are given. Newton's second interpolation formula for interpolation/extrapolation is given at the end of the data table. The average relative error of MARE was used to assess the accuracy of the prediction. It is shown that the prediction error is smaller when using data with less discreteness. It is shown that when using the Adams method with a prediction horizon of up to 30 min, within ± 34% of the average energy value, the drive can be controlled or discharged in a controlled manner. References 13, figures 2, tables 3.

Autonomous energy supply based on the wind-energy complex and hydrogen energy storage

2019 ◽  
pp. 12-26
Author(s):  
S. I. Nefedkin ◽  
A. O. Barsukov ◽  
M. I. Mozgova ◽  
M. S. Shichkov ◽  
M. A. Klimova
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Power Supply ◽  
Energy Supply ◽  
Heat Supply ◽  
Hot Water ◽  
Successful Implementation ◽  
High Wind ◽  
Wind Generators ◽  
Weak Wind

The paper proposes an alternative scheme of guaranteed electricity and heat supply of an energy-insulated facility with a high potential of wind energy without the use of imported or local fuel. The scheme represents a wind power complex containing the park of wind generators located at the points with high wind potential. The wind generators provide guaranteed power supply even in periods of weak wind. For heat supply of the consumer, all surplus of the electric power goes on thermoelectric heating of water in tanks of accumulators, and also on receiving hydrogen by a method of electrolysis of water. The current heat supply is carried out with the use of hot water storage tanks, and the heat supply during the heat shortage is carried out by burning the stored hydrogen in condensing hydrogen boilers. We have developed the algorithm of calculation and the program "Wind in energy" which allows calculating annual balance of energy and picking up necessary quantity of the equipment for implementation of the scheme proceeding from the annual schedule of thermal and electric loading, and also potential of wind energy in the chosen region. The calculation-substantiation of the scheme proposed in relation to the real energy-insulated object Ust-Kamchatsk (Kamchatka) is carried out. The equipment for the implementation of an alternative energy supply scheme without the use of imported fuel is selected and compared with the traditional energy supply scheme based on a diesel power plant and a boiler house operating on imported fuel. With the introduction of an alternative power supply scheme, the equipment of the traditional scheme that has exhausted its resource can be used for backup power supply. Using climate databases, a number of energy-insulated facilities in the North and East of Russia with high wind energy potential are considered and the conditions for the successful implementation of the energy supply scheme are analyzed. This requires not only a high average annual wind speed, but also a minimum number of days of weak wind. In addition, it is necessary that the profile of the wind speed distribution in the annual section coincides with the profile of the heat load consumption.

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.

Prediction of Atmospheric Turbulence Characteristics for Surface Boundary Layer using Empirical Spectral Methods

2020 ◽  
Author(s):  
Yagya Dutta Dwivedi ◽  
Vasishta Bhargava Nukala ◽  
Satya Prasad Maddula ◽  
Kiran Nair
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
Surface Roughness ◽  
Wind Speed ◽  
Atmospheric Turbulence ◽  
Surface Boundary ◽  
Low Frequencies ◽  
Surface Boundary Layer ◽  
Power Spectral ◽  
Mean Wind Speed

Abstract Atmospheric turbulence is an unsteady phenomenon found in nature and plays significance role in predicting natural events and life prediction of structures. In this work, turbulence in surface boundary layer has been studied through empirical methods. Computer simulation of Von Karman, Kaimal methods were evaluated for different surface roughness and for low (1%), medium (10%) and high (50%) turbulence intensities. Instantaneous values of one minute time series for longitudinal turbulent wind at mean wind speed of 12 m/s using both spectra showed strong correlation in validation trends. Influence of integral length scales on turbulence kinetic energy production at different heights is illustrated. Time series for mean wind speed of 12 m/s with surface roughness value of 0.05 m have shown that variance for longitudinal, lateral and vertical velocity components were different and found to be anisotropic. Wind speed power spectral density from Davenport and Simiu profiles have also been calculated at surface roughness of 0.05 m and compared with k−1 and k−3 slopes for Kolmogorov k−5/3 law in inertial sub-range and k−7 in viscous dissipation range. At high frequencies, logarithmic slope of Kolmogorov −5/3rd law agreed well with Davenport, Harris, Simiu and Solari spectra than at low frequencies.

An Efficient Hybrid Forecasting Approach for Wind Speed Time Series

2017 ◽  
Vol 7 (9) ◽  
pp. 13
Author(s):  
Bhargavi Munnaluri ◽  
K. Ganesh Reddy
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Wind Speed ◽  
Fossil Fuels ◽  
Renewable Energy Sources ◽  
Support Vector ◽  
Hybrid Forecasting ◽  
Artificial Neural ◽  
Future Utilization

Wind forecasting is one of the best efficient ways to deal with the challenges of wind power generation. Due to the depletion of fossil fuels renewable energy sources plays a major role for the generation of power. For future management and for future utilization of power, we need to predict the wind speed.  In this paper, an efficient hybrid forecasting approach with the combination of Support Vector Machine (SVM) and Artificial Neural Networks(ANN) are proposed to improve the quality of prediction of wind speed. Due to the different parameters of wind, it is difficult to find the accurate prediction value of the wind speed. The proposed hybrid model of forecasting is examined by taking the hourly wind speed of past years data by reducing the prediction error with the help of Mean Square Error by 0.019. The result obtained from the Artificial Neural Networks improves the forecasting quality.

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