Temporal and spatial projection of wind speed based on modular network SOM for installation of off-shore wind generation

2015 ◽  
Author(s):  
Mitsuharu Hayashi ◽  
Ken Nagasaka
Keyword(s):  
Wind Speed ◽  
Wind Generation ◽  
Modular Network ◽  
Temporal And Spatial

Application of Modular Network Self-Organization Map to Temporal and Spatial Projection of Wind Speed with Wind Data at Biased Positions

2018 ◽  
Vol 22 (1) ◽  
pp. 133-140
Author(s):  
Mitsuharu Hayashi ◽  
◽  
Ken Nagasaka
Keyword(s):  
Wind Speed ◽  
Weather Condition ◽  
Weather Conditions ◽  
Self Organization ◽  
Wind Generation ◽  
Target Area ◽  
Modular Network ◽  
Wind Characteristics ◽  
Temporal And Spatial ◽  
Artificial Neural Network Ann

Wind generation is one of the fastest growing resources among renewable energies worldwide including Japan. As Japan is an island country surrounded by ocean, the on-shore landscape topography suitable for wind generation is limited. Therefore, based on the wind map until the year 2030, it is expected that new off-shore wind generation installations will be more suitable. For this reason, it is very important to determine the wind characteristics of the candidate areas for installing wind generation; however, in most off-shore installation sites, availability of weather condition data is poor and significant time and cost are required to accurately measure pin-point wind/weather conditions data. In this study, our goal is to project the wind speed of an unseen area (where weather condition data are not available) by mapping the seen areas (where weather condition data are available) around the target area using a modularized Artificial Neural Network (ANN) referred to as a Self-Organization Map (SOM). By learning the correlation between modularized ANNs of seen and unseen areas, the result of this temporal and spatial projection is the prediction of wind speed of a target area. We believe that the proposed technique will significantly reduce the amount of time and cost involved in selection of off-shore installation sites. Moreover, it should contribute to accelerated development and implementation of off-shore wind power generation in the future.

scholarly journals Analysis of Ozone Pollution Characteristics and Influencing Factors in Northeast Economic Cooperation Region, China

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 843
Author(s):  
Jiaqi Tian ◽  
Chunsheng Fang ◽  
Jiaxin Qiu ◽  
Ju Wang
Keyword(s):  
Wind Speed ◽  
Sunshine Duration ◽  
Meteorological Data ◽  
Economic Cooperation ◽  
Ozone Pollution ◽  
Temporal And Spatial Variation ◽  
Temporal And Spatial ◽  
Pm2.5 And Pm10 ◽  
Peak Pattern ◽  
Pm2.5 Concentration

The increase in tropospheric ozone (O3) concentration has become one of the factors restricting urban development. This paper selected the important economic cooperation areas in Northeast China as the research object and collected the hourly monitoring data of pollutants and meteorological data in 11 cities from 1 January 2015 to 31 December 2019. The temporal and spatial variation trend of O3 concentration and the effects of meteorological factors and other pollutants, including CO (carbon monoxide), SO2 (sulfur dioxide), NO2 (nitrogen dioxide), and PM2.5 and PM10 (PM particles with aerodynamic diameters less than 2.5 μm and 10 μm) on ozone concentration were analyzed. At the same time, the variation period of O3 concentration was further analyzed by Morlet wavelet analysis. The results showed that the O3 pollution in the study area had a significant spatial correlation. The spatial distribution showed that the O3 concentration was relatively high in the south and low in the northeast. Seasonally, the O3 concentration was the highest in spring, followed by summer, and the lowest in winter. The diurnal variation of O3 concentration presented a “single peak” pattern. O3 concentration had a significant positive correlation with temperature, sunshine duration, and wind speed and a significant anticorrelation with CO, NO2, SO2, and PM2.5 concentration. Under the time scale of a = 9, 23, O3 had significant periodic fluctuation, which was similar to those of wind speed and temperature.

Beneficial role of diurnal smoothing for grid integration of wind power

2021 ◽  
Author(s):  
Anasuya Gangopadhyay ◽  
Ashwin K Seshadri ◽  
Ralf Toumi
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Diurnal Cycle ◽  
Power Plants ◽  
Large Scale ◽  
Positive Impact ◽  
Forecast Error ◽  
Wind Generation ◽  
Grid Integration ◽  
Wind Maximum

<p>Smoothing of wind generation variability is important for grid integration of large-scale wind power plants. One approach to achieving smoothing is aggregating wind generation from plants that have uncorrelated or negatively correlated wind speed. It is well known that the wind speed correlation on average decays with increasing distance between plants, but the correlations may not be explained by distance alone. In India, the wind speed diurnal cycle plays a significant role in explaining the hourly correlation of wind speed between location pairs. This creates an opportunity of “diurnal smoothing”. At a given separation distance the hourly wind speeds correlation is reduced for those pairs that have a difference of +/- 12 hours in local time of wind maximum. This effect is more prominent for location pairs separated by 200 km or more and where the amplitude of the diurnal cycle is more than about  0.5 m/s. “Diurnal smoothing” also has a positive impact on the aggregate wind predictability and forecast error. “Diurnal smoothing” could also be important for other regions with diurnal wind speed cycles.</p>

Analysis and Observations of Wind Turbine Yaw Dynamics

1989 ◽  
Vol 111 (4) ◽  
pp. 367-371 ◽  
Author(s):  
A. C. Hansen ◽  
X. Cui
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Quantitative Agreement ◽  
Complex Model ◽  
New Methods ◽  
New Models ◽  
Solution Methods ◽  
Horizontal Axis Wind Turbines ◽  
Temporal And Spatial ◽  
Prediction Techniques

Two models of the yaw behavior of horizontal axis wind turbines are presented and discussed. Emphasis in this paper is on the description of the models and underlying assumptions with details of the equations and solution methods referenced in technical reports. The more complex model (YawDyn) considers the coupling of blade flap motions and yaw motions which result from temporal and spatial variations in the approaching wind speed. The new methods are unique in that they simultaneously model the effects of skewed wake aerodynamics and blade stall. Both of these effects must be considered if yaw behavior is to be adequately understood. The models are validated by comparison with other prediction techniques, wind tunnel tests and full-scale atmospheric tests. In all cases the models are shown to give excellent qualitative agreement and reasonable quantitative agreement. It is concluded that the new models represent a significant improvement in the methods available to the wind turbine designer for understanding yaw loads and motions.

Abundance and Temporal and Spatial Distribution of Culicoides Brevitarsis Kieffer (Diptera: Ceratopogonidae) on Cattle in South-East Queensland.

1979 ◽  
Vol 27 (2) ◽  
pp. 251 ◽  
Author(s):  
MM Campbell ◽  
DS Kettle
Keyword(s):  
Spatial Distribution ◽  
Wind Speed ◽  
Vapour Pressure ◽  
Vapour Pressure Deficit ◽  
Negative Temperature ◽  
Direct Sunlight ◽  
Temporal And Spatial Distribution ◽  
Small Areas ◽  
Temporal And Spatial ◽  
Time Of Year

Numbers of C. brevitarsis on cattle in south-east Queensland increased rapidly from zero at 0.5 h before sunset, to a peak during the half hour after sunset, then decreased to zero in the following 5-6 h and remained at zero throughout the day. On standing animals abundance was greatest on the ridgeline at the tail, decreasing rapidly down the flank and less rapidly towards the head. On mature animals abundance after sunset halved with each increase of 0.53 m s-1 in wind speed, each increase of 6.4�C, each decrease of 158 Pa vapour pressure deficit, and each additional 38 min after sunset. Only females were collected from cattle; 97% of nullipars were mated. They did not always feed at their first attempt and were much less likely to feed on some hosts than others. Close shaving did not alter the number of flies on small areas and did not prevent feeding. Before sunset C. brevitarsis were observed more frequently on hosts in the absence of direct sunlight. In direct sunlight, abundance was influenced most by wind speed (positive), minutes before sunset (negative) and temperature (negative), in order of decreasing importance. Without direct sunlight, the factors were minutes before sunset (negative), temperature (positive), and wind speed (negative); after sunset the factors were wind speed (negative), vapour pressure deficit (positive), minutes after sunset (negative) and minor effects from time of year and temperature.

Circuit Configuration and Control of a Grid-Tie Small-Scale Wind Generation System for Expanded Wind Speed Range

2017 ◽  
Vol 32 (7) ◽  
pp. 5227-5247 ◽  
Author(s):  
Chengshan Wang ◽  
Liang Yang ◽  
Yifeng Wang ◽  
Zhun Meng ◽  
Wei Li ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Generation ◽  
Small Scale ◽  
Generation System ◽  
Speed Range ◽  
Wind Generation System ◽  
And Control ◽  
Circuit Configuration

Research on Control Strategy of Maximum Power Point Tracking of VSCF Wind Generation

2010 ◽  
Vol 29-32 ◽  
pp. 2176-2181
Author(s):  
Wen Jin Dai ◽  
Hai Jing Liu
Keyword(s):  
Wind Speed ◽  
Control Strategy ◽  
Maximum Power ◽  
Wind Generation ◽  
Induction Generator ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Variable Step ◽  
Power Point

Variable speed constant frequency wind turbines can get the maximum power by adjusting the rotor speed of the induction generator according to the variable wind speed. The mathematical relationship between wind speed of wind generation and power of wind turbine power is studied in this paper, then control strategy of maximum power point tracking consists of comparative law of the greatest power, table look-up scheme of the best tip speed ratio and a variable step mountain climb algorithm and the like., and advantages and drawbacks of them are compared. Finally a variable step mountain climb algorithm for an induction generator is studied and the wind turbine model is tested by MATLAB simulation. System simulation results have confirmed the functionality and performance of this method.

Modeling box - jenkins applied a prediction of wind speed in the regions of the brazilian northeast for the fins of wind generation

2018 ◽  
Vol 40 ◽  
pp. 16
Author(s):  
Henrique Do Nascimento Camelo ◽  
Paulo Sérgio Lucio ◽  
João Bosco Verçosa Leal Junior ◽  
Paulo Cesar Marques de Carvalho
Keyword(s):  
Wind Speed ◽  
Wind Generation ◽  
Brazilian Northeast

scholarly journals Short-Term Forecast of Wind Speed through Mathematical Models

2018 ◽  
Author(s):  
Moniki Ferreira ◽  
Alexandre Santos ◽  
Paulo Lucio
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Coastal Region ◽  
Good Method ◽  
Wind Generation ◽  
Use Of Resources ◽  
Reducing Costs ◽  
Power Project ◽  
Modern Era ◽  
Terrain Characteristics

The predictability of wind information in a given location is essential for the evaluation of a wind power project. Predicting wind speed accurately improves the planning of wind power generation, reducing costs and improving the use of resources. This paper seeks to predict the mean hourly wind speed in anemometric towers (at a height of 50 meters) at two locations: a coastal region and one with complex terrain characteristics. To this end, the Holt-Winters (HW), Artificial Neural Networks (ANN) and Hybrid time-series models were used. Observational data evaluated by the Modern-Era Retrospective analysis for Research and Applications-Version 2 (MERRA-2) reanalysis at the same height of the towers. The results show that the hybrid model had a better performance in relation to the others, including when compared to the evaluation with MERRA-2. For example, in terms of statistical residuals, RMSE and MAE were 0.91 and 0.62 m/s, respectively. As such, the hybrid models are a good method to forecast wind speed data for wind generation.

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