scholarly journals A Two-Stage Wind Grid Inverter with Boost Converter

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Yanbo Che ◽  
Wen Zhang ◽  
Leijiao Ge ◽  
Jijie Zhang
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Topological Structure ◽  
Boost Converter ◽  
Superior Performance ◽  
Practical Significance ◽  
Energy Output ◽  
Low Wind Speed ◽  
And Control ◽  
Inverter Topology

At present, the conversion efficiency of commercial small wind grid inverter is low, and, in case of low wind speed, the wind energy cannot be used efficiently. In order to resolve this problem, it is necessary to improve the topological structure and control strategy, and design a new small wind grid inverter. In this paper, we apply a two-voltage stage topology with boost converter. The boost circuit is to achieve the maximum power output of the wind energy by the segmented regulation, while the improved inverter topology realizes the overall system function with the former stage circuit. The experimental results show that the new wind grid inverter has superior performance in the low wind speed, and has the high quality energy output. This research has an important practical significance to improve the utilization of renewable energy.

Creating the Wind Energy for Operating the 3-C-Section Blades Wind Car

2012 ◽  
Vol 622-623 ◽  
pp. 1188-1193 ◽  
Author(s):  
Hüseyin Çamur ◽  
Youssef Kassem
Keyword(s):  
Wind Speed ◽  
Angular Velocity ◽  
Wind Energy ◽  
Drag Force ◽  
Mechanical Energy ◽  
Main Shaft ◽  
Airflow Velocity ◽  
Low Speed ◽  
Low Wind Speed

The purpose of this work is to determine the drag characteristics and the torque of three C-section blades wind car. Three C-section blades are directly connected to wheels by using of various kinds of links. Gears are used to convert the wind energy to mechanical energy to overcome the load exercised on the main shaft under low speed. Previous work on three vertical blades wind car resulted in discrepancies when compared to this work. Investigating these differences was the motivation for this series of work. The calculated values were compared to the data of three vertical blades wind car. The work was conducted in a low wind speed. The drag force acting on each model was calculated with an airflow velocity of 4 m/s and angular velocity of the blade of 13.056 rad/s.

Calculation of Weibull Distribution parameters at low wind speed and performance analysis

2021 ◽  
pp. 1-24
Author(s):  
Yusuf Alper Kaplan
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Weibull Distribution ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Statistical Indicator ◽  
Low Wind Speed ◽  
Distribution Parameters ◽  
Wind Energy Potential ◽  
And Performance

In this study, the compatibility of the real wind energy potential to the estimated wind energy potential by Weibull Distribution Function (WDF) of a region with low average wind speed potential was examined. The main purpose of this study is to examine the performance of six different methods used to find the coefficients of the WDF and to determine the best performing method for selected region. In this study seven-year hourly wind speed data obtained from the general directorate of meteorology of this region was used. The root mean square error (RMSE) statistical indicator was used to compare the efficiency of all used methods. Another main purpose of this study is to observe the how the performance of the used methods changes over the years. The obtained results showed that the performances of the used methods showed slight changes over the years, but when evaluated in general, it was observed that all method showed acceptable performance. Based on the obtained results, when the seven-year data is evaluated in this selected region, it can be said that the MM method shows the best performance.

scholarly journals Climate Change Induced Uncertainty of Wind Energy Potential for the Azov and Black Seas Coastal Zone

2020 ◽  
Author(s):  
V. P. Evstigneev ◽  
◽  
N. A. Lemeshko ◽  
V. A. Naumova ◽  
M. P. Evstigneev ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Black Sea ◽  
Operating Time ◽  
Energy Output ◽  
Energy Potential ◽  
Wind Energy Potential ◽  
Wind Climate

The paper deals with assessing an impact of wind climate change on the wind energy potential of the Azov and Black Sea coast region. A lower estimate of operating time for wind power installation and a potential annual energy output for the region are given for the case of Vestas V117-4.2MW. Calculation has been performed of a long-term mean wind speed for two adjacent climatic periods (1954–1983 and 1984–2013) based on data from meteorological stations of the Black and Azov Sea region. The results show a decrease in wind speed at all meteorological stations except for Novorossiysk. The wind climate change is confirmed by comparing two adjoined 30-year periods and by estimating linear trends of the mean annual wind speed for the period 1954–2013, which are negative and significant for almost all meteorological stations in the region (α = 1 %). The trend values were estimated by the nonparametric method of robust linear smoothing using the Theil – Sen function. In the present study, the uncertainty of wind energy resource induced by a gradual wind climate change is estimated for perspective planning of this branch of energy sector. Despite the observed trends in the wind regime, average wind speeds in the Azov and Black Sea region are sufficient for planning the location of wind power plants.

Ensemble-Based Data Assimilation for Wind Forecasting – Application to Wind Farm

2020 ◽  
Author(s):  
Yang-Ming Fan
Keyword(s):  
Wind Speed ◽  
Natural Gas ◽  
Data Assimilation ◽  
Wind Energy ◽  
Wind Farm ◽  
Initial Conditions ◽  
Wind Farms ◽  
Weather Conditions ◽  
Energy Output ◽  
Combining Data

<p>The purpose of this study is to develop an ensemble-based data assimilation method to accurately predict wind speed in wind farm and provide it for the use of wind energy intelligent forecasting platform. As Taiwan government aimed to increase the share of renewable energy generation to 20% by 2025, among them, the uncertain wind energy output will cause electricity company has to reserve a considerable reserve capacity when dispatching power, and it is usually high cost natural gas power generation. In view of this, we will develop wind energy intelligent forecasting platform with an error of 10% within 72 hours and expect to save hundred millions of dollars of unnecessary natural gas generators investment. Once the wind energy can be predicted more accurately, the electricity company can fully utilize the robustness and economy of smart grid supply. Therefore, the mastery of the change of wind speed is one of the key factors that can reduce the minimum error of wind energy intelligent forecasting.</p><p>There are many uncertainties in the numerical meteorological models, including errors in the initial conditions or defects in the model, which may affect the accuracy of the prediction. Since the deterministic prediction cannot fully grasp the uncertainty in the prediction process, so it is difficult to obtain all possible wind field changes. The development of ensemble-based data assimilation prediction is to make up for the weakness of deterministic prediction. With the prediction of 20 wind fields as ensemble members, it is expected to include the uncertainty of prediction, quantify the uncertainty, and integrate the wind speed observations of wind farms as well to provide the optimal prediction of wind speed for the next 72 hours. The results show that the prediction error of wind speed within 72 hours is 6% under different weather conditions (excluding typhoons), which proves that the accuracy of wind speed prediction by combining data assimilation technology and ensemble approach is better.</p>

scholarly journals U.S. Department of Energy Wind Energy Research Program for Low Wind Speed Technology of the Future

2002 ◽  
Vol 124 (4) ◽  
pp. 455-458 ◽  
Author(s):  
Stan Calvert ◽  
Robert Thresher, ◽  
Susan Hock, ◽  
Alan Laxson, and ◽  
Brian Smith
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Research Program ◽  
Department Of Energy ◽  
Energy Research ◽  
Low Wind Speed ◽  
The Future

scholarly journals Evaluation of wind energy potential of the state of Tamil Nadu, India based on trend analysis

2021 ◽  
Vol 49 (1) ◽  
pp. 244-251
Author(s):  
Narayanan Natarajan ◽  
S. Rehman ◽  
Nandhini Shiva ◽  
M. Vasudevan
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Trend Analysis ◽  
Tamil Nadu ◽  
Wind Farm ◽  
Linear Trend ◽  
Energy Output ◽  
Energy Yield ◽  
Energy Potential ◽  
Increasing Trend

An accurate estimate of wind resource assessment is essential for the identification of potential site for wind farm development. The hourly average wind speed measured at 50 m above ground level over a period of 39 years (1980-2018) from 25 locations in Tamil Nadu, India have been used in this study. The annual and seasonal wind speed trends are analyzed using linear and Mann-Kendall statistical methods. The annual energy yield, and net capacity factor are obtained for the chosen wind turbine with 2 Mega Watt rated power. As per the linear trend analysis, Chennai and Kanchipuram possess a significantly decreasing trend, while Nagercoil, Thoothukudi, and Tirunelveli show an increasing trend. Mann-Kendall trend analysis shows that cities located in the southern peninsula and in the vicinity of the coastal regions have significant potential for wind energy development. Moreover, a majority of the cities show an increasing trend in the autumn season due to the influence of the retreating monsoons which is accompanied with heavy winds. The mean wind follows an oscillating pattern throughout the year at all the locations. Based on the net annual energy output, Nagercoil, Thoothukudi and Nagapattinam are found to be the most suitable locations for wind power deployment in Tamil Nadu, followed by Cuddalore, Kumbakonam, Thanjavur and Tirunelveli.

scholarly journals A Techno-Economic Model for Wind Energy Costs Analysis for Low Wind Speed Areas

Processes ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1463 ◽  
Author(s):  
Kehinde A. Adeyeye ◽  
Nelson Ijumba ◽  
Jonathan S. Colton
Keyword(s):  
Renewable Energy ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Economic Model ◽  
African Continent ◽  
Financial Return ◽  
Levelized Cost Of Electricity ◽  
Low Wind Speed ◽  
Ferris Wheel

The global population is moving away from fossil fuel technologies due to their many disadvantages, such as air pollution, greenhouse gases emission, global warming, acid rain, health problems, and high costs. These disadvantages make fossil fuels unsustainable. As a result, renewable energy is becoming more attractive due to its steadily decreasing costs. Harnessing renewable energy promises to meet the present energy demands of the African continent. The enormous renewable energy potential available across the African continent remains largely untapped, especially for wind energy. However, marginal and fair wind speeds and power densities characterize African wind energy resulting in low and unsustainable power in many areas. This research develops a techno-economic model for wind energy cost analysis for a novel, Ferris wheel-based wind turbine. The model is used to techno-economically analyze the siting of wind turbine sites in low wind speed areas on the African continent. The wind turbine’s technical performance is characterized by calculating the annual energy production and the capacity factor using the wind Weibull probability distribution of the cities and theoretical power curve of the wind turbine. Its economic performance is evaluated using annualized financial return on investment, simple payback period, and levelized cost of electricity. The techno-economic model is validated for 21 African cities and shows that the Ferris wheel-based design is very competitive with four current, commercial wind turbines, as well as with other sources of energy. Hence, the new wind turbine may help provide the economical, clean, renewable energy that Africa needs.

Wind characteristics and wind energy assessment in the Barents Sea based on ERA-Interim reanalysis

2018 ◽  
Vol 47 (4) ◽  
pp. 415-428
Author(s):  
Chenglin Duan ◽  
Zhifeng Wang ◽  
Sheng Dong ◽  
Liao Zhenkun
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Wind Energy ◽  
Wind Power ◽  
Barents Sea ◽  
Energy Output ◽  
Free Zone ◽  
The Barents Sea ◽  
Pearson Type ◽  
Wind Characteristics

Abstract The basic analysis of long-term wind characteristics and wind energy resources in the Barents Sea was carried out from 1996 to 2015 based on the ERA-Interim reanalysis dataset from ECMWF. In recent years, it has been possible to exploit the wind power resources in the Barents Sea at the hub height due to the sea ice cover retreat in the northeast direction. Based on the NSDIC monthly sea ice concentration data, the entire Barents Sea has been partitioned into the ice-free zone and the ice zone. Spatial and temporal distributions of the mean monthly and annual wind speed and wind power density are presented in both zones. Seven points were selected at different locations in the ice-free zone so as to obtain and study the wind roses, the interannual wind power variation and the annual average net electric energy output. For extreme wind speed parameters, the Pearson type III distribution provides better fitness of annual speed extrema and the Gumbel distribution performs well with higher speeds at longer return periods.

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