Increase Power Efficientand Reliability of Electrosupply of Consumers of Low Power

GIS Business ◽  
2019 ◽  
Vol 14 (4) ◽  
pp. 42-52
Author(s):  
Sadullayev Nasillo Nematovich ◽  
Safarov Alisher Bekmurodovich ◽  
Nematov Shuhrat Nasilloyevich ◽  
Mamedov Rasul Akif- Ogli
Keyword(s):  
Wind Speed ◽  
Probability Distribution ◽  
Low Power ◽  
Electric Power ◽  
Energy Sources ◽  
Wind Flow ◽  
Wind Rose ◽  
Energy Potential ◽  
Wind Power Installation ◽  
Wind Energy Potential

This article assesses the wind speed data and wind energy potential in the Bukhara region of Uzbekistan. In article it is stated a principle construction "hybrid" a source of the electric power consisting from wind power installation with mechanical store of energy, the solar panel with аккумулятор in common working with an electric network. The speed and direction of the wind measured at a height of 10 m were analyzed by the Weibull probability distribution functionTo determine the direction of wind flow (wind rose), a graph in Matlab environment was constructed. The method of an estimation energy of efficiency of the objects eating from several energy sources is offered. It is proved efficiency of application of such source of the electric power low power consumers

scholarly journals Wind Data Analysis and Wind Flow Simulation Over Large Areas

2014 ◽  
Vol 10 (1) ◽  
pp. 38-45
Author(s):  
Angel Terziev ◽  
Ivan Antonov ◽  
Rositsa Velichkova
Keyword(s):  
Renewable Energy ◽  
Wind Energy ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Wind Flow ◽  
Energy Potential ◽  
Wind Potential ◽  
Wind Energy Potential ◽  
The Impact

Abstract Increasing the share of renewable energy sources is one of the core policies of the European Union. This is because of the fact that this energy is essential in reducing the greenhouse gas emissions and securing energy supplies. Currently, the share of wind energy from all renewable energy sources is relatively low. The choice of location for a certain wind farm installation strongly depends on the wind potential. Therefore the accurate assessment of wind potential is extremely important. In the present paper an analysis is made on the impact of significant possible parameters on the determination of wind energy potential for relatively large areas. In the analysis the type of measurements (short- and long-term on-site measurements), the type of instrumentation and the terrain roughness factor are considered. The study on the impact of turbulence on the wind flow distribution over complex terrain is presented, and it is based on the real on-site data collected by the meteorological tall towers installed in the northern part of Bulgaria. By means of CFD based software a wind map is developed for relatively large areas. Different turbulent models in numerical calculations were tested and recommendations for the usage of the specific models in flows modeling over complex terrains are presented. The role of each parameter in wind map development is made. Different approaches for determination of wind energy potential based on the preliminary developed wind map are presented.

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.

scholarly journals Wind Power potential in Kigali and Western provinces of Rwanda

2015 ◽  
Vol 2 (1) ◽  
pp. 25-36
Author(s):  
Otieno Fredrick Onyango ◽  
Sibomana Gaston ◽  
Elie Kabende ◽  
Felix Nkunda ◽  
Jared Hera Ndeda
Keyword(s):  
Wind Speed ◽  
Probability Density ◽  
Wind Power ◽  
Wind Direction ◽  
Small Scale ◽  
Energy Potential ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Energy Potential ◽  
Low Wind Speeds

Wind speed and wind direction are the most important characteristics for assessing wind energy potential of a location using suitable probability density functions. In this investigation, a hybrid-Weibull probability density function was used to analyze data from Kigali, Gisenyi, and Kamembe stations. Kigali is located in the Eastern side of Rwanda while Gisenyi and Kamembe are to the West. On-site hourly wind speed and wind direction data for the year 2007 were analyzed using Matlab programmes. The annual mean wind speed for Kigali, Gisenyi, and Kamembe sites were determined as 2.36m/s, 2.95m/s and 2.97m/s respectively, while corresponding dominant wind directions for the stations were ,  and  respectively. The annual wind power density of Kigali was found to be  while the power densities for Gisenyi and Kamembe were determined as and . It is clear, the investigated regions are dominated by low wind speeds thus are suitable for small-scale wind power generation especially at Kamembe site.

Assessment of wind energy potential and characteristics in Qatar for clean electricity generation

2021 ◽  
pp. 0309524X2110438
Author(s):  
Carlos Méndez ◽  
Yusuf Bicer
Keyword(s):  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Rose ◽  
Energy Potential ◽  
Wind Power Density ◽  
Wind Speeds ◽  
Wind Energy Potential

The present study analyzes the wind energy potential of Qatar, by generating a wind atlas and a Wind Power Density map for the entire country based on ERA-5 data with over 41 years of measurements. Moreover, the wind speeds’ frequency and direction are analyzed using wind recurrence, Weibull, and wind rose plots. Furthermore, the best location to install a wind farm is selected. The results indicate that, at 100 m height, the mean wind speed fluctuates between 5.6054 and 6.5257 m/s. Similarly, the Wind Power Density results reflect values between 149.46 and 335.06 W/m2. Furthermore, a wind farm located in the selected location can generate about 59.7437, 90.4414, and 113.5075 GWh/y electricity by employing Gamesa G97/2000, GE Energy 2.75-120, and Senvion 3.4M140 wind turbines, respectively. Also, these wind farms can save approximately 22,110.80, 17,617.63, and 11,637.84 tons of CO2 emissions annually.

Wind Energy Potential in Nine Coastal Sites in Malaysia

2013 ◽  
Vol 1 (1) ◽  
pp. 10-15
Author(s):  
Kamaruzzaman Sopian ◽  
Tamer Khatib
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Data Bank ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Speed Distribution ◽  
Average Wind ◽  
Wind Speed Distribution ◽  
Wind Energy Potential ◽  
Swept Area

 In this paper, the wind energy potential in Malaysia is examined by analyzing hourly wind speed data for nine coastal sites namely Bintulu, Kota Kinabalu, Kuala Terengganu, Kuching, Kudat, Mersing, Sandakan, Tawau and Pulau Langkawi. The monthly averages of wind speed and wind energy are calculated. Moreover, the wind speed distribution histogram is constructed for these sites. The results showed that the average wind speed for these sites is in the range of (1.8-2.9) m/s while the annual energy of the wind hitting a wind turbine with a 1 m2 swept area is in the range of (15.4-25.2) kWh/m2.annum. This paper provides a data bank for wind energy for Malaysia.

scholarly journals Assessment of wind energy potential across varying topographical features of Tamil Nadu, India

2019 ◽  
Vol 38 (1) ◽  
pp. 175-200 ◽  
Author(s):  
Shafiqur Rehman ◽  
Narayanan Natarajan ◽  
Mangottiri Vasudevan ◽  
Luai M Alhems
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Tamil Nadu ◽  
High Energy ◽  
Energy Potential ◽  
Annual Average ◽  
Wind Power Density ◽  
Wind Energy Potential

Wind energy is one of the abundant, cheap and fast-growing renewable energy sources whose intensive extraction potential is still in immature stage in India. This study aims at the determination and evaluation of wind energy potential of three cities located at different elevations in the state of Tamil Nadu, India. The historical records of wind speed, direction, temperature and pressure were collected for three South Indian cities, namely Chennai, Erode and Coimbatore over a period of 38 years (1980-2017). The mean wind power density was observed to be highest at Chennai (129 W/m2) and lowest at Erode (76 W/m2) and the corresponding mean energy content was highest for Chennai (1129 kWh/m2/year) and lowest at Erode (666 kWh/m2/year). Considering the events of high energy-carrying winds at Chennai, Erode and Coimbatore, maximum wind power density were estimated to be 185 W/m2, 190 W/m2 and 234 W/m2, respectively. The annual average net energy yield and annual average net capacity factor were selected as the representative parameters for expressing strategic wind energy potential at geographically distinct locations having significant variation in wind speed distribution. Based on the analysis, Chennai is found to be the most suitable site for wind energy production followed by Coimbatore and Erode.

scholarly journals An Assessment of Wind Energy Potential for the Three Topographic Regions of Eritrea

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1846 ◽  
Author(s):  
Teklebrhan Negash ◽  
Erik Möllerström ◽  
Fredric Ottermo
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Coastal Region ◽  
Energy Potential ◽  
Wind Power Density ◽  
Prevailing Wind Direction ◽  
Central Highland ◽  
Wind Energy Potential

This paper presents the wind energy potential and wind characteristics for 25 wind sites in Eritrea, based on wind data from the years 2000–2005. The studied sites are distributed all over Eritrea, but can roughly be divided into three regions: coastal region, western lowlands, and central highlands. The coastal region sites have the highest potential for wind power. An uncertainty, due to extrapolating the wind speed from the 10-m measurements, should be noted. The year to year variations are typically small and, for the sites deemed as suitable for wind power, the seasonal variations are most prominent in the coastal region with a peak during the period November–March. Moreover, Weibull parameters, prevailing wind direction, and wind power density recalculated for 100 m above ground are presented for all 25 sites. Comparing the results to values from the web-based, large-scale dataset, the Global Wind Atlas (GWA), both mean wind speed and wind power density are typically higher for the measurements. The difference is especially large for the more complex-terrain central highland sites where GWA results are also likely to be more uncertain. The result of this study can be used to make preliminary assessments on possible power production potential at the given sites.

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