scholarly journals Evaluation of Wind Potential for the Generation of Electricity in Aliero, Kebbi State

2020 ◽  
pp. 1-7
Author(s):  
A. A. Yahaya ◽  
I. M. Bello ◽  
N. Mudassir ◽  
I. Mohammed ◽  
M. I. Mukhtar
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Power ◽  
Power Density ◽  
Horizontal Wind ◽  
Average Wind Speed ◽  
Wind Power Density ◽  
North East ◽  
Average Wind ◽  
Wind Potential

One of the major developments in the technology today is the wind turbine that generates electricity and feed it directly to the grid which is used in many part of the world. The main purpose of this work is to determine the wind potential for electricity generation in Aliero, Kebbi state. Five years Data (2014-2018) was collected from the metrological weather station (Campell Scientific Model), the equipment installed at Kebbi State University of Science And Technology Aliero The data was converted to monthly and annual averages, and compared with the threshold average wind speed values that can only generate electricity in both vertical and horizontal wind turbines. The highest average wind speed 2.81 m/s was obtained in the month of January and the minimum average wind speed of 1.20 m/s in the month of October. Mean annual wind speed measured in the study area shows that there has been an increase in the wind speed from 2014 which peaked in 2015 and followed by sudden decrease to a minimum seasonal value in the year 2016. The highest wind direction is obtained from the North North-East (NNE) direction. From the results of wind power density it shows that we have highest wind power density in month of January and December with  0.8635 w/ m2 and 0.8295 w/ m2 respectively, while lowest wind power density in the month of October and September with 0.6780 w/ m2 and 0.6575 w/ m2  respectively. Result of the type Wind Turbine to be selected in the study area shows that the site is not viable for power generation using a horizontal wind turbine but the vertical wind turbine will be suitable for the generation of electricity.

scholarly journals Wind Farming Feasibility Assessment in 16 Locations of Nepal

2020 ◽  
Vol 15 (3) ◽  
pp. 205-215
Author(s):  
Raju Laudari ◽  
Bal Krishna Sapkota ◽  
Kamal Banskota
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Power Density ◽  
Wind Rose ◽  
Average Wind Speed ◽  
Wind Power Density ◽  
Feasibility Assessment ◽  
Average Wind ◽  
Acceptance Range ◽  
Study Sites

The paper assesses the feasibility of wind farming at the 16 sites scattered in different ecological regions of Nepal. The wind speed, the hourly and seasonal variation of wind, the wind-rose, the wind turbulence rate, the wind power density, the Weibull probability distribution and the frequency of the wind speed above cut in speed were computed. The average wind speed at all the sites was found to be higher during the dry season from March to May. The wind speed of the modern turbine for power generation at eight sites was found to be above cut-in speed. However, the wind power density was found to be good only at the two sites and fairly good at the six sites. More than 50 % time of a year at these eight sites had over 3.5 m/s wind speed. However, the turbulence rate at all the studied sites was found to be above the acceptance range of 25 %. Among the study sites, Kagbeni, Thini, Jumla, Ramechhap, Vorleni, Patan west, Hansapur and Baddanda were found to be technically feasible sites for wind energy generation in Nepal.

scholarly journals Wind potential estimation and proposed energy production in Southern Punjab using Weibull probability density function and surface measured data

2020 ◽  
pp. 014459872092074 ◽  
Author(s):  
Muhammad Sumair ◽  
Tauseef Aized ◽  
Syed Asad Raza Gardezi ◽  
Syed Ubaid Ur Rehman ◽  
Syed Muhammad Sohail Rehman
Keyword(s):  
Wind Speed ◽  
Energy Density ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Energy Production ◽  
Economic Assessment ◽  
Weibull Model ◽  
Wind Power Density ◽  
Wind Potential

Current work focusses on the wind potential assessment in South Punjab. Eleven locations from South Punjab have been analyzed using two-parameter Weibull model (with Energy Pattern Factor Method to estimate Weibull parameters) and five years (2014–2018) hourly wind data measured at 50 m height and collected from Pakistan Meteorological Department. Techno-economic analysis of energy production using six different turbine models was carried out with the purpose of presenting a clear picture about the importance of turbine selection at particular location. The analysis showed that Rahim Yar Khan carries the highest wind speed, highest wind power density, and wind energy density with values 4.40 ms−1, 77.2 W/m2 and 677.76 kWh/m2/year, respectively. On the other extreme, Bahawalnagar observes the least wind speed i.e. 3.60 ms−1 while Layyah observes the minimum wind power density and wind energy density as 38.96 W/m2 and 352.24 kWh/m2/year, respectively. According to National Renewable Energy Laboratory standards, wind potential ranging from 0 to 200 W/m2 is considered poor. Economic assessment was carried out to find feasibility of the location for energy harvesting. Finally, Polar diagrams drawn to show the optimum wind blowing directions shows that optimum wind direction in the region is southwest.

scholarly journals The Investigation of Wind Energy Potential in Order to Estimate Power Plants in Baladeh Mazandaran, Iran

2012 ◽  
pp. 29-33
Author(s):  
S. Asghar Gholamian ◽  
S. Bagher Soltani ◽  
R. Ilka
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Power Plants ◽  
Weather Station ◽  
Energy Potential ◽  
Wind Power Density ◽  
Synoptic Weather ◽  
Wind Potential

First step for achieving wind energy is to locate points with appropriate wind power density in a country. Wind data which are recorded in a synoptic weather station, are the best way to study the wind potential of an area. In this paper wind speed period of Baladeh synoptic weather station is studied, since it has the maximum average of wind speed among 15 stations of the MAZANDARAN Province. Weibull factors k and c are calculated for 40 months from September 2006 to December 2009 and wind power density is determined based on these data. The total average of factors k and c for a height for 50 m are 1.442 m/s and 5.1256 respectively. By using the average of factors, wind power density in 50 m height will be 147.40 watt/m2 which is categorized as weak potential in wind class. However by monthly investigation it is shown that with a 50 m wind, this station can be put in medium class in hot months of the year.

scholarly journals Assessment of Wind Energy Potential In Zwara, Libya

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Alhassan A. Teyabeen ◽  
Fathi R. Akkari ◽  
Ali E. Jwaid ◽  
Ashraf Zaghwan ◽  
Rehab Abodelah
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Ground Level ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Wind Power Density ◽  
Wind Energy Potential ◽  
Wind Resource

To assess the wind energy potential at any site, the wind power density should be estimated; it evaluates the wind resource and indicates the amount of available wind energy. The purpose of this study is to estimate the monthly and annual wind power density based on the Weibull distribution using wind speed data collected in Zwara, Libya during 2007. The wind date are measured at the three hub heights of 10m, 30m, and 50m above ground level, and recorded every 10 minutes. The analysis showed that the annual average wind speed are 4.51, 5.86, 6.26 m/s for the respective mentioned heights. The average annual wind power densities at the mentioned heights were 113.71, 204.19, 243.48 , respectively.

A Study of Estimation of Wind Potential and Prediction of Grid-Connected Wind Power Development in Vietnam

2020 ◽  
Vol 11 (2) ◽  
pp. 27-37
Author(s):  
Co Xuan Hoang ◽  
Linh Thi Hai Dang ◽  
Da Van Ta ◽  
Cuong Manh Dinh ◽  
Chinh Van Kim ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Power Plants ◽  
Wind Farms ◽  
Ground Level ◽  
Correlation Equation ◽  
Electricity Production ◽  
Average Wind Speed ◽  
Average Wind ◽  
Wind Potential

The construction of grid-connected wind power plants has increased sharply in Vietnam due to the rapid rise of energy demands. Previous studies of wind energy have shown that the wind potential of Vietnam compared to other countries of Southeast Asia and examined wind speed levels of each region of Vietnam. In this study, the annual electricity production (AEP), which is an important factor of project's cost and benefit calculation, was calculated for 13 study areas. A correlation equation between AEP and the average wind speed at 60m above ground level was also developed to estimate AEP where there exists only data of the annual average wind speed. Moreover, other resources of the development of grid-connected wind power were discussed in this research such as the Vietnamese supporting mechanism, international co-operation, turbine technology development, etc. The article then predicts the trend, and proposes some recommendations of developing grid-connected wind farms in Vietnam.

scholarly journals Contribution of Cartography to the Optimization of the Evaluation of Wind Energy Potential in the Republic of Cameroon: Case of Bitchoua Highlands

2021 ◽  
pp. 53-66
Author(s):  
VadelTsopgni Eneckdem ◽  
Rodrigue Aimé Feumba ◽  
Odovie Tsomo ◽  
Jean Roger Bogning
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Power Density ◽  
Average Power ◽  
Operating Conditions ◽  
In Situ Observation ◽  
Average Wind Speed ◽  
Average Wind ◽  
Average Maximum ◽  
Wind Potential

This study deals with a model combining cartography with mathematical simulation for the optimal evaluation of wind potential in the context of the absence of networks of in-situ observation stations. It is based on both geographic Information Systems (GIS), climate data from NASA Surface Meteorology and Solar Energy (SSE) from 1985 to 2018, and field survey data from 2018.The NASA-SSE data, made it possible to obtain information on the direction of the winds, to determine parameters of distribution of wind speed frequencies (by the Weibull method).Then, we proceeded to the processing and numerical simulation of the data to provide predictions of the electrical energy that could be generated. By mobilizing GIS, the study proposes a decisional mapping allowing the planning and realization of wind energy projects in the studied area. It appears from the work carried out in the field that with an average wind speed of 2.56m / s (at 50 m from the ground) the winds of Bitchoua have an average power density estimated at 1612.64 W. Under current operating conditions defined by the Betz limit, it would be possible to recover from the local wind, thanks to a 50 m diameter wind turbine, an electrical power of approximately 956.87 W / s, for a maximum average of 974.17 W / s. The spatial representation of this potential presents the Center and North-East of Bitchoua as the most suitable sectors for the installation of wind turbines in the locality. Indeed, with an average wind speed of 2.8m / s, the area has an average wind power density evaluated at 13.45 W, for an available power of 4221.53 W. Under current conditions of exploitability, the recoverable potential in this part would be about 1251.79 W / s, for 1275.07W / s on average maximum (well above the local average).

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.

scholarly journals Remaining Useful Life Estimation of Wind Turbine Blades under Variable Wind Speed Conditions Using Particle Filters

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Bhavana Valeti ◽  
Shamim N. Pakzad
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Turbine Blades ◽  
Remaining Useful Life ◽  
Structural Components ◽  
Wind Turbine Blades ◽  
Average Wind Speed ◽  
Average Wind ◽  
Useful Life ◽  
Variable Wind

Rotor blades are the most complex structural components in a wind turbine and are subjected to continuous cyclic loads of wind and self-weight variation. The structural maintenance operations in wind farms are moving towards condition based maintenance (CBM) to avoid premature failures. For this, damage prognosis with remaining useful life (RUL) estimation in wind turbine blades is necessary. Wind speed variation plays an important role influencing the loading and consequently the RUL of the structural components. This study investigates the effect of variable wind speed between the cutin and cut-out speeds of a typical wind farm on the RUL of a damage detected wind turbine blade as opposed to average wind speed assumption. RUL of wind turbine blades are estimated for different initial crack sizes using particle filtering method which forecasts the evolution of fatigue crack addressing the non-linearity and uncertainty in crack propagation. The stresses on a numerically simulated life size onshore wind turbine blade subjected to the above wind speed loading cases are used in computing the crack propagation observation data for particle filters. The effects of variable wind speed on the damage propagation rates and RUL in comparison to those at an average wind speed condition are studied and discussed.

scholarly journals The super-turbine wind power conversion paradox: using machine learning to reduce errors caused by Jensen's inequality

2019 ◽  
Vol 4 (2) ◽  
pp. 343-353 ◽  
Author(s):  
Tyler C. McCandless ◽  
Sue Ellen Haupt
Keyword(s):  
Machine Learning ◽  
Standard Deviation ◽  
Wind Speed ◽  
Wind Power ◽  
Power Conversion ◽  
Jensen’S Inequality ◽  
Jensen's Inequality ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Average Wind

Abstract. Wind power is a variable generation resource and therefore requires accurate forecasts to enable integration into the electric grid. Generally, the wind speed is forecast for a wind plant and the forecasted wind speed is converted to power to provide an estimate of the expected generating capacity of the plant. The average wind speed forecast for the plant is a function of the underlying meteorological phenomena being predicted; however, the wind speed for each turbine at the farm is also a function of the local terrain and the array orientation. Conversion algorithms that assume an average wind speed for the plant, i.e., the super-turbine power conversion, assume that the effects of the local terrain and array orientation are insignificant in producing variability in the wind speeds across the turbines at the farm. Here, we quantify the differences in converting wind speed to power at the turbine level compared with a super-turbine power conversion for a hypothetical wind farm of 100 2 MW turbines as well as from empirical data. The simulations with simulated turbines show a maximum difference of approximately 3 % at 11 m s−1 with a 1 m s−1 standard deviation of wind speeds and 8 % at 11 m s−1 with a 2 m s−1 standard deviation of wind speeds as a consequence of Jensen's inequality. The empirical analysis shows similar results with mean differences between converted wind speed to power and measured power of approximately 68 kW per 2 MW turbine. However, using a random forest machine learning method to convert to power reduces the error in the wind speed to power conversion when given the predictors that quantify the differences due to Jensen's inequality. These significant differences can lead to wind power forecasters overestimating the wind generation when utilizing a super-turbine power conversion for high wind speeds, and indicate that power conversion is more accurately done at the turbine level if no other compensatory mechanism is used to account for Jensen's inequality.

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.

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