Log in

Relevant bibliographies by topics / Analysis of wind potential / Journal articles

Journal articles on the topic 'Analysis of wind potential'

To see the other types of publications on this topic, follow the link: Analysis of wind potential.

Author: Grafiati

Published: 11 March 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Analysis of wind potential.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Mohammed, Daoudi, Ait Sidi Mou Abdelaziz, Elkhomri Mohammed, and Elkhouzai Elmostapha. "Analysis of wind speed data and wind energy potential using Weibull distribution in Zagora, Morocco." International Journal of Renewable Energy Development 8, no. 3 (October 15, 2019): 267–73. http://dx.doi.org/10.14710/ijred.8.3.267-273.

Full text

Abstract:

This paper presents the wind energy potential at 10 m during a period of 09 years (2009-2017) in the province of Zagora using the Weibull distribution method. Extrapolation of the 10 m data, using the power Law, has been used to determine the wind data at heights of 30 m; 50 m and 70 m. The objective is to evaluate the most important characteristics of wind energy in the studied site . The statistical attitudes permit us to estimate the mean wind speed, the wind speed distribution function and the mean wind power density in the site at the height of 30 m; 50 m and 70 m. From the primary evaluation indicate that the annual energy output and capacity factor increases with increasing the wind speed, it can obtain about 2.62 GWh/year, that is acceptable quantity for the wind energy. ©2019. CBIORE-IJRED. All rights reserved

APA, Harvard, Vancouver, ISO, and other styles

2

Rivera G., Mario E. "An analysis of Guatemalan wind potential." Solar & Wind Technology 4, no. 3 (January 1987): 331–36. http://dx.doi.org/10.1016/0741-983x(87)90065-8.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Ciobanu, Daniela, Radu Saulescu, Codruta Jaliu, and Oliver Climescu. "Wind Potential Analysis in Brasov Built Environment." Applied Mechanics and Materials 659 (October 2014): 337–42. http://dx.doi.org/10.4028/www.scientific.net/amm.659.337.

Full text

Abstract:

Implementing renewables in the built environment represents a must, considering the target of Nearly Zero Energy Buildings set by the European legal frame, starting with 2020. One specific feature of the built environment is that it additionally imposes constraints, and can distort the renewable energy potential, particularly the wind energy. Therefore, the development of optimized, efficient small wind turbines requires on-site monitoring and, further on, models developed/adjusted according to these. Thus, the main purpose of this study is the analysis of the available wind potential in the built environment – particularly in the Colina Campus of the Transilvania University, in order to implement small wind energy conversion systems. Wind data are collected during one year (2013) from the meteorological station from Brasov - Ghimbav (located 8 km far from Brasov), and from a second weather station, which is mounted on the rooftop of the university building in Brasov city (University hill). The results indicate that the area has a promising wind potential for the implementation in this built environment of small-sized wind turbines, which can start operating from 0.8 m/s and producing electricity from min. 1.8 m/s.

APA, Harvard, Vancouver, ISO, and other styles

4

Kwon, Soon-Duck. "Uncertainty analysis of wind energy potential assessment." Applied Energy 87, no. 3 (March 2010): 856–65. http://dx.doi.org/10.1016/j.apenergy.2009.08.038.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Soe, Paing Hein, and Thein Min Htike. "WIND CHARACTERISTICS ANALYSIS IN FOUR POTENTIAL TOWNSHIPS IN MYANMAR." ASEAN Engineering Journal 12, no. 1 (February 28, 2022): 119–29. http://dx.doi.org/10.11113/aej.v12.17225.

Full text

Abstract:

Myanmar has set renewable energy aspirations in the energy mix of the country to meet growing energy demand and to increase clean access to electricity as indicated in Myanmar’s Intended Nationally Determined Contribution. Among renewable energy resources, solar and wind energy are expected to contribute to 9% of total energy mix. Although there have been initiatives on the implementation of solar photovoltaic in Myanmar, implementation of wind energy has not been reported. Few studies on wind energy in Myanmar focused on resource assessment investigating the spatial variation of wind speed and power density. Little has been studied on the seasonal nature and persistence of wind in Myanmar from the perspective of energy generation. This study aims at generating wind speed and power density maps of Myanmar using most recent wind data from 2010 to 2017 to identify potential townships with favourable wind conditions. Prominent wind direction, seasonal variations and wind speed persistence were analyzed for four townships with favourable wind conditions. Weibull parameters suggest that frequency of wind is also favourable for wind energy generation. Hence, this study has identified Chauk, Kyaukpadaung, Meiktila and Natogyi townships as potential regions for wind energy development with estimated power producing time of 53.17% and 65.91% of a year at average wind speed of 4 m/s above. This study serves as a basis for further resource assessment for micrositing of wind turbines to identify feasible sites for wind energy generation in Myanmar.

APA, Harvard, Vancouver, ISO, and other styles

6

Umaid Ali, Syed, Rafilullah Khan, and Athar Masood Syed. "Analysis of Wind Energy Potential and Optimum Wind Blade Design for Jamshoro Wind Corridor." Mehran University Research Journal of Engineering and Technology 36, no. 4 (October 1, 2017): 781–88. http://dx.doi.org/10.22581/muet1982.1704.03.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Shamshad, A., M. A. Bawadi, W. M. A. Wan Hussin, and A. M. Taksiah. "Analysis of prevailing wind speed and direction for wind energy potential at windy site in Malaysia." International Journal of Ecodynamics 2, no. 1 (August 9, 2007): 10–23. http://dx.doi.org/10.2495/eco-v2-n1-10-23.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Ahmad, Aftab, Fareed Husssain Mangi, Yasir Fazlani, Athar Chachar, and Kashif Khan. "Wind Potential Assessment Analysis of Jhampir, District Thatta Sindh, Pakistan." July 2019 38, no. 3 (July 1, 2019): 571–80. http://dx.doi.org/10.22581/muet1982.1903.04.

Full text

Abstract:

Wind potential analysis is analyzing how much wind energy is available in particular region. It is most important step because the economics of project depends on the site wind resources. Wind plant depends on the variation of long-term mean wind speed and other characteristics which vary from a distance to distance. This study discusses the wind speed characteristics and wind potential analysis using three years 2014-2016 wind data of Jhampir located in district Thatta, situated in the Southeast of Sindh province. The numerical Weibull distribution approach is used to estimate parameters. The correct estimation of wind parameters and class is essential before developing any wind project in the region. The data used in this study is measured at 80 m height. The region is classified as from class 1-7. The results show that monthly mean speed values lie between 4.79-10.96 m/s. The annual mean scale and shape parameters lie in the range of 7.42-7.59. The wind power density was found in a range of 303.31355.64. This study is related to the decision-making process on a significant wind project in Thatta or nearby region. The stable wind energy pattern is observed in the region for harnessing wind energy almost throughout the year. The Weibull probability density curves also indicate a trend of a boost in the chances of observing wind from 2014-2016.

APA, Harvard, Vancouver, ISO, and other styles

9

Rosen, Karen, Robert Van Buskirk, and Karina Garbesi. "WIND ENERGY POTENTIAL OF COASTAL ERITREA: AN ANALYSIS OF SPARSE WIND DATA." Solar Energy 66, no. 3 (June 1999): 201–13. http://dx.doi.org/10.1016/s0038-092x(99)00026-2.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Al Zohbi, Gaydaa, Patrick Hendrick, and Philippe Bouillard. "Wind characteristics and wind energy potential analysis in five sites in Lebanon." International Journal of Hydrogen Energy 40, no. 44 (November 2015): 15311–19. http://dx.doi.org/10.1016/j.ijhydene.2015.04.115.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Shu, Z. R., Q. S. Li, and P. W. Chan. "Statistical analysis of wind characteristics and wind energy potential in Hong Kong." Energy Conversion and Management 101 (September 2015): 644–57. http://dx.doi.org/10.1016/j.enconman.2015.05.070.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Onat, Nevzat, and Sedat Ersoz. "Analysis of wind climate and wind energy potential of regions in Turkey." Energy 36, no. 1 (January 2011): 148–56. http://dx.doi.org/10.1016/j.energy.2010.10.059.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Kose, Ramazan, M. Arif Ozgur, Oguzhan Erbas, and Abtullah Tugcu. "The analysis of wind data and wind energy potential in Kutahya, Turkey." Renewable and Sustainable Energy Reviews 8, no. 3 (June 2004): 277–88. http://dx.doi.org/10.1016/j.rser.2003.11.003.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Shih, David Ching-Fang. "Wind characterization and potential assessment using spectral analysis." Stochastic Environmental Research and Risk Assessment 22, no. 2 (March 6, 2007): 247–56. http://dx.doi.org/10.1007/s00477-007-0112-7.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Pourasl, Hamed H., and Vahid M. Khojastehnezhad. "Techno-economic analysis of wind energy potential in Kazakhstan." Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 235, no. 6 (March 16, 2021): 1563–76. http://dx.doi.org/10.1177/09576509211001598.

Full text

Abstract:

The use of renewable energy as a future energy source is attracting considerable research interest globally. In particular, there is a significant growth in wind energy utilization during the last few years. This present study through a detailed and systematic literature survey assesses the wind energy potential of Kazakhstan for the first time. Using the Weibull distribution function and hourly wind speed data, the annual power and energy density of the sites are calculated. For the 50 sites considered in this study and at a height of 10 m above the ground, the annual average wind speed, the power density, and energy production of Kazakhstan range from 0.94–5.15 m/s, 4.50–169.34 W/m2 and 39.56–1502.50 kWh/m2/yr, respectively. It was found that Fort Sevcenko, Atbasar, and Akmola are the three best locations for wind turbine installation with wind power densities of 169.34, 135.30, and 111.51 W/m2, respectively. Fort Sevcenko demonstrates the highest potential for wind energy harvesting with an energy density of 1483.46 kWh/m2/yr. For the 15 commercial wind turbines, it was observed that the annual energy production of the selected turbines ranges between 3.8 GWh/yr in Petropavlovsk to 15.4 GWh/yr in Fort Sevcenko among the top six locations. The lowest and highest capacity factors correspond to the same sites with the values of 29.21% and 58.66%, respectively. Overall, it is the intention of this study to constitute a database for the users and developers of wind power in Kazakhstan.

APA, Harvard, Vancouver, ISO, and other styles

16

Tafrikhatin, Asni, Hendi Purnata, Rafli Hafid Kusuma, Anggi Faisal Efendi, and Guffaro Mahfud. "Wind Speed Analysis Study for Wind Power Plant in Kebumen." Jurnal E-Komtek (Elektro-Komputer-Teknik) 5, no. 2 (December 29, 2021): 142–49. http://dx.doi.org/10.37339/e-komtek.v5i2.698.

Full text

Abstract:

Reserves of fossil energy sources are starting to run low, so the government has launched renewable energy sources. The National Energy Policy (KEN) targets Indonesia by 2025 to use renewable energy sources of 23% of its energy needs. Because of this, the government has started opening places that have the potential for generating renewable energy, especially the areas where PLN electricity cannot reach, withincluding the southern coastal area of Kebumen.. The wind potential in this coastal area of Java Island meets the criteria for a Wind Power Plant. The purpose of this research was to analyze the wind potential in the southern coastal area of Kebumen. The specific purpose of this study was to determine the wind speed and the location and calculate the power generated by the wind in the southern coastal area of Kebumen to determine the potential of PLTB in Kebumen area. The stages of this research consisted of retrieval of secondary data, analysis using Excel, and power analysis using HOMER. Based on wind speed data from NASA, the southern coastal area of Kebumen is suitable for making PLTB, especially Buayan and Ayah, because the wind speed between 2016-2020 is 2.15 m/s. Then, the power produced annually in these places, based on the HOMER application, was 86.50 kWh/year.

APA, Harvard, Vancouver, ISO, and other styles

17

Terziev, Angel, Ivan Antonov, and Rositsa Velichkova. "Wind Data Analysis and Wind Flow Simulation Over Large Areas." Mathematical Modelling in Civil Engineering 10, no. 1 (March 1, 2014): 38–45. http://dx.doi.org/10.2478/mmce-2014-0005.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

18

Natarajan, Narayanan, S. Rehman, Nandhini Shiva, and M. Vasudevan. "Evaluation of wind energy potential of the state of Tamil Nadu, India based on trend analysis." FME Transactions 49, no. 1 (2021): 244–51. http://dx.doi.org/10.5937/fme2101244n.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

19

NASKAR, PRAVAT RABI. "Statistical analysis of wind characteristics and wind energy potential of Port Blair, India." MAUSAM 72, no. 2 (October 28, 2021): 443–56. http://dx.doi.org/10.54302/mausam.v72i2.615.

Full text

APA, Harvard, Vancouver, ISO, and other styles

20

Li, DHW, KL Cheung, WWH Chan, CCK Cheng, and TCH Wong. "An analysis of wind energy potential for micro wind turbine in Hong Kong." Building Services Engineering Research and Technology 35, no. 3 (June 19, 2013): 268–79. http://dx.doi.org/10.1177/0143624413486997.

Full text

APA, Harvard, Vancouver, ISO, and other styles

21

Evans, Laura E., Nives Dolšak, and Aseem Prakash. "Do windy areas have more wind turbines: An empirical analysis of wind installed capacity in Native tribal nations." PLOS ONE 17, no. 2 (February 25, 2022): e0261752. http://dx.doi.org/10.1371/journal.pone.0261752.

Full text

Abstract:

The decarbonization of the electricity sector is leading to a substantial increase in the demand for wind energy. Will tribal nations, which account for 7.8% of utility-scale wind capacity, benefit from this policy shift? To examine why tribal nations vary in translating wind energy potential into wind installed capacity, we have constructed an original dataset of the potential as well as the location of wind turbines across tribal nations. Our statistical analysis of 286 tribal nations suggests that wind energy potential is not associated with wind installed capacity. Instead, casino square footage, a proxy for tribal nation’s administrative capacity and business acumen, is associated with wind installed capacity. Political orientation plays a role as well: tribal nations are more likely to have wind installed capacity when they value tribal sovereignty. While tribes suffering from natural disasters do not install more wind turbines, those receiving federal grants for wind energy projects, and located in states that already have a substantial number of wind turbines, are more apt to have wind turbines. Surprisingly, tribes located in states with renewable portfolio standards do not show an association with installed wind turbines capacity.

APA, Harvard, Vancouver, ISO, and other styles

22

Brahmi, Nabiha, Sana Charfi, and Maher Chaabene. "Wind potential assessment for an efficient wind farm sizing." Wind Engineering 41, no. 6 (August 1, 2017): 369–82. http://dx.doi.org/10.1177/0309524x17721999.

Full text

Abstract:

The effectiveness of autonomous wind plants depends basically on the characterization, sizing, and environmental design and analysis of its renewable energy conversion system. This article presents an assessment on wind potential characterization to be used to compute the size of a wind farm turbine. Different methods are adopted to estimate parameters of the Weibull distribution. The modified maximum likelihood method is selected as the most accurate with reference to comparison between many approaches output results and measurements provided by the National Institute of Meteorology. Also, an artificial neural network–based algorithm is developed to optimize the MMLM parameters. The monthly wind potential distribution is consequently computed for Sfax, Tunisia. Obtained results are used to optimize the size calculation of wind turbine blades and battery capacity for a standalone wind farm. The proposed approach profitability is evaluated upon the lost produced energy.

APA, Harvard, Vancouver, ISO, and other styles

23

DUGGAL, Y. M., BHUKAN LAL, H. C. MEHRA, and R. BHARTI. "Wind power potential over Delhi." MAUSAM 42, no. 1 (February 28, 2022): 53–56. http://dx.doi.org/10.54302/mausam.v42i1.2833.

Full text

Abstract:

An attempt is made to investigate in the field of renewable source of wind energy available in nature by estimating the wind power potential over Delhi and it~ effective utilisation for windmills for different speed ranges. Frequency and wind speed fine spectral analysis indicates that windmills designed for upper light wind range. (6 to 8 km/hr) can be effectively put into operation during the daytime for about 8-12 hrs., the time depending upon the month and the range of the wind speed at which the windmill can be operated. The max power potential over Delhi varies from 720 watt hr/m2/day during the months of March to min. of 130 watt hr/m2/day in the month of November.

APA, Harvard, Vancouver, ISO, and other styles

24

Hennecke, David, and Carsten Croonenbroeck. "Spatial-Economic Potential Analysis of Wind Power Plants in Germany." Wind 1, no. 1 (November 22, 2021): 77–89. http://dx.doi.org/10.3390/wind1010005.

Full text

Abstract:

Before a new wind farm can be built, politics and regional planning must approve of the respective area as a suitable site. For this purpose, large-scale potential computations were carried out to identify suitable areas. The calculation of wind power plant potential usually focuses on capturing the highest energy potential. In Germany, due to an energy production reimbursement factor defined in the Renewable Energy Sources Act (“Erneuerbare-Energien-Gesetz”, EEG) in 2017, the influence of energy quantities on the power plant potential varies, economically and spatially. Therefore, in addition to the calculation of energy potentials, it was also necessary to perform a potential analysis in terms of economic efficiency. This allows, on the one hand, an economic review of the areas tendered by the regional planning and, on the other hand, a spatial-economic analysis that expands the parameters in the search for new areas. In this work, (a) potentials with regard to the levelized cost of electricity (LCOE) were calculated by the example of the electricity market in Germany, which were then (b) spatially and statistically processed on the level of the federal states.

APA, Harvard, Vancouver, ISO, and other styles

25

Standridge, Charles R., Daivd Zeitler, Aaron Clark, Tyson Spoolma, Erik Nordman, T. Arnold Boezaart, Jim Edmonson, et al. "Lake Michigan Wind Assessment Analysis, 2012 and 2013." International Journal of Renewable Energy Development 6, no. 1 (March 22, 2017): 19–27. http://dx.doi.org/10.14710/ijred.6.1.19-27.

Full text

Abstract:

A study was conducted to address the wind energy potential over Lake Michigan to support a commercial wind farm. Lake Michigan is an inland sea in the upper mid-western United States. A laser wind sensor mounted on a floating platform was located at the mid-lake plateau in 2012 and about 10.5 kilometers from the eastern shoreline near Muskegon Michigan in 2013. Range gate heights for the laser wind sensor were centered at 75, 90, 105, 125, 150, and 175 meters. Wind speed and direction were measured once each second and aggregated into 10 minute averages. The two sample t-test and the paired-t method were used to perform the analysis. Average wind speed stopped increasing between 105 m and 150 m depending on location. Thus, the collected data is inconsistent with the idea that average wind speed increases with height. This result implies that measuring wind speed at wind turbine hub height is essential as opposed to using the wind energy power law to project the wind speed from lower heights. Average speed at the mid-lake plateau is no more that 10% greater than at the location near Muskegon. Thus, it may be possible to harvest much of the available wind energy at a lower height and closer to the shoreline than previously thought. At both locations, the predominate wind direction is from the south-southwest. The ability of the laser wind sensor to measure wind speed appears to be affected by a lack of particulate matter at greater heights.Article History: Received June 15th 2016; Received in revised form January 16th 2017; Accepted February 2nd 2017 Available onlineHow to Cite This Article: Standridge, C., Zeitler, D., Clark, A., Spoelma, T., Nordman, E., Boezaart, T.A., Edmonson, J., Howe, G., Meadows, G., Cotel, A. and Marsik, F. (2017) Lake Michigan Wind Assessment Analysis, 2012 and 2013. Int. Journal of Renewable Energy Development, 6(1), 19-27.http://dx.doi.org/10.14710/ijred.6.1.19-27

APA, Harvard, Vancouver, ISO, and other styles

26

Sahebzadeh, Sadra, Hamid Montazeri, and Abdolrahim Rezaeiha. "Impact of wind direction on wind energy potential for building- integrated ducted wind turbines: a numerical analysis." Journal of Physics: Conference Series 2042, no. 1 (November 1, 2021): 012107. http://dx.doi.org/10.1088/1742-6596/2042/1/012107.

Full text

Abstract:

Abstract The aerodynamic performance of building-integrated ducted wind turbines depends on several parameters such as the duct geometry, variation in wind speed and direction (which are inherent characteristics of the urban wind). This study focuses on the impact of wind direction on wind energy potential of a previously optimized building-integrated duct geometry [1], embedded in a generic isolated high-rise building. The mean power density at the duct throat (where the turbine can be installed) is investigated in four wind directions of θ = 0°, 30°, 60° and 90°. High-fidelity steady RANS simulations, validated with experimental data, are used. The results show that the studied duct can increase the mean power density at its throat (i.e. rotor plane) up to 7.08 – 24.8 times that of the freestream flow at the same height for a wide range of -60° ⩽ 0 ⩽ 60°. The variation of wind energy potential in different wind directions is shown to be due to the increased size of the nozzle stagnation and separation regions for θ > 0° which limit the nozzle effective area and lower flowrate through the throat. Flow deviation from the duct central axis towards its walls further depletes the wind energy in friction.

APA, Harvard, Vancouver, ISO, and other styles

27

Nunumete, R. A. "ANALYSIS OF WIND POWER POTENTIAL IN AMBON ISLAND, INDONESIА." Alternative Energy and Ecology (ISJAEE), no. 1 (November 13, 2015): 26–32. http://dx.doi.org/10.15518/isjaee.2015.01.002.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Ahmed, A. "Analysis of Wind Energy Potential in North East Nigeria." Journal of Energy and Natural Resources 3, no. 4 (2014): 46. http://dx.doi.org/10.11648/j.jenr.20140304.11.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Mohamed El Yazidi, Abdelbari Redouane, Mohammed Benzirar, and Mimoun Zazoui. "Analysis of Wind Data and Assessment of Wind Energy Potential in Lamhiriz Village, Morocco." Applied Solar Energy 55, no. 6 (November 2019): 429–37. http://dx.doi.org/10.3103/s0003701x19060033.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Nzuka Mwanzia, Justus, David Wafula Wekesa, and Joseph Ngugi Kamau. "Analysis of Wind Resource Potential for Small-Scale Wind Turbine Performance in Kiseveni, Kenya." International Journal of High Energy Physics 6, no. 1 (2019): 17. http://dx.doi.org/10.11648/j.ijhep.20190601.13.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

Ucar, Aynur, and Figen Balo. "A Seasonal Analysis of Wind Turbine Characteristics and Wind Power Potential in Manisa, Turkey." International Journal of Green Energy 5, no. 6 (December 4, 2008): 466–79. http://dx.doi.org/10.1080/15435070802498101.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Nasyrova, E. V., N. F. Timerbayev, O. V. Leukhina, and I. Yu Mazarov. "Data analysis wind monitoring in the Republic of Tatarstan." Power engineering: research, equipment, technology 21, no. 6 (April 21, 2020): 39–50. http://dx.doi.org/10.30724/1998-9903-2019-21-6-39-50.

Full text

Abstract:

The paper presents the results of wind monitoring carried out in order to confirm the feasibility of building a wind farm in the Republic of Tatarstan. The task of wind monitoring is to determine and study the dynamics of the average annual wind regime and calculate the wind energy potential at promising sites for placing a wind power plant. On the given sites, after the annual cycle of meteorological parameters measurements, the average annual wind speeds, wind power, preferred directions, wind density, vertical profile of the wind flow and other data necessary for a detailed calculation of the wind power potential of the sites and the selection of specific models of wind generators and their arrangements for operation will be determined at these sites. An important component of the work performed is the development of methods for calculating wind potential at heights other than the heights of direct measurements.

APA, Harvard, Vancouver, ISO, and other styles

33

Talama, Fatonga, Saiyad S. Kutty, Ajal Kumar, MGM Khan, and M. Rafiuddin Ahmed. "Assessment of wind energy potential for Tuvalu with accurate estimation of Weibull parameters." Energy Exploration & Exploitation 38, no. 5 (July 21, 2020): 1742–73. http://dx.doi.org/10.1177/0144598720940874.

Full text

Abstract:

Wind resource assessments are carried out for two sites in Tuvalu: Funafuti and Nukufetau. The wind speeds at 34 and 20 m above ground level were recorded for approximately 12 months and analyzed. The averages of each site are computed as the overall, daily, monthly, annual, and seasonal averages. The overall average wind speeds for Funafuti and Nukufetau at 34 m above ground level were estimated to be 6.19 and 5.36 m/s, respectively. The turbulence intensities at the two sites were also analyzed. The turbulence intensity is also computed for windy and low-wind days. Wind shear analysis was carried out and correlated with temperature variation. Ten different methods: median and quartiles method, the empirical method of Lysen, the empirical method of Justus, the moments method, the least squares method, the maximum likelihood method, the modified maximum likelihood method, the energy pattern factor method, method of multi-objective moments, and the wind atlas analysis and application program method were used to find the Weibull parameters. From these methods, the best method is used to determine the wind power density for the site. The wind power density for Funafuti is 228.18 W/m2 and for Nukufetau is 145.1 W/m2. The site maps were digitized and with the WAsP software, five potential locations were selected for each site from the wind resource map. The annual energy production for the sites was computed using wind atlas analysis and application program to be 2921.34 and 1848.49 MWh. The payback periods of installing the turbines for each site are calculated by performing an economic analysis, which showed payback periods of between 3.13 and 4.21 years for Funafuti and between 4.83 to 6.72 years for Nukufetau.

APA, Harvard, Vancouver, ISO, and other styles

34

Lu, Lin, Hongxing Yang, and John Burnett. "Investigation on wind power potential on Hong Kong islands—an analysis of wind power and wind turbine characteristics." Renewable Energy 27, no. 1 (September 2002): 1–12. http://dx.doi.org/10.1016/s0960-1481(01)00164-1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Risch, Stanley, Rachel Maier, Junsong Du, Noah Pflugradt, Peter Stenzel, Leander Kotzur, and Detlef Stolten. "Potentials of Renewable Energy Sources in Germany and the Influence of Land Use Datasets." Energies 15, no. 15 (July 30, 2022): 5536. http://dx.doi.org/10.3390/en15155536.

Full text

Abstract:

Potential analyses identify possible locations for renewable energy installations, such as wind turbines and photovoltaic arrays. The results of previous potential studies for Germany, however, are not consistent due to different assumptions, methods, and datasets being used. For example, different land-use datasets are applied in the literature to identify suitable areas for technologies requiring open land. For the first time, commonly used datasets are compared regarding the area and position of identified features to analyze their impact on potential analyses. It is shown that the use of Corine Land Cover is not recommended as it leads to potential area overestimation in a typical wind potential analyses by a factor of 4.7 and 5.2 in comparison to Basis-DLM and Open Street Map, respectively. Furthermore, we develop scenarios for onshore wind, offshore wind, and open-field photovoltaic potential estimations based on land-eligibility analyses using the land-use datasets that were proven to be best by our pre-analysis. Moreover, we calculate the rooftop photovoltaic potential using 3D building data nationwide for the first time. The potentials have a high sensitivity towards exclusion conditions, which are also currently discussed in public. For example, if restrictive exclusions are chosen for the onshore wind analysis the necessary potential for climate neutrality cannot be met. The potential capacities and possible locations are published for all administrative levels in Germany in the freely accessible database (Tool for Renewable Energy Potentials—Database), for example, to be incorporated into energy system models.

APA, Harvard, Vancouver, ISO, and other styles

36

Ayodele, Temitope R., Adisa A. Jimoh, Josiah L. Munda, and John T. Agee. "Statistical analysis of wind speed and wind power potential of Port Elizabeth using Weibull parameters." Journal of Energy in Southern Africa 23, no. 2 (May 1, 2012): 30–38. http://dx.doi.org/10.17159/2413-3051/2012/v23i2a3160.

Full text

Abstract:

This paper analyses wind speed characteristics and wind power potential of Port Elizabeth using statistical Weibull parameters. A measured 5–minute time series average wind speed over a period of 5 years (2005 - 2009) was obtained from the South African Weather Service (SAWS). The results show that the shape parameter (k) ranges from 1.319 in April 2006 to 2.107 in November 2009, while the scale parameter (c) varies from 3.983m/s in May 2008 to 7.390 in November 2009.The average wind power density is highest during Spring (September–October), 256.505W/m2 and lowest during Autumn (April-May), 152.381W/m2. This paper is relevant to a decision-making process on significant investment in a wind power project.

APA, Harvard, Vancouver, ISO, and other styles

37

Adefarati, Temitope, and G. D. Obikoya. "Evaluation of Wind Resources Potential and Economic Analysis of Wind Power Generation in South Africa." International Journal of Engineering Research in Africa 44 (August 2019): 150–81. http://dx.doi.org/10.4028/www.scientific.net/jera.44.150.

Full text

Abstract:

The presence of adequate renewable energy resources and the rapid development of wind projects in South Africa have led to mapping out of the country’s wind capability. In view of this, the economic prospects of utilizing wind energy as a potential energy alternative in South Africa are examined and discussed from the perspectives of green energy strategies for sustainable energy development. This research work is designed to investigate the economic effects of using the wind turbine (WT) in ten locations in South Africa based on the grid planning and power sector reform. The HOMER application software is utilized in this study to assess the wind resources on provincial and national scales, along with estimating the annual energy generation of the selected locations. The wind energy potential of South Africa is analysed by utilizing the capacity factor (CF), wind penetration and mean output of the WT for various locations in South Africa. The results obtained from the study indicate that the selected sites fall within the range of Class 1V of IEC wind classifications with the annual average wind speed of 4.04 m/s for Pretoria and 6.39 m/s for Cape Town at 50m hub heights. The economic assessment of the WT for electric power generation is carried out by using some key performance indicators (KPIs) such as net energy purchased, energy sold, revenue, grid energy purchased, annual utility bill savings, net present cost (NPC) and cost of energy (COE). It is established from the study that Cape Town is the most suitable location for installation of the WT by utilizing the same load profile and system configuration. The output of this research work can be used by the renewable energy development agencies as inputs to harness the potential of wind resources for strategic planning of the power sector reform and industrial development.

APA, Harvard, Vancouver, ISO, and other styles

38

AlGhamdi, Saeed A., Ahmed M. Abdel-Latif, Ossama S. Abd El-Kawi, and Ossama B. Abouelatta. "Analysis of Wind Speed Data and Wind Energy Potential for Seven Selected Locations in KSA." Journal of Power and Energy Engineering 10, no. 04 (2022): 1–26. http://dx.doi.org/10.4236/jpee.2022.104001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Al-Salem, Khaled, and Waleed Al-Nassar. "Assessment of wind energy potential at Kuwaiti Islands by statistical analysis of wind speed data." E3S Web of Conferences 51 (2018): 01001. http://dx.doi.org/10.1051/e3scconf/20185101001.

Full text

Abstract:

Kuwait possesses a potential of renewable energy, such as solar and wind energy. Wind energy is an alternative clean energy source compared to fossil fuel, which pollute the lower layer of the atmosphere. In this study, statistical methods are used to analyze the wind speed data at Mubarak port (at Bubiyan Island), Failaka Island and Um-AlMaradim Island; which are located respectively in the north, mid and south of Kuwait territorial waters. Wind speed is the most important parameter in the design and study of wind energy conversion systems. The wind speed data were obtained from the Costal Information System Database (CIS) at Kuwait Institute for Scientific Research [1, 2 and 3]over a thirty seven years period, 1979 to 2015. In the present study, the wind energy potential of the locations was statistically analyzed based on wind speed data, over a period of thirty seven years. The probability distributions are derived from the wind data and their distributional parameters are identified. Two probability density functions are fitted to the probability distributions on a yearly basis. The wind energy potential of the locations was studied based on the Weibull and the Rayleigh models.

APA, Harvard, Vancouver, ISO, and other styles

40

Al-Salem, Khaled, and Waleed Al-Nassar. "Assessment of wind energy potential at Kuwaiti Islands by statistical analysis of wind speed data." E3S Web of Conferences 51 (2018): 01001. http://dx.doi.org/10.1051/e3sconf/20185101001.

Full text

Abstract:

Kuwait possesses a potential of renewable energy, such as solar and wind energy. Wind energy is an alternative clean energy source compared to fossil fuel, which pollute the lower layer of the atmosphere. In this study, statistical methods are used to analyze the wind speed data at Mubarak port (at Bubiyan Island), Failaka Island and Um-AlMaradim Island; which are located respectively in the north, mid and south of Kuwait territorial waters. Wind speed is the most important parameter in the design and study of wind energy conversion systems. The wind speed data were obtained from the Costal Information System Database (CIS) at Kuwait Institute for Scientific Research [1, 2 and 3]over a thirty seven years period, 1979 to 2015. In the present study, the wind energy potential of the locations was statistically analyzed based on wind speed data, over a period of thirty seven years. The probability distributions are derived from the wind data and their distributional parameters are identified. Two probability density functions are fitted to the probability distributions on a yearly basis. The wind energy potential of the locations was studied based on the Weibull and the Rayleigh models.

APA, Harvard, Vancouver, ISO, and other styles

41

Zhang, Jingyu, Mingjin Zhang, Yongle Li, Jingxi Qin, Kai Wei, and Lili Song. "Analysis of wind characteristics and wind energy potential in complex mountainous region in southwest China." Journal of Cleaner Production 274 (November 2020): 123036. http://dx.doi.org/10.1016/j.jclepro.2020.123036.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

Manomaiphiboon, Kasemsan, Carina P. Paton, Thayukorn Prabamroong, Nuttee Rajpreeja, Nosha Assareh, and Montana Siriwan. "Wind energy potential analysis for Thailand: Uncertainty from wind maps and sensitivity to turbine technology." International Journal of Green Energy 14, no. 6 (March 15, 2017): 528–39. http://dx.doi.org/10.1080/15435075.2017.1305963.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Cabello, M., and J. A. G. Orza. "Wind speed analysis in the province of Alicante, Spain. Potential for small-scale wind turbines." Renewable and Sustainable Energy Reviews 14, no. 9 (December 2010): 3185–91. http://dx.doi.org/10.1016/j.rser.2010.07.002.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Görmüş, Tahsin, Burak Aydoğan, and Berna Ayat. "Offshore wind power potential analysis for different wind turbines in the Mediterranean Region, 1959–2020." Energy Conversion and Management 274 (December 2022): 116470. http://dx.doi.org/10.1016/j.enconman.2022.116470.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Hussain, Mariam, and Seon Ki Park. "Systematic Analysis of Wind Resources for Eolic Potential in Bangladesh." Applied Sciences 11, no. 17 (August 27, 2021): 7924. http://dx.doi.org/10.3390/app11177924.

Full text

Abstract:

Energy consumption in Bangladesh increased for economic, industrial, and digitalization growth. Reductions in conventional sources such as natural gas (54%) and coal (5.6%) are calls to enhance renewable resources. This paper aims to investigate the atmospheric variables for potential wind zones and develop a statistical power-forecasting model. The study-site is Bangladesh, focusing on eight divisions across two regions. First, the southern zone includes Dhaka (Capital), Chittagong, Barishal, and Khulna. The northern regions are Rajshahi, Rangpur, Mymensingh, and Sylhet. This investigation illustrates wind (m/s) speeds at various heights (m) and analyzes the boundary layer height (BLH) from the European Center for Medium Range Weather Forecast reanalysis 5th generation (ERA5). The data is from a period of 40 years from 1979 to 2018, assessing with a climatic base of 20 years (1979 to 2000). The climatological analysis comprises trends, time series, anomalies, and linear correlations. The results for the wind speed (BLH) indicate that the weakest (lower) and strongest (higher) regions are Sylhet and Barishal, respectively. Based on power-curve relationships, a simple power predictive model (SPPM) is developed using global wind atlas (GWA) data (sample: 1100) to estimate the power density (W/m2) and found an accuracy of 0.918 and 0.892 for Exponential (EXP) and Polynomial (PN) with mean absolute percentage errors (MAPE) of 22.92 and 21.8%, respectively. For validation, SPPM also forecasts power incorporating historical observations for Chittagong and obtains correlations of 0.970 and 0.974 for EXP and PN with a MAPE of 10.26 and 7.69% individually. Furthermore, calculations for annual energy production reveal an average megawattage of 1748 and 1070 in the southern and northern regions, with an MAPE of 15.71 and 5.85% for EXP and PN models, except Sylhet. The SPPM’s predictability can be improved with observed wind speeds and turbine types. The research wishes to apply SPPM for estimating energy in operational power plants.

APA, Harvard, Vancouver, ISO, and other styles

46

Ershad, Ahmad Murtaza, Robert J. Brecha, and Kevin Hallinan. "Analysis of solar photovoltaic and wind power potential in Afghanistan." Renewable Energy 85 (January 2016): 445–53. http://dx.doi.org/10.1016/j.renene.2015.06.067.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Bardenhagen, Yannek, and Toshihiko Nakata. "Regional Spatial Analysis of the Offshore Wind Potential in Japan." Energies 13, no. 23 (November 29, 2020): 6303. http://dx.doi.org/10.3390/en13236303.

Full text

Abstract:

This study presents an approach for estimating the offshore wind potential of Japan. Bathymetry data (1 km mesh) and near shore wind speed data of the year 2018 were used to assess the potential. A turbine with a peak power of 10.6 MW was employed for the analysis. The potential was calculated for multiple regions. These regions are based on the service areas of the major electricity supply companies in Japan. Overall, the results show that Japan has the potential to produce up to 32,028 PJ electricity per year. The electricity demand of 2018 amounts to 3231 PJ. The potential is therefore large enough to cover Japan’s electricity needs ten-times over. The capacity that could theoretically be installed amounts to 2720 GW, which is a multiple of the current worldwide installed capacity of 29.1 GW (2019). In addition to the huge potential, the regional assessment shows that the regions vary greatly in their potential; of all the considered regions, Hokkaido and Kyushu have the highest overall potential.

APA, Harvard, Vancouver, ISO, and other styles

48

Wang, B., L. D. Cot, L. Adolphe, S. Geoffroy, and S. Sun. "Cross indicator analysis between wind energy potential and urban morphology." Renewable Energy 113 (December 2017): 989–1006. http://dx.doi.org/10.1016/j.renene.2017.06.057.

Full text

APA, Harvard, Vancouver, ISO, and other styles

49

Lashin, Aref, and Ahmed Shata. "An analysis of wind power potential in Port Said, Egypt." Renewable and Sustainable Energy Reviews 16, no. 9 (December 2012): 6660–67. http://dx.doi.org/10.1016/j.rser.2012.08.012.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Vogiatzis, N., K. Kotti, S. Spanomitsios, and M. Stoukides. "Analysis of wind potential and characteristics in North Aegean, Greece." Renewable Energy 29, no. 7 (June 2004): 1193–208. http://dx.doi.org/10.1016/j.renene.2003.11.017.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!