scholarly journals Wind Energy Resource Assessment and Feasibility Study of Wind Farm in Kaligandaki Riverbank of Mustang District

1970 ◽  
Vol 11 ◽  
pp. 159-166
Author(s):  
Mukesh Ghimire ◽  
Ram C Poudel

This study presents wind energy resource assessment and financial analysis of a 15 MW wind farm in Mustang for utility scale power generation. Hourly meteorological data at Kagbeni and Thini measured at 10 m and 20 m height from 2001 to 2005 have been analyzed and annual average wind speed and power density at 75 m above ground level at Kagbeni 8.05 m/s and 851 W/m2 whereas the same for Thini are 6.99 m/s and 337 W/m2 respectively.WAsP analysis showed that the wind speed and wind power density in the study area (20 × 20 km2) varied from 2.72 m/s to 44.51 m/s and 0.23 kW/m2 to 173.27 kW/m2. Optimized layout of a 15 MW wind farm that comprised of twenty five S52 -600 kW turbines, developed by open Wind software yields annual gross energy 63.58 GWh, and net energy 41.66 GWh with capacity factor of 31.68 %. The economic analysis of the farm suggests that the unit energy cost stands on range NRs 4.57 to NRs 6.10 under different energy availability scenario to meet the project MARR of 16.1%. Based on the results, it is apparent that the wind resources at Mustang are suitable for harnessing wind energy especially for the purpose of utility scale electricity generation. Site accessibility is a major challenging factor to establish a wind farm currently. Key words: WAsP; wind energy; wind farm DOI: 10.3126/njst.v11i0.4139Nepal Journal of Science and Technology 11 (2010) 159-166

1970 ◽  
Vol 8 (1-2) ◽  
pp. 93-104 ◽  
Author(s):  
Mukesh Ghimire ◽  
Ram C. Poudel ◽  
Nawraj Bhattarai ◽  
Mahesh Chandra Luintel

This study presents the wind energy resource assessment and financial analysis of a 15 MW proposed wind farm in Mustang for utility scale power generation. Hourly meteorological data at Kagbeni and Thini measured at 10 m and 20 m height from 2001 to 2005 have been analyzed and the annual average wind speed and power density 75 m above ground level at Kagbeni are 8.05 m/s and 851 W/m2 whereas the same for Thini is 6.99 m/s and 337 W/m2, respectively. WAsP analysis shows that the wind speed and wind power density in the study area (20 × 20 km2) varies from 2.72 m/s to 44.51 m/s and 0.23 kW/m2 to 173.27 kW/m2. Optimized layout of a 15 MW wind farm that is comprised of twenty-five S52 -600 kW turbines, developed by openWind software, yields annual gross energy 63.58 GWh, and net energy 41.66 GWh with a capacity factor of 31.68%. The economic analysis of the farm suggests that the unit energy cost is in the range of NRs 4.57 to NRs 6.10 under different energy availability scenarios when meeting the project MARR of 16.1%. Based on the results, it is apparent that the wind resources at Mustang are suitable for harnessing wind energy especially for the purpose of utility scale electricity generation. Site accessibility is a major challenging factor to establish a wind farm currently.Keywords: WAsP; OpenWind; Resource Assessment; Wind Farm; Feasibility StudyDOI: http://dx.doi.org/10.3126/jie.v8i1-2.5099Journal of the Institute of Engineering Vol. 8, No. 1&2, 2010/2011Page: 93-104Uploaded Date: 20 July, 2011


2011 ◽  
Vol 130-134 ◽  
pp. 1295-1297
Author(s):  
Hui Qun Ma ◽  
Qi Feng Wang

In feasible research of wind farm construction, wind resources assessment is an important process. The grade of wind resources is the crucial qualification in the construction. It determines whether this wind farm is profitable or not. his paper introduces the theory of wind energy resource assessment firstly, including: wind power density, wind speed correction and Weibull distribution. Then take Yishui wind farm as example to calculate the wind energy resource assessment.


2020 ◽  
pp. 0309524X2092540
Author(s):  
Addisu Dagne Zegeye

Although Ethiopia does not have significant fossil fuel resource, it is endowed with a huge amount of renewable energy resources such as hydro, wind, geothermal, and solar power. However, only a small portion of these resources has been utilized so far and less than 30% of the nation’s population has access to electricity. The wind energy potential of the country is estimated to be up to 10 GW. Yet less than 5% of this potential is developed so far. One of the reasons for this low utilization of wind energy in Ethiopia is the absence of a reliable and accurate wind atlas and resource maps. Development of reliable and accurate wind atlas and resource maps helps to identify candidate sites for wind energy applications and facilitates the planning and implementation of wind energy projects. The main purpose of this research is to assess the wind energy potential and model wind farm in the Mossobo-Harena site of North Ethiopia. In this research, wind data collected for 2 years from Mossobo-Harena site meteorological station were analyzed using different statistical software to evaluate the wind energy potential of the area. Average wind speed and power density, distribution of the wind, prevailing direction, turbulence intensity, and wind shear profile of the site were determined. Wind Atlas Analysis and Application Program was used to generate the generalized wind climate of the area and develop resource maps. Wind farm layout and preliminary turbine micro-sitting were done by taking various factors into consideration. The IEC wind turbine class of the site was determined and an appropriate wind turbine for the study area wind climate was selected and the net annual energy production and capacity factor of the wind farm were determined. The measured data analysis conducted indicates that the mean wind speed at 10 and 40 m above the ground level is 5.12 and 6.41 m/s, respectively, at measuring site. The measuring site’s mean power density was determined to be 138.55 and 276.52 W/m2 at 10 and 40 m above the ground level, respectively. The prevailing wind direction in the site is from east to south east where about 60% of the wind was recorded. The resource grid maps developed by Wind Atlas Analysis and Application Program on a 10 km × 10 km area at 50 m above the ground level indicate that the selected study area has a mean wind speed of 5.58 m/s and a mean power density of 146 W/m2. The average turbulence intensity of the site was found to be 0.136 at 40 m which indicates that the site has a moderate turbulence level. According to the resource assessment done, the area is classified as a wind Class IIIB site. A 2-MW rated power ENERCON E-82 E2 wind turbine which is an IEC Class IIB turbine with 82 m rotor diameter and 98 m hub height was selected for estimation of annual energy production on the proposed wind farm. 88 ENERCON E-82 E2 wind turbines were properly sited in the wind farm with recommended spacing between the turbines so as to reduce the wake loss. The rated power of the wind farm is 180.4 MW and the net annual energy production and capacity factor of the proposed wind farm were determined to be 434.315 GWh and 27.48% after considering various losses in the wind farm.


Author(s):  
Onur Koşar ◽  
Mustafa Arif Özgür

Kütahya is considered as a candidate region for a wind farm investment due to Turkey's 2023 energy targets and its proximity to other wind farm investments. In this study, two years of wind data collected from a hill near the Evliya Çelebi Campus of Kütahya Dumlupınar University was used to evaluate the wind farm potential of Kütahya. First, the wind speed, wind direction, wind shear, turbulence intensity and wind speed ramp characteristics were determined. Second, the WAsP software was used to create a wind atlas for the region. Three sites with strong wind potential were evaluated. A techno-economic analysis was conducted using five types of wind turbines selected from the WAsP database. Third, optimization of a wind farm layout was conducted by considering different hub height options for 14 commercial wind turbines using MATLAB software. It was shown theoretically that a wind farm with a power capacity of 25 MW can operate with a capacity factor of 35%. However, due to the relatively high topographical ruggedness index on the wind farm site, the calculated value for the capacity factor could not be reached in a real-life application.


2014 ◽  
Vol 541-542 ◽  
pp. 972-976 ◽  
Author(s):  
Sidi Mohammed Boudia ◽  
Abdelhalim Benmansour ◽  
Mohamed Abdellatif Tabet Hellal

In this paper, with the help of two-parameter Weibull distribution, the monthly, seasonal and annual assessment of wind energy potentiality was made using the wind speed data collected in the last decade, from 2001 to 2010 for the meteorological station of Tindouf region. The vertical extrapolation of Weibull parameters and mean wind speed at a height of 50m and the analysis of temporal energy efficiency using a wind turbine of 600kW rated power from Fuhrländer manufacturer was made. The results show that Tindouf situated in extreme Algerian southwest, in the natural region of the Sahara, on the border with Morocco (west), the non-autonomous territory of Western Sahara (south-west) and Mauritania (south), is one of windiest region in the country, swept by local winds with a good annual mean wind speed =5.67m/s and an annual mean wind power density equal to 200W/m2at 10m, while the highest monthly wind energy produced may be reached in May, the seasonal in Spring and the annual gross electric energy produced is equal to 1.85GWh/year.


2020 ◽  
pp. 014459872093042
Author(s):  
Muhammad Sumair ◽  
Tauseef Aized ◽  
Syed Asad Raza Gardezi ◽  
Syed Muhammad Sohail Rehman ◽  
Syed Ubaid ur Rehman

Ten-year hourly recorded wind meteorological data at six sites along the coastline of Pakistan at two heights (10 and 50 m) were extrapolated to two higher heights (80 and 100 m). Monthly and seasonal analysis of variation in air density (ρ), wind speed, Weibull parameters ( K and C), wind power density, and wind energy density with height was investigated. Analysis shows that wind shear coefficient is highest in winter and lowest in summer. ρ, wind speed, wind power density, and wind energy density all increase with increasing hub height, with the most prominent increment in winter and the lowest in summer. With increasing height, K has been found to decrease slightly while C increases. Techno-economic feasibility analysis of annual energy production using 15 turbines was carried out which shows that capacity factor alone cannot render a turbine feasible but also economic assessment is mandatory to evaluate the feasibility of turbines. G1 and G2 turbines have been found the best options while B5 and V2 as the worst. Comparison among sites shows that Karachi is the most potential site with cost of energy of $0.017/kW h while Jiwani is the worst site with cost of energy of $0.039/kW h both at 100 m height.


2015 ◽  
Vol 8 (9) ◽  
pp. 106 ◽  
Author(s):  
Talla Pierre Kisito ◽  
Bawe Gerard Nfor, Jr ◽  
Yemele David ◽  
Ghogomu Patrick Ndinakie

<p>Three-hourly wind speed data measured using the Beaufort scale at a height of 10m, from 6am to 6pm local time (5 periods per day), was obtained from the Bafoussam Airport. It was analyzed using the Weibull and Rayleigh probability density models and wind rose plots. It was determined that the lowest wind speeds (most calms) were observed during the first period (6am) and the highest at 3pm (fourth period). The very low morning wind speed adversely affected the daily mean wind speed. Better, but still poor, power density results were obtained at this fourth (3pm) period. The monthly and yearly mean speeds varied between 1.9 and 3.1m/s and with very low standard deviations. The wind rose plots also showed that all the significant winds fell in the first quadrant (NE) and predominantly on angle 10<sup>o</sup> with some discernibly on 20<sup>o</sup> and 30<sup>o</sup>, only. Three goodness-of-fit tests: the chi square, coefficient of determination or R<sup>2</sup> and root mean square error, showed the Weibull to be a better fit to the wind regime than the Rayleigh model. The shape parameters were always greater than the scale parameters. Results show that, using the Weibull parameters, the power density of Bafoussam falls in the category 1 of the wind energy resource group and hence is not a very good wind energy exploitable candidate.</p>


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