Evaluation of Wind Energy Potential for Four Sites in Ireland using the Weibull Distribution Model
Abstract
Wind speed is receiving greater attention in the design and study of wind energy conversion systems (WECS). Usingmeteorological data, this paper studies the availability of wind energy potential at four sites in Ireland: Malin Head,Dublin Airport, Belmullet and Mullingar. An analysis is made of mean wind speed data collected at a height of 50m above ground level at each site over a period of seven years. A two parameter Weibull distribution model is usedto analyze wind speed pattern variations. Weibull parameters are calculated by the Least Squares Method (LSM). Theresults relating to wind energy potential are given in terms of the density function. Analysis shows that coastal sites ofIreland such as Malin Head, Dublin Airport and Belmullet have good wind power potential.References
[1] Bansal, R.C. Bhatti, T.S. and Kothari, D.P. (2002) On some of the design aspects of wind energy conversion system, Energy Conversion Management, 43(16), pp. 2175 - 2187.
[2] Celick, A. N. (2004) A statistical analysis of wind density based on the Weibull and Rayleigh models at the southern region of Turkey, Energy Conversion Management, 29(4), pp. 593 - 604.
[3] Carta, J. A. and Ramiez, P. (2005) Influence of the data sampling interval in the estimation of the parameters of the weibull wind speed probability density distribution: a case study, Energy Conversion Management, 46(15), pp. 2419 - 2438.
[4] Bansal, R. C. Zobaa, A.F. and Saket, R.K. (2005) Some issues related to power generation using wind energy conversion systems: An overview, International Journal Emerging Electrical Power System, 3(2), pp. 1 - 19.
[5] Chang, T. J. and Tu, Y.L. (2007) Evaluation of monthly capacity factor of WECS using chronological and probabilistic wind speed data: A case study of Taiwan, Renewable Energy, 32(2), pp. 1999 - 2010.
[6] Tingem, M., Rivington, M., Ali, S. A. and Colls, J. (2007) Assessment of the ClimGen stochastic weather generator at Cameroon sites, African Journal of Environmental Science and Technology, 1(4), pp. 86 - 92.
[7] Huang, S. J. and Wan, H.H. (2009) Enhancement of matching turbine generators with wind regime using capacity factor curves stratergies, IEEE Transaction Energy Conversion, 24(2), pp. 551 - 553.
[8] Prasad, R. D., Bansal, R.C. and Sauturaga, M. (2009) Wind energy analysis for Vadravadra site in Fiji islands: A case study, IEEE Transaction Energy Conversion, 24(3), pp. 1537 - 1543.
[9] Pryor, S. C. and Barthelmie, R. J. (2010) Climate change impacts on wind energy: a review, Renewable and Sustainable Energy Reviews, 14, pp. 430 - 437.
[10] Jamdade, S. G. and Jamdade, P. G. (2012) Extreme Value Distribution Model for Analysis of Wind Speed Data for Four Locations in Ireland, International Journal of Advanced Renewable Energy Research, 1(5), pp. 254 - 259.
[11] Jamdade, S. G. and Jamdade, P. G. (2012) Analysis of Wind Speed Data for Four Locations in Ireland based on Weibull Distribution’s Linear Regression Model, International Journal of Renewable Energy Research, 2(3), pp. 451 - 455.
[2] Celick, A. N. (2004) A statistical analysis of wind density based on the Weibull and Rayleigh models at the southern region of Turkey, Energy Conversion Management, 29(4), pp. 593 - 604.
[3] Carta, J. A. and Ramiez, P. (2005) Influence of the data sampling interval in the estimation of the parameters of the weibull wind speed probability density distribution: a case study, Energy Conversion Management, 46(15), pp. 2419 - 2438.
[4] Bansal, R. C. Zobaa, A.F. and Saket, R.K. (2005) Some issues related to power generation using wind energy conversion systems: An overview, International Journal Emerging Electrical Power System, 3(2), pp. 1 - 19.
[5] Chang, T. J. and Tu, Y.L. (2007) Evaluation of monthly capacity factor of WECS using chronological and probabilistic wind speed data: A case study of Taiwan, Renewable Energy, 32(2), pp. 1999 - 2010.
[6] Tingem, M., Rivington, M., Ali, S. A. and Colls, J. (2007) Assessment of the ClimGen stochastic weather generator at Cameroon sites, African Journal of Environmental Science and Technology, 1(4), pp. 86 - 92.
[7] Huang, S. J. and Wan, H.H. (2009) Enhancement of matching turbine generators with wind regime using capacity factor curves stratergies, IEEE Transaction Energy Conversion, 24(2), pp. 551 - 553.
[8] Prasad, R. D., Bansal, R.C. and Sauturaga, M. (2009) Wind energy analysis for Vadravadra site in Fiji islands: A case study, IEEE Transaction Energy Conversion, 24(3), pp. 1537 - 1543.
[9] Pryor, S. C. and Barthelmie, R. J. (2010) Climate change impacts on wind energy: a review, Renewable and Sustainable Energy Reviews, 14, pp. 430 - 437.
[10] Jamdade, S. G. and Jamdade, P. G. (2012) Extreme Value Distribution Model for Analysis of Wind Speed Data for Four Locations in Ireland, International Journal of Advanced Renewable Energy Research, 1(5), pp. 254 - 259.
[11] Jamdade, S. G. and Jamdade, P. G. (2012) Analysis of Wind Speed Data for Four Locations in Ireland based on Weibull Distribution’s Linear Regression Model, International Journal of Renewable Energy Research, 2(3), pp. 451 - 455.
Published
2015-03-17
How to Cite
JAMDADE, Parikshit Gautam; JAMDADE, Shrinivas Gautamrao.
Evaluation of Wind Energy Potential for Four Sites in Ireland using the Weibull Distribution Model.
Journal of Power Technologies, [S.l.], v. 95, n. 1, p. 48--53, mar. 2015.
ISSN 2083-4195.
Available at: <https://papers.itc.pw.edu.pl/index.php/JPT/article/view/564>. Date accessed: 01 dec. 2024.
Issue
Section
Renewable and Sustainable Energy
Keywords
Wind Energy Conversion Systems (WECS); Wind Power Potential (WPP); Weibull Distribution Model (WDM); Cumulative Density Function (CDF); Least Squares Fit Method (LSM)
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).