Share This Article:

Subtle Influence of the Weibull Shape Parameter on Homer Optimization Space of a Wind Diesel Hybrid Gen Set for Use in Southern Brazil

Full-Text HTML XML Download Download as PDF (Size:2177KB) PP. 38-48
DOI: 10.4236/jpee.2016.48004    886 Downloads   1,051 Views  

ABSTRACT

Wind power is an increasingly important alternative for obtaining energy supplies, both in large interconnected power systems and in smaller hybrid systems and even in backup systems. The temporal and spatial variability of the winds represent an obstacle to be overcome so that wind energy can be increasingly used. The capacity factor of wind farms shows how this variability impacts the operation of the plants and its value is of the order of 30% to 35%. The variability of the wind speed is influenced if the point of interest is on land or on sea, the shape of the surface, the proximity of water bodies, among other factors. The availability of wind is best described by the Weibull probability distribution, which has as one of its defining parameters one which is termed as shape parameter. This parameter is much higher as higher is the variability of the wind speed. This paper studies the subtle influence of Weibull shape parameter on the optimal combination of components in a wind diesel hybrid system, by means of computer simulations with the well known software Homer. The results indicate a relatively small influence (as expected) in the studied system, which appears particularly when the cost of diesel is higher and the availability of wind is lower.

Cite this paper

Benevit, M. , Silva, J. , Gewehr, A. and Beluco, A. (2016) Subtle Influence of the Weibull Shape Parameter on Homer Optimization Space of a Wind Diesel Hybrid Gen Set for Use in Southern Brazil. Journal of Power and Energy Engineering, 4, 38-48. doi: 10.4236/jpee.2016.48004.

References

[1] The World Wind Energy Association. Annual Report. 2012. www.wwindea.org/home/index.php
[2] Brazil, Department of Mines and Energy. Annual Energy Balance, Edition 2012, Base Year 2011. Brasília, DF, Brazil, 2012. https://ben.epe.gov.br/downloads/Relatorio_Final_BEN_2012.pdf
[3] Weis, T.M. and Ilinca, A. (2010) Assessing the Potential for a Wind Power Incentive for Remote Villages in Canada. Energy Policy, 38, 5504-5511.
http://dx.doi.org/10.1016/j.enpol.2010.04.039
[4] Antoine, B., Goran, K. and Neven, D. (2008) Energy Scenarios for Malta. International Journal of Hydrogen Energy, 33, 4235-4246.
http://dx.doi.org/10.1016/j.ijhydene.2008.06.010
[5] Pandey, S.K., Mohanty, S.R. and Kishor, N. (2013) A Literature Survey on Load Frequency Control for Conventional and Distribution Generation Power Systems. Renewable and Sustainable Energy Reviews, 25, 318-334.
http://dx.doi.org/10.1016/j.rser.2013.04.029
[6] Geem, Z.W. and Hong, J. (2013) Improved Formulation for the Optimization of Wind Turbine Placement in a Wind Farm. Mathematical Problems in Engineering, 2013, Article ID: 481364.
[7] Brazilian Agency for Electrical Energy, ANEEL. Capacity of Power Generation in Brazil.
http://www.aneel.gov.br/aplicacoes/capacidadebrasil/capacidadebrasil.cfm
[8] State of Rio Grande do Sul (Brazil), Department of Mines, Energy and Communications. Wind Atlas of Rio Grande do Sul. Porto Alegre, RS, Brazil, 2002. (In Portuguese) www.cresesb.cepel.br/publicacoes/download/atlas_eolico/atlas_eolico_RGS.pdf
[9] Anagnostopoulos, J.S. and Papantonis, D.E. (2008) Simulation and Size Optimization of a Pumped Storage Power Plant for the Recovery of Wind Farms Rejected Energy. Renewable Energy, 33, 1685-1694.
http://dx.doi.org/10.1016/j.renene.2007.08.001
[10] Rodríguez, O., del Río, J.A., Jaramillo, O. and Martínez, M. (2015) Wind Power Error Estimation in Resource Assessments. PLoS ONE, 10, e0124830.
http://dx.doi.org/10.1371/journal.pone.0124830
[11] Masseran, N. (2015) Evaluating Wind Power Density Models and Their Statistical Properties. Energy, Elsevier, 84, 533-541.
http://dx.doi.org/10.1016/j.energy.2015.03.018
[12] Lun, I.Y.F. and Lam, J.C. (2000) A Study of Weibull Parameters Using Long-Term Wind Observations. Renewable Energy, 20, 145-153.
http://dx.doi.org/10.1016/S0960-1481(99)00103-2
[13] Rocha, P.A.C., Sousa, R.C., Andrade, C.F. and Silva, M.E.V. (2012) Comparison of Seven Numerical Methods for Determining Weibull Parameters for Wind Energy Generation in the Northeast Region of Brazil. Applied Energy, 89, 395-400.
http://dx.doi.org/10.1016/j.apenergy.2011.08.003
[14] State of Rio Grande do Sul (Brazil), Department of Mines, Energy and Communications (2002) Wind Atlas of Rio Grande do Sul. Porto Alegre, RS, Brazil, 38. (In Portuguese)
[15] State of Rio Grande do Sul (Brazil), Department of Mines, Energy and Communications (2002) Wind Atlas of Rio Grande do Sul. Porto Alegre, RS, Brazil, 40. (In Portuguese)
[16] State of Rio Grande do Sul (Brazil), Department of Mines, Energy and Communications (2002) Wind Atlas of Rio Grande do Sul. Porto Alegre, RS, Brazil, 42. (In Portuguese)
[17] State of Rio Grande do Sul (Brazil), Department of Mines, Energy and Communications (2002) Wind Atlas of Rio Grande do Sul. Porto Alegre, RS, Brazil, 45. (In Portuguese)
[18] Seaforth Energy. Wind Turbine Model AOC 15/50. seaforthenergy.com/aoc-1550/specifications/
[19] Vision Group. Battery Model 6FM55D. www.vision-batt.com
[20] Software HOMER, Version 2.68 Beta. The Micropower Opyimization Model, Homer Energy. www.homerenergy.com
[21] Lambert, T.W., Gilman, P. and Lilienthal, P.D. (2005) Micropower System Modeling with Homer. In: Farret, F.A. and Simões, M.G., Eds., Integration of Alternative Sources of Energy, John Wiley & Sons, Boca Raton, 379-418.
http://dx.doi.org/10.1002/0471755621.ch15
[22] Lilienthal, P.D., Lambert, T.W. and Gilman, P. (2004) Computer Modeling of Renewable Power Systems. In: Cleveland, C.J., Ed., Encyclopedia of Energy, Vol. 1, Elsevier, 633-647.
http://dx.doi.org/10.1016/b0-12-176480-x/00522-2

  
comments powered by Disqus

Copyright © 2017 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.