skip to main content

Lake Michigan Wind Assessment Analysis, 2012 and 2013

1Seymour and Esther Padnos College of Engineering and Computing, United States

2Grand Valley State University, United States

3Meijer Incoporated, United States

4 Meijer Incorporated, United States

5 Edmonson Associates, United States

6 AXYS Technologies Incorporated, Canada

7 Michigan Technological University, United States

8 University of Michigan, United States

View all affiliations
Published: 22 Mar 2017.
Editor(s): H Hadiyanto

Citation Format:
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 online

How 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

Fulltext View|Download
Funding: wind assessment; Lake Michigan; LIDAR wind sensor; statistical analysis

Article Metrics:

  1. Ajayi, O., Fagbenle, R., Katende, J., Aasa, S., & Okeniyi, J. (2013) Wind profile characteristics and turbine performance analysis in Kano, northwestern Nigeria. International Journal of Energy and Environmental Engineering, 4(27), http://www.sid.ir/en/VEWSSID/J_pdf/10251201304JUL01.pdf. Accessed on 1 September 2016
  2. Babayani, D., Khaleghi, M. & Hashemi-Tilehnoee, M. (2016) Assessment of wind energy potential in Golestan Province of Iran. Int. Journal of Renewable Energy Development, 5(1), 25-31. http://dx.doi.org/10.14710/ijred.5.1.25-31. Accessed on 1 September 2016
  3. Babayani, D., Khaleghi, M., Tashakor, S., & Hashemi-Tilehnoee.,M. (2016) Evaluating wind energy potential in Gorgan–Iran using two methods of Weibull distribution function. Int. Journal of Renewable Energy Development, 5(1), 43-48. http://dx.doi.org/10.14710/ijred.5.1.43-48. Accessed on 2 September 2016
  4. Bagiorgas, H. S., Mihalakakou, G. , Rehman, S. & Al-Hadhrami, L. M. (2012) Wind power potential assessment for seven buoys data collection stations in Aegean Sea using Weibull distribution function. Journal of Renewable and Sustainable Energy, 4. http://dx.doi.org/10.1063/1.3688030. Accessed on 2 September 2016
  5. Elliott, D. L., Holladay, C.G., Barchet, W.R., Foote, H.P. & Sandusky, W.F. (1986) Wind Energy Resource Atlas of the United States, Pacific Northwest Laboratory, Richland, WA
  6. Jamdade, S. G. & 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). http://www.ijrer.org/ijrer/index.php/ijrer/article/view/258/pdf. Accessed on 4 February 2015
  7. Law, A. M. (2007) Simulation Modeling & Analysis, 4th ed., New York: McGraw-Hill
  8. Lu, L., Yang, H. & Burnett, J. (2012) Investigation on wind power potential on Hong Kong islands—an analysis of wind power and wind turbine characteristics. Renewable Energy, 27(1), 1–12. http://dx.doi.org/10.1016/S0960-1481(01)00164-1. Accessed on 2 September 2016
  9. Nedaei, M. (2012) Wind resource assessment in Abadan Airport in Iran. Int. Journal of Renewable Energy Development, 1(3), 2012:87-97. DOI: 10.14710/ijred.1.3.87-97.Accessedon2September2016
  10. Olaofe, Z. O., & Folly, K. A. (2012) Statistical analysis of wind energy resources at Darling for energy production. International Journal of Renewable Energy Research, 2(2), http://www.ijrer.org/ijrer/index.php/ijrer/article/view/176/pdf. Accessed on 9 February 2015
  11. Oyedepo, S. O., Adaramola, M. S. & Paul, S. S. (2012) Analysis of wind speed data and wind energy potential in three selected locations in south-east Nigeria. International Journal of Energy and Environmental Engineering, 3(7), http://link.springer.com/article/10.1186/2251-6832-3-7. Accessed on 10 February 2015
  12. Peterson, E.W. & Hennessey, Jr., J.P. (1978) On the use of power laws for estimates of wind power potential. Journal of Applied Meteorology, 17, 390-394
  13. Roy, A., (2012) Reliable estimation of density distribution in potential wind power sites in Bangladesh. International Journal of Renewable Energy Research, 2(2), http://www.ijrer.org/ijrer/index.php/ijrer/article/view/159/pdf, Accessed on 9 February 2015
  14. Standridge, C., Zeitler, D., Nordman, E., Boezaart, T.A., Edmonson, J., Nieves, Y., Turnage, T. J., Phillips, R., Howe, G., Meadows, G., Cotel, A. & Marsik, F. (2015) A case study of laser wind sensor performance validation by comparison to an existing gage. International Journal of Renewable Energy Research, 5(2), http://www.ijrer.org/ijrer/index.php/ijrer/article/view/2167. Accessed on 9 January 2016
  15. Veigas, M. & Iglesias, G. (2012) Evaluation of the wind resource and power performance of a turbine in Tenerife. Journal of Renewable and Sustainable Energy, 4, doi: 10.1063/1.4754155

Last update:

  1. EOSOLAR Project: Assessment of Wind Resources of a Coastal Equatorial Region of Brazil—Overview and Preliminary Results

    Arcilan T. Assireu, Felipe M. Pimenta, Ramon M. de Freitas, Osvaldo R. Saavedra, Francisco L. A. Neto, Audálio R. Torres Júnior, Clóvis B. M. Oliveira, Denivaldo C. P. Lopes, Shigeaki L. de Lima, Rafael B. S. Veras, Natália P. Saraiva, Luiz G. P. Marcondes, Denisson Q. Oliveira. Energies, 15 (7), 2022. doi: 10.3390/en15072319

Last update: 2024-12-23 18:26:55

No citation recorded.