Wind Farm Layout Optimization with Emphasis on the Wake Effect
Subject Areas : electrical and computer engineering
A.
Farajipoor
1
F.
Faghihi
2
R.
Sharifi
3
Keywords: Wind farm wind turbine layout design optimization algorithms renewable energy,
Abstract :
Construction of wind farms rise for wind energy capture as a renewable energy around the world. The purpose of wind farm layout optimization, absorb maximum energy from wind farms. In this paper, a new hybrid algorithm is presented to maximize the expected energy output. Considerations of algorithm wake loss, which is based on wind turbine location and wind direction. The proposed model is illustrated with a scenario of the wind speed and its direction distribution of windy sites and is compared with ant colony algorithm and evolutionary strategy algorithm in six steps layout. The results show that the combination of ant colony algorithm and genetic algorithm performs better than existing strategies based on maximum values of the expected energy output and wake loss.
[1] Y. Eroglu and S. Seckiner, "Wind farm layout optimization using particle filtering approach," Renew Energy, vol. 58, pp. 95-107, Oct. 2013.
[2] A. Mostafaeipour, et al., "Evaluation of wind energy potential as a power generation source for electricity production in Binalood, Iran," Renew Energy, vol. 52, pp. 222-229, Apr. 2013.
[3] K. Mohammadi, A. Mostafaeipour, and M. Sabzpooshani, "Assessment of solar and wind energy potentials for three free economic and industrial zones of Iran," Energy, vol. 67, pp. 117-128, Apr. 2014.
[4] Y. Eroglu and S. Seckiner, "Design of wind farm layout using ant colony algorithm," Renew. Energy, vol. 44, pp. 53-62, Aug. 2012.
[5] A. Kusiak and Z. Song, "Design of wind farm layout for maximum wind energy capture," Renew. Energy, vol. 35, no. 3, pp. 685-694, Mar. 2010.
[6] M. Wagner, J. Day, and F. Neumann, "A fast and effective local search algorithm for optimizing the placement of wind turbines," Renew Energy, vol. 51, pp. 64-70, Mar. 2013.
[7] E. Son, S. Lee, B. Hwang, and S. Lee, "Characteristics of turbine spacing in a wind farm using an optimal design process," Renew Energy, vol. 65, pp. 245-249, May 2014.
[8] J. C. Mora, J. M. C. Baron, J. M. R. Santos, and M. Burgos, "An evolutive algorithm for wind farm optimal design," Neurocomputing, vol. 70, no. 16-18, pp. 2651-2658, Oct. 2007.
[9] J. S. Gonzales, A. G. G. Rodriguez, J. C. Mora, J. R. Santos, and M. B. Payan, "Optimization of wind farm turbines layout using an evolutive algorithm," Renew. Energy, vol. 35, pp. 1671-1681, Aug. 2010.
[10] M. Bilbao and E. Alba, "Simulated annealing for optimization of wind farm annual profit," in Proc. 2nd Int. Symp. on Logistics and Industrial Informatics, 5 pp., Linz, Austria, 10-12 Sep. 2009.
[11] U. A. Ozturk and A. B. Norman, "Heuristic methods for wind energy conversion system positioning," Electric Power Syst. Res., vol. 70, no. 3?, pp. 179-185, Aug. 2004.
[12] J. F. Manwell, J. G. McGowan, and A. L. Rogers, Wind Energy Explained: Theory, Design, and Application, 1st Ed. London, John Wiley & Sons, 2002.
[13] H. E. Neustadter, "Method for evaluating wind turbine wake effects on wind farm performance," J. Solar Energy Eng., vol. 107, pp. 240-243, 1985.
[14] N. O. Jensen, A Note on Wind Generator Interaction, Roskilde, Denmark, RisøeM-2411: Risø National Laboratory, 1983.
[15] I. Katic, J. Hojstrub, and O. N. Jensen, "A simple model for cluster efficiency," in Proc. European Wind Energy Association Conf. and Exhibition, vol. 1, pp. 407-410, Rome, Italy, Oct. 1986.
[16] M. Dorigo, M. Birattari, and T. Stutzle, "Ant colony optimization," IEEE Computational Intelligence Magazine, vol. 1, no. 4, pp. 28-39, Nov. 2006.
[17] K. Socha and C. Blum, "An ant colony optimization algorithm for continuous optimization: application to feed - forward neural network training," Neural Comput Appl., vol. 16, no. 3, pp. 235-247, May 2007.
[18] J. Zhang, S. Chowdhury, A. Messac, and L. Castillo, "A response surface - based cost model for wind farm design," Energy Policy, vol. 42, issue C, pp. 538-550, 2012.