Evaluation of Optimal Fuzzy Membership Function for Wind Speed Forecasting

Subject Areas : International Journal of Smart Electrical Engineering

Shahram Javadi ¹ ( Electrical Engineering Department, Central Tehran Branch, Islamic Azad University, Tehran, Iran. )
Zeinab Hojjatinia ² ( Electrical Engineering Department, Tehran South Branch, Islamic Azad University, Tehran, Iran. )

Received: 2015-04-13 Accepted : 2015-04-13 Published : 2012-06-01

Keywords:

References:

[1] Burton T, Sharpe D, Jenkins N, Bossanyi E., “Wind Energy Handbook”, John Wiley and Sons, 2001.

[2] R. Billiton, and L. Gan, “Wind Power Modelling and Application in Generating Adequacy Assessment”, WESCANEX 93 Communication Computers and Power in the Modern Environment, Conference Proceedings, pp. 100-106, 1993.

[3] R. Karki, P. Hu, and R. Billinton, “Reliability evaluation of a wind power delivery system using an approximate wind model”, Proceedings of the 41st International Universities Power Engineering Conference (UPEC 06), pp. 113-117, 2006.

[4] A. V. Machias, and G. D. Skikos, “Fuzzy Risk Index of Wind Sites,” IEEE Transactions on Energy Conversation, Vol. 7, No. 4, pp. 638-643, 1992.

[5] H. Nachtmann, and J. R. Chimka, “Fuzzy Reliability in Conceptual Design”, Annual Reliability & Maintainability Symposium, pp. 360-364, 2003.

[6] M. Mohandes, S. Rehman, and S. M. Rahman,“Estimation of Wind Speed Profile Using Adaptive Neuro-Fuzzy Inference System (ANFIS)”, Applied Energy, Vol.88, No.11, pp. 4024-4032, 2011.

[7] F. J. Chang, and Y. T. Chang, “Adaptive Neuro-Fuzzy Inference System for Prediction of Water Level in Reservoir”, Advances in Water Resources, Vol.29, No.1, pp. 1-10, 2006. [8] L. X. Wang, and M. Jerry, “Generating fuzzy rules by learning from examples”, IEEE Transactions on Systems, Man, and Cybernetics, Vol.22, No.6, pp. 1414-1427, 1992.