COMPARISON BETWEEN TWO METHODS OF PREDICTION OF ELECTRIC POWER GENERATION FROM WIND POWER | ||||
| Journal of Al-Azhar University Engineering Sector | ||||
| Article 25, Volume 11, Issue 38, January 2016, Page 159-163 PDF (297.15 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/auej.2016.19500 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Mohamed Ahmed El-Mahlawy1; Said Fouad Mekhamer2; Mohamed Abd-Elatif Badr3 | ||||
| 1Electrical Information Department, Ministry of Electricity and Renewable Energy, Cairo, Egypt | ||||
| 2Electrical Power and Machines Engineering Department, Ain Shams University, Cairo, Egypt | ||||
| 3Electrical Power and Machines Engineering Department, Ain Shams University, Cairo, Egypt2 | ||||
| Abstract | ||||
| More growth of wind power generation that will be established in Egypt in the coming years has highlighted the importance of wind power prediction. However, wind power is very difficult for modelling and forecasting. Despite the performed research works in the area, more efficient wind power forecast methods are still demanded. In this paper, two methods of prediction of electric power generation from wind power are presented. The first method is by using the artificial neural network for prediction of power generation in the next 10 minutes base on wind speed prediction input from weather authorities. The second method is by using poly fit function to perform regression on wind power by using MATLAB program in Zafarana site. For optimum generation management strategy, the capacity credit will be used by the best selected method of prediction of the wind power for Gabal El-zeit site of future wind farm. | ||||
| Keywords | ||||
| Wind power forecast; Artificial Neural network (ANN); Poly fit function; Capacity Credit | ||||
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