Title of article :
COMPARISON BETWEEN TWO METHODS OF PREDICTION OF ELECTRIC POWER GENERATION FROM WIND POWER
Author/Authors :
el-mahlawy, mohamed ahmed ministry of electricity and renewable energy - electrical information department, Egypt , mekhamer, said fouad ain shams university - electrical power and machines engineering department, Egypt , badr, mohamed abd-elatif ain shams university - electrical power and machines engineering department, Egypt
From page :
159
To page :
163
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
Journal title :
Journal of Al Azhar University Engineering Sector (JAUES)
Journal title :
Journal of Al Azhar University Engineering Sector (JAUES)
Record number :
2649687
Link To Document :
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