Title of article :
Assessment of optimum tip speed ratio in wind turbines using artificial neural networks
Author/Authors :
M.A. Yurdusev، نويسنده , , R. Ata، نويسنده , , N.S. Cetin، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2006
Pages :
9
From page :
2153
To page :
2161
Abstract :
Wind turbine blade design depends on several factors, such as turbine profile used, blade number, power factor, and tip speed ratio. The key to designing a wind turbine is to assess the optimal tip speed ratio (TSR). This will directly affect the power generated and, in turn, the effectiveness of the investment made. TSR is suggested to be taken between 7 and 8 and in practice generally taken as 7 for a 3-blade network-connected wind turbine. However, the optimal TSR is dependent upon the profile type used and the blade number and could fall out of the boundaries suggested. Therefore, it has to be assessed accordingly. In this study, the optimal TSR and the power factor of a wind turbine are predicted using artificial neural networks (ANN) based on the parameters involved for NACA 4415 and LS-1 profile types with 3 and 4 blades. The ANN structure built is found to be more successful than the conventional approach in estimating the TSR and power factor.
Keywords :
Wind Energy , Neural networks , Tip speed ratio , wind turbine , power factor
Journal title :
Energy
Serial Year :
2006
Journal title :
Energy
Record number :
416878
Link To Document :
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