Modeling passive variable pitch cross flow hydrokinetic turbines to maximize performance and smooth operation

L Lazauskas, BK Kirke - Renewable energy, 2012 - Elsevier
L Lazauskas, BK Kirke
Renewable energy, 2012Elsevier
Darrieus type hydrokinetic turbines (HKTs) with fixed pitch blades, like their wind turbine
equivalents, exhibit poor starting torque whether blades are straight, troposkein or helical.
High solidity improves starting torque to some extent but reduces peak efficiency. Straight
blade turbines have been observed to shake violently due to cyclical hydrodynamic forces
on blades. To solve this problem, the computer program VAWTEX-B was used to model
blade forces and to predict how variable pitch might reduce shaking while maintaining …
Darrieus type hydrokinetic turbines (HKTs) with fixed pitch blades, like their wind turbine equivalents, exhibit poor starting torque whether blades are straight, troposkein or helical. High solidity improves starting torque to some extent but reduces peak efficiency. Straight blade turbines have been observed to shake violently due to cyclical hydrodynamic forces on blades. To solve this problem, the computer program VAWTEX-B was used to model blade forces and to predict how variable pitch might reduce shaking while maintaining strong starting torque and high peak efficiency Cpmax. A memetic algorithm was developed to search for optimum pitching parameters to achieve these objectives. Five optimization objectives were initially used, to maximize starting torque and Cpmax, to minimize downstream and the side force fluctuations causing shaking, and to minimize a function combining these four variables. A second optimization used a different objective function incorporating Cpmax and then minimizing a shaking force parameter while allowing a small reduction in CPmax. Modeling predicted reduced shaking while maintaining starting torque and peak efficiency well above those achievable with fixed pitch, and only slightly lower than the maxima achievable with variable pitch.
Elsevier
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