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CFD-AI modelling and optimizing of vertical axis wind turbine with two co-axial rotors
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DOI：10.1177/0309524X261436761.png)
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Abstract
En 中文
Vertical axis wind turbines (VAWTs) offer attractive features such as independence from wind direction, low-noise operation, and suitability for wind speed at urban areas. For straight bladed VAWTs, the power coefficient typically reaches its maximum and then decreases. Thus, a VAWT with two half-height coaxial rotors arranged at different phase angles is proposed. The above proposed coaxial rotor is modelled and optimized by the combination of computational fluid dynamics (CFD), artificial neural networks (ANN), and genetic algorithm (GA). Based on 180 CFD simulation results as initial input for ANN, the optimization results showed rotor diameter of 2.5 m, a phase difference of 60 degrees, an airfoil chord length of 0.213 m, and a tip speed ratio of 2.3 as the optimum values of decision variables. Under these conditions, the average power coefficient reaches 0.319, which is approximately 15.1% higher than that of a H-type VAWT with the same overall height (0.277).
Keywords:
vertical axis wind turbine (VAWT)
co-axial rotors
computational fluid dynamics (CFD)
neural network method
genetic algorithm (GA)
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