Towards the Optimal Performance of Vertical Wind Turbine: Numerical Simulation and Experimental Validation

Abstract

In this thesis, the role of active blade pitching on vertical axis wind turbine (VAWTs) technology is investigated under several turbine design parameters, i.e., geometrical (different number and aerofoil thickness, solidity) and operational conditions like Reynolds number (𝑅𝑒), tip speed ratio (TSR). This research mainly focuses towards identifying the flow-sensitive design parameters that can eliminate the dead band issue of wind turbines operating in low wind speed regions. The performance was evaluated utilizing high fidelity computational and low fidelity numerical approach. An analytical model was developed using the double multiple stream tube (DMST) method by integrating blade element with momentum theories. In addition, a high-fidelity URANS CFD model was set up to study the performance of H-rotor VAWTs. Active blade pitching was integrated in both models. The results were initially compared well with experimental literature data. The results indicate that the local widening of the angle of attack as function of azimuth position was very effective in performance enhancement as it minimizes boundary layer separation and maximizes the lift/torque force during the complete cyclic operation. The dead band issue of wind turbines at low TSR (1-3) can be eliminated by either adding a number of blades, increasing blade chord length, and reducing the rotor radius. Moreover, the investigation also shows that the pitching algorithm was very effective for three and four bladed rotor design to achieve maximum possible torque. The effect of varying aerofoil profiles, aspect ratio, solidity, and the number of aerofoil was also investigated, targeting the improvement in the self-starting of VAWTs for regions with low wind speed. The results obtained from soap film provided high-resolution information of boundary layer formation around variable pitching aerofoil that demonstrated the physics of flow behind the blades of VAWTs experiencing low performance.

Date of Award	Dec 2022
Original language	American English
Supervisor	Isam Janajreh (Supervisor)