The study presented here uses Computational Fluid Dynamics (CFD) models and a development of the Blade Element Momentum (BEM) approach to evaluate the effect of rotor solidity on the performance of a three-bladed H-Darrieus vertical axis wind turbine (VAWT), particularly during its critical starting phase. BEM based models (for example the Double Multiple Stream Tube model) require low computational effort but are unable to provide information about the turbine dynamic start-up process or about the flow structure around the blades. Conversely CFD methods provide detail of the flow structure but are computationally expensive. In this study, an advanced BEM model, the Start-Up model, has been developed which is able to model the turbine dynamic start-up process under different wind and geometric parameters. The developments presented here are supported by 2-D CFD simulations. In this study, the predicted turbine tip speed ratio (TSR) versus power coefficient (Cp) curves from the enhanced BEM approach are compared directly with the CFD results and show good agreement. The study highlights that turbines with larger solidity, which is a function of the ratio of blade chord to turbine rotor radius, (σ = nc/R), demonstrate better self-starting capability at the expense of lower peak efficiency. It is also observed that for a given solidity, turbines with larger blade chord length and correspondingly larger rotor radius have better performance over the entire working range. A comparison between selected aerofoil sections demonstrated that the DU 06 W200 aerofoil section, designed specifically for VAWT application and having 20% thickness with 0.8% camber, has slightly better performance at low tip speed ratio compared with the widely adopted symmetric NACA0018 and NACA0021 sections which themselves have proven self-starting capability. It is also demonstrated using the BEM model that the predicted turbine performance is highly sensitive to the accuracy of aerofoil performance data. The acquisition and publication of extensive, high quality data over the full-range of incidence that is experienced during VAWT start-up and at appropriate Reynolds numbers is shown to be a high priority for predicting turbine performance accurately.

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