Vertical axis wind turbines (VAWTs) are compact, costless, less noisy and operate at low cut-in wind speed, which are promising for applications in urban environment. Their performance could be further improved by coupling with each other constructively in clusters. The first section of this research work focuses on optimizing the layout of turbine clusters that contain three Savonius wind turbines for development of compact and efficient VAWT wind farms. A rigorous parallel Genetic Algorithm (GA) combined with two-dimensional (2D) computational fluid dynamics (CFD) is utilized to maximize the power output. The optimal turbine cluster is improved significantly by 36.8% in terms of ensemble-averaged power coefficient (C͠_p) compared to an isolated Savonius turbine at TSR = 0.8. Mo...[ Read more ]

Vertical axis wind turbines (VAWTs) are compact, costless, less noisy and operate at low cut-in wind speed, which are promising for applications in urban environment. Their performance could be further improved by coupling with each other constructively in clusters. The first section of this research work focuses on optimizing the layout of turbine clusters that contain three Savonius wind turbines for development of compact and efficient VAWT wind farms. A rigorous parallel Genetic Algorithm (GA) combined with two-dimensional (2D) computational fluid dynamics (CFD) is utilized to maximize the power output. The optimal turbine cluster is improved significantly by 36.8% in terms of ensemble-averaged power coefficient (C͠_p) compared to an isolated Savonius turbine at TSR = 0.8. Moreover, three coupling mechanisms causing constructive interactions are proposed based on aerodynamic forces on blades and flow structures. In terms of applications, a wind farm consisting of 12 turbines (4 clusters) is proposed by expanding the optimal cluster as a basic unit in lateral directions based on the coupling mechanisms, which achieves 30% increase in C͠_p compared to an isolated Savonius wind turbine. It is observed from the wind farm that local blockage effect and oncoming flow deflection is critical that influences turbines’ efficiency. In the second section of this work, linear Savonius wind farms are investigated focusing on the effect of interaxial distance, number of turbines, rotational direction of turbines and phase angle shift, with an objective of further studying the local blockage effect. It is shown that an 8-turbine linear wind farm from Layout D is improved significantly in terms of C͠_p. Limiting numbers of turbines for efficient and economic wind farms are also identified and recommended.