Chapter 5
98 z0 ε μ μt μeff ρ σk σε Cε1, Cε2 Cμ, gi I y* z0 k
κ L p P ui ABL BCT BIM CIM CKC CTBUH ES ET FSP GT HOMER IFC JH OIFC RANS SMO TI WPD WRA
5.1
Aerodynamic roughness length [m] Turbulent energy dissipation rate Dynamic viscosity Turbulent viscosity Effective viscosity Density Turbulent constant, 1.0 Turbulent constant, 1.3 Turbulent constant, 1.44 Turbulent constant, 1.92 Turbulent constant, 0.09 Gravitational acceleration in the i axis Average turbulence intensity Dimensionless wall distance Aerodynamic roughness length [m] Turbulent kinetic energy von Karman constant Turbulence length scale [m] Pressure Turbulent production term Velocity component in the i axis Atmospheric boundary layer Bank of China Tower Building information modeling City information modeling Cheung Kong Center Council on Tall Buildings and Urban Habitat Exchange Square Edinburgh Tower Four Seasons Place Gloucester Tower Hybrid Optimization Model for Electric Renewables International Finance Centre Jardine House One International Finance Centre Reynolds-averaged Navier–Stokes Survey and Mapping Office Turbulence intensity Wind power density Wind resource assessment
Introduction
Wind power, and associated harnessing technologies, have become an imperative part of the renewable energy industry and the move towards a sustainable economy [4, 157-159]. Power that can be generated by harvesting wind within urban environments (hereafter, ‘urban wind energy’) is a promising energy source. However, it is currently not exploited because the wind speed distributions around buildings are highly complicated with great turbulence intensities (TIs) [8, 9, 160], and no studies have attempted to determine the optimal locations for wind turbines in such environments. Severe turbulence can make it very difficult to capture good-quality wind.
