Onshore wind farms usually consist of numerous horizontal axis wind turbines closely placed in clusters, and they are often cited on complex terrain. This paper proposes a computational framework for modeling and simulation of wind flow over micro-scale (and early meso-scale) wind farms using distributed memory, massively parallel high performance computing platforms. The present framework uses the Reynolds Averaged Navier–Stokes (RANS) to model the wind flow over the wind farms, as the flow is considered to be fully turbulent, isothermal and incompressible. The wind turbines installed in the wind farm are modeled by the virtual blade model (VBM). This technique considers the presence of a wind turbine's rotor implicitly through momentum sources placed in an actuator disc, yielding indirectly a pressure jump across the disk, which varies with its radius and azimuth. The nonlinear, aerodynamic interaction between the rotor wakes with each other and with the terrain of the wind farm is simulated by coupling the VBM with the governing flow field equations. In this manner, an efficient parallel algorithm for implementing the VBM was developed and integrated with parallel computational fluid dynamics (CFD) core simulation engine. The accuracy and performance of the proposed framework were confirmed through several test cases carried out on the IBM Blue Gene ultra-scale supercomputer.
Modeling and Simulation of a 12 MW Active-Stall Constant-Speed Wind Farm