Kirchner Bossi, NicolasPorté-Agel, Fernando2019-01-252019-01-252019-01-252018-12-0110.3390/en11123268https://infoscience.epfl.ch/handle/20.500.14299/154111WOS:000455358300029Wind Farm Layout Optimization (WFLO) can be useful to minimize power losses associated with turbine wakes in wind farms. This work presents a new evolutionary WFLO methodology integrated with a recently developed and successfully validated Gaussian wake model (Bastankhah and Porte-Agel model). Two different parametrizations of the evolutionary methodology are implemented, depending on if a baseline layout is considered or not. The proposed scheme is applied to two real wind farms, Horns Rev I (Denmark) and Princess Amalia (the Netherlands), and two different turbine models, V80-2MW and NREL-5MW. For comparison purposes, these four study cases are also optimized under the traditionally used top-hat wake model (Jensen model). A systematic overestimation of the wake losses by the Jensen model is confirmed herein. This allows it to attain bigger power output increases with respect to the baseline layouts (between 0.72% and 1.91%) compared to the solutions attained through the more realistic Gaussian model (0.24-0.95%). The proposed methodology is shown to outperform other recently developed layout optimization methods. Moreover, the electricity cable length needed to interconnect the turbines decreases up to 28.6% compared to the baseline layouts.Energy & FuelsEnergy & Fuelswind farm layout optimizationgaussian wake modelgenetic algorithmsevolutionary computationhorns revprincess amaliaturbine wakesoptimal placementturbulencesystemdesignflowspeedtext::journal::journal article::research article