Wind farm layout optimization based on numerical simulations.
This work consists in developing a tool for wind farm layout optimization based on Computational Fluid Dynamics (CFD) simulations of the atmospheric wind flow and inter-turbine interference. Since it is not feasible to simulate a whole wind farm using the complete geometry of the wind turbines, the...
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| Formato: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | Brasil |
| Recursos: | Universidade de São Paulo (USP) |
| Repositorio: | Biblioteca Digital de Teses e Dissertações da USP |
| Idioma: | inglés |
| OAI Identifier: | oai:teses.usp.br:tde-28112019-145825 |
| Acesso em linha: | http://www.teses.usp.br/teses/disponiveis/3/3150/tde-28112019-145825/ |
| Access Level: | acceso abierto |
| Palavra-chave: | Actuator disk Algoritmos genéticos Dakota Dinâmica dos fluidos computacional Disco atuador Layout optimization OpenFOAM Otimização de layout Turbinas Wind turbine |
| Resumo: | This work consists in developing a tool for wind farm layout optimization based on Computational Fluid Dynamics (CFD) simulations of the atmospheric wind flow and inter-turbine interference. Since it is not feasible to simulate a whole wind farm using the complete geometry of the wind turbines, the need for models to represent their effects on the wind flow and the interference of one turbine on the others arises, and the most commonly used model is the Actuator Disk model and its variations. The procedure for wind turbine behavior evaluation using a CFD model was implemented in the OpenFOAM software, and this model was coupled with the Dakota optimization toolkit. A Genetic Algorithm was selected for the optimization task due to its robustness and the characteristics of the problem solved. With this new tool in hand, three different terrain cases were tested considering different numbers of turbines on a cylindrical domain in order to achieve the best wind farm layout in terms of AEP that respects the imposed physical restrictions. The optimization process was successful, leading to the maximization of the AEP. In addition, the algorithm correctly avoided the wakes generated by the upstream wind turbines for each case and was able to take advantage of the wake-terrain interaction during the optimization process. It was concluded that the results are promising despite the high computational resources required. |
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