Solving the problem of optimizing wind farm design using genetic algorithms
Renewable energies have become a topic of great interest in recent years because the natural sources used for the generation of these energies are inexhaustible and non-polluting. In fact, environmental sustainability requires a considerable reduction in the use of fossil fuels, which are highly pol...
- Autores:
-
amelec, viloria
Nuñez Lobo, Hugo
Pineda, Omar
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2020
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7967
- Acceso en línea:
- https://hdl.handle.net/11323/7967
https://doi.org/10.1088/1757-899X/872/1/012029
https://repositorio.cuc.edu.co/
- Palabra clave:
- Wind Turbines
Wind Fields
Wake Effect
Combinatorial Optimization
Genetic Algorithms
- Rights
- openAccess
- License
- CC0 1.0 Universal
| Summary: | Renewable energies have become a topic of great interest in recent years because the natural sources used for the generation of these energies are inexhaustible and non-polluting. In fact, environmental sustainability requires a considerable reduction in the use of fossil fuels, which are highly polluting and unsustainable [1]. In addition, serious environmental pollution is threatening human health, and many public concerns have been raised [2]. As a result, many countries have proposed ambitious plans for the production of green energy, including wind power, and consequently, the market for wind energy is expanding rapidly worldwide [3]. In this research, an evolutionary metaheuristic is implemented, specifically genetic algorithms. |
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