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A novel review on optimization techniques used in wind farm modelling

The important interest and efforts devoted by industries and academic research institutions to electricity production from renewable and clean energy with the maturity of existed technologies justify the biggest exploitation of wind energy over the recent years. With the reduction in oil prices, ren...

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Detalles Bibliográficos
Autores principales: Balasubramanian, Karthik, Thanikanti, Sudhakar Babu, Subramaniam, Umashankar, N., Sudhakar, Sichilalu, Sam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7494509/
http://dx.doi.org/10.1016/j.ref.2020.09.001
Descripción
Sumario:The important interest and efforts devoted by industries and academic research institutions to electricity production from renewable and clean energy with the maturity of existed technologies justify the biggest exploitation of wind energy over the recent years. With the reduction in oil prices, renewable energy is way forward for efficient and environment friendly energy generation. Out of all existing available renewable energy, Wind Energy is the front runner owing to its ability of efficient power generation and to produce energy at large scale. Due to the non linear nature of wind energy, Optimization techniques are extremely critical as they are solely responsible for building an effective wind farm. Layout optimization is performed by using soft computing techniques and are extensively studied in the available literature. Therefore, this review paper highlights the significant research works of wind farm modelling using optimization techniques. This work also addresses the new approaches used in wind farm modelling. Further, it also presents a critical evaluation of existing research methodologies used for wind farm layout optimization. Hence, the objective of this work is to benefit scientists and new entrants in the field of modelling and layout optimization of the wind farm.