A Differential Evolution Algorithm for Wind Farm Layout Optimization Using a New Bilevel Programming Model

2022 ◽  
pp. 584-596
Author(s):  
Lijuan Chen ◽  
Hecheng Li ◽  
Yu Shen
Keyword(s):  
Differential Evolution ◽  
Bilevel Programming ◽  
Wind Farm ◽  
Programming Model ◽  
Differential Evolution Algorithm ◽  
Layout Optimization ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization ◽  
Evolution Algorithm ◽  
Bilevel Programming Model

scholarly journals Numerical data concerning wind farm layout optimization using differential evolution algorithm at different wind speeds

Data in Brief ◽  
2017 ◽  
Vol 15 ◽  
pp. 244-248
Author(s):  
Shafiq-ur-Rehman Massan ◽  
Asim Imdad Wagan ◽  
Muhammad Mujtaba Shaikh ◽  
Muhammad Saleh Shah
Keyword(s):  
Differential Evolution ◽  
Wind Farm ◽  
Differential Evolution Algorithm ◽  
Numerical Data ◽  
Layout Optimization ◽  
Wind Farm Layout ◽  
Wind Speeds ◽  
Wind Farm Layout Optimization ◽  
Evolution Algorithm

Offshore Wind Farm Layout Optimization via Differential Evolution

2018 ◽  
Vol 22 (3) ◽  
Author(s):  
José Valentín Osuna Enciso ◽  
José Israel Espinoza Haro ◽  
Diego Oliva ◽  
Irán Fernando Hernández Ahuactzi
Keyword(s):  
Differential Evolution ◽  
Wind Farm ◽  
Layout Optimization ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization

Large Wind Farm Layout Optimization Using Nature Inspired Meta-Heuristic Algorithms

2021 ◽  
pp. 1-18
Author(s):  
Sanjeev K. Aggarwal ◽  
Lalit M. Saini ◽  
Vijay Sood
Keyword(s):  
Wind Farm ◽  
Heuristic Algorithms ◽  
Layout Optimization ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization ◽  
Large Wind

A Comparative Study of the Influence of Different Wake Models on Wind Farm Layout Optimization

2021 ◽  
Author(s):  
Puyi Yang ◽  
Hamidreza Najafi
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Vital Role ◽  
Layout Optimization ◽  
Zone Model ◽  
Wind Farm Layout ◽  
Yaw Control ◽  
Wind Farm Layout Optimization ◽  
Wake Model ◽  
Large Wind

Abstract The accuracy of analytical wake models applied in wind farm layout optimization (WFLO) problems plays a vital role in the present era that the high-fidelity methods such as LES and RANS are still not able to handle an optimization problem for large wind farms. Based on a verity of analytical wake models developed in the past decades, FLOw Redirection and Induction in Steady State (FLORIS) has been published as a tool integrated several widely used wake models and the expansions for them. This paper compares four wake models selected from FLORIS by applying three classical WFLO scenarios. The results illustrate that the Jensen wake model is the fastest one but the defect of underestimation of velocity deficit is obvious. The Multi Zone model needs to be applied additional tunning on the parameters inside the model to fit specific wind turbines. The Gaussian-Curl wake model as an advanced expansion of the Gaussian wake model does not perform an observable improvement in the current study that the yaw control is not included. The default Gaussian wake model is recommended to be used in the WFLO projects which implemented under the FLROIS framework and has similar wind conditions with the present work.

Double-stage genetic algorithm for wind farm layout optimization on complex terrains

2014 ◽  
Vol 6 (3) ◽  
pp. 033127 ◽  
Author(s):  
Goran Dobrić ◽  
Željko Đurišić
Keyword(s):  
Genetic Algorithm ◽  
Wind Farm ◽  
Layout Optimization ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization
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