Open AccessEngineering an optimal wind farm using surrogate models
Author(s) -
Mahulja Stjepan,
Larsen Gunner Chr.,
Elham Ali
Publication year - 2018
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.2255
Subject(s) - surrogate model , mathematical optimization , profit (economics) , net present value , optimal design , wind power , engineering , operations research , computer science , marine engineering , mathematics , economics , machine learning , microeconomics , production (economics) , electrical engineering
A framework for optimal design of wind farm layouts using a surrogate‐based Dynamic Wake Meandering model is presented. The optimization platform is set‐up as a hybrid strategy combining genetic search with the gradient‐based algorithm. The design variables are the number of turbines in the layout and their relative position within the bounded area. The objective function is defined as the net present value of the wind farm's profit, thus including the relevant expenditures throughout the farm's lifespan. Results show that an optimal design is reached by maximizing investment and accepting a minor sacrifice of the wind farm performance.