Engineering an optimal wind farm using surrogate models: EOWF using SUMO

Research output: Contribution to journalJournal article – Annual report year: 2018Researchpeer-review

DOI

View graph of relations

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.
Original languageEnglish
JournalWind Energy
Volume21
Issue number12
Pages (from-to)1296-1308
ISSN1095-4244
DOIs
Publication statusPublished - 2018
CitationsWeb of Science® Times Cited: No match on DOI
Download as:
Download as PDF
Select render style:
APAAuthorCBE/CSEHarvardMLAStandardVancouverShortLong
PDF
Download as HTML
Select render style:
APAAuthorCBE/CSEHarvardMLAStandardVancouverShortLong
HTML
Download as Word
Select render style:
APAAuthorCBE/CSEHarvardMLAStandardVancouverShortLong
Word

ID: 152195928