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

Stjepan Mahulja, Gunner Chr. Larsen*, Ali Elham

*Corresponding author for this work

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    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

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