Open-Source Web-Based Planning Support Application for Wind Farm Layout

This work presents an open-source and web-based application to optimise wind farm layouts. Despite recent progress in wind farm layout optimisation research, a gap remains in translating research into practical and widely accessible tools. In this context, the proposed application offers a comprehensive and user-friendly framework to support wind farm designers in the planning process. By integrating global wind data, the application optimises wind farm layouts with the Genetic Algorithm to maximise annual energy production. Additionally, it presents a detailed summary of energy production and efficiency, facilitating effective planning practices.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-16
DOI
https://doi.org/10.5281/zenodo.15231037
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
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article

Open-Source Web-Based Planning Support Application for Wind Farm Layout

Zenodo (CERN European Organization for Nuclear Research)
Wind Energy Research and Development
article

Open-Source Web-Based Planning Support Application for Wind Farm Layout

article en

Abstract

This work presents an open-source and web-based application to optimise wind farm layouts. Despite recent progress in wind farm layout optimisation research, a gap remains in translating research into practical and widely accessible tools. In this context, the proposed application offers a comprehensive and user-friendly framework to support wind farm designers in the planning process. By integrating global wind data, the application optimises wind farm layouts with the Genetic Algorithm to maximise annual energy production. Additionally, it presents a detailed summary of energy production and efficiency, facilitating effective planning practices.

Zenodo (CERN European Organization for Nuclear Research)
University College London (GB)
Affordable and clean energy
Openalex Percentile: Top 39%
Wind Energy Research and Development
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