Mathematical Optimization and Algorithms for Offshore Wind Farm Design: An Overview
Abstract
Wind energy is a fast evolving field that has attracted a lot of attention and investments in the last decades. Being an increasingly competitive market, it is very important to minimize establishment costs and increase production profits already at the design phase of new wind parks. This paper is based on many years of collaboration with Vattenfall, a leading wind energy developer and wind power operator, and aims at giving an overview of the experience of using Mathematical Optimization in the field. The paper illustrates some of the practical needs defined by energy companies, showing how optimization can help the designers to increase production and reduce costs in the design of offshore parks. In particular, the study gives an overview of the individual phases of designing an offshore wind farm, and some of the optimization problems involved. Finally it goes in depth with three of the most important optimization tasks: turbine location, electrical cable routing and foundation optimization. The paper is concluded with a discussion of future challenges.
- Citation
- BibTeX
Fischetti, M. & Pisinger, D.,
(2019).
Mathematical Optimization and Algorithms for Offshore Wind Farm Design: An Overview.
Business & Information Systems Engineering: Vol. 61, No. 4.
Springer.
(S. 469-485).
DOI: 10.1007/s12599-018-0538-0
@article{mci/Fischetti2019,
author = {Fischetti, Martina AND Pisinger, David},
title = {Mathematical Optimization and Algorithms for Offshore Wind Farm Design: An Overview},
journal = {Business & Information Systems Engineering},
volume = {61},
number = {4},
year = {2019},
,
pages = { 469-485 } ,
doi = { 10.1007/s12599-018-0538-0 }
}
author = {Fischetti, Martina AND Pisinger, David},
title = {Mathematical Optimization and Algorithms for Offshore Wind Farm Design: An Overview},
journal = {Business & Information Systems Engineering},
volume = {61},
number = {4},
year = {2019},
,
pages = { 469-485 } ,
doi = { 10.1007/s12599-018-0538-0 }
}
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More Info
ISSN: 1867-0202
xmlui.MetaDataDisplay.field.date: 2019
Content Type: Text/Journal Article