Proximity search heuristics for wind farm optimal layout

Martina Fischetti; Michele Monaci

doi:10.1007/s10732-015-9283-4

Proximity search heuristics for wind farm optimal layout

Martina Fischetti, Michele Monaci

University of Padua

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Abstract

A heuristic framework for turbine layout optimization in a wind farm is proposed that combines ad-hoc heuristics and mixed-integer linear programming. In our framework, large-scale mixed-integer programming models are used to iteratively refine the current best solution according to the recently-proposed proximity search paradigm. Computational results on very large scale instances involving up to 20,000 potential turbine sites prove the practical viability of the overall approach.

Original language	English
Journal	Journal of Heuristics
Volume	22
Issue number	4
Pages (from-to)	459–474
ISSN	1381-1231
DOIs	https://doi.org/10.1007/s10732-015-9283-4
Publication status	Published - 2016

Keywords

Heuristics
Mixed integer linear programming
Wind farm optimization
Electric utilities
Heuristic algorithms
Heuristic programming
Optimization
Turbines
Wind power
Ad-hoc heuristics
Computational results
Mixed integer programming model
Search heuristics
Turbine layouts
Wind farm
Integer programming

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Proxy wind farms JOH rev2Accepted author manuscript, 536 KB

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title = "Proximity search heuristics for wind farm optimal layout",

abstract = "A heuristic framework for turbine layout optimization in a wind farm is proposed that combines ad-hoc heuristics and mixed-integer linear programming. In our framework, large-scale mixed-integer programming models are used to iteratively refine the current best solution according to the recently-proposed proximity search paradigm. Computational results on very large scale instances involving up to 20,000 potential turbine sites prove the practical viability of the overall approach.",

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AU - Monaci, Michele

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AB - A heuristic framework for turbine layout optimization in a wind farm is proposed that combines ad-hoc heuristics and mixed-integer linear programming. In our framework, large-scale mixed-integer programming models are used to iteratively refine the current best solution according to the recently-proposed proximity search paradigm. Computational results on very large scale instances involving up to 20,000 potential turbine sites prove the practical viability of the overall approach.

KW - Heuristics

KW - Mixed integer linear programming

KW - Wind farm optimization

KW - Electric utilities

KW - Heuristic algorithms

KW - Heuristic programming

KW - Optimization

KW - Turbines

KW - Wind power

KW - Ad-hoc heuristics

KW - Computational results

KW - Mixed integer programming model

KW - Search heuristics

KW - Turbine layouts

KW - Wind farm

KW - Integer programming

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SP - 459

EP - 474

JO - Journal of Heuristics

JF - Journal of Heuristics

IS - 4

ER -

Proximity search heuristics for wind farm optimal layout

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