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.
Notes
SWT-2.3-93 Turbine, Technical Specications. http://www.energy.siemens.com.
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Acknowledgments
The research of the second author was supported by Miur (Project PRIN 2012) and by the University of Padova (Progetto di Ateneo “Exploiting randomness in Mixed Integer Linear Programming”). We thank Jakob Stoustrup and John Leth (Automation and Control, Department of Electronic Systems, Aalborg University) who supervised the thesis work of first author in Aalborg, and Benjamin Martinez (R&D Wind Engineer, Vattenfall AB) who provided the real-world wind scenarios used in our tests. Thanks are also due to three anonymous referees for their helpful comments.
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Fischetti, M., Monaci, M. Proximity search heuristics for wind farm optimal layout. J Heuristics 22, 459–474 (2016). https://doi.org/10.1007/s10732-015-9283-4
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DOI: https://doi.org/10.1007/s10732-015-9283-4