Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/108011
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Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Lückehe, D. | - |
dc.contributor.author | Wagner, M. | - |
dc.contributor.author | Kramer, O. | - |
dc.contributor.editor | Silva, S. | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Proceedings of the 2015 on Genetic and Evolutionary Computation Conference, 2015 / Silva, S. (ed./s), pp.1223-1230 | - |
dc.identifier.isbn | 9781450334723 | - |
dc.identifier.uri | http://hdl.handle.net/2440/108011 | - |
dc.description.abstract | Wind turbine placement, i.e., the geographical planning of wind turbine locations, is an important first step to an efficient integration of wind energy. The turbine placement problem becomes a difficult optimization problem due to varying wind distributions at different locations and due to the mutual interference in the wind field known as wake effect. Artificial and environmental geological constraints make the optimization problem even more difficult to solve. In our paper, we focus on the evolutionary turbine placement based on an enhanced wake effect model fed with real-world wind distributions. We model geo-constraints with realworld data from OpenStreetMap. Besides the realistic modeling of wakes and geo-constraints, the focus of the paper is on the comparison of various evolutionary optimization approaches. We propose four variants of evolution strategies with turbine-oriented mutation operators and compare to state-of-the-art optimizers like the CMA-ES in a detailed experimental analysis on three benchmark scenarios. | - |
dc.description.statementofresponsibility | Daniel Lückehe, Markus Wagner, Oliver Kramer | - |
dc.language.iso | en | - |
dc.publisher | ACM press | - |
dc.relation.ispartofseries | GECCO ’15 | - |
dc.rights | ©2015 ACM | - |
dc.source.uri | http://doi.acm.org/10.1145/2739480.2754690 | - |
dc.subject | Wind Power; Wind Farm Layout; Evolutionary Optimization; Self-Adaptation; CMA-ES | - |
dc.title | On evolutionary approaches to wind turbine placement with geo-constraints | - |
dc.type | Conference paper | - |
dc.contributor.conference | Annual Conference on Genetic and Evolutionary Computation (GECCO) (11 Jul 2015 - 15 Jul 2015 : Madrid, Spain) | - |
dc.identifier.doi | 10.1145/2739480.2754690 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Wagner, M. [0000-0002-3124-0061] | - |
Appears in Collections: | Aurora harvest 8 Computer Science publications |
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File | Description | Size | Format | |
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RA_hdl_108011.pdf Restricted Access | Restricted Access | 4.24 MB | Adobe PDF | View/Open |
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