Author
Listed:
- Martin Westbomke
(Institut für Integrierte Produktion Hannover)
- Jan-Hendrik Piel
(Leibniz University Hanover)
- Michael H. Breitner
(Leibniz University Hanover)
- Peter Nyhius
(Institut für Integrierte Produktion Hannover)
- Malte Stonis
(Institut für Integrierte Produktion Hannover)
Abstract
In average, more than 1,275 wind turbines were installed annually since 1997 in Germany and more than 27,000 wind turbines are in operation today. The technical and economic life time of wind turbines is around 20 to 25 years. Consequently, dismantling of aging wind turbines will increase significantly in upcoming years due to repowering or decommissioning of wind farms and lead to millions of costs for operators. An option to supersede the costly and time-consuming dismantling of wind turbines entirely on-site is to establish a dismantling network in which partly dismantled wind turbines are transported to specialized dismantling sites for further handling. This network requires an optimization model to determine optimal locations and an appropriate distribution of disassembly steps to dismantling sites. The challenge is to consider the networks dependency on the trade-off between transportation and dismantling costs which, in turn, depends on the selection of dismantling depths and sites. Building on the Koopmans-Beckmann problem, we present a mathematical optimization model to address the described location planning and allocation problem. To permit a proof-of-concept, we apply our model to a case-study of an exemplary wind farm in Northern Germany. Our results show that the model can assist dismantling companies to arrange efficient dismantling networks for wind turbines and to benefit from emerging economic advantages.
Suggested Citation
Martin Westbomke & Jan-Hendrik Piel & Michael H. Breitner & Peter Nyhius & Malte Stonis, 2018.
"An Optimization Model to Develop Efficient Dismantling Networks for Wind Turbines,"
Operations Research Proceedings, in: Natalia Kliewer & Jan Fabian Ehmke & Ralf Borndörfer (ed.), Operations Research Proceedings 2017, pages 239-244,
Springer.
Handle:
RePEc:spr:oprchp:978-3-319-89920-6_33
DOI: 10.1007/978-3-319-89920-6_33
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