Abstract

In Germany, more than one third of the installed wind energy capacity will leave the feed-in tariff funding between 2021 and 2025. Operators of affected turbines are therefore increasingly concerned with the design of profitable end-of-funding strategies. This requires feasibility analyses of both lifetime extension and repowering options and entails the subsequent challenge to determine the optimal lifetime extension and corresponding repowering timing. To support operators and other stakeholders dealing with wind turbines’ end-of-life issues, this study presents a geographic information system that permits evaluating optimal end-of-funding strategies at different spatial scales reaching down to detailed analyses on individual turbine level. The decision support system processes topographic, wind, turbine, and finance data in an integrated system of resource simulations, spatial planning analyses and economic viability assessments. Case-study results show that a uniform end-of-funding strategy cannot be applied to all ageing turbines. Conducted sensitivity analyses rather indicate that the best strategy highly depends on various turbine-specific aspects, especially the location, type and maintenance costs as well as exogenous factors, including the developments of electricity spot market prices and tendered feed-in premiums. In light of latest trends regarding the exogenous factors, lifetime extension and repowering potentials increase. However, the results also indicate that dismantling, disposal and recycling of numerous ageing turbines will become a major challenge for the wind energy sector in the next decade.

Details

Title
Lifetime Extension, Repowering or Decommissioning? Decision Support for Operators of Ageing Wind Turbines
Author
Piel, J H 1 ; Stetter, C 1 ; Heumann, M 2 ; Westbomke, M 3 ; Breitner, M H 2 

 Institut für Wirtschaftsinformatik, Leibniz Universit¨at Hannover, Königsworther Platz 1, 30167 Hannover, Germany; Nefino GmbH, c/o Leibniz Universit¨at Hannover, Königsworther Platz 1, 30167 Hannover, Germany 
 Institut für Wirtschaftsinformatik, Leibniz Universit¨at Hannover, Königsworther Platz 1, 30167 Hannover, Germany 
 Nefino GmbH, c/o Leibniz Universit¨at Hannover, Königsworther Platz 1, 30167 Hannover, Germany; Institut für Integrierte Produktion, Leibniz Universit¨at Hannover, Hollerithallee 6, 30419 Hannover, Germany 
Publication year
2019
Publication date
May 2019
Publisher
IOP Publishing
ISSN
17426588
e-ISSN
17426596
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2566165017
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.