A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations
| Autor: | Diclehan Tezcaner Öztürk, Kerem Akartunali, Evangelos Boulougouris, Matthew Revie, Euan Barlow, Alexander Day |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Schedule
Information Systems and Management General Computer Science Process (engineering) Computer science 020209 energy Operations Research & Management Science TK 020208 electrical & electronic engineering 02 engineering and technology Management Science and Operations Research Asset (computer security) Investment (macroeconomics) Industrial engineering Industrial and Manufacturing Engineering Management Offshore wind power Modeling and Simulation Component (UML) Business & Economics 0202 electrical engineering electronic engineering information engineering HD28 Operations management Duration (project management) |
| ISSN: | 0377-2217 |
| Popis: | With a typical investment in excess of 100 million for each project, the installation phase of offshore wind farms (OWFs) is an area where substantial cost-reductions can be achieved; however, to-date there have been relatively few studies exploring this. In this paper, we develop a mixed-method framework which exploits the complementary strengths of two decision-support methods: discrete-event simulation and robust optimisation. The simulation component allows developers to estimate the impact of user defined asset selections on the likely cost and duration of the full or partial completion of the installation process. The optimisation component provides developers with an installation schedule that is robust to changes in operation durations due to weather uncertainties. The combined framework provides a decision-support tool which enhances the individual capability of both models by feedback channels between the two, and provides a mechanism to address current OWF installation projects. The combined framework, verified and validated by external experts, was applied to an installation case study to illustrate the application of the combined approach. An installation schedule was identified which accounted for seasonal uncertainties and optimised the ordering of activities. (C) 2017 Elsevier B.V. All rights reserved. University of Strathclyde Technology and Innovation Centre |
| Databáze: | OpenAIRE |
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