Presentations - WindEurope Annual Event 2024

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Development and verification of a discrete event simulation tool for high-fidelity modelling of offshore wind farm decommissioning campaigns

Simone Mancini, Project Manager | Wind Energy, TNO


As some early commercial-scale offshore wind farms (OWFs) in the North Sea region approach their twentieth anniversary, offshore wind decommissioning and end-of-life (EoL) research is gaining attention. Anticipating the sharp increase in volumes expected in the next decade, detailed decommissioning plans will have to be prepared in the next 2-5 years. So far, only small-scale wind farms consisting of relatively small turbines located in shallow, near-shore, or confined waters have been decommissioned. The limited experience and data available yield high uncertainty in the estimation of costs, duration, and environmental footprint of upcoming OWF decommissioning campaigns. Proposed figures range from ~250 k€/MW to ~500 k€/MW, but the uniqueness of each project's specifications and requirements makes it hard to come up with general numbers. In this context, high-fidelity logistic simulation tools as well as high-level cost models are both needed to support upcoming OWF EoL decision-making and decommissioning campaign planning. While several holistic cost models have been proposed, the OWF decommissioning literature lacks high-fidelity logistic models to support detailed project planning and execution. Such models allow taking into account offshore operation complexities like weather dependencies and resource constraints, which are not included or crudely approximated in holistic cost models, and thus enable the detailed assessment of alternative decommissioning method statements. To fill this gap, a new high-fidelity logistic simulation module has been developed within TNO's UWiSE discrete event simulation platform ( The new tool, named UWiSE Decommission, has been verified by modelling the decommissioning campaign of the Lincs OWF in the UK and comparing the results against estimates from the available decommissioning plan as well as cost model results from the literature.

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