2019
DOI: 10.3390/app9235030
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Evaluation of Loading Bay Restrictions for the Installation of Offshore Wind Farms Using a Combination of Mixed-Integer Linear Programming and Model Predictive Control

Abstract: Featured Application: This article demonstrates a combination of Mixed-Integer LinearProgramming with methods usually applied for short-term control, namely the Model Predictive Control scheme, to achieve decision support for the scheduling of installation activities for offshore wind farms. The general approach applies to several areas of application, where time-dependent uncertainties complicate mid-to long-term planning.Abstract: The installation of offshore wind farms poses particular challenges due to exp… Show more

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Cited by 10 publications
(2 citation statements)
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“…They can inquire the external framework which of these to choose for the next iteration. In general, the model contains various functions to estimate the duration of operations given a weather forecast and the operations' weather limits as proposed in the literature [17].…”
Section: Simulation Modelmentioning
confidence: 99%
See 1 more Smart Citation
“…They can inquire the external framework which of these to choose for the next iteration. In general, the model contains various functions to estimate the duration of operations given a weather forecast and the operations' weather limits as proposed in the literature [17].…”
Section: Simulation Modelmentioning
confidence: 99%
“…Afterward, it SNE 32(3) -9/2022 iterates through the database, selecting each year Y s in the database and a viable number of historical years Y N ∈ {0, 1, 2, 5, 10, 20} and calculates the mean value and hourly standard deviation. The framework again estimates the duration of installation operations using the Markov-Chain-based approach described in [17] using these values as input. Finally, it calculates the Pearson-Correlation Coefficient between these sets and the last three months to decide for a constellation that matches the current data as good as possible.…”
Section: Simulation Modelmentioning
confidence: 99%