Constrained-based discrete-event simulation of an assembly job shop in the offshore wind industry

2020 ◽  
Author(s):  
A. Lamas-Rodríguez ◽  
J. Pernas-Álvarez ◽  
I. Taracido-López
Keyword(s):  
Discrete Event Simulation ◽  
Job Shop ◽  
Discrete Event ◽  
Offshore Wind ◽  
Event Simulation ◽  
Offshore Wind Industry

scholarly journals Evaluation of the Impact of Weather-Related Limitations on the Installation of Offshore Wind Turbine Towers

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3778
Author(s):  
Stephan Oelker ◽  
Aljoscha Sander ◽  
Markus Kreutz ◽  
Abderrahim Ait-Alla ◽  
Michael Freitag
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Weather Conditions ◽  
Tuned Mass Damper ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Measurement Campaign ◽  
Event Simulation ◽  
Mass Damper ◽  
Wave Heights

Weather conditions have a significant impact on the installation of offshore wind turbines. The rules for installation set clear limits. These limits are usually based on estimations of various experts and not on real assumptions and measurements on-site. When wind speeds and wave heights are too high, work cannot be carried out, and this leads to delays and additional costs. Therefore, we have carried out a measurement campaign during the installation of rotor blades to investigate to which extent the limits can be adjusted by using a tuned mass damper. The results from the measurement campaign—specifically empirically derived significant wave height limits—are used in a discrete event simulation. This study simulates delays resulting from weather conditions. Based on this, the total installation costs are considered. The results of the measurement campaign show that a safe installation with the use of a damper is possible at wave heights of up to 1.6 m. With the discrete event simulation, it is possible to prove that 17.9% can be saved for the costs of the installation vessel. In addition, the wind farm could be erected 32 days faster. Thus, it can be stated that the use of a tuned mass damper simplifies the installation from a technical point of view and is economical.

scholarly journals Implementing ManPy, a Semantic-free Open-source Discrete Event Simulation Package, in a Job Shop

Procedia CIRP ◽  
2014 ◽  
Vol 25 ◽  
pp. 253-260 ◽  
Author(s):  
Oladipupo Olaitan ◽  
John Geraghty ◽  
Paul Young ◽  
Georgios Dagkakis ◽  
Cathal Heavey ◽  
...  
Keyword(s):  
Open Source ◽  
Discrete Event Simulation ◽  
Job Shop ◽  
Discrete Event ◽  
Event Simulation ◽  
Free Open Source ◽  
Simulation Package

scholarly journals Improving the Installation of Offshore Wind Farms by the use of Discrete Event Simulation

2015 ◽  
Author(s):  
Yohannes T. Muhabie ◽  
Jean-David Caprace ◽  
Cristian Petcu ◽  
Philippe Rigo
Keyword(s):  
Discrete Event Simulation ◽  
Wind Farm ◽  
Discrete Event ◽  
Probabilistic Approach ◽  
Wind Farms ◽  
Distance Matrix ◽  
Offshore Wind ◽  
Weather Data ◽  
The Real ◽  
Event Simulation

The offshore wind energy development is highly affected by the condition of the weather at sea. Hence, it demands a well-organized planning of the overall process starting from the producers’ sites until the offshore site where the turbines will finally be installed. The planning phase can be supported with the help of Discrete Event Simulation (DES) where weather restrictions, distance matrix, vessel characteristics and assembly scenarios are taken into account. The purpose of this paper is to simulate the overall transport, assembly and installation of the wind turbine components at sea. The analysis is carried out through DES considering both the real historical weather data (wind speed and wave height) and probabilistic approach. Results of the study, applied to the real Offshore Wind Farm (OWF) configuration, are showing a good agreement between the two proposed models. The results point out that the probabilistic\ approach is highly affected by the semi-random numbers used to model the stochastic behavior of the input variable so that several iterations (200 to 400) are required to reach the convergence of the simulation outputs. We suggest that seasonality of the outputs of both models are preserved, i.e. the variation of the results depending on the variation of the weather along the year. These findings provide a new framework to address risks and uncertainties in OWF installations.

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