Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm

Irawan, Chandra Ade; Eskandarpour, Majid; Ouelhadj, Djamila; Jones, Dylan

Document type :

Compte-rendu et recension critique d'ouvrage

DOI :

10.1016/j.ejor.2019.08.032

Title :

Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm

Author(s) :

Irawan, Chandra Ade [Auteur]
Eskandarpour, Majid [Auteur]
Institut de Recherche en Communications et en Cybernétique de Nantes [IRCCyN]
Lille économie management - UMR 9221 [LEM]
Ouelhadj, Djamila [Auteur]
Jones, Dylan [Auteur]
Department of Physics [Toronto]

Journal title :

European Journal of Operational Research

Publisher :

Elsevier

Publication date :

2019-08-20

ISSN :

0377-2217

English keyword(s) :

Stochastic routing
Maintenance
Offshore windfarm

HAL domain(s) :

Sciences de l'Homme et Société/Gestion et management

English abstract : [en]

Scheduling maintenance routing for an offshore wind farm is a challenging and complex task. The problem is to find the best routes for the Crew Transfer Vessels to maintain the turbines in order to minimise the total cost. ...
Show more >Scheduling maintenance routing for an offshore wind farm is a challenging and complex task. The problem is to find the best routes for the Crew Transfer Vessels to maintain the turbines in order to minimise the total cost. This paper primarily proposes an efficient solution method to solve the deterministic maintenance routing problem in an offshore wind farm. The proposed solution method is based on the Large Neighbourhood Search metaheuristic. The efficiency of the proposed metaheuristic is validated against state of the art algorithms. The results obtained from the computational experiments validate the effectiveness of the proposed method. In addition, as the maintenance activities are affected by uncertain conditions, a simulation-based optimisation algorithm is developed to tackle these uncertainties. This algorithm benefits from the fast computational time and solution quality of the proposed metaheuristic, combined with Monte Carlo simulation. The uncertain factors considered include the travel time for a vessel to visit turbines, the required time to maintain a turbine, and the transfer time for technicians and equipment to a turbine. Moreover, the proposed simulation-based optimisation algorithm is devised to tackle unpredictable broken-down turbines. The performance of this algorithm is evaluated using a case study based on a reference wind farm scenario developed in the EU FP7 LEANWIND project.Show less >

Language :

Anglais

Popular science :

Non

Collections :

Lille Économie Management (LEM) - UMR 9221

Source :

Harvested from HAL

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