Multi-objective optimization of the operation and maintenance assets of an offshore wind farm using genetic algorithms. Issue 4 (August 2020)

• Record Type: Journal Article
• Authors: Rinaldi, Giovanni; Pillai, Ajit C; Thies, Philipp R; Johanning, Lars
• Is Part Of: Wind engineering. Volume 44:Issue 4(2020)
• Page Start: 390
• Page End: 409
• Publication Date: 2020-08
• Subjects: Operation and maintenance -- offshore wind -- genetic algorithm -- optimization -- decision-making; Wind-pressure -- Periodicals; Winds -- Periodicals; Wind power -- Periodicals; Engineering meteorology -- Periodicals; Pression du vent; Vents; Énergie éolienne; Météorologie appliquée; Engineering meteorology; Wind power; Wind-pressure; Winds; Periodicals; 621.4505
• DOI: 10.1177/0309524X19849826
• Languages: English
• ISSNs: 0309-524X

Abstract

This article explores the use of genetic algorithms to optimize the operation and maintenance assets of an offshore wind farm. Three different methods are implemented in order to demonstrate the approach. The optimization problem simultaneously considers both the reliability characteristics of the offshore wind turbines and the composition of the maintenance fleet, seeking to identify the optimal configurations for the strategic assets. These are evaluated in order to minimize the operating costs of the offshore farm while maximizing both its reliability and availability. The considerations used for the application of genetic algorithms as an effective way to support the assets management are described, and a case study to show the applicability of the approach is presented. The variation of the economic performance indicators as a consequence of the optimization procedure is discussed, and the implementation of this method in a wider computational framework for the operation and maintenance assets improvement is introduced.