Multi-objective optimization of the operation and maintenance assets of an offshore wind farm using genetic algorithms

Giovanni Rinaldi*, Ajit C. Pillai, Philipp R. Thies, Lars Johanning

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)390-409
Number of pages20
JournalWind Engineering
Volume44
Issue number4
DOIs
Publication statusPublished - 1 Aug 2020

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology

Keywords

  • decision-making
  • genetic algorithm
  • offshore wind
  • Operation and maintenance
  • optimization

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