A reliability-and-cost-based fuzzy approach to optimize preventive maintenance scheduling for offshore wind farms

Shuya Zhong, Athanasios A. Pantelous, Mark Goh, Jian Zhou

Research output: Contribution to journalArticleResearchpeer-review

Abstract

We study the preventive maintenance scheduling problem of wind farms in the offshore wind energy sector which operates under uncertainty due to the state of the ocean and market demand. We formulate a fuzzy multi-objective non-linear chance-constrained programming model with newly-defined reliability and cost criteria and constraints to obtain satisfying schedules for wind turbine maintenance. To solve the optimization model, a 2-phase solution framework integrating the operational law for fuzzy arithmetic and the non-dominated sorting genetic algorithm II for multi-objective programming is developed. Pareto-optimal solutions of the schedules are obtained to form the trade-offs between the reliability maximization and cost minimization objectives. A numerical example is illustrated to validate the model.

Original languageEnglish
Pages (from-to)643-663
Number of pages21
JournalMechanical Systems and Signal Processing
Volume124
DOIs
Publication statusPublished - 1 Jun 2019

Keywords

  • Fuzzy chance-constrained programming
  • Fuzzy multi-objective programming
  • Maintenance cost
  • Offshore wind energy
  • Preventive maintenance scheduling
  • Reliability

Cite this

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title = "A reliability-and-cost-based fuzzy approach to optimize preventive maintenance scheduling for offshore wind farms",
abstract = "We study the preventive maintenance scheduling problem of wind farms in the offshore wind energy sector which operates under uncertainty due to the state of the ocean and market demand. We formulate a fuzzy multi-objective non-linear chance-constrained programming model with newly-defined reliability and cost criteria and constraints to obtain satisfying schedules for wind turbine maintenance. To solve the optimization model, a 2-phase solution framework integrating the operational law for fuzzy arithmetic and the non-dominated sorting genetic algorithm II for multi-objective programming is developed. Pareto-optimal solutions of the schedules are obtained to form the trade-offs between the reliability maximization and cost minimization objectives. A numerical example is illustrated to validate the model.",
keywords = "Fuzzy chance-constrained programming, Fuzzy multi-objective programming, Maintenance cost, Offshore wind energy, Preventive maintenance scheduling, Reliability",
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A reliability-and-cost-based fuzzy approach to optimize preventive maintenance scheduling for offshore wind farms. / Zhong, Shuya; Pantelous, Athanasios A.; Goh, Mark; Zhou, Jian.

In: Mechanical Systems and Signal Processing, Vol. 124, 01.06.2019, p. 643-663.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - A reliability-and-cost-based fuzzy approach to optimize preventive maintenance scheduling for offshore wind farms

AU - Zhong, Shuya

AU - Pantelous, Athanasios A.

AU - Goh, Mark

AU - Zhou, Jian

PY - 2019/6/1

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N2 - We study the preventive maintenance scheduling problem of wind farms in the offshore wind energy sector which operates under uncertainty due to the state of the ocean and market demand. We formulate a fuzzy multi-objective non-linear chance-constrained programming model with newly-defined reliability and cost criteria and constraints to obtain satisfying schedules for wind turbine maintenance. To solve the optimization model, a 2-phase solution framework integrating the operational law for fuzzy arithmetic and the non-dominated sorting genetic algorithm II for multi-objective programming is developed. Pareto-optimal solutions of the schedules are obtained to form the trade-offs between the reliability maximization and cost minimization objectives. A numerical example is illustrated to validate the model.

AB - We study the preventive maintenance scheduling problem of wind farms in the offshore wind energy sector which operates under uncertainty due to the state of the ocean and market demand. We formulate a fuzzy multi-objective non-linear chance-constrained programming model with newly-defined reliability and cost criteria and constraints to obtain satisfying schedules for wind turbine maintenance. To solve the optimization model, a 2-phase solution framework integrating the operational law for fuzzy arithmetic and the non-dominated sorting genetic algorithm II for multi-objective programming is developed. Pareto-optimal solutions of the schedules are obtained to form the trade-offs between the reliability maximization and cost minimization objectives. A numerical example is illustrated to validate the model.

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KW - Fuzzy multi-objective programming

KW - Maintenance cost

KW - Offshore wind energy

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