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

•Preventive maintenance of offshore wind farms is discussed in the fuzzy environment.•A fuzzy multi-objective non-linear chance-constrained programming model is proposed.•Reliability and cost goals, and constraints are newly defined for offshore scenario.•A 2-phase solution framework combining opera...

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Vydané v:Mechanical systems and signal processing Ročník 124; s. 643 - 663
Hlavní autori: Zhong, Shuya, Pantelous, Athanasios A., Goh, Mark, Zhou, Jian
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin Elsevier Ltd 01.06.2019
Elsevier BV
Predmet:
Classification
Fuzzy chance-constrained programming
Fuzzy multi-objective programming
Genetic algorithms
Maintenance cost
Maintenance management
Mathematical models
Mathematical programming
Multiple objective analysis
Offshore energy sources
Offshore wind energy
Optimization
Preventive maintenance
Preventive maintenance scheduling
Production scheduling
Reliability
Schedules
Scheduling
Sorting algorithms
Wind farms
Wind power
Wind power generation
Wind turbines
Maintenance cost
Fuzzy chance-constrained programming
Offshore wind energy
Preventive maintenance scheduling
Reliability
Fuzzy multi-objective programming
ISSN:0888-3270, 1096-1216
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Shrnutí:•Preventive maintenance of offshore wind farms is discussed in the fuzzy environment.•A fuzzy multi-objective non-linear chance-constrained programming model is proposed.•Reliability and cost goals, and constraints are newly defined for offshore scenario.•A 2-phase solution framework combining operational law and NSGA-II is developed.•Corrective maintenance cost is considered to get optimal solution and cost benefit. 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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0888-3270
1096-1216
DOI:10.1016/j.ymssp.2019.02.012