Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 347-369 |
| Seitenumfang | 23 |
| Fachzeitschrift | Mechanical Systems and Signal Processing |
| Jahrgang | 104 |
| Frühes Online-Datum | 10 Nov. 2017 |
| Publikationsstatus | Veröffentlicht - 1 Mai 2018 |
Abstract
Offshore wind farm is an emerging source of renewable energy, which has been shown to have tremendous potential in recent years. In this blooming area, a key challenge is that the preventive maintenance of offshore turbines should be scheduled reasonably to satisfy the power supply without failure. In this direction, two significant goals should be considered simultaneously as a trade-off. One is to maximise the system reliability and the other is to minimise the maintenance related cost. Thus, a non-linear multi-objective programming model is proposed including two newly defined objectives with thirteen families of constraints suitable for the preventive maintenance of offshore wind farms. In order to solve our model effectively, the nondominated sorting genetic algorithm II, especially for the multi-objective optimisation is utilised and Pareto-optimal solutions of schedules can be obtained to offer adequate support to decision-makers. Finally, an example is given to illustrate the performances of the devised model and algorithm, and explore the relationships of the two targets with the help of a contrast model.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
- Informatik (insg.)
- Signalverarbeitung
- Ingenieurwesen (insg.)
- Tief- und Ingenieurbau
- Ingenieurwesen (insg.)
- Luft- und Raumfahrttechnik
- Ingenieurwesen (insg.)
- Maschinenbau
- Informatik (insg.)
- Angewandte Informatik
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in: Mechanical Systems and Signal Processing, Jahrgang 104, 01.05.2018, S. 347-369.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Constrained non-linear multi-objective optimisation of preventive maintenance scheduling for offshore wind farms
AU - Zhong, Shuya
AU - Pantelous, Athanasios A.
AU - Beer, Michael
AU - Zhou, Jian
N1 - Funding information: The authors would like to thank the anonymous reviewers for their insightful comments that significantly improved the quality of this paper. Moreover, the gracious supports of the EPSRC and ESRC Centre for Doctoral Training on Quantification and Management of Risk and Uncertainty in Complex Systems and Environment (EP/L015927/1), the Recruitment Program of High-end Foreign Experts (Grant No. GDW20163100009), and the China Scholarship Council ([2014]3026) should be acknowledged.
PY - 2018/5/1
Y1 - 2018/5/1
N2 - Offshore wind farm is an emerging source of renewable energy, which has been shown to have tremendous potential in recent years. In this blooming area, a key challenge is that the preventive maintenance of offshore turbines should be scheduled reasonably to satisfy the power supply without failure. In this direction, two significant goals should be considered simultaneously as a trade-off. One is to maximise the system reliability and the other is to minimise the maintenance related cost. Thus, a non-linear multi-objective programming model is proposed including two newly defined objectives with thirteen families of constraints suitable for the preventive maintenance of offshore wind farms. In order to solve our model effectively, the nondominated sorting genetic algorithm II, especially for the multi-objective optimisation is utilised and Pareto-optimal solutions of schedules can be obtained to offer adequate support to decision-makers. Finally, an example is given to illustrate the performances of the devised model and algorithm, and explore the relationships of the two targets with the help of a contrast model.
AB - Offshore wind farm is an emerging source of renewable energy, which has been shown to have tremendous potential in recent years. In this blooming area, a key challenge is that the preventive maintenance of offshore turbines should be scheduled reasonably to satisfy the power supply without failure. In this direction, two significant goals should be considered simultaneously as a trade-off. One is to maximise the system reliability and the other is to minimise the maintenance related cost. Thus, a non-linear multi-objective programming model is proposed including two newly defined objectives with thirteen families of constraints suitable for the preventive maintenance of offshore wind farms. In order to solve our model effectively, the nondominated sorting genetic algorithm II, especially for the multi-objective optimisation is utilised and Pareto-optimal solutions of schedules can be obtained to offer adequate support to decision-makers. Finally, an example is given to illustrate the performances of the devised model and algorithm, and explore the relationships of the two targets with the help of a contrast model.
KW - Cost parameters
KW - Maintenance
KW - Multi-objective Programming
KW - Offshore wind farms
KW - Reliability
KW - Scheduling
UR - http://www.scopus.com/inward/record.url?scp=85037808208&partnerID=8YFLogxK
U2 - 10.1016/j.ymssp.2017.10.035
DO - 10.1016/j.ymssp.2017.10.035
M3 - Article
AN - SCOPUS:85037808208
VL - 104
SP - 347
EP - 369
JO - Mechanical Systems and Signal Processing
JF - Mechanical Systems and Signal Processing
SN - 0888-3270
ER -