Optimal preventive maintenance scheduling for wind turbines under condition monitoring
Artikel i vetenskaplig tidskrift, 2024

Renewable energy sources, such as wind and solar, are positioned to play a pivotal role in future energy systems. In this paper, we propose a mathematical model for calculating and regularly updating the next preventive maintenance plan for a wind farm. Our optimization criterion considers various factors, including the current ages of key components, major maintenance costs, eventual energy production losses, and available data monitoring the condition of the wind turbines. Employing Cox proportional hazards analysis, we develop a comprehensive approach that accounts for the current ages of critical components, significant maintenance costs, potential energy production losses, and data collected from monitoring the condition of wind turbines. We illustrate the effectiveness of our approach through a case study based on data collected from multiple wind farms in Sweden. Our results demonstrate that preventive maintenance planning yields positive effects, particularly when the wind turbine components in question have significantly shorter lifespans than the turbine itself.

Wind turbine

Preventive maintenance

Linear programming

Cox proportional hazards

Weibull survival function

Författare

Quanjiang Yu

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

Pramod Bangalore

Chalmers, Data- och informationsteknik

Sara Fogelström

Chalmers, Elektroteknik, Elkraftteknik

Serik Sagitov

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Energies

1996-1073 (ISSN) 19961073 (eISSN)

Vol. 17 2 280

Site-specifika analysmetoder för att förutsäga och öka livstiden för vindturbiner

Svensk Vindkraftstekniskt Centrum (SWPTC), 2019-07-01 -- 2022-12-31.

Drivkrafter

Hållbar utveckling

Ämneskategorier

Beräkningsmatematik

Tillförlitlighets- och kvalitetsteknik

Styrkeområden

Energi

DOI

10.3390/en17020280

Mer information

Senast uppdaterat

2024-02-06