Optimal Preventive Maintenance Scheduling for Wind Turbines under Condition Monitoring

Quanjiang Yu, Pramod Bangalore, Sara Fogelström and Serik Sagitov ()
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Quanjiang Yu: Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, SE-42196 Gothenburg, Sweden
Pramod Bangalore: Greenbyte AB, SE-41109 Gothenburg, Sweden
Sara Fogelström: Department of Electrical Engineering, Chalmers University of Technology, SE-42196 Gothenburg, Sweden
Serik Sagitov: Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, SE-42196 Gothenburg, Sweden

Energies, 2024, vol. 17, issue 2, 1-16

Abstract: 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.

Keywords: preventive maintenance; linear programming; Cox proportional hazards; wind turbine; Weibull survival function (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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