Optimal scheduling of the next preventive maintenance activity for a wind farm
Journal article, 2021

A large part of the operational cost for a wind power farm is due to the cost of equipment maintenance, especially for offshore wind farms. How to reduce the maintenance cost, and hence increase profitability, is this article’s focus. It presents a binary linear optimization model whose solution may suggest the wind turbine owners which components, and when, should undergo the next preventive maintenance (PM) replacements. The suggested short-term scheduling strategy takes into account eventual failure events of the multi-component system, in that after the failed system is repaired, the previously scheduled PM plan should be updated, assuming that the restored components are as good as new.
The optimization algorithm of this paper, NextPM, is tested through numerical case studies applied to a four component model of a wind turbine. The first study addresses the important case of a single component system, used for parameter calibration purposes. The second study analyses the case of seasonal variations of mobilization costs, as compared to the constant mobilization cost setting. Among other things, this analysis reveals a 35% cost reduction achieved by the NextPM model, as compared to the pure corrective maintenance (CM) strategy. The third case study compares the NextPM model with another optimization model - the preventive maintenance scheduling problem with interval costs (PMSPIC), which was the major source of inspiration for this article. This comparison demonstrates that the NextPM model is accurate and much faster in terms of computational time.

Age-based preventive maintenance scheduling

Wind turbine maintenance

Integer linear optimization


Quanjiang Yu

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Michael Patriksson

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Serik Sagitov

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Wind Energy Science

23667443 (ISSN) 23667451 (eISSN)

Vol. 6 3 949-959

Site-Adaptive Analysis Methods to Predict and Enhance Lifetime of Wind Turbines

Swedish Wind Power Technology Center (SWPTC), 2019-07-01 -- 2022-12-31.

Development of mathematical optimization models and methods towards a successful integration of production and condition-based multi-component maintenance in the wind power industry

Swedish Research Council (VR) (2014-5138), 2015-01-01 -- 2018-12-31.

Driving Forces

Sustainable development

Subject Categories

Computational Mathematics

Reliability and Maintenance

Areas of Advance




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7/2/2021 7