  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. %In these two case studies, the costs are reduced by around. 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.
