Abstract. Global warming has been attributed to increased greenhouse gas emission concentrations in the atmosphere through the burning of fossil fuels. Renewable energy, as an alternative, is capable of displacing energy from fossil fuels. Wind power is abundant, renewable, and produces almost no greenhouse gas during operation. A large part of the cost of operations is due to the cost of maintaining the wind power equipment, especially for offshore wind farms. How to reduce the maintenance cost is what this article focus on. This article presents a binary linear optimisation model whose solution may suggest wind turbine owners which components, and when, should undergo the next preventive maintenance (PM). The 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 treating the restored components to be as good as new. The optimisation model NextPM is tested through three numerical case studies. The first study addresses the illuminating case of a single component system. The second study analyses the case of seasonal variations of set-up costs, as compared to the constant set-up cost setting. Among other things, this analysis reveals a dramatic cost reduction achieved by the NextPM model as compared to the the pure CM strategy. In these two case studies, the cost are reduced by around 35 %. The third case study compares the NextPM model with another optimisation model 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 more effective. In conclusion, the NextPM model is both accurate and fast to solve. The algorithm stemming from the proposed model can be used as a key module in a maintenance scheduling app.
Optimal scheduling of the next preventive maintenance activity for a
wind farm
