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During the life of a wind farm, various types of costs arise. A large share of the operational cost for a wind farm is due to maintenance of the wind turbine equipment; these costs are especially pronounced for offshore wind farms and provide business opportunities in the wind energy industry. An effective scheduling of the maintenance activities may reduce the costs related to maintenance. We combine mathematical modelling of preventive maintenance scheduling with corrective maintenance strategies. We further consider different types of contracts between the wind farm owner and a maintenance or insurance company, and during different phases of the turbines lives and the contract periods. Our combined preventive and corrective maintenance models are then applied to relevant combinations of the phases of the turbines lives and the contract types. Our case studies show that even with the same initial criteria, the optimal maintenance schedules differ between different phases of time as well as between contract types. One case study reveals a 40% cost reduction and a significantly higher production availability -- 1.8% points -- achieved by our optimization model as compared to a pure corrective maintenance strategy. Another study shows that the number of planned preventive maintenance occasions for a wind farm decreases with an increasing level of an insurance contract regarding reimbursement of costs for broken components.
We suggest a mathematical model for computing and regularly updating the next preventive maintenance plan for a wind farm. Our optimization criterium takes into account the current ages of the key components, the major maintenance costs including eve
In the wind energy industry, it is of great importance to develop models that accurately forecast the power output of a wind turbine, as such predictions are used for wind farm location assessment or power pricing and bidding, monitoring, and prevent
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We explore the use of deep reinforcement learning to provide strategies for long term scheduling of hydropower production. We consider a use-case where the aim is to optimise the yearly revenue given week-by-week inflows to the reservoir and electric
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