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Preventive maintenance is essential for the reliable operation of hydroelectric systems. However, maintenance planning is a complex activity since outages of hydro-turbines for maintenance can impact hydropower operation costs. In addition, operation costs are also determined by physical laws governing water and electricity, uncertain water precipitations and interdependencies between short-term decisions and long-term operations. In this project, we propose to develop and implement mathematical optimization techniques for solving the maintenance-scheduling problem of the hydroelectric generators in Rio Tinto, a large aluminium producer in Québec. The solution of this problem could yield significant savings for the company as well as more efficient usage of hydroelectricity in Quebec.
Miguel Anjos
Jesus Rodriguez
Rio Tinto Alcan
Mathematics
Energy
Accelerate
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