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• W4313216213 abstract "This paper studies the coordinated optimization between generator maintenance scheduling and long-term unit commitment in hydrothermal power systems, which can deal with the increased conflicts between these two tasks brought on by the extensive integration of cascade hydropower, but encounters difficulty in finding solutions when the system scale is large. A coordinated optimization model between hydrothermal generator maintenance scheduling and long-term unit commitment is proposed, in which the network security constraints and coupling characteristics between cascade hydro plants are considered. To accelerate the solution of this complex mixed-integer linear programming problem, an improved two-stage heuristic algorithm based on the objective scaling ensemble approach is proposed. The first stage is a detection process in which a maintenance interval detection strategy is used to probe the maintenance variables to be fixed. The second stage is a fix-and-solve process in which the reduced model is solved after fixing the maintenance variables detected at the first stage. Finally, simulations on a modified IEEE 30-bus and 6-unit hydrothermal power system and a real 1348-bus and 155-unit hydrothermal power system are conducted, focusing on the solution quality and the acceleration effect of the proposed algorithms, as well as the results of the proposed model. The numerical results reveal that the proposed algorithm can speed up the process of finding a near-optimal solution for large-scale systems through a detection strategy with high accuracy and efficiency. The proposed model can plan out feasible and coordinated maintenance scheduling and long-term unit commitment scheme simultaneously." @default.
• W4313216213 created "2023-01-06" @default.
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• W4313216213 date "2023-05-01" @default.
• W4313216213 modified "2023-09-27" @default.
• W4313216213 title "A mathematical programming–based heuristic for coordinated hydrothermal generator maintenance scheduling and long-term unit commitment" @default.
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• W4313216213 doi "https://doi.org/10.1016/j.ijepes.2022.108833" @default.
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