期刊
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
卷 147, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2022.108833
关键词
Maintenance scheduling; Long -term unit commitment; Coordinated optimization; Cascade hydropower; Heuristic algorithm
This paper proposes a coordinated optimization model between hydrothermal generator maintenance scheduling and long-term unit commitment, considering the network security constraints and coupling characteristics between cascade hydro plants. An improved two-stage heuristic algorithm based on the objective scaling ensemble approach is proposed to accelerate the solution of this complex problem. Simulation results show that the proposed algorithm can speed up the process of finding a near-optimal solution for large-scale systems, and the proposed model can plan out feasible and coordinated maintenance scheduling and long-term unit commitment scheme simultaneously.
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-andsolve 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.
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