Generator maintenance schedule of hydro-thermal power systems considering randomness of natural water inflow

被引:0
|
作者
Dai J. [1 ]
Tian N. [1 ]
Jiang Y. [1 ]
Zheng Z. [2 ]
Liu M. [2 ]
Xie M. [2 ]
机构
[1] Electric Power Dispatching and Control Center of Guizhou Power Grid Co., Ltd., Guiyang
[2] School of Electric Power Engineering, South China University of Technology, Guangzhou
基金
中国国家自然科学基金;
关键词
generator maintenance schedule; hydro-thermal power system; multi-disciplinary collaborative optimization; nonanticipative constraints; scenario-based method;
D O I
10.19783/j.cnki.pspc.211035
中图分类号
学科分类号
摘要
How to rationally arrange maintenance of generators is an important task in the dispatch and operation of hydro-thermal power systems. On a long timescale, the randomness of natural water inflow makes the generator maintenance schedule (GMS) essentially a stochastic optimization problem. The scenario-based method is usually used to describe the randomness, but it is difficult to solve efficiently the high-dimensional optimization problem with this method. This paper establishes a coupled multi-scenario GMS model of hydro-thermal power systems, applies a multi-disciplinary collaborative optimization (MCO) method to decouple the nonanticipative and the coupling constraints on maintenance variables between scenarios. Thus, the dimension of the multi-scenario GMS model is reduced and the MCO-based structure has inherent parallelism. In addition, in the MCO-based system-level optimization problem, an absolute value penalty term is introduced to replace the quadratic penalty term to ensure that the problem is a mixed integer linear programming model. This helps improve computational efficiency. Finally, a simulation calculation on a real provincial hydro-thermal power system is carried out to verify the effectiveness of the model and algorithm proposed. © 2022 Power System Protection and Control Press. All rights reserved.
引用
收藏
页码:44 / 53
页数:9
相关论文
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