全球能源互联网（英文）2021，Vol.4Issue(5)：493-500,8.DOI:10.14171/j.2096-5117.gei.2021.05.006
一种基于贝叶斯优化的输电线路检修优化加速求解方法
Accelerated solution of the transmission maintenance schedule problem: a Bayesian optimization approach
摘要
Abstract
To maximize the maintenance willingness of the owner of transmission lines, this study presents a transmission maintenance scheduling model that considers the energy constraints of the power system and the security constraints of on-site maintenance operations. Considering the computational complexity of the mixed integer programming (MIP) problem, a machine learning (ML) approach is presented to solve the transmission maintenance scheduling model efficiently. The value of the branching score factor value is optimized by Bayesian optimization (BO) in the proposed algorithm, which plays an important role in the size of the branch-and-bound search tree in the solution process. The test case in a modified version of the IEEE 30-bus system shows that the proposed algorithm can not only reach the optimal solution but also improve the computational efficiency.关键词
输电维护调度/混合整数规划/机器学习/贝叶斯优化/分支和定界Key words
Transmission maintenance scheduling/Mixed integer programming (MIP)/Machine learning/Bayesian optimization (BO)/Branch-and-bound引用本文复制引用
梅竞成,张国江,齐冬莲,张建良..一种基于贝叶斯优化的输电线路检修优化加速求解方法[J].全球能源互联网（英文）,2021,4(5):493-500,8.基金项目
This work was supported by the National Key Research and Development Program of China(Basic Research Class)(No.2017YFB0903000)and the National Natural Science Foundation of China(No.U1909201). （Basic Research Class）
