新型电力系统与综合能源

大规模电网机组组合状态迭代路径搜索优化方法

  • 崔一阳 ,
  • 潘斗南 ,
  • 黎灿兵 ,
  • 刘健哲
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  • 上海交通大学 a. 国家电投智慧能源创新学院; b. 电子信息与电气工程学院,上海 200240
崔一阳(2000—),硕士生,从事电力系统优化调度研究.
黎灿兵,教授,博士生导师;E-mail:licanbing@sjtu.edu.cn.

收稿日期: 2024-07-29

  录用日期: 2024-09-12

  网络出版日期: 2024-10-08

基金资助

国家重点研发计划资助项目(2022YFB2404200)

An Optimization Method for Iteration Path Search of Large-Scale Power Grid Unit Commitment State

  • CUI Yiyang ,
  • PAN Dounan ,
  • LI Canbing ,
  • LIU Jianzhe
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  • a. College of Smart Energy; b. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received date: 2024-07-29

  Accepted date: 2024-09-12

  Online published: 2024-10-08

摘要

针对大规模电网机组组合问题中传统分支定界法计算量随计算规模指数级增长的“维数灾”问题,提出一种机组组合状态迭代路径搜索优化方法.为避免简化问题和缩减可行域导致最优解丢失,将机组状态方案的确定划分为深度遍历与广度迭代双阶段进行;在优选初始解的基础上,以机组动态优先顺序表作为机组状态迭代路径的搜索方向,通过深度遍历确定最佳关停冗余机组及对应关停时刻,并利用广度迭代拓展问题可行域以提高解的最优性.IEEE 118和ACTIVSg10k系统上的测试结果表明,所提方法能够缩小问题规模,减少机组状态尝试数,实现机组状态的高效搜索迭代,计算速度快、效率高,对大规模机组组合优化问题求解具有一定实用性和有效性.

本文引用格式

崔一阳 , 潘斗南 , 黎灿兵 , 刘健哲 . 大规模电网机组组合状态迭代路径搜索优化方法[J]. 上海交通大学学报, 2025 , 59(6) : 711 -719 . DOI: 10.16183/j.cnki.jsjtu.2024.301

Abstract

To address the computational challenge posed by the “curse of dimensionality” inherent in traditional branch and bound algorithms for large-scale power grid unit commitment problems, an optimization method for iteration path search of unit commitment state is proposed. To prevent the loss of the optimal solution due to the simplification of the problem and the reduction of the feasible region, the determination of the unit state scheme is divided into a two-stage process of depth traverse and breadth iteration. Based on an initial solution, the unit dynamic priority list is used as the search direction for the unit state iteration path. In deep traverse stage, the optimal shutdown redundant units and their corresponding shutdown time are determined. Breadth iteration is then used to expand the feasible region of the problem to improve the optimality of the solution. The results of a comparative case study conducted on the IEEE 118 system and ACTIVSg10k system indicate that the proposed method effectively reduces the scale of the problem, minimizes the number of unit state attempts, and achieves efficient search and iteration of unit states, exhibiting fast computational speed, high efficiency, which has practical applicability for solving problems of large-scale unit commitment.

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