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。为避免简化问题缩减可行域导致的最优解丢失，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。

To address the computational challenge known as "curse of dimensionality" inherent in traditional branch and bound algorithms for large-scale power grid unit commitment problem, an optimization method for unit commitment state iteration path search is proposed. To avoid the loss of the optimal solution caused by simplifying the problem and reducing the feasible region, the determination of the unit state scheme is divided into two stages: deep traverse and breadth iteration. On the basis of initial solution, the unit dynamic priority list is used as the search direction for the unit state iteration path. Through deep traverse, the optimal shutdown redundant unit and corresponding shutdown time are determined, and breadth iteration is used to expand the feasible region of the problem to improve the optimality of the solution. A comparative case study is conducted on IEEE 118 system and ACTIVSg10k system. The results indicate that the proposed method can reduce the scale of the problem, decrease the number of unit state attempts, and achieve efficient search iteration of the unit state, exhibiting fast computational speed and high efficiency, and demonstrating practicality and effectiveness in solving large-scale unit commitment problems.