The optimal transmission switching problem (OTSP) is an established problem of changing a power grid's topology to obtain an improved operation by controlling the switching status of transmission lines. This problem was proven to be NP-hard. Thus, different solution techniques have been proposed, that each has its advantages. These include mixed-integer formulations, which can be solved using branch-and-bound algorithms to obtain global optimal solutions, as well as heuristics methods. Whether optimal solutions can be found, however, largely depends on the specific size of a problem instance. In this paper, we solve the full OTSP alongside reduced instances of it. A parallel algorithmic architecture is proposed where full OTSP formulation is run in parallel to another process that generates solutions to be injected into the solution procedure of the full OTSP during run time. Our method is tested on 14 instances from the pglib-opf library --the largest problem consisting of 13659 buses and 20467 branches. Our results show a good performance for large problem instances. If no optimal solution can be obtained for a test case within a few seconds, improvements can be reported consistently over off-the-shelf solvers' stock performance.

中文翻译：

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最优传输切换问题求解：并行化和基准测试

最优输电切换问题 (OTSP) 是通过控制输电线路的切换状态来改变电网拓扑以获得改进运行的既定问题。这个问题被证明是 NP-hard 问题。因此，已经提出了不同的解决方案技术，每种技术都有其优点。这些包括混合整数公式，可以使用分支定界算法求解以获得全局最优解，以及启发式方法。然而，能否找到最优解，很大程度上取决于问题实例的具体大小。在本文中，我们解决了完整的 OTSP 及其减少的实例。提出了一种并行算法架构，其中完整的 OTSP 公式与另一个过程并行运行，该过程生成要在运行时注入完整 OTSP 的求解过程的解决方案。我们的方法在 pglib-opf 库中的 14 个实例上进行了测试——最大的问题包括 13659 条总线和 20467 个分支。我们的结果显示了对大型问题实例的良好性能。如果在几秒钟内无法为测试用例获得最佳解决方案，则可以一致地报告对现成求解器的库存性能的改进。