发表机构
EPB Quantum; Oak Ridge National Laboratory（EPB量子; 橡树岭国家实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出一种混合量子-经典算法，结合辐射状保持的支路交换编码与暖启动迭代QITE，在十个测试案例中实现六个最小损耗配置，其余损耗超参考值0.2%-2.18%。
AI 中文摘要
我们提出了一种用于配电网重构的混合量子-经典算法，这是一个电力配电网上的组合优化问题，该算法将保持辐射状的支路交换编码与迭代暖启动量子虚时演化相结合，以最小化有功线损。该编码采用固定宽度的二进制表示顺序支路交换动作，确保每个寄存器输出解码后都对应一个辐射状配置。量子子程序由拟合到经典求解的交流潮流（ACPF）标签上的代理模型提供信息。在消耗完预设的ACPF求解和电路采样预算后，算法返回所见到的损耗最低的配置。我们在十个测试案例上应用了我们的算法，包括七个常用基准案例和三个我们从这些及类似标准系统修改而来的案例。我们包含了两种减小问题规模的方法，这使得算法能够扩展到更大的网络。我们成功地在六个案例中达到了最小损耗配置，并在其余四个案例中找到了损耗比所报告的参考最小损耗高出0.2%至2.18%的配置。
英文摘要
We present a hybrid quantum-classical algorithm for distribution network reconfiguration, a combinatorial optimization problem on power distribution networks, that combines a radiality preserving branch-exchange encoding with iterative warm-start quantum imaginary-time evolution to minimize active line losses. The encoding uses a fixed-width binary representation of sequential branch-exchange actions, ensuring that every register outcome decodes to a radial configuration. The quantum subroutine is informed by a surrogate model fit to classically-solved alternating current power flow (ACPF) labels. After a set budget of ACPF solves and circuit samples is exhausted, the algorithm returns the lowest-loss configuration seen. We employ our algorithm on ten test cases, including seven commonly-used benchmark cases and three cases we modified from these and similar standard systems. We include two methods to reduce problem size, which enable extensions of the algorithm to larger networks. We successfully reach minimal-loss configurations for six cases and find configurations with losses from 0.2 percent to 2.18 percent above the reported reference minimal loss for the other four.
Comments23 pgs, 11 figures
