考虑数据中心负载灵活迁移特性的主动配电网阻塞管理

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中图分类号：TM72 文献标志码：A

Abstract：To address the congestion problem in distribution networks caused by high penetration of renewable energy and uneven spatial distribution of data center workload，a two-stage hierarchical congestion management method based on a model-data hybrid-driven approach is proposed. In the first stage，considering the regulation capabilities of resources such as on-load tap changers and shunt capacitor banks in the active distribution network，a long-timescale congestion management method based on direct resource control is established and optimized using a data-driven deep reinforcement learning algorithm to adjust their switching positions. In the second stage，a short-timescale congestion management method for the active distribution network is developed based on the flexible migration characteristics of data center cluster workload. This method integrates dynamic frequency regulation technology and dynamic server configuration technology of data centers with flexible workload migration characteristics，and employs a model-driven second-order cone programming algorithm to optimize renewable energy inverters and workload migration. Test results on a modified IEEE 33-node system show that the proposed two-stage congestion management method can effectively alleviate line congestion， reducing the maximum branch load ratio from 139.59% to 83.92% on the test day. Compared with traditional optimization methods，the proposed method shortens the solution time to 18.73 s with only a 0.8% cost increase，demonstrating better solution efficiency and robustness，and achieving friendly and coordinated interaction between data center clusters and the active distribution network.

Keywords： active distribution network；data center； congestion management； hybrid modeldata method

随着分布式新能源在配电网中的大规模接入，传统配电网将逐渐向主动配电网转变[1]。（剩余18652字）