计及非线性灵活性聚合的输配电系统分布式协调
Distributed coordination for transmission-distribution systems with nonlinear flexibility aggregation
中文总结 AI 辅助
针对输配电一体化协调中线性模型的误判问题，本文提出分层优化框架下的非迭代预测-校正聚合方法，大幅降低了计算时间并提升了灵活性聚合的准确性。
中文摘要 AI 辅助
高比例分布式能源资源（DERs）使配电系统成为输配电一体化（ITD）运行的主动参与者。线性模型可实现配电层级灵活性聚合的可扩展性，但可能误判交流可行运行点；而直接非线性聚合成本高昂，尤其在多周期ITD协调中。本文在分层优化框架内重新构建输配电协调，提出一种非迭代预测-校正聚合方法，利用实时最优控制中的路径跟踪技术，该方法可实现可处理的计算并保证误差边界。在24个辐射型配电网案例及7个含真实KIT校园北区电网的网状变体案例中，所提方法的采样误判率与灵活性损失率均显著低于线性替代模型与凸松弛方法。在两个24周期ITD测试案例中，该方案通过降维，与对应集中式方案相比，端到端 wall-clock 时间减少了6倍。
英文摘要
High shares of distributed energy resources (DERs) transform distribution systems into active participants in integrated transmission and distribution (ITD) operations. Linear models enable scalable distribution-level flexibility aggregation but can misclassify AC feasible operating points, whereas direct nonlinear aggregation becomes costly, especially in multiperiod ITD coordination. This paper reformulates transmission-distribution coordination within a hierarchical optimization framework and introduces a non-iterative predictor-corrector aggregation method. By leveraging path-following techniques from real-time optimal control, the approach achieves tractable computation with guaranteed error bounds. Across 24 radial distribution-network cases and seven meshed variants, including the real KIT Campus North grid, the proposed method yields substantially lower sampled false- and lost-flexibility rates than linear surrogates and a convex relaxation. On two 24-period ITD testcases, the formulation reduces end-to-end wall-clock time by factors of 6 relative to the corresponding centralized formulation, primarily through dimensionality reduction.
