用于分析不可行联合输配电网网络的分布式原对偶内点框架
Distributed Primal-Dual Interior Point Framework for Analyzing Infeasible Combined Transmission and Distribution Grid Networks
AI总结：
针对互联输配电网的不可行分析问题，提出基于GJN的分布式原对偶内点优化算法，能隔离薄弱节点并在70k+节点网络上优于ADMM方法。
摘要：
分布式能源的激增加剧了输电与配电（T&D）系统之间的交互，需要对互联T&D网络的可靠运行和规划进行新的分析。一个关键的空白是一种能够识别和定位联合T&D网络中薄弱环节的分析方法，为系统规划者和运营商提供有价值的信息。研究目标是利用统一的求解算法，高效地建模和仿真不可行（即在一般设置下无法求解）的联合正序输电和三相配电网络。我们采用等效电路公式对联合T&D网络进行建模。为了求解整体T&D网络，我们构建了基于Gauss-Jacobi-Newton（GJN）的分布式原对偶内点优化算法，该算法能够隔离薄弱节点。我们在具有70k+输电和15k+配电节点的大型联合T&D网络上验证了该方法，并展示了其相对于交替方向乘子法（ADMM）的性能提升。
英文摘要：
The proliferation of distributed energy resources has heightened the interactions between transmission and distribution (T&D) systems, necessitating novel analyses for the reliable operation and planning of interconnected T&D networks. A critical gap is an analysis approach that identifies and localizes the weak spots in the combined T\&D networks, providing valuable information to system planners and operators. The research goal is to efficiently model and simulate infeasible (i.e. unsolvable in general settings) combined positive sequence transmission and three-phase distribution networks with a unified solution algorithm. We model the combined T&D network with the equivalent circuit formulation. To solve the overall T&D network, we build a Gauss-Jacobi-Newton (GJN) based distributed primal dual interior point optimization algorithm capable of isolating weak nodes. We validate the approach on large combined T&D networks with 70k+ T and 15k+ D nodes and demonstrate performance improvement over the alternating direction method of multipliers (ADMM) method.
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