论文标题
分布式网络等效算法的收敛保证，用于分布
Convergence Guarantees of a Distributed Network Equivalence Algorithm for Distribution-OPF
论文作者
论文摘要
分布式能源资源的大规模整合改变了电源分配系统的运行需求，激发了基于优化的方法。所得最佳功率流（OPF）问题的增加的计算复杂性通常由近似或放松的模型管理。但是，它们可能导致不可行或不准确的解决方案。基于分解的方法也已用于解决OPF问题。但是现有的方法需要对相对较小的系统进行几个消息传递，从而导致决策延迟。相关基于反馈的方法还慢慢地跟踪了最佳解决方案。在本文中，我们提出了一种可证明的收敛分布式算法，以解决功率分配系统的非线性OPF问题。我们的方法基于采用网络等效方法的先前开发的基于分解的优化方法。我们提出了一项彻底的数学分析，其中包括足够的条件来保证该方法的收敛性。我们还使用IEEE-123总线测试系统提出了仿真结果，以证明该算法的有效性，并为理论结果提供更多见解。
The massive integration of distributed energy resources changes the operational demands of the electric power distribution system, motivating optimization-based approaches. The added computational complexities of the resulting optimal power flow (OPF) problem have generally been managed by approximated or relaxed models; however, they may lead to infeasible or inaccurate solutions. Decomposition-based methods have also been used to solve the OPF problems. But the existing methods require several message passing rounds for relatively small systems, causing significant delays in decision making; related feedback-based methods also suffer from slow tracking of the optimal solutions. In this paper, we propose a provably convergent distributed algorithm to solve the nonlinear OPF problem for power distribution systems. Our method is based on a previously developed decomposition-based optimization method that employs the network equivalence method. We present a thorough mathematical analysis that includes sufficient conditions that guarantee convergence of the method. We also present simulation results using the IEEE-123 bus test system to demonstrate the algorithm's effectiveness and provide additional insights into theoretical results.
