论文标题
分销网络的在线联合优化估计架构
An Online Joint Optimization-Estimation Architecture for Distribution Networks
论文作者
论文摘要
在本文中，我们提出了针对分销网络的最佳控制估计体系结构，该结构共同解决了通过基于在线梯度的反馈算法的最佳功率流（OPF）问题（OPF）问题和静态状态估计（SE）问题。主要目的是在传感器测量有限的最佳控制器和状态估计器之间实现快速，及时的相互作用。首先，分析提出的算法的收敛性和最佳性。然后，通过引入固有估计和线性化误差的统计信息来修改所提出的基于梯度的算法，以改善在线控制决策。总体而言，提出的方法消除了控制和操作的传统分离，在这些方法中，控制和估计通常在不同的层和不同的时间尺度下运行。因此，它可以为在随着时间变化的设置下的分销网络提供一个计算负担得起，高效且可靠的在线操作框架。
In this paper, we propose an optimal control-estimation architecture for distribution networks, which jointly solves the optimal power flow (OPF) problem and static state estimation (SE) problem through an online gradient-based feedback algorithm. The main objective is to enable a fast and timely interaction between the optimal controllers and state estimators with limited sensor measurements. First, convergence and optimality of the proposed algorithm are analytically established. Then, the proposed gradient-based algorithm is modified by introducing statistical information of the inherent estimation and linearization errors for an improved and robust performance of the online control decisions. Overall, the proposed method eliminates the traditional separation of control and operation, where control and estimation usually operate at distinct layers and different time-scales. Hence, it enables a computationally affordable, efficient and robust online operational framework for distribution networks under time-varying settings.
