Online optimization in closed loop on the power flow manifold
Online optimization in closed loop on the power flow manifold
复制标题
DOI：
10.1109/ptc.2017.7980998
复制
发表时间：
2017-06
期刊：
影响因子：
--
通讯作者：
Adrian Hauswirth;A. Zanardi;S. Bolognani;F. Dörfler;G. Hug
中科院分区：
文献类型：
--
作者：
Adrian Hauswirth;A. Zanardi;S. Bolognani;F. Dörfler;G. Hug
本文的研究重点是电力系统在闭环状态下的在线潮流优化问题。与传统方法（在应用于系统之前计算AC OPF解）相反，我们的目标是设计一个自适应反馈控制器，使系统实时地转向最佳工作点，而无需显式地解决AC OPF问题。例如，我们的方法可用于同时调节电压，缓解线路拥塞，并在时变条件下优化运营成本。与主要关注配电网的相关工作相反，我们介绍了一种适用于一般场景的流形优化建模方法。为此，我们将潮流方程视为自然强制执行的隐式约束，从而产生潮流流形（PFM）。基于这类优化问题的理论结果，我们提出了一种离散时间投影梯度下降方案。在这项工作中，我们通过详细的仿真研究证实，该算法在更现实的电力系统设置中表现良好，并可靠地跟踪底层交流OPF问题的时变最优。
The focus of this paper is the online load flow optimization of power systems in closed loop. In contrast to the conventional approach where an AC OPF solution is computed before being applied to the system, our objective is to design an adaptive feedback controller that steers the system in real time to the optimal operating point without explicitly solving an AC OPF problem. Our approach can be used for example to simultaneously regulate voltages, mitigate line congestion, and optimize operating costs under time-varying conditions. In contrast to related work which is mostly focused on distribution grids, we introduce a modeling approach in terms of manifold optimization that is applicable in general scenarios. For this, we treat the power flow equations as implicit constraints that are naturally enforced and hence give rise to the power flow manifold (PFM). Based on our theoretical results for this type of optimization problems, we propose a discrete-time projected gradient descent scheme on the PFM. In this work, we confirm through a detailed simulation study that the algorithm performs well in a more realistic power system setup and reliably tracks the time-varying optimum of the underlying AC OPF problem.