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Date
2017Type
- Conference Paper
Citations
Cited 37 times in
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Cited 49 times in
Scopus
ETH Bibliography
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Abstract
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. Show more
Publication status
publishedExternal links
Book title
2017 IEEE Manchester PowerTechPages / Article No.
Publisher
IEEEEvent
Subject
adaptive control; load flow; power distribution control; AC OPF; adaptive feedback controller; discrete-time projected gradient descent scheme; distribution grids; online load flow optimization; power flow equations; Feedback control; Manifolds; Mathematical model; Optimization; Power systems; Voltage control; Gradient methods; Load flow control; Manifold optimization; Nonlinear dynamical systemsOrganisational unit
09478 - Dörfler, Florian / Dörfler, Florian
09481 - Hug, Gabriela / Hug, Gabriela
Funding
160573 - Plug-and-Play Control & Optimization in Microgrids (SNF)
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Show all metadata
Citations
Cited 37 times in
Web of Science
Cited 49 times in
Scopus
ETH Bibliography
yes
Altmetrics