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Real-time feedback optimization on the power flow manifold

Presented by: 
Florian Doerfler
Thursday 10th January 2019 - 09:00 to 10:00
INI Seminar Room 1
Session Title: 
AM - Optimization & Control
I will focus on online optimization of AC power systems in closed loop. In contrast to the conventional approach where an optimal power flow solution is computed offline and online controllers enforce these set-points, our objective is to design an adaptive feedback controller that steers the system robustly and in real time to the optimal operating point. Our methodological approach is based on online algorithms for manifold optimization that can be applied in feedback with real-time measurements and actuation. We treat the power flow equations as implicit constraints that are naturally enforced by the physics and hence give rise to the power flow manifold. Based on our theoretical results for this type of optimization problems, we propose a projected gradient descent scheme on the power flow manifold. In detailed simulation case studies we validate the performance of our algorithm and show that it reliably tracks the time-varying optimum of the underlying AC optimal power flow problem.

Co-authors: Adrian Hauswirth (ETH Zurich), Saverio Bolognani (ETH Zurich), Gabriela Hug (ETH Zurich)
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Presentation Material: 
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons