Kiel Nano, Surface and Interface Science (KiNSIS)

Kolloquium der Technischen Fakultät

Recent Progress on Distributed and Stochastic Optimization for Power Systems (Timm Faulwasser, KIT)

12.02.2018 von 17:15 bis 18:00

Institute Ostufer, Geb. D, "Aquarium", Kaiserstr. 2, 24143 Kiel


The increasing need for the de-carbonization of energy supply calls for new operational methods for power systems. In this context, tailored system and control approaches are pivotal- The specific challenges include the consideration of volatile renewable generation, uncertain forecasts thereof, and highly nonlinear system behavior.

In this talk, we focus on the so-called Optimal Power Flow (OPF) problem, which refers to a class of large-scale non-convex steady-state optimization problems frequently arising in power systems. For example, OPF problems provide optimal set points for power dispatch that satisfy the power flow equations and technical limitations such as generation and/or transmission limits. However, OPF problems are highly non-convex and subject to considerable uncertainties, which includes forecasts of renewable generation and household consumption, line parameters and grid topology.

After a concise problem statement, we provide an overview of the state of the art techniques to considering uncertainties in OPF problems and their bottlenecks. Moreover, we will discuss the concept of Polynomial Chaos Expansions (PCE) which allows to consider non-Gaussian uncertainties in OPF problems. PCE builds upon a series expansion of random-variables. We will present recent results on PCE for convex DC-OPF problems and non-convex AC-OPF problems [1, 2]. Moreover, we will comment on the quantification of PCE truncation errors [3].

Due to their large-scale nature, the distributed solution of OPF problems is subject to considerable research efforts. Thus, we will also comment on our recent results on the distributed solution of OPF problems [4].


[1] Mühlpfordt, T.; Faulwasser, T.; Roald, L. & Hagenmeyer, V. Solving optimal power flow with non-Gaussian uncertainties via polynomial chaos expansion. 56th IEEE Conference on Decision and Control, 2017. To appear.
[2] Mühlpfordt, T.; Faulwasser, T. & Hagenmeyer, V. Solving stochastic AC power flow via polynomial chaos expansion. IEEE International Conference on Control Applications, 2016, 70-76.
[3] Mühlpfordt, T.; Findeisen, R.; Hagenmeyer, V. & Faulwasser, T. Comments on Quantifying Truncation Errors for Polynomial Chaos Expansions. arXiv:1708.07655.
[4] Engelmann, A.; Mühlpfordt, T.; Jiang, Y.; Houska, B. & Faulwasser, T. Distributed AC optimal power flow using ALADIN. 20th IFAC World Congress, 2017.


Dr. Timm Faulwasser has studied Engineering Cybernetics at the University Stuttgart, with majors in systems and control and philosophy, where he graduated 2006. In 2007 he joined the group of Rolf Findeisen at the Institute of Automation Engineering at the Otto-von-Guericke University Magdeburg, Germany. From 2008-2012 he was a member of the International Max Planck Research School for Analysis, Design and Optimization in Chemical and Biochemical Process Engineering Magdeburg. In 2012 he obtained his PhD (with distinction) from Faculty of Electrical Engineering and Information Engineering, Otto-von-Guericke University Magdeburg, Germany. 2013-2016 he was with the Laboratoire d’Automatique, Ecole Polytechnique Fédérale de Lausanne, Switzerland. Since April 2015, he is with the Institute for Applied Informatics at the Karlsruhe Institute for Technology, where he leads the Optimization and Control Group.

His main research interests are optimization-based and predictive control of nonlinear systems with applications in energy systems, mechatronics/robotics, physics, process systems engineering and climate economics.

Prof. Meurer

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