Search Results for author: Christian Becker

Found 9 papers, 0 papers with code

Physics-informed Actor-Critic for Coordination of Virtual Inertia from Power Distribution Systems

no code implementations17 Apr 2024 Simon Stock, Davood Babazadeh, Sari Eid, Christian Becker

To this end, this paper presents the Physics-informed Actor-Critic (PI-AC) algorithm for coordination of Virtual Inertia (VI) from renewable Inverter-based Resources (IBRs) in power distribution systems.

Reinforcement Learning (RL)

Bayesian Physics-informed Neural Networks for System Identification of Inverter-dominated Power Systems

no code implementations20 Mar 2024 Simon Stock, Davood Babazadeh, Christian Becker, Spyros Chatzivasileiadis

The BPINN combines the advantages of Physics-informed Neural Networks (PINNs), such as inverse problem applicability, with Bayesian approaches for uncertainty quantification.

Transfer Learning Uncertainty Quantification

Multi-energy Grid Expansion Planning Under Uncertainty: A Robust Optimization Approach

no code implementations8 May 2023 Marwan Mostafa, Davood Babazadeh, Christian Becker

In response to these challenges, this paper proposes a novel approach to apply robust optimization methods in the integrated planning of multi-energy grids, to reduce the risk of investment in grid expansion and to optimize the use of different carbon-neutral energy carriers.

Decision Making

Towards a more comprehensive open-source model for interdisciplinary smart integrated energy systems

no code implementations12 Apr 2023 Béla Wiegel, Tom Steffen, Davood Babazadeh, Christian Becker

In order to make the integration of renewable energies as cost-effective, secure and sustainable as possible and to develop new paradigms for the energy system, many energy system models have been developed in research in the past to evaluate the solutions.

Optimized utilization of decentral flexibility for the operational management of cellular multi-modal distribution grids

no code implementations10 Feb 2023 Béla Wiegel, Lando Helmrich von Elgott, Davood Babazadeh, Christian Becker

Aim is to provide flexibility with a cell by optimally distributing a flexibility request to subordinate prosumers changing their active and reactive power.

Management

Integrated Planning of Multi-energy Grids: Concepts and Challenges

no code implementations20 Jan 2023 Marwan Mostafa, Daniela Vorwerk, Johannes Heise, Alex Povel, Natalia Sanina, Davood Babazadeh, Christian Töbermann, Arne Speerforck, Christian Becker, Detlef Schulz

In order to meet ever-stricter climate targets and achieve the eventual decarbonization of the energy supply of German industrial metropolises, the focus is on gradually phasing out nuclear power, then coal and gas combined with the increased use of renewable energy sources and employing hydrogen as a clean energy carrier.

Novel Concepts

Bayesian Physics-Informed Neural Networks for Robust System Identification of Power Systems

no code implementations22 Dec 2022 Simon Stock, Jochen Stiasny, Davood Babazadeh, Christian Becker, Spyros Chatzivasileiadis

Bayesian Physics-Informed Neural Networks (BPINNs) combine the advantages of Physics-Informed Neural Networks (PINNs), being robust to noise and missing data, with Bayesian modeling, delivering a confidence measure for their output.

Roadmap for Edge AI: A Dagstuhl Perspective

no code implementations27 Nov 2021 Aaron Yi Ding, Ella Peltonen, Tobias Meuser, Atakan Aral, Christian Becker, Schahram Dustdar, Thomas Hiessl, Dieter Kranzlmuller, Madhusanka Liyanage, Setareh Magshudi, Nitinder Mohan, Joerg Ott, Jan S. Rellermeyer, Stefan Schulte, Henning Schulzrinne, Gurkan Solmaz, Sasu Tarkoma, Blesson Varghese, Lars Wolf

Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI.

Edge-computing

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