| Evaluating different machine learning techniques as surrogate for low voltage grids S Balduin, T Westermann, E Puiutta Energy Informatics 3 (Suppl 1), 24, 2020 | 17 | 2020 |
| Analyzing power grid, ict, and market without domain knowledge using distributed artificial intelligence E Veith, S Balduin, N Wenninghoff, M Tröschel, L Fischer, A Nieße, ... arXiv preprint arXiv:2006.06074, 2020 | 11 | 2020 |
| Towards domain-specific surrogate models for smart grid co-simulation S Balduin, M Tröschel, S Lehnhoff Energy Informatics 2 (Suppl 1), 27, 2019 | 11 | 2019 |
| Distributed ledger technology for fully automated congestion management A Nieße, N Ihle, S Balduin, M Postina, M Tröschel, S Lehnhoff Energy Informatics 1 (Suppl 1), 22, 2018 | 9 | 2018 |
| Surrogate models for composed simulation models in energy systems S Balduin Energy Informatics 1 (Suppl 1), 30, 2018 | 9 | 2018 |
| Towards a universally applicable neural state estimation through transfer learning S Balduin, EMSP Veith, A Berezin, S Lehnhoff, T Oberließen, C Kittl, J Hiry, ... 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), 1-6, 2021 | 4 | 2021 |
| Large-Scale Co-Simulation of Power Grid and Communication Network Models with Software in the Loop E Veith, J Kazmi, S Balduin arXiv preprint arXiv:2005.11369, 2020 | 3 | 2020 |
| Tool-assisted surrogate selection for simulation models in energy systems S Balduin, F Oest, M Blank-Babazadeh, A Nieße, S Lehnhoff 2019 Federated Conference on Computer Science and Information Systems …, 2019 | 3 | 2019 |
| ANALYSE—Learning to attack cyber–physical energy systems with intelligent agents T Wolgast, N Wenninghoff, S Balduin, E Veith, B Fraune, T Woltjen, ... SoftwareX 23, 101484, 2023 | 2 | 2023 |
| Learning to Attack Powergrids with DERs E Veith, N Wenninghoff, S Balduin, T Wolgast, S Lehnhoff arXiv preprint arXiv:2204.11352, 2022 | 1 | 2022 |
| Sampling strategies for static powergrid models S Balduin, E Veith, S Lehnhoff arXiv preprint arXiv:2204.09053, 2022 | 1 | 2022 |
| Application of Recurrent Graph Convolutional Networks to the Neural State Estimation Problem A Berezin, S Balduin, T Oberließen, E Veith, S Peter, S Lehnhoff | 1 | 2022 |
| Dynamic Portfolio Optimization for Distributed Energy Resources in Virtual Power Plants S Balduin, D Brauer, L Elend, S Holly, J Korte, C Krüger, A Meier, F Oest, ... Advances and New Trends in Environmental Informatics: Stability, Continuity …, 2017 | 1 | 2017 |
| Imitation Game: A Model-based and Imitation Learning Deep Reinforcement Learning Hybrid E Veith, T Logemann, A Berezin, A Wellßow, S Balduin arXiv preprint arXiv:2404.01794, 2024 | | 2024 |
| Towards the Automatic Generation of Models for Prediction, Monitoring, and Testing of Cyber-Physical Systems M Knitt, S Plambeck, JC Wieck, J Kohlisch, S Balduin, EMSP Veith, ... 2023 IEEE 28th International Conference on Emerging Technologies and Factory …, 2023 | | 2023 |
| Midas: An Open-Source Framework for Simulation-Based Analysis of Energy Systems S Balduin, EMSP Veith, S Lehnhoff International Conference on Simulation and Modeling Methodologies …, 2022 | | 2022 |
| Learning to Attack Powergrids with DERs E MSP Veith, N Wenninghoff, S Balduin, T Wolgast, S Lehnhoff arXiv e-prints, arXiv: 2204.11352, 2022 | | 2022 |
| Deliverable D1. 1–Whitepaper Large-Scale Smart Grid Application Roll-Out FP Andrén, J Kazmi, C Gavriluta, E Piatkowska, PS AIT, E Veith, S Balduin, ... | | 2020 |
| PALAESTRAI: A TRAINING GROUND FOR AUTONOMOUS AGENTS EMSP Veith, S Balduin, N Wenninghoff, T Wolgast, M Baumann, ... | | |
