The listed papers present research conducted during my time as a research assistant at ie³ institute of TU Dortmund university. My research interest lays in efficient large scale and interdisciplinary power system simulation with focus on electrical distribution grids as well as the generation of open research data.
[1] S. C. Müller et al., “The impact of forecasting errors and remedial actions on operational security and efficiency in classical and probabilistic market coupling,” in 2014 power systems computation conference, Aug. 2014, pp. 1–8, doi: 10.1109/PSCC.2014.7038490.
[2] C. Rehtanz et al., “Verteilnetzstudie für das land baden"=Württemberg,” ef.Ruhr GmbH, Studie, Apr. 2017 [Online]. Available: https://um.baden-wuerttemberg.de/fileadmin/redaktion/m-um/intern/Dateien/Dokumente/5_Energie/Versorgungssicherheit/170413_Verteilnetzstudie_BW.pdf. [Accessed: Sep. 06, 2017]
[3] L. Robitzky et al., “Impact of active distribution networks on voltage stability of electric power systems,” in 10th bulk power systems dynamics and control symposium (irep), Aug. 2017.
[4] A. Shapovalov, C. Kittl, C. Rehtanz, L. Jendernalik, A. C. Schneider, and D. Giavarra, “Application of time-resolved input data for smart grid simulation,” CIRED - Open Access Proceedings Journal, vol. 2017, no. 1, pp. 2106–2109, Oct. 2017, doi: 10.1049/oap-cired.2017.0380.
[5] L. Jendernalik, D. Giavarra, C. Engels, J. Hiry, C. Kittl, and C. Rehtanz, “Holistic network planning approach: Enhancement of the grid expansion using the flexibility of network participants,” CIRED - Open Access Proceedings Journal, vol. 2017, no. 1, pp. 2312–2315, Oct. 2017, doi: 10.1049/oap-cired.2017.0061.
[6] J. Hiry, C. Kittl, Z. Hagemann, and C. Rehtanz, “Das potential spannungsebenenübergreifender zeitreihensimulationen für die verteilnetzplanung,” in Smart energy 2017, U. Großmann, I. Kunold, and C. Engels, Eds. 2017.
[7] C. Wagner, C. Kittl, S. Kippelt, and C. Rehtanz, “A heuristic process for an automated evaluation of distribution grid expansion planning approaches,” in Proceedings of international etg congress 2017, Nov. 2017.
[8] C. Römer, J. Hiry, C. Kittl, T. Liebig, and C. Rehtanz, “Charging control of electric vehicles using contextual bandits considering the electrical distribution grid,” in KNOWMe: 2nd international workshop on knowledge discovery from mobility and transportation systems, Dublin, 2018.
[9] C. Kittl, D. Sarajlić, and C. Rehtanz, “K-means based identification of common supply tasks for low voltage grids,” in 2018 IEEE PES innovative smart grid technologies conference europe (ISGT-europe), Oct. 2018, doi: 10.1109/isgteurope.2018.8571658.
[10] C. Kittl, J. Hiry, C. Pfeiffer, C. Rehtanz, and C. Engels, “Large scale agent based simulation of distribution grid loading and its practical application,” in 25th international conference on electricity distribution (cired), 2019, doi: 10.34890/521.
[11] J. Hiry, C. Kittl, C. Römer, C. Rehtanz, L. Willmes, and S. Schimmeyer, “Automated time series based grid extensions planning using a coupled agent based simulation and genetic algorithm approach,” in 25th international conference on electricity distribution (cired), 2019, doi: 10.34890/548.
[12] C. Spalthoff et al., “SimBench: Open source time series of power load, storage and generation for the simulation of electrical distribution grids,” in Internationaler etg-kongress 2019, May 2019.
[13] J. Hiry, J. Peper, S. Peter, C. Kittl, and C. Rehtanz, “Regional spatial distribution of electric vehicles – a data-driven approach for distribution grid impact case studies,” in ETG-kongress 2021 - von komponenten bis zum gesamtsystem für die energiewende, May 2021.
[14] S. Balduin et al., “Towards a universally applicable neural state estimation through transfer learning,” in 2021 IEEE PES innovative smart grid technologies europe (ISGT europe), Oct. 2021, doi: 10.1109/isgteurope52324.2021.9639919.
[15] J. Hiry, C. Kittl, D. S. Sarma, T. Oberließen, and C. Rehtanz, “Multi-voltage level distributed backward-forward sweep power flow algorithm in an agent-based discrete-event simulation framework,” in 22nd power systems computation conference (pscc), 2022.