FH Bielefeld
University of
Applied Sciences
Foto von Katrin Schulte

Katrin Schulte

M.Eng.
Kontakt
Raum D 433
Telefon +49.521.106-70839
katrin.schulte@fh-bielefeld.de
Aufgabenbeschreibung
Publikationen

2021

M. Schwienheer, K. Schulte, K. Kröger and J. Haubrock, "Realization of a power distributing electric vehicle charging system," NEIS 2021; Conference on Sustainable Energy Supply and Energy Storage Systems, 2021, pp. 1-6.

K. Schulte and J. Haubrock, "Linear programming to increase the directly used photovoltaic power for charging several electric vehicles," 2021 IEEE Madrid PowerTech, 2021, pp. 1-6, doi: 10.1109/PowerTech46648.2021.9494914.

2020

M. Kelker, K. Schulte and J. Haubrock, "State estimation in low-voltage grids by using artificial neural networks in consideration of optimal micro phasor measurement unit placement," NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems, 2020, pp. 1-6.

K. Schulte, M. Kelker and J. Haubrock, "Artificial neural networks to predict the node voltages in a low-voltage grid," NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems, 2020, pp. 1-6.

M. Kelker, A. Berrada, K. Schulte and J. Haubrock, "Entwicklung und Validierung eines optimalen Platzierungsalgorithmus für µPMUS im Niederspannungsnetz, " EnInnov 2020; 16. Symposium Energieinnovation, 2020 February 12 – 14, Austria, Graz 2020.

P. Lohmann, M. Kelker, K. Schulte and J. Haubrock, "Auslegung eines Antriebstranges für einen Batterie-Elektrischen Zug, " EnInnov 2020; 16. Symposium Energieinnovation, 2020 February 12 – 14, Austria, Graz 2020.

2019

M. Kelker, K. Schulte, K. Kröger and J. Haubrock, "Development and validation of a neural network for state estimation in the distribution grid based on μPMU data," 2019 Modern Electric Power Systems (MEPS), 2019, pp. 1-6, doi: 10.1109/MEPS46793.2019.9394975.

K. Schulte, M. Kelker, and J. Haubrock, “Predicting the local generated photovoltaic power by creating a forecast model using artificial neural networks and verifying the model with real data,” Power and Energy Student Summit PESS, July 9 – 11, Magdeburg 2019.

M. Kelker, K. Schulte, D. Hansmeier, F. Annen, K. Kröger, P. Lohmann and J. Haubrock, "Development of a forecast model for the prediction of photovoltaic power using neural networks and validating the model based on real measurement data of a local photovoltaic system," 2019 IEEE Milan PowerTech, 2019, pp. 1-6, doi: 10.1109/PTC.2019.8810719.