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

K. Schulte, O. Runde, M. Kelker and J. Haubrock, "Prediction of the local cloud cover to optimize photovoltaic system power forecast," 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), 2021, pp. 01-05, doi: 10.1109/ISGTEurope52324.2021.9640074.

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.