Katrin Schulte
18 Publikationen
2025 | Artikel | FH-PUB-ID: 5850
Gurcke, M., Cziomer, M., Schulte, K., & Haubrock, J. (2025). Grid-assistive use of private battery energy storage systems based on fuzzy logic. IET Conference Proceedings, 2024(29), 697–702. https://doi.org/10.1049/icp.2024.4742
HSBI-PUB
| DOI
2024 | Konferenzbeitrag | FH-PUB-ID: 5761
Quakernack, L., Gurcke, M., Schulte, K., & Haubrock, J. (2024). Grid-Oriented Control of Vehicle Batteries in a Cellular Grid Setup Based on Fuzzy Logic. In IEEE (Ed.), 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1–5). Dubrovnik, Croatia: IEEE. https://doi.org/10.1109/ISGTEUROPE62998.2024.10863623
HSBI-PUB
| DOI
2024 | Konferenzbeitrag | FH-PUB-ID: 5719
Liegmann, F., Schulte, K., Annen, F., Haubrock, J., Kelker, M., Joseph, S., … Rehtanz, C. (2024). Concept of a test bench for research into automatic resupply to improve the resilience of critical infrastructure. In Institute of Electrical and Electronics Engineers (IEEE) (Ed.), 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1–5). Dubrovnik, Croatia: IEEE. https://doi.org/10.1109/ISGTEUROPE62998.2024.10863253
HSBI-PUB
| DOI
2024 | Konferenzbeitrag | FH-PUB-ID: 5557
Schulte, K., Engel, L., Quakernack, L., Liegmann, F., & Haubrock, J. (2024). A comparison of machine learning algorithms for the optimization of a day-ahead photovoltaic power forecast. In N. Holjevac, T. Baškarad, M. Zidar, & I. Kuzle (Eds.), IEEE PES ISGT Europe 2024 Conference book. Dubrovnik, Croatia.
HSBI-PUB
2023 | Konferenzbeitrag | FH-PUB-ID: 5561
Handel, K., Schulte, K., Rigo-Mariani, R., Haubrock, J., & Arens, J. (2023). Control of distributed energy storage systems for minimum reverse flow in a distribution grid with high share of photovoltaic. In Institute of Electrical and Electronics Engineers (IEEE) (Ed.), 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1–5). Grenoble, France: IEEE. https://doi.org/10.1109/ISGTEUROPE56780.2023.10408443
HSBI-PUB
| DOI
2023 | Konferenzbeitrag | FH-PUB-ID: 4359
Jungh, T., Steinhagen, B., Hesse, M., & Schulte, K. (2023). Comparison of Different Machine Learning Models for Short-Term Load Forecasting at Transformer Level with High Amounts of Photovoltaic Generation. In 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1–5). Grenoble, France: IEEE. https://doi.org/10.1109/ISGTEUROPE56780.2023.10407216
HSBI-PUB
| DOI
2023 | Konferenzbeitrag | FH-PUB-ID: 4358
Handel, K., Schulte, K., Rigo-Mariani, R., Haubrock, J., & Arens, J. (2023). Control of distributed energy storage systems for minimum reverse flow in a distribution grid with high share of photovoltaic. In 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1–5). Grenoble, France: IEEE. https://doi.org/10.1109/ISGTEUROPE56780.2023.10408443
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| DOI
2023 | Konferenzbeitrag | FH-PUB-ID: 4357
Schulte, K., Engel, L., Quakernack, L., & Haubrock, J. (2023). Optimized photovoltaic power forecast using k-means clustering based error reduction. In 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1–5). Grenoble, France: IEEE. https://doi.org/10.1109/ISGTEUROPE56780.2023.10407521
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| DOI
2022 | Konferenzbeitrag | FH-PUB-ID: 3114 | 
Annen, F., Kröger, K., Schulte, K., & Haubrock, J. (2022). Aufbau eines HIL Teststandes zur Vaildierung von Algorithmen zur Steuerung von Smart Micro Grids. Presented at the 17. Symposium Energieinnovation, Graz.
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2021 | Konferenzbeitrag | FH-PUB-ID: 3355
Schulte, K., Runde, O., Kelker, M., & Haubrock, J. (2021). Prediction of the local cloud cover to optimize photovoltaic system power forecast. In 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe) (pp. 01–05). Espoo, Finland: IEEE. https://doi.org/10.1109/ISGTEurope52324.2021.9640074
HSBI-PUB
| DOI
2021 | Konferenzbeitrag | FH-PUB-ID: 3375
Schwienheer, M., Schulte, K., Kröger, K., & Haubrock, J. (2021). Realization of a power distributing electric vehicle charging system. In D. Schulz (Ed.), NEIS 2021. Conference on Sustainable Energy Supply and Energy Storage Systems Hamburg, 13 – 14 September 2021 (pp. 249–253). Berlin: VDE Verlag GmbH.
HSBI-PUB
2021 | Konferenzbeitrag | FH-PUB-ID: 3374
Schulte, K., & Haubrock, J. (2021). Linear programming to increase the directly used photovoltaic power for charging several electric vehicles. In 2021 IEEE Madrid PowerTech (pp. 1–6). Madrid, Spain: IEEE. https://doi.org/10.1109/PowerTech46648.2021.9494914
HSBI-PUB
| DOI
2020 | Konferenzbeitrag | FH-PUB-ID: 3359
Schulte, K., Kelker, M., & Haubrock, J. (2020). Artificial neural networks to predict the node voltages in a low-voltage grid. In NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems. Hamburg.
HSBI-PUB
2020 | Konferenzbeitrag | FH-PUB-ID: 3358
Lohmann, P., Kelker, M., Schulte, K., & Haubrock, J. (2020). Auslegung eines Antriebstranges für einen Batterie-Elektrischen Zug. In EnInnov 2020; 16. Symposium Energieinnovation. Graz.
HSBI-PUB
2020 | Konferenzbeitrag | FH-PUB-ID: 3354
Kelker, M., Schulte, K., & Haubrock, J. (2020). State estimation in low-voltage grids by using artificial neural networks in consideration of optimal micro phasor measurement unit placement. In NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems. Hamburg.
HSBI-PUB
2020 | Konferenzbeitrag | FH-PUB-ID: 3353 |
Kelker, M., Berrada, A., Schulte, K., & Haubrock, J. (2020). Entwicklung und Validierung eines optimalen Platzierungsalgorithmus für µPMUS im Niederspannungsnetz. In EnInnov 2020; 16. Symposium Energieinnovation. Graz.
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2019 | Konferenzbeitrag | FH-PUB-ID: 3351
Kelker, M., Schulte, K., Kröger, K., & Haubrock, J. (2019). Development and validation of a neural network for state estimation in the distribution grid based on μPMU data. In 2019 Modern Electric Power Systems (MEPS) (pp. 1–6). Wroclaw, Poland: IEEE. https://doi.org/10.1109/MEPS46793.2019.9394975
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| DOI
2019 | Konferenzbeitrag | FH-PUB-ID: 3350
Kelker, M., Schulte, K., Hansmeier, D., Annen, F., Kröger, K., Lohmann, P., & Haubrock, J. (2019). 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. In 2019 IEEE Milan PowerTech (pp. 1–6). Milan, Italy: IEEE. https://doi.org/10.1109/PTC.2019.8810719
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18 Publikationen
2025 | Artikel | FH-PUB-ID: 5850
Gurcke, M., Cziomer, M., Schulte, K., & Haubrock, J. (2025). Grid-assistive use of private battery energy storage systems based on fuzzy logic. IET Conference Proceedings, 2024(29), 697–702. https://doi.org/10.1049/icp.2024.4742
HSBI-PUB
| DOI
2024 | Konferenzbeitrag | FH-PUB-ID: 5761
Quakernack, L., Gurcke, M., Schulte, K., & Haubrock, J. (2024). Grid-Oriented Control of Vehicle Batteries in a Cellular Grid Setup Based on Fuzzy Logic. In IEEE (Ed.), 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1–5). Dubrovnik, Croatia: IEEE. https://doi.org/10.1109/ISGTEUROPE62998.2024.10863623
HSBI-PUB
| DOI
2024 | Konferenzbeitrag | FH-PUB-ID: 5719
Liegmann, F., Schulte, K., Annen, F., Haubrock, J., Kelker, M., Joseph, S., … Rehtanz, C. (2024). Concept of a test bench for research into automatic resupply to improve the resilience of critical infrastructure. In Institute of Electrical and Electronics Engineers (IEEE) (Ed.), 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1–5). Dubrovnik, Croatia: IEEE. https://doi.org/10.1109/ISGTEUROPE62998.2024.10863253
HSBI-PUB
| DOI
2024 | Konferenzbeitrag | FH-PUB-ID: 5557
Schulte, K., Engel, L., Quakernack, L., Liegmann, F., & Haubrock, J. (2024). A comparison of machine learning algorithms for the optimization of a day-ahead photovoltaic power forecast. In N. Holjevac, T. Baškarad, M. Zidar, & I. Kuzle (Eds.), IEEE PES ISGT Europe 2024 Conference book. Dubrovnik, Croatia.
HSBI-PUB
2023 | Konferenzbeitrag | FH-PUB-ID: 5561
Handel, K., Schulte, K., Rigo-Mariani, R., Haubrock, J., & Arens, J. (2023). Control of distributed energy storage systems for minimum reverse flow in a distribution grid with high share of photovoltaic. In Institute of Electrical and Electronics Engineers (IEEE) (Ed.), 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1–5). Grenoble, France: IEEE. https://doi.org/10.1109/ISGTEUROPE56780.2023.10408443
HSBI-PUB
| DOI
2023 | Konferenzbeitrag | FH-PUB-ID: 4359
Jungh, T., Steinhagen, B., Hesse, M., & Schulte, K. (2023). Comparison of Different Machine Learning Models for Short-Term Load Forecasting at Transformer Level with High Amounts of Photovoltaic Generation. In 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1–5). Grenoble, France: IEEE. https://doi.org/10.1109/ISGTEUROPE56780.2023.10407216
HSBI-PUB
| DOI
2023 | Konferenzbeitrag | FH-PUB-ID: 4358
Handel, K., Schulte, K., Rigo-Mariani, R., Haubrock, J., & Arens, J. (2023). Control of distributed energy storage systems for minimum reverse flow in a distribution grid with high share of photovoltaic. In 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1–5). Grenoble, France: IEEE. https://doi.org/10.1109/ISGTEUROPE56780.2023.10408443
HSBI-PUB
| DOI
2023 | Konferenzbeitrag | FH-PUB-ID: 4357
Schulte, K., Engel, L., Quakernack, L., & Haubrock, J. (2023). Optimized photovoltaic power forecast using k-means clustering based error reduction. In 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1–5). Grenoble, France: IEEE. https://doi.org/10.1109/ISGTEUROPE56780.2023.10407521
HSBI-PUB
| DOI
2022 | Konferenzbeitrag | FH-PUB-ID: 3114 |
Annen, F., Kröger, K., Schulte, K., & Haubrock, J. (2022). Aufbau eines HIL Teststandes zur Vaildierung von Algorithmen zur Steuerung von Smart Micro Grids. Presented at the 17. Symposium Energieinnovation, Graz.
HSBI-PUB
| Download (ext.)
2021 | Konferenzbeitrag | FH-PUB-ID: 3355
Schulte, K., Runde, O., Kelker, M., & Haubrock, J. (2021). Prediction of the local cloud cover to optimize photovoltaic system power forecast. In 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe) (pp. 01–05). Espoo, Finland: IEEE. https://doi.org/10.1109/ISGTEurope52324.2021.9640074
HSBI-PUB
| DOI
2021 | Konferenzbeitrag | FH-PUB-ID: 3375
Schwienheer, M., Schulte, K., Kröger, K., & Haubrock, J. (2021). Realization of a power distributing electric vehicle charging system. In D. Schulz (Ed.), NEIS 2021. Conference on Sustainable Energy Supply and Energy Storage Systems Hamburg, 13 – 14 September 2021 (pp. 249–253). Berlin: VDE Verlag GmbH.
HSBI-PUB
2021 | Konferenzbeitrag | FH-PUB-ID: 3374
Schulte, K., & Haubrock, J. (2021). Linear programming to increase the directly used photovoltaic power for charging several electric vehicles. In 2021 IEEE Madrid PowerTech (pp. 1–6). Madrid, Spain: IEEE. https://doi.org/10.1109/PowerTech46648.2021.9494914
HSBI-PUB
| DOI
2020 | Konferenzbeitrag | FH-PUB-ID: 3359
Schulte, K., Kelker, M., & Haubrock, J. (2020). Artificial neural networks to predict the node voltages in a low-voltage grid. In NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems. Hamburg.
HSBI-PUB
2020 | Konferenzbeitrag | FH-PUB-ID: 3358
Lohmann, P., Kelker, M., Schulte, K., & Haubrock, J. (2020). Auslegung eines Antriebstranges für einen Batterie-Elektrischen Zug. In EnInnov 2020; 16. Symposium Energieinnovation. Graz.
HSBI-PUB
2020 | Konferenzbeitrag | FH-PUB-ID: 3354
Kelker, M., Schulte, K., & Haubrock, J. (2020). State estimation in low-voltage grids by using artificial neural networks in consideration of optimal micro phasor measurement unit placement. In NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems. Hamburg.
HSBI-PUB
2020 | Konferenzbeitrag | FH-PUB-ID: 3353 |
Kelker, M., Berrada, A., Schulte, K., & Haubrock, J. (2020). Entwicklung und Validierung eines optimalen Platzierungsalgorithmus für µPMUS im Niederspannungsnetz. In EnInnov 2020; 16. Symposium Energieinnovation. Graz.
HSBI-PUB
| Download (ext.)
2019 | Konferenzbeitrag | FH-PUB-ID: 3351
Kelker, M., Schulte, K., Kröger, K., & Haubrock, J. (2019). Development and validation of a neural network for state estimation in the distribution grid based on μPMU data. In 2019 Modern Electric Power Systems (MEPS) (pp. 1–6). Wroclaw, Poland: IEEE. https://doi.org/10.1109/MEPS46793.2019.9394975
HSBI-PUB
| DOI
2019 | Konferenzbeitrag | FH-PUB-ID: 3350
Kelker, M., Schulte, K., Hansmeier, D., Annen, F., Kröger, K., Lohmann, P., & Haubrock, J. (2019). 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. In 2019 IEEE Milan PowerTech (pp. 1–6). Milan, Italy: IEEE. https://doi.org/10.1109/PTC.2019.8810719
HSBI-PUB
| DOI