PUBLIKATIONSSERVER

Katrin Schulte

13 Publikationen

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[13]
2023 | Konferenzbeitrag | FH-PUB-ID: 4359
Comparison of Different Machine Learning Models for Short-Term Load Forecasting at Transformer Level with High Amounts of Photovoltaic Generation
T. Jungh, B. Steinhagen, M. Hesse, K. Schulte, in: 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), IEEE, 2023, pp. 1–5.
HSBI-PUB | DOI
 
[12]
2023 | Konferenzbeitrag | FH-PUB-ID: 4358
Control of distributed energy storage systems for minimum reverse flow in a distribution grid with high share of photovoltaic
K. Handel, K. Schulte, R. Rigo-Mariani, J. Haubrock, J. Arens, in: 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), IEEE, 2023, pp. 1–5.
HSBI-PUB | DOI
 
[11]
2023 | Konferenzbeitrag | FH-PUB-ID: 4357
Optimized photovoltaic power forecast using k-means clustering based error reduction
K. Schulte, L. Engel, L. Quakernack, J. Haubrock, in: 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), IEEE, 2023, pp. 1–5.
HSBI-PUB | DOI
 
[10]
2022 | Konferenzbeitrag | FH-PUB-ID: 3114 | OA
Aufbau eines HIL Teststandes zur Vaildierung von Algorithmen zur Steuerung von Smart Micro Grids
F. Annen, K. Kröger, K. Schulte, J. Haubrock, in: 2022.
HSBI-PUB | Download (ext.)
 
[9]
2021 | Konferenzbeitrag | FH-PUB-ID: 3355
Prediction of the local cloud cover to optimize photovoltaic system power forecast
K. Schulte, O. Runde, M. Kelker, J. Haubrock, in: 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), IEEE, 2021, pp. 01–05.
HSBI-PUB | DOI
 
[8]
2021 | Konferenzbeitrag | FH-PUB-ID: 3375
Realization of a power distributing electric vehicle charging system
M. Schwienheer, K. Schulte, K. Kröger, J. Haubrock, in: D. Schulz (Ed.), NEIS 2021. Conference on Sustainable Energy Supply and Energy Storage Systems Hamburg, 13 – 14 September 2021, VDE Verlag GmbH, Berlin, 2021, pp. 249–253.
HSBI-PUB
 
[7]
2021 | Konferenzbeitrag | FH-PUB-ID: 3374
Linear programming to increase the directly used photovoltaic power for charging several electric vehicles
K. Schulte, J. Haubrock, in: 2021 IEEE Madrid PowerTech, IEEE, 2021, pp. 1–6.
HSBI-PUB | DOI
 
[6]
2020 | Konferenzbeitrag | FH-PUB-ID: 3359
Artificial neural networks to predict the node voltages in a low-voltage grid
K. Schulte, M. Kelker, J. Haubrock, in: NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems, 2020.
HSBI-PUB
 
[5]
2020 | Konferenzbeitrag | FH-PUB-ID: 3358
Auslegung eines Antriebstranges für einen Batterie-Elektrischen Zug
P. Lohmann, M. Kelker, K. Schulte, J. Haubrock, in: EnInnov 2020; 16. Symposium Energieinnovation, 2020.
HSBI-PUB
 
[4]
2020 | Konferenzbeitrag | FH-PUB-ID: 3354
State estimation in low-voltage grids by using artificial neural networks in consideration of optimal micro phasor measurement unit placement
M. Kelker, K. Schulte, J. Haubrock, in: NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems, 2020.
HSBI-PUB
 
[3]
2020 | Konferenzbeitrag | FH-PUB-ID: 3353 | OA
Entwicklung und Validierung eines optimalen Platzierungsalgorithmus für µPMUS im Niederspannungsnetz
M. Kelker, A. Berrada, K. Schulte, J. Haubrock, in: EnInnov 2020; 16. Symposium Energieinnovation, 2020.
HSBI-PUB | Download (ext.)
 
[2]
2019 | Konferenzbeitrag | FH-PUB-ID: 3351
Development and validation of a neural network for state estimation in the distribution grid based on μPMU data
M. Kelker, K. Schulte, K. Kröger, J. Haubrock, in: 2019 Modern Electric Power Systems (MEPS), IEEE, 2019, pp. 1–6.
HSBI-PUB | DOI
 
[1]
2019 | Konferenzbeitrag | FH-PUB-ID: 3350
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
M. Kelker, K. Schulte, D. Hansmeier, F. Annen, K. Kröger, P. Lohmann, J. Haubrock, in: 2019 IEEE Milan PowerTech, IEEE, 2019, pp. 1–6.
HSBI-PUB | DOI
 
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13 Publikationen

Alle markieren

[13]
2023 | Konferenzbeitrag | FH-PUB-ID: 4359
Comparison of Different Machine Learning Models for Short-Term Load Forecasting at Transformer Level with High Amounts of Photovoltaic Generation
T. Jungh, B. Steinhagen, M. Hesse, K. Schulte, in: 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), IEEE, 2023, pp. 1–5.
HSBI-PUB | DOI
 
[12]
2023 | Konferenzbeitrag | FH-PUB-ID: 4358
Control of distributed energy storage systems for minimum reverse flow in a distribution grid with high share of photovoltaic
K. Handel, K. Schulte, R. Rigo-Mariani, J. Haubrock, J. Arens, in: 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), IEEE, 2023, pp. 1–5.
HSBI-PUB | DOI
 
[11]
2023 | Konferenzbeitrag | FH-PUB-ID: 4357
Optimized photovoltaic power forecast using k-means clustering based error reduction
K. Schulte, L. Engel, L. Quakernack, J. Haubrock, in: 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), IEEE, 2023, pp. 1–5.
HSBI-PUB | DOI
 
[10]
2022 | Konferenzbeitrag | FH-PUB-ID: 3114 | OA
Aufbau eines HIL Teststandes zur Vaildierung von Algorithmen zur Steuerung von Smart Micro Grids
F. Annen, K. Kröger, K. Schulte, J. Haubrock, in: 2022.
HSBI-PUB | Download (ext.)
 
[9]
2021 | Konferenzbeitrag | FH-PUB-ID: 3355
Prediction of the local cloud cover to optimize photovoltaic system power forecast
K. Schulte, O. Runde, M. Kelker, J. Haubrock, in: 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), IEEE, 2021, pp. 01–05.
HSBI-PUB | DOI
 
[8]
2021 | Konferenzbeitrag | FH-PUB-ID: 3375
Realization of a power distributing electric vehicle charging system
M. Schwienheer, K. Schulte, K. Kröger, J. Haubrock, in: D. Schulz (Ed.), NEIS 2021. Conference on Sustainable Energy Supply and Energy Storage Systems Hamburg, 13 – 14 September 2021, VDE Verlag GmbH, Berlin, 2021, pp. 249–253.
HSBI-PUB
 
[7]
2021 | Konferenzbeitrag | FH-PUB-ID: 3374
Linear programming to increase the directly used photovoltaic power for charging several electric vehicles
K. Schulte, J. Haubrock, in: 2021 IEEE Madrid PowerTech, IEEE, 2021, pp. 1–6.
HSBI-PUB | DOI
 
[6]
2020 | Konferenzbeitrag | FH-PUB-ID: 3359
Artificial neural networks to predict the node voltages in a low-voltage grid
K. Schulte, M. Kelker, J. Haubrock, in: NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems, 2020.
HSBI-PUB
 
[5]
2020 | Konferenzbeitrag | FH-PUB-ID: 3358
Auslegung eines Antriebstranges für einen Batterie-Elektrischen Zug
P. Lohmann, M. Kelker, K. Schulte, J. Haubrock, in: EnInnov 2020; 16. Symposium Energieinnovation, 2020.
HSBI-PUB
 
[4]
2020 | Konferenzbeitrag | FH-PUB-ID: 3354
State estimation in low-voltage grids by using artificial neural networks in consideration of optimal micro phasor measurement unit placement
M. Kelker, K. Schulte, J. Haubrock, in: NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems, 2020.
HSBI-PUB
 
[3]
2020 | Konferenzbeitrag | FH-PUB-ID: 3353 | OA
Entwicklung und Validierung eines optimalen Platzierungsalgorithmus für µPMUS im Niederspannungsnetz
M. Kelker, A. Berrada, K. Schulte, J. Haubrock, in: EnInnov 2020; 16. Symposium Energieinnovation, 2020.
HSBI-PUB | Download (ext.)
 
[2]
2019 | Konferenzbeitrag | FH-PUB-ID: 3351
Development and validation of a neural network for state estimation in the distribution grid based on μPMU data
M. Kelker, K. Schulte, K. Kröger, J. Haubrock, in: 2019 Modern Electric Power Systems (MEPS), IEEE, 2019, pp. 1–6.
HSBI-PUB | DOI
 
[1]
2019 | Konferenzbeitrag | FH-PUB-ID: 3350
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
M. Kelker, K. Schulte, D. Hansmeier, F. Annen, K. Kröger, P. Lohmann, J. Haubrock, in: 2019 IEEE Milan PowerTech, IEEE, 2019, pp. 1–6.
HSBI-PUB | DOI
 
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