Lars Quakernack
12 Publikationen
2024 | Konferenzbeitrag | FH-PUB-ID: 5720
L. Quakernack, T. Engelmann, J. Haubrock, and V. Vaquet, “LSTM Autoencoder Model to Identify Electric Vehicles in Grouped Smart Meter Data,” in 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Dubrovnik, Croatia, 2024, pp. 1–5.
HSBI-PUB
| DOI
2024 | Konferenzbeitrag | FH-PUB-ID: 5761
L. Quakernack, M. Gurcke, K. Schulte, and J. Haubrock, “Grid-Oriented Control of Vehicle Batteries in a Cellular Grid Setup Based on Fuzzy Logic,” in 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Dubrovnik, Croatia, 2024, pp. 1–5.
HSBI-PUB
| DOI
2024 | Konferenzbeitrag | FH-PUB-ID: 5557
K. Schulte, L. Engel, L. Quakernack, F. Liegmann, and J. Haubrock, “A comparison of machine learning algorithms for the optimization of a day-ahead photovoltaic power forecast,” in IEEE PES ISGT Europe 2024 Conference book, Dubrovnik, Croatia, 2024.
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2023 | Konferenzbeitrag | FH-PUB-ID: 5723
T. Engelmann, L. Quakernack, and J. Haubrock, “Q-learning based control algorithm with dynamic combination of peak shaving and self-consumption optimization for industrial battery storage systems,” in PESS 2023; Power and Energy Student Summit, Bielefeld, 2023.
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2023 | Konferenzbeitrag | FH-PUB-ID: 4357
K. Schulte, L. Engel, L. Quakernack, and J. Haubrock, “Optimized photovoltaic power forecast using k-means clustering based error reduction,” in 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Grenoble, France, 2023, pp. 1–5.
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| DOI
2023 | Konferenzbeitrag | FH-PUB-ID: 3105
L. Quakernack, J. Hövelmann, K. Kröger, and J. Haubrock, “AI-based heat demand forecasting in industrial buildings for flexible operation of combined heat and power plants,” presented at the International ETG-Congress 2023, Magdeburg, Germany, 2023.
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2023 | Konferenzbeitrag | FH-PUB-ID: 3096
B. Steinhagen et al., “Evaluation of the Usage of Edge Computing and LoRa for the Control of Electric Vehicle Charging in the Low Voltage Grid,” in 2023 IEEE PES Conference on Innovative Smart Grid Technologies - Middle East (ISGT Middle East), Abu Dhabi, United Arab Emirates, 2023, pp. 1–5.
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| DOI
2022 | Konferenzbeitrag | FH-PUB-ID: 3113
L. Quakernack, M. Kelker, and J. Haubrock, “Deep Reinforcement Learning For Autonomous Control Of Low Voltage Grids With Focus On Grid Stability In Future Power Grids,” in 2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Novi Sad, Serbia, 2022, pp. 1–5.
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| DOI
2022 | Konferenzbeitrag | FH-PUB-ID: 3112
M. Kelker, L. Quakernack, J. Haubrock, and D. Westermann, “Multi agent double deep Q-network with multiple reward functions for electric vehicle charge control,” in 2022 IEEE Power & Energy Society General Meeting (PESGM), Denver, CO, USA, 2022, pp. 01–05.
HSBI-PUB
| DOI
2022 | Konferenzbeitrag | FH-PUB-ID: 3097 | 
L. Quakernack, M. Kelker, U. Rückert, and J. Haubrock, “Deep Reinforcement Learning als Methode zur autonomen Steuerung von Niederspannungsnetzen mit Fokus auf die Netzstabilität,” presented at the 17. Symposium Energieinnovation, Graz, 2022.
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2018 | Konferenzbeitrag | FH-PUB-ID: 3360
L. Quakernack, M. Kelker, and J. Haubrock, “Simulation of a Smart-Micro-Grid to Analyse an Intelligent Charge Management in Matlab Simulink for a Local Bakery Chain,” presented at the 8. IEEE Germany Student Conference, Magdeburg, 2018.
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12 Publikationen
2024 | Konferenzbeitrag | FH-PUB-ID: 5720
L. Quakernack, T. Engelmann, J. Haubrock, and V. Vaquet, “LSTM Autoencoder Model to Identify Electric Vehicles in Grouped Smart Meter Data,” in 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Dubrovnik, Croatia, 2024, pp. 1–5.
HSBI-PUB
| DOI
2024 | Konferenzbeitrag | FH-PUB-ID: 5761
L. Quakernack, M. Gurcke, K. Schulte, and J. Haubrock, “Grid-Oriented Control of Vehicle Batteries in a Cellular Grid Setup Based on Fuzzy Logic,” in 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Dubrovnik, Croatia, 2024, pp. 1–5.
HSBI-PUB
| DOI
2024 | Konferenzbeitrag | FH-PUB-ID: 5557
K. Schulte, L. Engel, L. Quakernack, F. Liegmann, and J. Haubrock, “A comparison of machine learning algorithms for the optimization of a day-ahead photovoltaic power forecast,” in IEEE PES ISGT Europe 2024 Conference book, Dubrovnik, Croatia, 2024.
HSBI-PUB
2023 | Konferenzbeitrag | FH-PUB-ID: 5723
T. Engelmann, L. Quakernack, and J. Haubrock, “Q-learning based control algorithm with dynamic combination of peak shaving and self-consumption optimization for industrial battery storage systems,” in PESS 2023; Power and Energy Student Summit, Bielefeld, 2023.
HSBI-PUB
| Download (ext.)
2023 | Konferenzbeitrag | FH-PUB-ID: 4357
K. Schulte, L. Engel, L. Quakernack, and J. Haubrock, “Optimized photovoltaic power forecast using k-means clustering based error reduction,” in 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Grenoble, France, 2023, pp. 1–5.
HSBI-PUB
| DOI
2023 | Konferenzbeitrag | FH-PUB-ID: 3105
L. Quakernack, J. Hövelmann, K. Kröger, and J. Haubrock, “AI-based heat demand forecasting in industrial buildings for flexible operation of combined heat and power plants,” presented at the International ETG-Congress 2023, Magdeburg, Germany, 2023.
HSBI-PUB
2023 | Konferenzbeitrag | FH-PUB-ID: 3096
B. Steinhagen et al., “Evaluation of the Usage of Edge Computing and LoRa for the Control of Electric Vehicle Charging in the Low Voltage Grid,” in 2023 IEEE PES Conference on Innovative Smart Grid Technologies - Middle East (ISGT Middle East), Abu Dhabi, United Arab Emirates, 2023, pp. 1–5.
HSBI-PUB
| DOI
2022 | Konferenzbeitrag | FH-PUB-ID: 3113
L. Quakernack, M. Kelker, and J. Haubrock, “Deep Reinforcement Learning For Autonomous Control Of Low Voltage Grids With Focus On Grid Stability In Future Power Grids,” in 2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Novi Sad, Serbia, 2022, pp. 1–5.
HSBI-PUB
| DOI
2022 | Konferenzbeitrag | FH-PUB-ID: 3112
M. Kelker, L. Quakernack, J. Haubrock, and D. Westermann, “Multi agent double deep Q-network with multiple reward functions for electric vehicle charge control,” in 2022 IEEE Power & Energy Society General Meeting (PESGM), Denver, CO, USA, 2022, pp. 01–05.
HSBI-PUB
| DOI
2022 | Konferenzbeitrag | FH-PUB-ID: 3097 |
L. Quakernack, M. Kelker, U. Rückert, and J. Haubrock, “Deep Reinforcement Learning als Methode zur autonomen Steuerung von Niederspannungsnetzen mit Fokus auf die Netzstabilität,” presented at the 17. Symposium Energieinnovation, Graz, 2022.
HSBI-PUB
| Download (ext.)
2018 | Konferenzbeitrag | FH-PUB-ID: 3360
L. Quakernack, M. Kelker, and J. Haubrock, “Simulation of a Smart-Micro-Grid to Analyse an Intelligent Charge Management in Matlab Simulink for a Local Bakery Chain,” presented at the 8. IEEE Germany Student Conference, Magdeburg, 2018.
HSBI-PUB