PUBLIKATIONSSERVER

Michael Kelker

21 Publikationen

Alle markieren

[21]
2024 | Konferenzbeitrag | FH-PUB-ID: 5719
Liegmann F, Schulte K, Annen F, et al. 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). IEEE; 2024:1-5. doi:10.1109/ISGTEUROPE62998.2024.10863253
HSBI-PUB | DOI
 
[20]
2023 | Dissertation | FH-PUB-ID: 3363 | OA
Kelker M. Optimierte Ladung von Elektrofahrzeugen Als Markow Entscheidungsprozess Mittels Maschineller Lernalgorithmen. Universitätsverlag Ilmenau; 2023. doi:10.22032/DBT.55670
HSBI-PUB | DOI | Download (ext.)
 
[19]
2023 | Konferenzbeitrag | FH-PUB-ID: 3096
Steinhagen B, Jungh T, Hesse M, 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). IEEE; 2023:1-5. doi:10.1109/ISGTMiddleEast56437.2023.10078593
HSBI-PUB | DOI
 
[18]
2022 | Konferenzbeitrag | FH-PUB-ID: 3113
Quakernack L, Kelker M, Haubrock J. 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). IEEE; 2022:1-5. doi:10.1109/ISGT-Europe54678.2022.9960416
HSBI-PUB | DOI
 
[17]
2022 | Konferenzbeitrag | FH-PUB-ID: 3112
Kelker M, Quakernack L, Haubrock J, Westermann D. Multi agent double deep Q-network with multiple reward functions for electric vehicle charge control. In: 2022 IEEE Power & Energy Society General Meeting (PESGM). IEEE; 2022:01-05. doi:10.1109/PESGM48719.2022.9917038
HSBI-PUB | DOI
 
[16]
2022 | Konferenzbeitrag | FH-PUB-ID: 3111
Liegmann F, Schorge L, Kelker M, Haubrock J. Virtual reality grid control station for learning the operational management of real electrical grids on emergency situation. In: 2022 IEEE German Education Conference (GeCon). IEEE; 2022:1-6. doi:10.1109/GeCon55699.2022.9942753
HSBI-PUB | DOI
 
[15]
2022 | Konferenzbeitrag | FH-PUB-ID: 3100 | OA
Liegmann F, Gurcke M, Kelker M, Haubrock J. Entwicklung einer Virtual Reality Netzleitwarte. In: ; 2022.
HSBI-PUB | Download (ext.)
 
[14]
2022 | Konferenzbeitrag | FH-PUB-ID: 3099 | OA
Gurcke M, Timpe K, Kelker M, Haubrock J. Adaption und Validierung einer Low Cost µPMU zur Netzüberwachung im Niederspannungsnetz. In: ; 2022.
HSBI-PUB | Download (ext.)
 
[13]
2022 | Konferenzbeitrag | FH-PUB-ID: 3097 | OA
Quakernack L, Kelker M, Rückert U, Haubrock J. Deep Reinforcement Learning als Methode zur autonomen Steuerung von Niederspannungsnetzen mit Fokus auf die Netzstabilität. In: ; 2022.
HSBI-PUB | Download (ext.)
 
[12]
2021 | Konferenzbeitrag | FH-PUB-ID: 3355
Schulte K, Runde O, Kelker M, Haubrock J. Prediction of the local cloud cover to optimize photovoltaic system power forecast. In: 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe). IEEE; 2021:01-05. doi:10.1109/ISGTEurope52324.2021.9640074
HSBI-PUB | DOI
 
[11]
2021 | Konferenzbeitrag | FH-PUB-ID: 3361
Liegmann F, Murtovi A, Kelker M, Haubrock J. Analysis of user behaviour for modelling an electric vehicle loading profile generator. In: ; 2021.
HSBI-PUB
 
[10]
2021 | Konferenzbeitrag | FH-PUB-ID: 3356
Kelker M, Quakernack L, Haubrock J. Multi agent deep Q-reinforcement learning for autonomous low voltage grid control. In: 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe). IEEE; 2021:1-6. doi:10.1109/ISGTEurope52324.2021.9639897
HSBI-PUB | DOI
 
[9]
2020 | Konferenzbeitrag | FH-PUB-ID: 3359
Schulte K, Kelker M, Haubrock J. 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. ; 2020.
HSBI-PUB
 
[8]
2020 | Konferenzbeitrag | FH-PUB-ID: 3358
Lohmann P, Kelker M, Schulte K, Haubrock J. Auslegung eines Antriebstranges für einen Batterie-Elektrischen Zug. In: EnInnov 2020; 16. Symposium Energieinnovation. ; 2020.
HSBI-PUB
 
[7]
2020 | Konferenzbeitrag | FH-PUB-ID: 3354
Kelker M, Schulte K, Haubrock J. 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. ; 2020.
HSBI-PUB
 
[6]
2020 | Konferenzbeitrag | FH-PUB-ID: 3353 | OA
Kelker M, Berrada A, Schulte K, Haubrock J. Entwicklung und Validierung eines optimalen Platzierungsalgorithmus für µPMUS im Niederspannungsnetz. In: EnInnov 2020; 16. Symposium Energieinnovation. ; 2020.
HSBI-PUB | Download (ext.)
 
[5]
2019 | Konferenzbeitrag | FH-PUB-ID: 3357
Kröger K, Annen F, Kelker M, Haubrock J. Development of a Microgrid Hardware Simulation System for Distributed Energy Resources in Combination with an Aggregated Battery Electric Vehicle. In: NEIS 2019; Conference on Sustainable Energy Supply and Energy Storage Systems, 2019. ; 2019.
HSBI-PUB
 
[4]
2019 | Konferenzbeitrag | FH-PUB-ID: 3351
Kelker M, Schulte K, Kröger K, Haubrock J. 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). IEEE; 2019:1-6. doi:10.1109/MEPS46793.2019.9394975
HSBI-PUB | DOI
 
[3]
2019 | Konferenzbeitrag | FH-PUB-ID: 3350
Kelker M, Schulte K, Hansmeier D, et al. 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. IEEE; 2019:1-6. doi:10.1109/PTC.2019.8810719
HSBI-PUB | DOI
 
[2]
2018 | Konferenzbeitrag | FH-PUB-ID: 3360
Quakernack L, Kelker M, Haubrock J. Simulation of a Smart-Micro-Grid to Analyse an Intelligent Charge Management in Matlab Simulink for a Local Bakery Chain. In: ; 2018.
HSBI-PUB
 
[1]
2018 | Konferenzbeitrag | FH-PUB-ID: 3349
Kelker M, Haubrock J. Modeling and simulation of a phasor measurement unit to analyse the grid reliability of a 110 kV grid. In: 2018 7th International Energy and Sustainability Conference (IESC). IEEE; 2018:1-6. doi:10.1109/IESC.2018.8439944
HSBI-PUB | DOI
 
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21 Publikationen

Alle markieren

[21]
2024 | Konferenzbeitrag | FH-PUB-ID: 5719
Liegmann F, Schulte K, Annen F, et al. 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). IEEE; 2024:1-5. doi:10.1109/ISGTEUROPE62998.2024.10863253
HSBI-PUB | DOI
 
[20]
2023 | Dissertation | FH-PUB-ID: 3363 | OA
Kelker M. Optimierte Ladung von Elektrofahrzeugen Als Markow Entscheidungsprozess Mittels Maschineller Lernalgorithmen. Universitätsverlag Ilmenau; 2023. doi:10.22032/DBT.55670
HSBI-PUB | DOI | Download (ext.)
 
[19]
2023 | Konferenzbeitrag | FH-PUB-ID: 3096
Steinhagen B, Jungh T, Hesse M, 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). IEEE; 2023:1-5. doi:10.1109/ISGTMiddleEast56437.2023.10078593
HSBI-PUB | DOI
 
[18]
2022 | Konferenzbeitrag | FH-PUB-ID: 3113
Quakernack L, Kelker M, Haubrock J. 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). IEEE; 2022:1-5. doi:10.1109/ISGT-Europe54678.2022.9960416
HSBI-PUB | DOI
 
[17]
2022 | Konferenzbeitrag | FH-PUB-ID: 3112
Kelker M, Quakernack L, Haubrock J, Westermann D. Multi agent double deep Q-network with multiple reward functions for electric vehicle charge control. In: 2022 IEEE Power & Energy Society General Meeting (PESGM). IEEE; 2022:01-05. doi:10.1109/PESGM48719.2022.9917038
HSBI-PUB | DOI
 
[16]
2022 | Konferenzbeitrag | FH-PUB-ID: 3111
Liegmann F, Schorge L, Kelker M, Haubrock J. Virtual reality grid control station for learning the operational management of real electrical grids on emergency situation. In: 2022 IEEE German Education Conference (GeCon). IEEE; 2022:1-6. doi:10.1109/GeCon55699.2022.9942753
HSBI-PUB | DOI
 
[15]
2022 | Konferenzbeitrag | FH-PUB-ID: 3100 | OA
Liegmann F, Gurcke M, Kelker M, Haubrock J. Entwicklung einer Virtual Reality Netzleitwarte. In: ; 2022.
HSBI-PUB | Download (ext.)
 
[14]
2022 | Konferenzbeitrag | FH-PUB-ID: 3099 | OA
Gurcke M, Timpe K, Kelker M, Haubrock J. Adaption und Validierung einer Low Cost µPMU zur Netzüberwachung im Niederspannungsnetz. In: ; 2022.
HSBI-PUB | Download (ext.)
 
[13]
2022 | Konferenzbeitrag | FH-PUB-ID: 3097 | OA
Quakernack L, Kelker M, Rückert U, Haubrock J. Deep Reinforcement Learning als Methode zur autonomen Steuerung von Niederspannungsnetzen mit Fokus auf die Netzstabilität. In: ; 2022.
HSBI-PUB | Download (ext.)
 
[12]
2021 | Konferenzbeitrag | FH-PUB-ID: 3355
Schulte K, Runde O, Kelker M, Haubrock J. Prediction of the local cloud cover to optimize photovoltaic system power forecast. In: 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe). IEEE; 2021:01-05. doi:10.1109/ISGTEurope52324.2021.9640074
HSBI-PUB | DOI
 
[11]
2021 | Konferenzbeitrag | FH-PUB-ID: 3361
Liegmann F, Murtovi A, Kelker M, Haubrock J. Analysis of user behaviour for modelling an electric vehicle loading profile generator. In: ; 2021.
HSBI-PUB
 
[10]
2021 | Konferenzbeitrag | FH-PUB-ID: 3356
Kelker M, Quakernack L, Haubrock J. Multi agent deep Q-reinforcement learning for autonomous low voltage grid control. In: 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe). IEEE; 2021:1-6. doi:10.1109/ISGTEurope52324.2021.9639897
HSBI-PUB | DOI
 
[9]
2020 | Konferenzbeitrag | FH-PUB-ID: 3359
Schulte K, Kelker M, Haubrock J. 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. ; 2020.
HSBI-PUB
 
[8]
2020 | Konferenzbeitrag | FH-PUB-ID: 3358
Lohmann P, Kelker M, Schulte K, Haubrock J. Auslegung eines Antriebstranges für einen Batterie-Elektrischen Zug. In: EnInnov 2020; 16. Symposium Energieinnovation. ; 2020.
HSBI-PUB
 
[7]
2020 | Konferenzbeitrag | FH-PUB-ID: 3354
Kelker M, Schulte K, Haubrock J. 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. ; 2020.
HSBI-PUB
 
[6]
2020 | Konferenzbeitrag | FH-PUB-ID: 3353 | OA
Kelker M, Berrada A, Schulte K, Haubrock J. Entwicklung und Validierung eines optimalen Platzierungsalgorithmus für µPMUS im Niederspannungsnetz. In: EnInnov 2020; 16. Symposium Energieinnovation. ; 2020.
HSBI-PUB | Download (ext.)
 
[5]
2019 | Konferenzbeitrag | FH-PUB-ID: 3357
Kröger K, Annen F, Kelker M, Haubrock J. Development of a Microgrid Hardware Simulation System for Distributed Energy Resources in Combination with an Aggregated Battery Electric Vehicle. In: NEIS 2019; Conference on Sustainable Energy Supply and Energy Storage Systems, 2019. ; 2019.
HSBI-PUB
 
[4]
2019 | Konferenzbeitrag | FH-PUB-ID: 3351
Kelker M, Schulte K, Kröger K, Haubrock J. 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). IEEE; 2019:1-6. doi:10.1109/MEPS46793.2019.9394975
HSBI-PUB | DOI
 
[3]
2019 | Konferenzbeitrag | FH-PUB-ID: 3350
Kelker M, Schulte K, Hansmeier D, et al. 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. IEEE; 2019:1-6. doi:10.1109/PTC.2019.8810719
HSBI-PUB | DOI
 
[2]
2018 | Konferenzbeitrag | FH-PUB-ID: 3360
Quakernack L, Kelker M, Haubrock J. Simulation of a Smart-Micro-Grid to Analyse an Intelligent Charge Management in Matlab Simulink for a Local Bakery Chain. In: ; 2018.
HSBI-PUB
 
[1]
2018 | Konferenzbeitrag | FH-PUB-ID: 3349
Kelker M, Haubrock J. Modeling and simulation of a phasor measurement unit to analyse the grid reliability of a 110 kV grid. In: 2018 7th International Energy and Sustainability Conference (IESC). IEEE; 2018:1-6. doi:10.1109/IESC.2018.8439944
HSBI-PUB | DOI
 
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Suche

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Darstellung / Sortierung

Zitationsstil: AMA

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