Deutsch Intern
Chair of Computer Science III

Prof. Dr.-Ing. Marco Pruckner

Telefon (0931) 31-89054
Telefax (0931) 31-86632




Lehrstuhl für Kommunikationsnetze (Informatik III)

Am Hubland
D-97074 Würzburg
2022[ to top ]
  • Heinrich, F., & Pruckner, M. Virtual experiments for battery state of health estimation based on neural networks and in-vehicle data. Journal of Energy Storage, 48, 103856.
  • Strobel, L., Schlund, J., & Pruckner, M. Joint analysis of regional and national power system impacts of electric vehicles - A case study for Germany on the county level in 2030. Applied Energy, 315, 118945. https://doi.org/10.1016/j.apenergy.2022.118945
  • Bayer, D., & Pruckner, M. Enhancing the Performance of Multi-Agent Reinforcement Learning for Controlling HVAC Systems. 2022 IEEE Conference on Technologies for Sustainability (SusTech), 187-194. https://doi.org/10.1109/SusTech53338.2022.9794179
2021[ to top ]
  • Heinrich, F., Noering, F.-D., Pruckner, M., & Jonas, K. Unsupervised data-preprocessing for Long Short-Term Memory based battery model under electric vehicle operation. Journal of Energy Storage, 38, 102598. https://doi.org/https://doi.org/10.1016/j.est.2021.102598
  • Tuchnitz, F., Ebell, N., Schlund, J., & Pruckner, M. Development and Evaluation of a Smart Charging Strategy for an Electric Vehicle Fleet Based on Reinforcement Learning. Applied Energy, 285, 116382. https://doi.org/https://doi.org/10.1016/j.apenergy.2020.116382
  • Scharrer, D., Pruckner, M., Bazan, P., & German, R. Dynamic modeling and sensitivity analysis of a stratified heat storage coupled with a heat pump and an organic rankine cycle. 2021 Winter Simulation Conference (WSC), 1-12.
  • Barthel, V., Schlund, J., Landes, P., Brandmeier, V., & Pruckner, M. Analyzing the Charging Flexibility Potential of Different Electric Vehicle Fleets Using Real-World Charging Data. Energies, 14(16), Article 16. https://doi.org/10.3390/en14164961
  • Iacobucci, R., Donhauser, J., Schm{\"o}cker, J.-D., & Pruckner, M. Frequency Control Reserve Provision from a Fleet of Shared Autonomous Electric Vehicles. 2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), 1-6.
  • Ebell, N., & Pruckner, M. Benchmarking a Decentralized Reinforcement Learning Control Strategy for an Energy Community. 2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 385-390.
  • Strobel, L., Schlund, J., Brandmeier, V., Schreiber, M., & Pruckner, M. Smart Charging and Renewable Grid Integration - A Case Study Based on Real-Data of the Island of Porto Santo. In J. L. Afonso, V. Monteiro, & J. G. Pinto (Eds.), Sustainable Energy for Smart Cities (pp. 200-215). Springer International Publishing.
  • Heinrich, F., Klapper, P., & Pruckner, M. A comprehensive study on battery electric modeling approaches based on machine learning. DACH Conference on Energy Informatics, 4(3), 1-17.
2020[ to top ]
  • Scharrer, D., Eppinger, B., Schmitt, P., Zenk, J., Bazan, P., Karl, J., Will, S., Pruckner, M., & German, R. Life Cycle Assessment of a Reversible Heat Pump�Organic Rankine Cycle�Heat Storage System with Geothermal Heat Supply. Energies, 13(12), Article 12. https://doi.org/10.3390/en13123253
  • Apostolaki-Iosifidou, E., Pruckner, M., Woo, S., & Lipman, T. Electric Vehicle Charge Management for Lowering Costs and Environmental Impact. 2020 IEEE Conference on Technologies for Sustainability (SusTech), 1-7. https://doi.org/10.1109/SusTech47890.2020.9150524
  • Pruckner, M., & Eckhoff, D. Shared Autonomous Electric Vehicles and the Power Grid: Applications and Research Challenges. ISGT-Europe, 1151-1155. http://dblp.uni-trier.de/db/conf/isgteurope/isgteurope2020.html#PrucknerE20
  • Schlund, J., Pruckner, M., & German, R. FlexAbility - Modeling and Maximizing the Bidirectional Flexibility Availability of Unidirectional Charging of Large Pools of Electric Vehicles. Proceedings of the Eleventh ACM International Conference on Future Energy Systems, 121�132. https://doi.org/10.1145/3396851.3397697
  • Doluweera, G., Hahn, F., Bergerson, J., & Pruckner, M. A scenario-based study on the impacts of electric vehicles on energy consumption and sustainability in Alberta. Applied Energy, 268, 114961. https://doi.org/https://doi.org/10.1016/j.apenergy.2020.114961
2019[ to top ]
  • Ebell, N., Gütlein, M., & Pruckner, M. Sharing of Energy Among Cooperative Households Using Distributed Multi-Agent Reinforcement Learning. ISGT Europe, 1-5. http://dblp.uni-trier.de/db/conf/isgteurope/isgteurope2019.html#EbellGP19
  • Spitzer, M., Schlund, J., Apostolaki-Iosifidou, E., & Pruckner, M. Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids. Energies, 12(21), Article 21. https://doi.org/10.3390/en12214059
2018[ to top ]
  • Ebell, N., & Pruckner, M. Coordinated Multi-Agent Reinforcement Learning for Swarm Battery Control. CCECE, 1-4. http://dblp.uni-trier.de/db/conf/ccece/ccece2018.html#EbellP18
  • Steber, D., Hubler, J., & Pruckner, M. A comprehensive electricity Market Model using simulation and Optimization Techniques. In B. Johansson & S. Jain (Eds.), WSC (pp. 2095-2106). IEEE. http://dblp.uni-trier.de/db/conf/wsc/wsc2018.html#SteberHP18
  • Bazan, P., Djanatliev, A., Pruckner, M., German, R., & Lauer, C. Rebalancing and fleet sizing of Mobility-on-demand Networks with combined simulation, Optimization and Queueing Network Analysis. In B. Johansson & S. Jain (Eds.), WSC (pp. 1527-1538). IEEE. http://dblp.uni-trier.de/db/conf/wsc/wsc2018.html#BazanDPGL18
  • Schlund, J., Steinert, R., & Pruckner, M. Coordinating E-Mobility Charging for Frequency Containment Reserve Power Provision. In H. Schmeck & V. Hagenmeyer (Eds.), e-Energy (pp. 556-563). ACM. http://dblp.uni-trier.de/db/conf/eenergy/eenergy2018.html#SchlundSP18
  • Steber, D., Pruckner, M., Schlund, J., Bazan, P., & German, R. Including a virtual battery storage into thermal unit commitment. Comput. Sci. Res. Dev., 33(1-2), 223-229. http://dblp.uni-trier.de/db/journals/ife/ife33.html#SteberPSBG18
  • Ebell, N., Heinrich, F., Schlund, J., & Pruckner, M. Reinforcement Learning Control Algorithm for a PV-Battery-System Providing Frequency Containment Reserve Power. SmartGridComm, 1-6. http://dblp.uni-trier.de/db/conf/smartgridcomm/smartgridcomm2018.html#EbellHSP18
  • Staub, S., Bazan, P., Braimakis, K., Müller, D., Regensburger, C., Scharrer, D., Schmitt, B., Steger, D., German, R., Karellas, S., Pruckner, M., Schl�cker, E., Will, S., & Karl, J. Reversible Heat Pump Organic Rankine Cycle Systems for the Storage of Renewable Electricity. Energies, 11(6), Article 6. https://doi.org/10.3390/en11061352
2017[ to top ]
  • Dicke, P., Meyer, B., & Pruckner, M. Electrification of public bus transport under the usage of electricity generated by renewables. 2017 2nd IEEE International Conference on Intelligent Transportation Engineering (ICITE), 314-319. https://doi.org/10.1109/ICITE.2017.8056931
  • Steber, D., Pruckner, M., Bazan, P., & German, R. SWARM � Providing 1 MW FCR power with residential PV-battery energy storage � Simulation and empiric validation. 2017 IEEE Manchester PowerTech, 1-6. https://doi.org/10.1109/PTC.2017.7981091
  • Longo, M., Lutz, N. M., Daniel, L., Zaninelli, D., & Pruckner, M. Towards an impact study of electric vehicles on the Italian electric power system using simulation techniques. RTSI, 1-5. http://dblp.uni-trier.de/db/conf/rtsi/rtsi2017.html#LongoLDZP17
  • Pruckner, M., German, R., & Eckhoff, D. Spatial and Temporal Charging Infrastructure Planning Using Discrete Event Simulation. In W. Cai, Y. M. Teo, P. Wilsey, & K. Jin (Eds.), SIGSIM-PADS (pp. 249-257). ACM. http://dblp.uni-trier.de/db/conf/pads/pads2017.html#PrucknerGE17
  • Dicke, P., Meyer, B., & Pruckner, M. Analysis of Various Charging Strategies for Electrified Public Bus Transport Utilizing a Lightweight Simulation Model. Proceedings of the 1st E-Mobility Power System Integration Symposium.
2016[ to top ]
  • Pruckner, M., & German, R. The impact of electric vehicles on the german energy system. In J. J. Padilla, A. Tolk, & S. Jafer (Eds.), SpringSim (ANSS) (p. 23). ACM. http://dblp.uni-trier.de/db/conf/springsim/springsim2016-2.html#PrucknerG16
  • Pruckner, M. Modeling the impact of electrical energy storage systems on future power systems. 2016 IEEE Electrical Power and Energy Conference (EPEC), 1-7. https://doi.org/10.1109/EPEC.2016.7771724
2015[ to top ]
  • Bazan, P., Pruckner, M., Steber, D., & German, R. Hierarchical Simulation of the German Energy System and Houses with PV and Storage Systems. In S. Gottwalt, L. König, & H. Schmeck (Eds.), D-A-CH EI (Vols. 9424, pp. 12-23). Springer. http://dblp.uni-trier.de/db/conf/energieinformatik/energieinformatik2015.html#BazanPSG15
  • Pruckner, M. Ein Simulationsmodell f{\"u}r den Energieumstieg in Bayern. Cuvillier Verlag.
2014[ to top ]
  • Pruckner, M., Eckhoff, D., & German, R. Modeling country-scale electricity demand profiles. In S. J. Buckley & J. A. Miller (Eds.), Winter Simulation Conference (pp. 1084-1095). IEEE/ACM. http://dblp.uni-trier.de/db/conf/wsc/wsc2014.html#PrucknerEG14
  • Awad, A., Pruckner, M., Bazan, P., & German, R. On the profit enhancement and state estimation services in the smart grid. ISGT, 1-5. http://dblp.uni-trier.de/db/conf/isgt/isgt2014.html#AwadPBG14
  • Pruckner, M., & German, R. Modeling and simulation of electricity generated by renewable energy sources for complex energy systems. SpringSim (ANSS), 4. http://dblp.uni-trier.de/db/conf/springsim/springsim2014-2.html#PrucknerG14
  • Pruckner, M., Seifert, G., Luther, M., & German, R. Gekoppeltes Energiesystemmodell f{\"u}r den Energieumstieg in Bayern. Energiesymposium 2014.
2013[ to top ]
  • Pruckner, M., & German, R. A hybrid simulation model for large-scaled electricity generation systems. Winter Simulation Conference, 1881-1892. http://dblp.uni-trier.de/db/conf/wsc/wsc2013.html#PrucknerG13
  • Pruckner, M., & German, R. A simulation model to analyze the residual load during the extension of highly fluctuating renewables in Bavaria, Germany. 4th International Conference on Power Engineering, Energy and Electrical Drives, 540-545. https://doi.org/10.1109/PowerEng.2013.6635666
2012[ to top ]
  • Pruckner, M., Bazan, P., & German, R. Towards a simulation model of the Bavarian electrical energy system. In U. Goltz, M. A. Magnor, H.-J. Appelrath, H. K. Matthies, W.-T. Balke, & L. C. Wolf (Eds.), GI-Jahrestagung: Vol. P-208 (pp. 597-612). GI. http://dblp.uni-trier.de/db/conf/gi/gi2012.html#PrucknerBG12
  • Pruckner, M., Awad, A., & German, R. A study on the impact of packet loss and latency on real-time demand response in smart grid. GLOBECOM Workshops, 1486-1490. http://dblp.uni-trier.de/db/conf/globecom/globecom2012w.html#PrucknerAG12
  • Pruckner, M., & German, R. An approach of a simulation model to analyze the future energy balance of Bavaria. 2012 International Conference on Smart Grid Technology, Economics and Policies (SG-TEP), 1-4. https://doi.org/10.1109/SG-TEP.2012.6642368