piwik-script

Intern
Lehrstuhl für Informatik III

Prof. Dr.-Ing. Marco Pruckner

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

marco.pruckner@uni-wuerzburg.de

Raum  

Anschrift

Lehrstuhl für Kommunikationsnetze (Informatik III)

Am Hubland
D-97074 Würzburg

Contents:  Overview | Publications | Research


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 (2022).
  • 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 (2022).
  • Bayer, D., Pruckner, M.: Enhancing the Performance of Multi-Agent Reinforcement Learning for Controlling HVAC Systems. 2022 IEEE Conference on Technologies for Sustainability (SusTech). pp. 187–194 (2022).
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 (2021).
  • 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 (2021).
  • 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). pp. 1–12. IEEE (2021).
  • 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, (2021).
  • 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). pp. 1–6. IEEE (2021).
  • 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). pp. 385–390. IEEE (2021).
  • 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: Afonso, J.L., Monteiro, V., and Pinto, J.G. (eds.) Sustainable Energy for Smart Cities. pp. 200–215. Springer International Publishing, Cham (2021).
  • Heinrich, F., Klapper, P., Pruckner, M.: A comprehensive study on battery electric modeling approaches based on machine learning. DACH Conference on Energy Informatics. 4, 1–17 (2021).
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, (2020).
  • 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). pp. 1–7 (2020).
  • Pruckner, M., Eckhoff, D.: Shared Autonomous Electric Vehicles and the Power Grid: Applications and Research Challenges. ISGT-Europe. pp. 1151–1155. IEEE (2020).
  • 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. p. 121�132. Association for Computing Machinery, Virtual Event, Australia (2020).
  • 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 (2020).
2019[ to top ]
  • Ebell, N., Gütlein, M., Pruckner, M.: Sharing of Energy Among Cooperative Households Using Distributed Multi-Agent Reinforcement Learning. ISGT Europe. pp. 1–5. IEEE (2019).
  • Spitzer, M., Schlund, J., Apostolaki-Iosifidou, E., Pruckner, M.: Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids. Energies. 12, (2019).
2018[ to top ]
  • Ebell, N., Pruckner, M.: Coordinated Multi-Agent Reinforcement Learning for Swarm Battery Control. CCECE. pp. 1–4. IEEE (2018).
  • Steber, D., Hubler, J., Pruckner, M.: A comprehensive electricity Market Model using simulation and Optimization Techniques. In: Johansson, B. and Jain, S. (eds.) WSC. pp. 2095–2106. IEEE (2018).
  • 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: Johansson, B. and Jain, S. (eds.) WSC. pp. 1527–1538. IEEE (2018).
  • Schlund, J., Steinert, R., Pruckner, M.: Coordinating E-Mobility Charging for Frequency Containment Reserve Power Provision. In: Schmeck, H. and Hagenmeyer, V. (eds.) e-Energy. pp. 556–563. ACM (2018).
  • Steber, D., Pruckner, M., Schlund, J., Bazan, P., German, R.: Including a virtual battery storage into thermal unit commitment. Comput. Sci. Res. Dev. 33, 223–229 (2018).
  • Ebell, N., Heinrich, F., Schlund, J., Pruckner, M.: Reinforcement Learning Control Algorithm for a PV-Battery-System Providing Frequency Containment Reserve Power. SmartGridComm. pp. 1–6. IEEE (2018).
  • 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, (2018).
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). pp. 314–319 (2017).
  • 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. pp. 1–6 (2017).
  • 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. pp. 1–5. IEEE (2017).
  • Pruckner, M., German, R., Eckhoff, D.: Spatial and Temporal Charging Infrastructure Planning Using Discrete Event Simulation. In: Cai, W., Teo, Y.M., Wilsey, P., and Jin, K. (eds.) SIGSIM-PADS. pp. 249–257. ACM (2017).
  • 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. , Berlin, Germany (2017).
2016[ to top ]
  • Pruckner, M., German, R.: The impact of electric vehicles on the german energy system. In: Padilla, J.J., Tolk, A., and Jafer, S. (eds.) SpringSim (ANSS). p. 23. ACM (2016).
  • Pruckner, M.: Modeling the impact of electrical energy storage systems on future power systems. 2016 IEEE Electrical Power and Energy Conference (EPEC). pp. 1–7 (2016).
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: Gottwalt, S., König, L., and Schmeck, H. (eds.) D-A-CH EI. pp. 12–23. Springer (2015).
  • Pruckner, M.: Ein Simulationsmodell f{\"u}r den Energieumstieg in Bayern. Cuvillier Verlag (2015).
2014[ to top ]
  • Pruckner, M., Eckhoff, D., German, R.: Modeling country-scale electricity demand profiles. In: Buckley, S.J. and Miller, J.A. (eds.) Winter Simulation Conference. pp. 1084–1095. IEEE/ACM (2014).
  • Awad, A., Pruckner, M., Bazan, P., German, R.: On the profit enhancement and state estimation services in the smart grid. ISGT. pp. 1–5. IEEE (2014).
  • Pruckner, M., German, R.: Modeling and simulation of electricity generated by renewable energy sources for complex energy systems. SpringSim (ANSS). p. 4. SCS/ACM (2014).
  • Pruckner, M., Seifert, G., Luther, M., German, R.: Gekoppeltes Energiesystemmodell f{\"u}r den Energieumstieg in Bayern. Energiesymposium 2014. , Graz, Austria (2014).
2013[ to top ]
  • Pruckner, M., German, R.: A hybrid simulation model for large-scaled electricity generation systems. Winter Simulation Conference. pp. 1881–1892. IEEE (2013).
  • 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. pp. 540–545 (2013).
2012[ to top ]
  • Pruckner, M., Bazan, P., German, R.: Towards a simulation model of the Bavarian electrical energy system. In: Goltz, U., Magnor, M.A., Appelrath, H.-J., Matthies, H.K., Balke, W.-T., and Wolf, L.C. (eds.) GI-Jahrestagung. pp. 597–612. GI (2012).
  • 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. pp. 1486–1490. IEEE (2012).
  • 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). pp. 1–4 (2012).