Paul Benz - Computer Science XI - Modeling and Simulation

Phone	(0931) 31-85146
E-Mail	paul.benz@uni-wuerzburg.de
Room	01.012 (Building M4)
Address	Lehrstuhl für Informatik XI Am Hubland 97074 Würzburg Germany

Researchgate

Research Interests

Hybrid modeling and simulation of mobility, transportation and landuse
Integration of charging infrastructures for electric vehicles into the power grid
Optimized use of renewable energies

Research projects

Recent Publications

2025[ to top ]

Identification of Spatial Energy Demand Shift Flexibilities of EV Charging on Regional Level through Agent-Based Simulation. Benz, Paul; Pruckner, Marco. In 2025 Winter Simulation Conference (WSC), pp. 1339–1350. 2025.
- [ Abstract ]
- [ BibTeX ]
- [ DOI ]
Open access to electric vehicle charging session data is limited to a small selection provided by operators of mostly public or workplace chargers. This restriction poses a hurdle in research on regional energy demand shift flexibilities enabled by smart charging, since usage characteristics between different charging options remain hidden. In this paper, we present an agent-based simulation model with parameterizable availability and usage preferences of public and private charging infrastructure to access insights of charging behavior otherwise only visible through proprietary data. Thus, we enable utility operators to estimate spatial charging energy distribution and support the integration of renewable energy by showing potentials for smart charging. In a first application, we point out how increased access and use of private charging facilities can lead to additional energy demand in rural municipalities, which, in turn, leads to a lower grid load in urban centers.

@inproceedings{11339027, abstract = {Open access to electric vehicle charging session data is limited to a small selection provided by operators of mostly public or workplace chargers. This restriction poses a hurdle in research on regional energy demand shift flexibilities enabled by smart charging, since usage characteristics between different charging options remain hidden. In this paper, we present an agent-based simulation model with parameterizable availability and usage preferences of public and private charging infrastructure to access insights of charging behavior otherwise only visible through proprietary data. Thus, we enable utility operators to estimate spatial charging energy distribution and support the integration of renewable energy by showing potentials for smart charging. In a first application, we point out how increased access and use of private charging facilities can lead to additional energy demand in rural municipalities, which, in turn, leads to a lower grid load in urban centers.}, author = {Benz, Paul and Pruckner, Marco}, booktitle = {2025 Winter Simulation Conference (WSC)}, keywords = {pruckner}, month = 12, pages = {1339-1350}, title = {Identification of Spatial Energy Demand Shift Flexibilities of EV Charging on Regional Level through Agent-Based Simulation}, year = 2025 }

2024[ to top ]

Lightweight Smart Charging vs. Immediate Charging with Buffer Storage: Towards a Simulation Study for Electric Vehicle Grid Integration at Workplaces. Benz, Paul; Pruckner, Marco. In Proceedings of the Winter Simulation Conference, of WSC ’23, pp. 922–933. IEEE Press, 2024.
- [ Abstract ]
- [ BibTeX ]
- [ URL ]
- [ DOI ]
The present study investigates the extension of an existing simulation model combining system dynamics and discrete event simulation by linear optimization for an electric vehicle charging system. The existing simulation framework is extended by a smart charging strategy based on linear programming in order to exploit the flexibility of real charging processes at a workplace parking lot for a better integration of solar photovoltaic electricity generation. Therefore, different smart charging strategies are evaluated. In multiple simulation runs, the strategies are compared with immediate charging using a stationary battery energy storage system for intermediate storage of electricity generated by solar photovoltaic. Results show that smart charging strategies can achieve similarly good results with respect to the self-sufficiency rate and self-consumption rate. In the context of a 100kWp PV system the combination of optimizing charging rates and stationary battery energy storage resulted in self-sufficiency rates of more than 90\% in the simulation.

@inproceedings{10.5555/3643142.3643218, abstract = {The present study investigates the extension of an existing simulation model combining system dynamics and discrete event simulation by linear optimization for an electric vehicle charging system. The existing simulation framework is extended by a smart charging strategy based on linear programming in order to exploit the flexibility of real charging processes at a workplace parking lot for a better integration of solar photovoltaic electricity generation. Therefore, different smart charging strategies are evaluated. In multiple simulation runs, the strategies are compared with immediate charging using a stationary battery energy storage system for intermediate storage of electricity generated by solar photovoltaic. Results show that smart charging strategies can achieve similarly good results with respect to the self-sufficiency rate and self-consumption rate. In the context of a 100kWp PV system the combination of optimizing charging rates and stationary battery energy storage resulted in self-sufficiency rates of more than 90\% in the simulation.}, author = {Benz, Paul and Pruckner, Marco}, booktitle = {Proceedings of the Winter Simulation Conference}, keywords = {pruckner}, pages = {922–933}, publisher = {IEEE Press}, series = {WSC '23}, title = {Lightweight Smart Charging vs. Immediate Charging with Buffer Storage: Towards a Simulation Study for Electric Vehicle Grid Integration at Workplaces}, year = 2024 }

Paul Benz M. Sc.

Research Interests

Research projects

Recent Publications

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