Jonas Schiller - Computer Science XI - Modeling and Simulation

Phone	0931 31-88578
Telefax
E-Mail	jonas.schiller@uni-wuerzburg.de
Room	01.017 (Building M4)
Address	Lehrstuhl für Informatik XI Am Hubland 97074 Würzburg Germany

ORCID

Research Interests

Optimization of Energy Usage and adaption towards decentralized energy resources
Modelling human behavior and uncertainty in energy and mobility models
Transformation of Mobility towards more sustainable modes of transportation systems

Research projects

Recent Publications

2025[ to top ]

Server-side performance and environmental impact evaluation of a hybrid e-learning website. Prantl, Thomas; Wolf, Luis; Schiller, Jonas; Pruckner, Marco; Kounev, Samuel; Dänzer, Tobias; von Kistowski, Jóakim. In Discover Applied Sciences. 2025.
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The importance of e-learning in modern education systems is increasing, and Server-Side Rendering (SSR) is making a comeback as a popular technique for building websites with dynamic content. This paper examines a real-world e-learning platform utilizing SSR and assesses its performance and environmental impact. An initial analysis of the platform's usage was conducted to replicate a realistic workload during which we captured realistic user behavior. Since existing load-generation tools do not support all the requirements of modern websites, we developed a custom load-generation tool built on top of established open-source tools. We use our load-generation tool to emulate virtual users, using captured user behavior as a basis. The load generator we developed is very low-maintenance and allows developers to easily test different configurations of a hybrid website without having to adapt the load generator. Therefore, thanks to our flexible load generator, we were able to measure the resources and energy consumption of the real-world e-learning platform under varying virtual user loads in different configurations. The results showed that using a caching mechanism significantly lowered system load compared to a system without caching. Regardless of whether caching was enabled, external network traffic remained nearly identical as all required resources (database, static files, etc.) were hosted on the system. Energy consumption was lower with the cache enabled, aligning with other system resource usage patterns. Specifically, our system would produce 0.161t {\$}{\$}{\backslash}hbox {\{}CO{\}}{\_}2{\$}{\$} emissions at idle in a year. Under permanent load with 600 concurrent users, the system would produce 0.192t {\$}{\$}{\backslash}hbox {\{}CO{\}}{\_}2{\$}{\$} with caching enabled and 0.203t {\$}{\$}{\backslash}hbox {\{}CO{\}}{\_}2{\$}{\$} without caching.

@article{Prantl2025, abstract = {The importance of e-learning in modern education systems is increasing, and Server-Side Rendering (SSR) is making a comeback as a popular technique for building websites with dynamic content. This paper examines a real-world e-learning platform utilizing SSR and assesses its performance and environmental impact. An initial analysis of the platform's usage was conducted to replicate a realistic workload during which we captured realistic user behavior. Since existing load-generation tools do not support all the requirements of modern websites, we developed a custom load-generation tool built on top of established open-source tools. We use our load-generation tool to emulate virtual users, using captured user behavior as a basis. The load generator we developed is very low-maintenance and allows developers to easily test different configurations of a hybrid website without having to adapt the load generator. Therefore, thanks to our flexible load generator, we were able to measure the resources and energy consumption of the real-world e-learning platform under varying virtual user loads in different configurations. The results showed that using a caching mechanism significantly lowered system load compared to a system without caching. Regardless of whether caching was enabled, external network traffic remained nearly identical as all required resources (database, static files, etc.) were hosted on the system. Energy consumption was lower with the cache enabled, aligning with other system resource usage patterns. Specifically, our system would produce 0.161t {\$}{\$}{\backslash}hbox {\{}CO{\}}{\_}2{\$}{\$} emissions at idle in a year. Under permanent load with 600 concurrent users, the system would produce 0.192t {\$}{\$}{\backslash}hbox {\{}CO{\}}{\_}2{\$}{\$} with caching enabled and 0.203t {\$}{\$}{\backslash}hbox {\{}CO{\}}{\_}2{\$}{\$} without caching.}, author = {Prantl, Thomas and Wolf, Luis and Schiller, Jonas and Pruckner, Marco and Kounev, Samuel and Dänzer, Tobias and von Kistowski, Jóakim}, journal = {Discover Applied Sciences}, keywords = {schiller}, month = 12, title = {Server-side performance and environmental impact evaluation of a hybrid e-learning website}, year = 2025 }
Optimal Charging at Electric Bus Depot integrating Stationary Battery Storage and Transmission Tariffs. Schiller, Jonas; Serejo-Kunz, Leticia; Pruckner, Marco. In 2025 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe), pp. 1–5. 2025.
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The transformation of municipal bus fleets from internal combustion to electric engines poses significant challenges for the operators. These include long charging times, shorter maximum driving distances, and consumption being highly dependent on outside temperature, requiring a sophisticated charging management. At the same time, adaptive charge scheduling can utilize fluctuating electricity prices and renewable energy sources to reduce costs and greenhouse gas emissions. This paper investigates the effects of integrating a stationary battery energy storage system and transmission tariffs on optimal policies for an electric bus depot operation. The battery storage enables charging time shifts and potential profits through arbitrage. We model different charging strategies for both buses and the stationary battery and investigate the effects of different transmission tariff classes based on a case study in Germany.

@inproceedings{11305508, abstract = {The transformation of municipal bus fleets from internal combustion to electric engines poses significant challenges for the operators. These include long charging times, shorter maximum driving distances, and consumption being highly dependent on outside temperature, requiring a sophisticated charging management. At the same time, adaptive charge scheduling can utilize fluctuating electricity prices and renewable energy sources to reduce costs and greenhouse gas emissions. This paper investigates the effects of integrating a stationary battery energy storage system and transmission tariffs on optimal policies for an electric bus depot operation. The battery storage enables charging time shifts and potential profits through arbitrage. We model different charging strategies for both buses and the stationary battery and investigate the effects of different transmission tariff classes based on a case study in Germany.}, author = {Schiller, Jonas and Serejo-Kunz, Leticia and Pruckner, Marco}, booktitle = {2025 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)}, keywords = {schiller}, month = 10, pages = {1-5}, title = {Optimal Charging at Electric Bus Depot integrating Stationary Battery Storage and Transmission Tariffs}, year = 2025 }
Sustainable, Situation-Aware Multi Objective Spatial Load Scheduling for Data Centers. Schiller, Jonas; Pruckner, Marco. In Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems, of E-Energy ’25, pp. 874–881. ACM, 2025.
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Data centers are already among the largest consumers of electricity worldwide and recent advancements in Large Language Models (LLM) will further increase this demand. Through their operation, they are responsible for large amounts of indirect carbon emissions as well as direct and indirect water consumption. This work proposes a novel multi-objective load shifting optimization focusing on low costs and reduced resource depletion. For the resource depletion we combine the long term effects of carbon emissions with the short term effects of water consumption, which in a novel approach is weighted based on a newly developed spatial and temporal drought risk indicator. We investigate a use case where we optimally shift the inference load of a LLM spatially when hosted in ten different European countries. Additionally, we extend previous research on the water intensity of the electric grid by providing the first automated framework called IntensityLib for calculating water intensity factors for the European electricity grid as well as integrating a flow-tracing algorithm which models the effect of imports and exports. We find that adjusting for water scarcity leads to entirely different solutions compared to simply minimizing water consumption and can prevent further stress on regions with reoccurring drought risks.

@inproceedings{Schiller_2025, abstract = {Data centers are already among the largest consumers of electricity worldwide and recent advancements in Large Language Models (LLM) will further increase this demand. Through their operation, they are responsible for large amounts of indirect carbon emissions as well as direct and indirect water consumption. This work proposes a novel multi-objective load shifting optimization focusing on low costs and reduced resource depletion. For the resource depletion we combine the long term effects of carbon emissions with the short term effects of water consumption, which in a novel approach is weighted based on a newly developed spatial and temporal drought risk indicator. We investigate a use case where we optimally shift the inference load of a LLM spatially when hosted in ten different European countries. Additionally, we extend previous research on the water intensity of the electric grid by providing the first automated framework called IntensityLib for calculating water intensity factors for the European electricity grid as well as integrating a flow-tracing algorithm which models the effect of imports and exports. We find that adjusting for water scarcity leads to entirely different solutions compared to simply minimizing water consumption and can prevent further stress on regions with reoccurring drought risks.}, author = {Schiller, Jonas and Pruckner, Marco}, booktitle = {Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems}, keywords = {schiller}, month = {06}, pages = {874–881}, publisher = {ACM}, series = {E-Energy ’25}, title = {Sustainable, Situation-Aware Multi Objective Spatial Load Scheduling for Data Centers}, year = 2025 }

2024[ to top ]

Evaluating Water-Energy Nexus related Water Saving Potentials of Residential Households with Solar PV and Electric Storage. Schiller, Jonas; Pruckner, Marco. In Proceedings of the 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, of BuildSys ’24, pp. 159–163. Association for Computing Machinery, Hangzhou, China, 2024.
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The energy sector is one of the largest consumers of water in Europe. As water scarcity has a severe impact on nature and human health, energy related water consumption, similar as for CO2 emissions, should be included in an environmental assessment. This study investigates the indirect water usage of households through their energy consumption based on a case study for two European countries, Germany and Spain. We calculate the water consumption of several thousand individual residential households based on their electricity consumption and the water intensity of the electric grid in an hourly resolution. Additionally, we investigate the effect of residential photovoltaic and battery electric storage systems on the water consumption and contrast potential optimization strategies towards high self-consumption and water consumption minimization. Our results show that the introduction of a small 0.89 kWp solar system can already reduce indirect water consumption by on average 20 % while a battery and solar photovoltaic system optimized for minimal water consumption achieves a mean reduction of over 40 % in Spain and 25 % in Germany.

@inproceedings{Schiller2024, abstract = {The energy sector is one of the largest consumers of water in Europe. As water scarcity has a severe impact on nature and human health, energy related water consumption, similar as for CO2 emissions, should be included in an environmental assessment. This study investigates the indirect water usage of households through their energy consumption based on a case study for two European countries, Germany and Spain. We calculate the water consumption of several thousand individual residential households based on their electricity consumption and the water intensity of the electric grid in an hourly resolution. Additionally, we investigate the effect of residential photovoltaic and battery electric storage systems on the water consumption and contrast potential optimization strategies towards high self-consumption and water consumption minimization. Our results show that the introduction of a small 0.89 kWp solar system can already reduce indirect water consumption by on average 20 % while a battery and solar photovoltaic system optimized for minimal water consumption achieves a mean reduction of over 40 % in Spain and 25 % in Germany.}, address = {New York, NY, USA}, author = {Schiller, Jonas and Pruckner, Marco}, booktitle = {Proceedings of the 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation}, keywords = {schiller}, month = 10, pages = {159–163}, publisher = {Association for Computing Machinery}, series = {BuildSys '24}, title = {Evaluating Water-Energy Nexus related Water Saving Potentials of Residential Households with Solar PV and Electric Storage}, year = 2024 }

Jonas Schiller M. Sc.

Research Interests

Research projects

Recent Publications

Bildnachweise