Prof. Dr.-Ing. Marco Pruckner

• A Large Scale Simulation of the Electrification Effects of SAVs Iacobucci, Riccardo; Pruckner, Marco; Schm{\"o}cker, Jan-Dirk in Smart Energy for Smart Transport, E. G. Nathanail, N. Gavanas, G. Adamos (eds.) (2023). 115–124.
  • [ Abstract ]
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  Shared autonomous electric vehicles (SAEVs) are expected to soon revolutionize the transport system, with cheap and convenient taxi-like services. SAEVs can induce a significant modal shift from other modes of travel, with effects ranging from beneficial, like reducing private car use, to negative, like making public transport uneconomical and increasing congestion. This modal shift will also be influenced by electrification, as charging time and range limitations will influence availability of these vehicles. In this work, we expand a SAEV simulationIacobucci, R.Pruckner, M.Schm{\"o}ecker, J.-D. model with mode choice to incorporate electric vehicles. In our model travelers choose between their current mode and SAEVs, which in addition to the fare, has a waiting time which depends on the real-time demand and fleet availability. We use a trip generation model based on a large person trip survey from Germany as our input data and scale-up the survey to obtain an OD matrix for the whole wider Munich area on a 1 km{\$}{\$}^2{\$}{\$}2mesh area and representing instances of all trips in the city. As the basis for our extension, we build on a previously published efficient and scalable simulation model. Thanks to its scalability, we are able to perform our simulation with the resulting 4.6 million trips per day over a whole week. We study the effect of electrification on modal shift considering different battery capacities and charging station numbers. We will show at what level of these three decision variables the impact of electrification is negligible compared to our previous results with (non-electric) SAVs.

  @inproceedings{10.1007/978-3-031-23721-8_9, abstract = {Shared autonomous electric vehicles (SAEVs) are expected to soon revolutionize the transport system, with cheap and convenient taxi-like services. SAEVs can induce a significant modal shift from other modes of travel, with effects ranging from beneficial, like reducing private car use, to negative, like making public transport uneconomical and increasing congestion. This modal shift will also be influenced by electrification, as charging time and range limitations will influence availability of these vehicles. In this work, we expand a SAEV simulationIacobucci, R.Pruckner, M.Schm{\"o}ecker, J.-D. model with mode choice to incorporate electric vehicles. In our model travelers choose between their current mode and SAEVs, which in addition to the fare, has a waiting time which depends on the real-time demand and fleet availability. We use a trip generation model based on a large person trip survey from Germany as our input data and scale-up the survey to obtain an OD matrix for the whole wider Munich area on a 1 km{\$}{\$}^2{\$}{\$}2mesh area and representing instances of all trips in the city. As the basis for our extension, we build on a previously published efficient and scalable simulation model. Thanks to its scalability, we are able to perform our simulation with the resulting 4.6 million trips per day over a whole week. We study the effect of electrification on modal shift considering different battery capacities and charging station numbers. We will show at what level of these three decision variables the impact of electrification is negligible compared to our previous results with (non-electric) SAVs.}, address = {Cham}, author = {Iacobucci, Riccardo and Pruckner, Marco and Schm{\"o}cker, Jan-Dirk}, booktitle = {Smart Energy for Smart Transport}, editor = {Nathanail, Eftihia G. and Gavanas, Nikolaos and Adamos, Giannis}, keywords = {pruckner}, pages = {115–124}, publisher = {Springer Nature Switzerland}, title = {A Large Scale Simulation of the Electrification Effects of SAVs}, year = 2023 }

  %0 Conference Paper %1 10.1007/978-3-031-23721-8_9 %A Iacobucci, Riccardo %A Pruckner, Marco %A Schm{\"o}cker, Jan-Dirk %B Smart Energy for Smart Transport %C Cham %D 2023 %E Nathanail, Eftihia G. %E Gavanas, Nikolaos %E Adamos, Giannis %I Springer Nature Switzerland %P 115--124 %T A Large Scale Simulation of the Electrification Effects of SAVs %X Shared autonomous electric vehicles (SAEVs) are expected to soon revolutionize the transport system, with cheap and convenient taxi-like services. SAEVs can induce a significant modal shift from other modes of travel, with effects ranging from beneficial, like reducing private car use, to negative, like making public transport uneconomical and increasing congestion. This modal shift will also be influenced by electrification, as charging time and range limitations will influence availability of these vehicles. In this work, we expand a SAEV simulationIacobucci, R.Pruckner, M.Schm{\"o}ecker, J.-D. model with mode choice to incorporate electric vehicles. In our model travelers choose between their current mode and SAEVs, which in addition to the fare, has a waiting time which depends on the real-time demand and fleet availability. We use a trip generation model based on a large person trip survey from Germany as our input data and scale-up the survey to obtain an OD matrix for the whole wider Munich area on a 1 km{\$}{\$}^2{\$}{\$}2mesh area and representing instances of all trips in the city. As the basis for our extension, we build on a previously published efficient and scalable simulation model. Thanks to its scalability, we are able to perform our simulation with the resulting 4.6 million trips per day over a whole week. We study the effect of electrification on modal shift considering different battery capacities and charging station numbers. We will show at what level of these three decision variables the impact of electrification is negligible compared to our previous results with (non-electric) SAVs. %@ 978-3-031-23721-8
• State of health estimation of lithium-ion batteries with a temporal convolutional neural network using partial load profiles Bockrath, Steffen; Lorentz, Vincent; Pruckner, Marco in Applied Energy (2023). 329 120307.
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  An accurate aging forecasting and state of health estimation is essential for a safe and economically valuable usage of lithium-ion batteries. However, the non-linear aging of lithium-ion batteries is dependent on various operating and environmental conditions wherefore the degradation estimation is a complex challenge. Moreover, for on-board estimations where only limited memory and computing power are available, a state of health estimation algorithm is needed that is able to process raw sensor data without complex preprocessing. This paper presents a data-driven state of health estimation algorithm for lithium-ion batteries using different segments of partial discharge profiles. Raw sensor data is directly input to a temporal convolutional neural network without the need of executing feature engineering steps. The neural network is able to process raw sensor data and estimate the state of health of battery cells for different aging and degradation scenarios. After executing Bayesian hyperparameter tuning together with a stratified cross validation approach for splitting the training and test data, the achieved generalized aging model estimates the state of health with an overall root mean squared error of 1.0%.

  @article{BOCKRATH2023120307, abstract = {An accurate aging forecasting and state of health estimation is essential for a safe and economically valuable usage of lithium-ion batteries. However, the non-linear aging of lithium-ion batteries is dependent on various operating and environmental conditions wherefore the degradation estimation is a complex challenge. Moreover, for on-board estimations where only limited memory and computing power are available, a state of health estimation algorithm is needed that is able to process raw sensor data without complex preprocessing. This paper presents a data-driven state of health estimation algorithm for lithium-ion batteries using different segments of partial discharge profiles. Raw sensor data is directly input to a temporal convolutional neural network without the need of executing feature engineering steps. The neural network is able to process raw sensor data and estimate the state of health of battery cells for different aging and degradation scenarios. After executing Bayesian hyperparameter tuning together with a stratified cross validation approach for splitting the training and test data, the achieved generalized aging model estimates the state of health with an overall root mean squared error of 1.0%.}, author = {Bockrath, Steffen and Lorentz, Vincent and Pruckner, Marco}, journal = {Applied Energy}, keywords = {pruckner}, pages = 120307, title = {State of health estimation of lithium-ion batteries with a temporal convolutional neural network using partial load profiles}, volume = 329, year = 2023 }

  %0 Journal Article %1 BOCKRATH2023120307 %A Bockrath, Steffen %A Lorentz, Vincent %A Pruckner, Marco %D 2023 %J Applied Energy %P 120307 %R https://doi.org/10.1016/j.apenergy.2022.120307 %T State of health estimation of lithium-ion batteries with a temporal convolutional neural network using partial load profiles %U https://www.sciencedirect.com/science/article/pii/S0306261922015641 %V 329 %X An accurate aging forecasting and state of health estimation is essential for a safe and economically valuable usage of lithium-ion batteries. However, the non-linear aging of lithium-ion batteries is dependent on various operating and environmental conditions wherefore the degradation estimation is a complex challenge. Moreover, for on-board estimations where only limited memory and computing power are available, a state of health estimation algorithm is needed that is able to process raw sensor data without complex preprocessing. This paper presents a data-driven state of health estimation algorithm for lithium-ion batteries using different segments of partial discharge profiles. Raw sensor data is directly input to a temporal convolutional neural network without the need of executing feature engineering steps. The neural network is able to process raw sensor data and estimate the state of health of battery cells for different aging and degradation scenarios. After executing Bayesian hyperparameter tuning together with a stratified cross validation approach for splitting the training and test data, the achieved generalized aging model estimates the state of health with an overall root mean squared error of 1.0%.
• A digital twin of a local energy system based on real smart meter data Bayer, Daniel; Pruckner, Marco in Energy Informatics (2023). 6(1)
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  @article{2023_Bayer_DT_LocalEnergySystem, author = {Bayer, Daniel and Pruckner, Marco}, journal = {Energy Informatics}, keywords = {pruckner}, month = {mar}, number = 1, publisher = {Springer Science and Business Media {LLC}}, title = {A digital twin of a local energy system based on real smart meter data}, volume = 6, year = 2023 }

  %0 Journal Article %1 2023_Bayer_DT_LocalEnergySystem %A Bayer, Daniel %A Pruckner, Marco %D 2023 %I Springer Science and Business Media {LLC} %J Energy Informatics %N 1 %R 10.1186/s42162-023-00263-6 %T A digital twin of a local energy system based on real smart meter data %V 6

• Virtual experiments for battery state of health estimation based on neural networks and in-vehicle data Heinrich, Felix; Pruckner, Marco in Journal of Energy Storage (2022). 48 103856.
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  @article{heinrich2022virtual, author = {Heinrich, Felix and Pruckner, Marco}, journal = {Journal of Energy Storage}, keywords = {pruckner}, pages = 103856, publisher = {Elsevier}, title = {Virtual experiments for battery state of health estimation based on neural networks and in-vehicle data}, volume = 48, year = 2022 }

  %0 Journal Article %1 heinrich2022virtual %A Heinrich, Felix %A Pruckner, Marco %D 2022 %I Elsevier %J Journal of Energy Storage %P 103856 %T Virtual experiments for battery state of health estimation based on neural networks and in-vehicle data %V 48
• Simulation and analysis of a Carnot Battery consisting of a reversible heat pump/organic Rankine cycle for a domestic application in a community with varying number of houses Scharrer, Daniel; Bazan, Peter; Pruckner, Marco; German, Reinhard in Energy (2022). 261 125166.
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  The storage of electric energy is considered to be a crucial element for grids with a high share of renewable energy generation. Carnot Batteries are a promising technology regarding sector coupling or peak shaving applications. In the domestic sector, current research focuses on an application of Carnot Battery systems in single houses with solar power to improve their self-sufficiency and reduce expenditures. However, due to the non-cellular structure (in contrast to li-ion) economies of scale contribute significantly to the viability of the technology. This is why a joint analysis of entire housing communities is necessary, as focusing only on one house neglects possibilities that arise with larger Carnot Battery systems. The Carnot Battery system is modelled after a pilot plant as a reversible heat pump (20 kW)/organic Rankine cycle (7–13 kW) system coupled with a sensible hot water storage. Operation data from a local energy supplier is used to validate the heat storage component of the simulation model, while the thermal machines are based on simulated and experimental data of the pilot plant. An extensive and comprehensive parameter variation is done to find possible application scenarios of the pilot plant and evaluate its financial viability in a community of varying number of houses. Major findings are, that the possible savings the pilot plant Carnot Battery can achieve in such a community depends on the market conditions considered and that it is not financial under current German market conditions. Varying the feed-in tariff and heat costs showcases the limits of a financial application. Based on current projections for the feed-in tariff, an application for a community of 10–30 houses becomes financial in the near future and saves more than 100 € on electricity costs per house per year, with an amortization period of 14 years depending on interest rates.

  @article{SCHARRER2022125166, abstract = {The storage of electric energy is considered to be a crucial element for grids with a high share of renewable energy generation. Carnot Batteries are a promising technology regarding sector coupling or peak shaving applications. In the domestic sector, current research focuses on an application of Carnot Battery systems in single houses with solar power to improve their self-sufficiency and reduce expenditures. However, due to the non-cellular structure (in contrast to li-ion) economies of scale contribute significantly to the viability of the technology. This is why a joint analysis of entire housing communities is necessary, as focusing only on one house neglects possibilities that arise with larger Carnot Battery systems. The Carnot Battery system is modelled after a pilot plant as a reversible heat pump (20 kW)/organic Rankine cycle (7–13 kW) system coupled with a sensible hot water storage. Operation data from a local energy supplier is used to validate the heat storage component of the simulation model, while the thermal machines are based on simulated and experimental data of the pilot plant. An extensive and comprehensive parameter variation is done to find possible application scenarios of the pilot plant and evaluate its financial viability in a community of varying number of houses. Major findings are, that the possible savings the pilot plant Carnot Battery can achieve in such a community depends on the market conditions considered and that it is not financial under current German market conditions. Varying the feed-in tariff and heat costs showcases the limits of a financial application. Based on current projections for the feed-in tariff, an application for a community of 10–30 houses becomes financial in the near future and saves more than 100 € on electricity costs per house per year, with an amortization period of 14 years depending on interest rates.}, author = {Scharrer, Daniel and Bazan, Peter and Pruckner, Marco and German, Reinhard}, journal = {Energy}, keywords = {pruckner}, pages = 125166, title = {Simulation and analysis of a Carnot Battery consisting of a reversible heat pump/organic Rankine cycle for a domestic application in a community with varying number of houses}, volume = 261, year = 2022 }

  %0 Journal Article %1 SCHARRER2022125166 %A Scharrer, Daniel %A Bazan, Peter %A Pruckner, Marco %A German, Reinhard %D 2022 %J Energy %P 125166 %R https://doi.org/10.1016/j.energy.2022.125166 %T Simulation and analysis of a Carnot Battery consisting of a reversible heat pump/organic Rankine cycle for a domestic application in a community with varying number of houses %U https://www.sciencedirect.com/science/article/pii/S0360544222020588 %V 261 %X The storage of electric energy is considered to be a crucial element for grids with a high share of renewable energy generation. Carnot Batteries are a promising technology regarding sector coupling or peak shaving applications. In the domestic sector, current research focuses on an application of Carnot Battery systems in single houses with solar power to improve their self-sufficiency and reduce expenditures. However, due to the non-cellular structure (in contrast to li-ion) economies of scale contribute significantly to the viability of the technology. This is why a joint analysis of entire housing communities is necessary, as focusing only on one house neglects possibilities that arise with larger Carnot Battery systems. The Carnot Battery system is modelled after a pilot plant as a reversible heat pump (20 kW)/organic Rankine cycle (7–13 kW) system coupled with a sensible hot water storage. Operation data from a local energy supplier is used to validate the heat storage component of the simulation model, while the thermal machines are based on simulated and experimental data of the pilot plant. An extensive and comprehensive parameter variation is done to find possible application scenarios of the pilot plant and evaluate its financial viability in a community of varying number of houses. Major findings are, that the possible savings the pilot plant Carnot Battery can achieve in such a community depends on the market conditions considered and that it is not financial under current German market conditions. Varying the feed-in tariff and heat costs showcases the limits of a financial application. Based on current projections for the feed-in tariff, an application for a community of 10–30 houses becomes financial in the near future and saves more than 100 € on electricity costs per house per year, with an amortization period of 14 years depending on interest rates.
• Modeling and Simulation to Improve Real Electric Vehicles Charging Processes by Integration of Renewable Energies and Buffer Storage Sing, Konstantin; Mertiny, Pierre; Pruckner, Marco in 2022 Winter Simulation Conference (WSC) (2022). 867–878.
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  @inproceedings{10015432, author = {Sing, Konstantin and Mertiny, Pierre and Pruckner, Marco}, booktitle = {2022 Winter Simulation Conference (WSC)}, keywords = {pruckner}, pages = {867-878}, title = {Modeling and Simulation to Improve Real Electric Vehicles Charging Processes by Integration of Renewable Energies and Buffer Storage}, year = 2022 }

  %0 Conference Paper %1 10015432 %A Sing, Konstantin %A Mertiny, Pierre %A Pruckner, Marco %B 2022 Winter Simulation Conference (WSC) %D 2022 %P 867-878 %R 10.1109/WSC57314.2022.10015432 %T Modeling and Simulation to Improve Real Electric Vehicles Charging Processes by Integration of Renewable Energies and Buffer Storage
• Synergy of Unidirectional and Bidirectional Smart Charging of Electric Vehicles for Frequency Containment Reserve Power Provision Schlund, Jonas; German, Reinhard; Pruckner, Marco in World Electric Vehicle Journal (2022). 13(9)
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  Besides the integration of renewable energies, electric vehicles pose an additional challenge to modern power grids. However, electric vehicles can also be a flexibility source and contribute to the power system stability. Today, the power system still heavily relies on conventional technologies to stay stable. In order to operate a future power system based on renewable energies only, we need to understand the flexibility potential of assets such as electric vehicles and become able to use their flexibility. In this paper, we analyzed how vast amounts of coordinated charging processes can be used to provide frequency containment reserve power, one of the most important ancillary services for system stability. Therefore, we used an extensive simulation model of a virtual power plant of millions of electric vehicles. The model considers not only technical components but also the stochastic behavior of electric vehicle drivers based on real data. Our results show that, in 2030, electric vehicles have the potential to serve the whole frequency containment reserve power market in Germany. We differentiate between using unidirectional and bidirectional chargers. Bidirectional chargers have a larger potential but also result in unwanted battery degradation. Unidirectional chargers are more constrained in terms of flexibility, but do not lead to additional battery degradation. We conclude that using a mix of both can combine the advantages of both worlds. Thereby, average private cars can provide the service without any notable additional battery degradation and achieve yearly earnings between EUR 200 and EUR 500, depending on the volatile market prices. Commercial vehicles have an even higher potential, as the results increase with vehicle utilization and consumption.

  @article{wevj13090168, abstract = {Besides the integration of renewable energies, electric vehicles pose an additional challenge to modern power grids. However, electric vehicles can also be a flexibility source and contribute to the power system stability. Today, the power system still heavily relies on conventional technologies to stay stable. In order to operate a future power system based on renewable energies only, we need to understand the flexibility potential of assets such as electric vehicles and become able to use their flexibility. In this paper, we analyzed how vast amounts of coordinated charging processes can be used to provide frequency containment reserve power, one of the most important ancillary services for system stability. Therefore, we used an extensive simulation model of a virtual power plant of millions of electric vehicles. The model considers not only technical components but also the stochastic behavior of electric vehicle drivers based on real data. Our results show that, in 2030, electric vehicles have the potential to serve the whole frequency containment reserve power market in Germany. We differentiate between using unidirectional and bidirectional chargers. Bidirectional chargers have a larger potential but also result in unwanted battery degradation. Unidirectional chargers are more constrained in terms of flexibility, but do not lead to additional battery degradation. We conclude that using a mix of both can combine the advantages of both worlds. Thereby, average private cars can provide the service without any notable additional battery degradation and achieve yearly earnings between EUR 200 and EUR 500, depending on the volatile market prices. Commercial vehicles have an even higher potential, as the results increase with vehicle utilization and consumption.}, author = {Schlund, Jonas and German, Reinhard and Pruckner, Marco}, journal = {World Electric Vehicle Journal}, keywords = {pruckner}, number = 9, title = {Synergy of Unidirectional and Bidirectional Smart Charging of Electric Vehicles for Frequency Containment Reserve Power Provision}, volume = 13, year = 2022 }

  %0 Journal Article %1 wevj13090168 %A Schlund, Jonas %A German, Reinhard %A Pruckner, Marco %D 2022 %J World Electric Vehicle Journal %N 9 %R 10.3390/wevj13090168 %T Synergy of Unidirectional and Bidirectional Smart Charging of Electric Vehicles for Frequency Containment Reserve Power Provision %U https://www.mdpi.com/2032-6653/13/9/168 %V 13 %X Besides the integration of renewable energies, electric vehicles pose an additional challenge to modern power grids. However, electric vehicles can also be a flexibility source and contribute to the power system stability. Today, the power system still heavily relies on conventional technologies to stay stable. In order to operate a future power system based on renewable energies only, we need to understand the flexibility potential of assets such as electric vehicles and become able to use their flexibility. In this paper, we analyzed how vast amounts of coordinated charging processes can be used to provide frequency containment reserve power, one of the most important ancillary services for system stability. Therefore, we used an extensive simulation model of a virtual power plant of millions of electric vehicles. The model considers not only technical components but also the stochastic behavior of electric vehicle drivers based on real data. Our results show that, in 2030, electric vehicles have the potential to serve the whole frequency containment reserve power market in Germany. We differentiate between using unidirectional and bidirectional chargers. Bidirectional chargers have a larger potential but also result in unwanted battery degradation. Unidirectional chargers are more constrained in terms of flexibility, but do not lead to additional battery degradation. We conclude that using a mix of both can combine the advantages of both worlds. Thereby, average private cars can provide the service without any notable additional battery degradation and achieve yearly earnings between EUR 200 and EUR 500, depending on the volatile market prices. Commercial vehicles have an even higher potential, as the results increase with vehicle utilization and consumption.
• Feasibility of completely electrified two-way car sharing Strobel, Leo; Pruckner, Marco in 2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) (2022). 206–211.
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  Car sharing is a more sustainable approach to personal mobility than vehicle ownership, especially if car sharing services electrify their fleets. However, due to the limited range and slow charging process of electric vehicles, car sharing providers might face problems keeping the vehicles adequately charged. This paper analyzes 4.5 years of real booking data from a German two-way car sharing provider. The dataset includes information on the booking time window, driven distance, and location. We use this data to study the customer behavior and simulate the past operation with a completely electrified fleet. Based on the simulation, we determine whether charging problems exist and how they can be solved by adapting the charging rate, battery capacity, and number of charging points. Our results indicate that the operation of the service with modern electric vehicles is entirely feasible. Per car sharing station, two charging points are sufficient if vehicles do not have to be connected immediately upon arrival (by the customer), but can connect later once another vehicle has finished charging. Somewhat problematic is that 4% of the bookings have a longer driven distance than the vehicle's range. In these cases, the disutility to customers is unclear but, in all likelihood, manageable. Furthermore, we find that 50% of the charging events can be shifted by more than 10h, indicating significant flexibility that could be utilized for smart charging and the provision of ancillary services in the future.

  @inproceedings{9961032, abstract = {Car sharing is a more sustainable approach to personal mobility than vehicle ownership, especially if car sharing services electrify their fleets. However, due to the limited range and slow charging process of electric vehicles, car sharing providers might face problems keeping the vehicles adequately charged. This paper analyzes 4.5 years of real booking data from a German two-way car sharing provider. The dataset includes information on the booking time window, driven distance, and location. We use this data to study the customer behavior and simulate the past operation with a completely electrified fleet. Based on the simulation, we determine whether charging problems exist and how they can be solved by adapting the charging rate, battery capacity, and number of charging points. Our results indicate that the operation of the service with modern electric vehicles is entirely feasible. Per car sharing station, two charging points are sufficient if vehicles do not have to be connected immediately upon arrival (by the customer), but can connect later once another vehicle has finished charging. Somewhat problematic is that 4% of the bookings have a longer driven distance than the vehicle's range. In these cases, the disutility to customers is unclear but, in all likelihood, manageable. Furthermore, we find that 50% of the charging events can be shifted by more than 10h, indicating significant flexibility that could be utilized for smart charging and the provision of ancillary services in the future.}, author = {Strobel, Leo and Pruckner, Marco}, booktitle = {2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)}, keywords = {strobel}, month = {oct}, pages = {206-211}, title = {Feasibility of completely electrified two-way car sharing}, year = 2022 }

  %0 Conference Paper %1 9961032 %A Strobel, Leo %A Pruckner, Marco %B 2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) %D 2022 %P 206-211 %R 10.1109/SmartGridComm52983.2022.9961032 %T Feasibility of completely electrified two-way car sharing %U https://ieeexplore.ieee.org/document/9961032/ %X Car sharing is a more sustainable approach to personal mobility than vehicle ownership, especially if car sharing services electrify their fleets. However, due to the limited range and slow charging process of electric vehicles, car sharing providers might face problems keeping the vehicles adequately charged. This paper analyzes 4.5 years of real booking data from a German two-way car sharing provider. The dataset includes information on the booking time window, driven distance, and location. We use this data to study the customer behavior and simulate the past operation with a completely electrified fleet. Based on the simulation, we determine whether charging problems exist and how they can be solved by adapting the charging rate, battery capacity, and number of charging points. Our results indicate that the operation of the service with modern electric vehicles is entirely feasible. Per car sharing station, two charging points are sufficient if vehicles do not have to be connected immediately upon arrival (by the customer), but can connect later once another vehicle has finished charging. Somewhat problematic is that 4% of the bookings have a longer driven distance than the vehicle's range. In these cases, the disutility to customers is unclear but, in all likelihood, manageable. Furthermore, we find that 50% of the charging events can be shifted by more than 10h, indicating significant flexibility that could be utilized for smart charging and the provision of ancillary services in the future.
• Joint analysis of regional and national power system impacts of electric vehicles - A case study for Germany on the county level in 2030 Strobel, Leo; Schlund, Jonas; Pruckner, Marco in Applied Energy (2022). 315 118945.
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  @article{Strobel_2022, author = {Strobel, Leo and Schlund, Jonas and Pruckner, Marco}, journal = {Applied Energy}, keywords = {strobel}, month = {jun}, pages = 118945, publisher = {Elsevier {BV}}, title = {Joint analysis of regional and national power system impacts of electric vehicles - A case study for Germany on the county level in 2030}, volume = 315, year = 2022 }

  %0 Journal Article %1 Strobel_2022 %A Strobel, Leo %A Schlund, Jonas %A Pruckner, Marco %D 2022 %I Elsevier {BV} %J Applied Energy %P 118945 %R 10.1016/j.apenergy.2022.118945 %T Joint analysis of regional and national power system impacts of electric vehicles - A case study for Germany on the county level in 2030 %U https://doi.org/10.1016%2Fj.apenergy.2022.118945 %V 315
• Enhancing the Performance of Multi-Agent Reinforcement Learning for Controlling HVAC Systems Bayer, Daniel; Pruckner, Marco in 2022 IEEE Conference on Technologies for Sustainability (SusTech) (2022). 187–194.
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  Systems for heating, ventilation and air-conditioning (HVAC) of buildings are traditionally controlled by a rule-based approach. In order to reduce the energy consumption and the environmental impact of HVAC systems more advanced control methods such as reinforcement learning are promising. Reinforcement learning (RL) strategies offer a good alternative, as user feedback can be integrated more easily and presence can also be incorporated. Moreover, multi-agent RL approaches scale well and can be generalized. In this paper, we propose a multi-agent RL framework based on existing work that learns reducing on one hand energy consumption by optimizing HVAC control and on the other hand user feedback by occupants about uncomfortable room temperatures. Second, we show how to reduce training time required for proper RL-agent-training by using parameter sharing between the multiple agents and apply different pretraining techniques. Results show that our framework is capable of reducing the energy by around 6% when controlling a complete building or 8% for a single room zone. The occupants complaints are acceptable or even better compared to a rule-based baseline. Additionally, our performance analysis show that the training time can be drastically reduced by using parameter sharing.

  @inproceedings{9794179, abstract = {Systems for heating, ventilation and air-conditioning (HVAC) of buildings are traditionally controlled by a rule-based approach. In order to reduce the energy consumption and the environmental impact of HVAC systems more advanced control methods such as reinforcement learning are promising. Reinforcement learning (RL) strategies offer a good alternative, as user feedback can be integrated more easily and presence can also be incorporated. Moreover, multi-agent RL approaches scale well and can be generalized. In this paper, we propose a multi-agent RL framework based on existing work that learns reducing on one hand energy consumption by optimizing HVAC control and on the other hand user feedback by occupants about uncomfortable room temperatures. Second, we show how to reduce training time required for proper RL-agent-training by using parameter sharing between the multiple agents and apply different pretraining techniques. Results show that our framework is capable of reducing the energy by around 6% when controlling a complete building or 8% for a single room zone. The occupants complaints are acceptable or even better compared to a rule-based baseline. Additionally, our performance analysis show that the training time can be drastically reduced by using parameter sharing.}, author = {Bayer, Daniel and Pruckner, Marco}, booktitle = {2022 IEEE Conference on Technologies for Sustainability (SusTech)}, keywords = {pruckner}, month = {April}, pages = {187-194}, title = {Enhancing the Performance of Multi-Agent Reinforcement Learning for Controlling HVAC Systems}, year = 2022 }

  %0 Conference Paper %1 9794179 %A Bayer, Daniel %A Pruckner, Marco %B 2022 IEEE Conference on Technologies for Sustainability (SusTech) %D 2022 %P 187-194 %R 10.1109/SusTech53338.2022.9794179 %T Enhancing the Performance of Multi-Agent Reinforcement Learning for Controlling HVAC Systems %U https://ieeexplore.ieee.org/document/9794179/ %X Systems for heating, ventilation and air-conditioning (HVAC) of buildings are traditionally controlled by a rule-based approach. In order to reduce the energy consumption and the environmental impact of HVAC systems more advanced control methods such as reinforcement learning are promising. Reinforcement learning (RL) strategies offer a good alternative, as user feedback can be integrated more easily and presence can also be incorporated. Moreover, multi-agent RL approaches scale well and can be generalized. In this paper, we propose a multi-agent RL framework based on existing work that learns reducing on one hand energy consumption by optimizing HVAC control and on the other hand user feedback by occupants about uncomfortable room temperatures. Second, we show how to reduce training time required for proper RL-agent-training by using parameter sharing between the multiple agents and apply different pretraining techniques. Results show that our framework is capable of reducing the energy by around 6% when controlling a complete building or 8% for a single room zone. The occupants complaints are acceptable or even better compared to a rule-based baseline. Additionally, our performance analysis show that the training time can be drastically reduced by using parameter sharing.

• A comprehensive study on battery electric modeling approaches based on machine learning Heinrich, Felix; Klapper, Patrick; Pruckner, Marco in DACH Conference on Energy Informatics (2021). 4(3) 1–17.
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  @article{heinrich2021comprehensive, author = {Heinrich, Felix and Klapper, Patrick and Pruckner, Marco}, journal = {DACH Conference on Energy Informatics}, keywords = {pruckner}, number = 3, pages = {1–17}, publisher = {Springer}, title = {A comprehensive study on battery electric modeling approaches based on machine learning}, volume = 4, year = 2021 }

  %0 Journal Article %1 heinrich2021comprehensive %A Heinrich, Felix %A Klapper, Patrick %A Pruckner, Marco %D 2021 %I Springer %J DACH Conference on Energy Informatics %N 3 %P 1--17 %T A comprehensive study on battery electric modeling approaches based on machine learning %V 4
• Smart Charging and Renewable Grid Integration - A Case Study Based on Real-Data of the Island of Porto Santo Strobel, Leo; Schlund, Jonas; Brandmeier, Veronika; Schreiber, Michael; Pruckner, Marco in Sustainable Energy for Smart Cities, J. L. Afonso, V. Monteiro, J. G. Pinto (eds.) (2021). 200–215.
  • [ Abstract ]
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  The penetration of battery electric vehicles is increasing. Due to their ability to store electrical power and to shift charging events, they offer a wide range of opportunities with regard to renewable grid integration and lowering the overall CO2 emissions. This is particularly evident for isolated microgrids, such as the Portuguese island of Porto Santo. In this paper, we conduct a data analysis of real-world charging data of 20 electric vehicles operated on the island of Porto Santo. We provide insights into the charging behavior of different users and analyze the opportunity of smart charging for better renewable grid integration using linear optimization models. The data analysis shows that drivers prefer home rather than publicly available charging stations, flexible charging events occur mostly overnight and the charging flexibility of the fleet decreases over the project duration. With regard to make charging more flexible, we can see that smart charging can help to raise the share of electricity generated by renewable energy sources for charging the electric vehicles to up to 33{\%}.

  @inproceedings{10.1007/978-3-030-73585-2_13, abstract = {The penetration of battery electric vehicles is increasing. Due to their ability to store electrical power and to shift charging events, they offer a wide range of opportunities with regard to renewable grid integration and lowering the overall CO2 emissions. This is particularly evident for isolated microgrids, such as the Portuguese island of Porto Santo. In this paper, we conduct a data analysis of real-world charging data of 20 electric vehicles operated on the island of Porto Santo. We provide insights into the charging behavior of different users and analyze the opportunity of smart charging for better renewable grid integration using linear optimization models. The data analysis shows that drivers prefer home rather than publicly available charging stations, flexible charging events occur mostly overnight and the charging flexibility of the fleet decreases over the project duration. With regard to make charging more flexible, we can see that smart charging can help to raise the share of electricity generated by renewable energy sources for charging the electric vehicles to up to 33{\%}.}, address = {Cham}, author = {Strobel, Leo and Schlund, Jonas and Brandmeier, Veronika and Schreiber, Michael and Pruckner, Marco}, booktitle = {Sustainable Energy for Smart Cities}, editor = {Afonso, Jo{\ a}o L. and Monteiro, Vitor and Pinto, Jos{\'e} Gabriel}, keywords = {strobel}, pages = {200–215}, publisher = {Springer International Publishing}, title = {Smart Charging and Renewable Grid Integration - A Case Study Based on Real-Data of the Island of Porto Santo}, year = 2021 }

  %0 Conference Paper %1 10.1007/978-3-030-73585-2_13 %A Strobel, Leo %A Schlund, Jonas %A Brandmeier, Veronika %A Schreiber, Michael %A Pruckner, Marco %B Sustainable Energy for Smart Cities %C Cham %D 2021 %E Afonso, Jo{\~a}o L. %E Monteiro, Vitor %E Pinto, Jos{\'e} Gabriel %I Springer International Publishing %P 200--215 %T Smart Charging and Renewable Grid Integration - A Case Study Based on Real-Data of the Island of Porto Santo %X The penetration of battery electric vehicles is increasing. Due to their ability to store electrical power and to shift charging events, they offer a wide range of opportunities with regard to renewable grid integration and lowering the overall CO2 emissions. This is particularly evident for isolated microgrids, such as the Portuguese island of Porto Santo. In this paper, we conduct a data analysis of real-world charging data of 20 electric vehicles operated on the island of Porto Santo. We provide insights into the charging behavior of different users and analyze the opportunity of smart charging for better renewable grid integration using linear optimization models. The data analysis shows that drivers prefer home rather than publicly available charging stations, flexible charging events occur mostly overnight and the charging flexibility of the fleet decreases over the project duration. With regard to make charging more flexible, we can see that smart charging can help to raise the share of electricity generated by renewable energy sources for charging the electric vehicles to up to 33{\%}. %@ 978-3-030-73585-2
• Development and Evaluation of a Smart Charging Strategy for an Electric Vehicle Fleet Based on Reinforcement Learning Tuchnitz, Felix; Ebell, Niklas; Schlund, Jonas; Pruckner, Marco in Applied Energy (2021). 285 116382.
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  @article{TUCHNITZ2021116382, author = {Tuchnitz, Felix and Ebell, Niklas and Schlund, Jonas and Pruckner, Marco}, journal = {Applied Energy}, keywords = {pruckner}, pages = 116382, title = {Development and Evaluation of a Smart Charging Strategy for an Electric Vehicle Fleet Based on Reinforcement Learning}, volume = 285, year = 2021 }

  %0 Journal Article %1 TUCHNITZ2021116382 %A Tuchnitz, Felix %A Ebell, Niklas %A Schlund, Jonas %A Pruckner, Marco %D 2021 %J Applied Energy %P 116382 %R https://doi.org/10.1016/j.apenergy.2020.116382 %T Development and Evaluation of a Smart Charging Strategy for an Electric Vehicle Fleet Based on Reinforcement Learning %U https://www.sciencedirect.com/science/article/pii/S0306261920317566 %V 285
• Dynamic modeling and sensitivity analysis of a stratified heat storage coupled with a heat pump and an organic rankine cycle Scharrer, Daniel; Pruckner, Marco; Bazan, Peter; German, Reinhard in 2021 Winter Simulation Conference (WSC) (2021). 1–12.
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  @inproceedings{scharrer2021dynamic, author = {Scharrer, Daniel and Pruckner, Marco and Bazan, Peter and German, Reinhard}, booktitle = {2021 Winter Simulation Conference (WSC)}, keywords = {pruckner}, organization = {IEEE}, pages = {1–12}, title = {Dynamic modeling and sensitivity analysis of a stratified heat storage coupled with a heat pump and an organic rankine cycle}, year = 2021 }

  %0 Conference Paper %1 scharrer2021dynamic %A Scharrer, Daniel %A Pruckner, Marco %A Bazan, Peter %A German, Reinhard %B 2021 Winter Simulation Conference (WSC) %D 2021 %P 1--12 %T Dynamic modeling and sensitivity analysis of a stratified heat storage coupled with a heat pump and an organic rankine cycle
• Benchmarking a Decentralized Reinforcement Learning Control Strategy for an Energy Community Ebell, Niklas; Pruckner, Marco in 2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) (2021). 385–390.
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  @inproceedings{ebell2021benchmarking, author = {Ebell, Niklas and Pruckner, Marco}, booktitle = {2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)}, keywords = {pruckner}, organization = {IEEE}, pages = {385–390}, title = {Benchmarking a Decentralized Reinforcement Learning Control Strategy for an Energy Community}, year = 2021 }

  %0 Conference Paper %1 ebell2021benchmarking %A Ebell, Niklas %A Pruckner, Marco %B 2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) %D 2021 %P 385--390 %T Benchmarking a Decentralized Reinforcement Learning Control Strategy for an Energy Community
• Analyzing the Charging Flexibility Potential of Different Electric Vehicle Fleets Using Real-World Charging Data Barthel, Vincent; Schlund, Jonas; Landes, Philipp; Brandmeier, Veronika; Pruckner, Marco in Energies (2021). 14(16)
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  @article{en14164961, author = {Barthel, Vincent and Schlund, Jonas and Landes, Philipp and Brandmeier, Veronika and Pruckner, Marco}, journal = {Energies}, keywords = {pruckner}, number = 16, title = {Analyzing the Charging Flexibility Potential of Different Electric Vehicle Fleets Using Real-World Charging Data}, volume = 14, year = 2021 }

  %0 Journal Article %1 en14164961 %A Barthel, Vincent %A Schlund, Jonas %A Landes, Philipp %A Brandmeier, Veronika %A Pruckner, Marco %D 2021 %J Energies %N 16 %R 10.3390/en14164961 %T Analyzing the Charging Flexibility Potential of Different Electric Vehicle Fleets Using Real-World Charging Data %U https://www.mdpi.com/1996-1073/14/16/4961 %V 14
• Frequency Control Reserve Provision from a Fleet of Shared Autonomous Electric Vehicles Iacobucci, Riccardo; Donhauser, Jonas; Schm{\"o}cker, Jan-Dirk; Pruckner, Marco in 2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) (2021). 1–6.
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  @inproceedings{iacobucci2021frequency, author = {Iacobucci, Riccardo and Donhauser, Jonas and Schm{\"o}cker, Jan-Dirk and Pruckner, Marco}, booktitle = {2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)}, keywords = {pruckner}, organization = {IEEE}, pages = {1–6}, title = {Frequency Control Reserve Provision from a Fleet of Shared Autonomous Electric Vehicles}, year = 2021 }

  %0 Conference Paper %1 iacobucci2021frequency %A Iacobucci, Riccardo %A Donhauser, Jonas %A Schm{\"o}cker, Jan-Dirk %A Pruckner, Marco %B 2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) %D 2021 %P 1--6 %T Frequency Control Reserve Provision from a Fleet of Shared Autonomous Electric Vehicles
• Unsupervised data-preprocessing for Long Short-Term Memory based battery model under electric vehicle operation Heinrich, F.; Noering, F.K.-D.; Pruckner, M.; Jonas, K. in Journal of Energy Storage (2021). 38 102598.
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  @article{HEINRICH2021102598, author = {Heinrich, F. and Noering, F.K.-D. and Pruckner, M. and Jonas, K.}, journal = {Journal of Energy Storage}, keywords = {pruckner}, pages = 102598, title = {Unsupervised data-preprocessing for Long Short-Term Memory based battery model under electric vehicle operation}, volume = 38, year = 2021 }

  %0 Journal Article %1 HEINRICH2021102598 %A Heinrich, F. %A Noering, F.K.-D. %A Pruckner, M. %A Jonas, K. %D 2021 %J Journal of Energy Storage %P 102598 %R https://doi.org/10.1016/j.est.2021.102598 %T Unsupervised data-preprocessing for Long Short-Term Memory based battery model under electric vehicle operation %U https://www.sciencedirect.com/science/article/pii/S2352152X2100339X %V 38

• Shared Autonomous Electric Vehicles and the Power Grid: Applications and Research Challenges. Pruckner, Marco; Eckhoff, David in ISGT-Europe (2020). 1151–1155.
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  @inproceedings{conf/isgteurope/PrucknerE20, author = {Pruckner, Marco and Eckhoff, David}, booktitle = {ISGT-Europe}, crossref = {conf/isgteurope/2020}, keywords = {pruckner}, pages = {1151-1155}, publisher = {IEEE}, title = {Shared Autonomous Electric Vehicles and the Power Grid: Applications and Research Challenges.}, year = 2020 }

  %0 Conference Paper %1 conf/isgteurope/PrucknerE20 %A Pruckner, Marco %A Eckhoff, David %B ISGT-Europe %D 2020 %I IEEE %P 1151-1155 %T Shared Autonomous Electric Vehicles and the Power Grid: Applications and Research Challenges. %U http://dblp.uni-trier.de/db/conf/isgteurope/isgteurope2020.html#PrucknerE20 %@ 978-1-7281-7100-5
• Electric Vehicle Charge Management for Lowering Costs and Environmental Impact Apostolaki-Iosifidou, Elpiniki; Pruckner, Marco; Woo, Soomin; Lipman, Timothy in 2020 IEEE Conference on Technologies for Sustainability (SusTech) (2020). 1–7.
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  @inproceedings{9150524, author = {Apostolaki-Iosifidou, Elpiniki and Pruckner, Marco and Woo, Soomin and Lipman, Timothy}, booktitle = {2020 IEEE Conference on Technologies for Sustainability (SusTech)}, keywords = {pruckner}, pages = {1-7}, title = {Electric Vehicle Charge Management for Lowering Costs and Environmental Impact}, year = 2020 }

  %0 Conference Paper %1 9150524 %A Apostolaki-Iosifidou, Elpiniki %A Pruckner, Marco %A Woo, Soomin %A Lipman, Timothy %B 2020 IEEE Conference on Technologies for Sustainability (SusTech) %D 2020 %P 1-7 %R 10.1109/SusTech47890.2020.9150524 %T Electric Vehicle Charge Management for Lowering Costs and Environmental Impact
• Life Cycle Assessment of a Reversible Heat Pump�Organic Rankine Cycle�Heat Storage System with Geothermal Heat Supply Scharrer, Daniel; Eppinger, Bernd; Schmitt, Pascal; Zenk, Johan; Bazan, Peter; Karl, J�rgen; Will, Stefan; Pruckner, Marco; German, Reinhard in Energies (2020). 13(12)
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  @article{en13123253, author = {Scharrer, Daniel and Eppinger, Bernd and Schmitt, Pascal and Zenk, Johan and Bazan, Peter and Karl, J�rgen and Will, Stefan and Pruckner, Marco and German, Reinhard}, journal = {Energies}, keywords = {pruckner}, number = 12, title = {Life Cycle Assessment of a Reversible Heat Pump�Organic Rankine Cycle�Heat Storage System with Geothermal Heat Supply}, volume = 13, year = 2020 }

  %0 Journal Article %1 en13123253 %A Scharrer, Daniel %A Eppinger, Bernd %A Schmitt, Pascal %A Zenk, Johan %A Bazan, Peter %A Karl, J�rgen %A Will, Stefan %A Pruckner, Marco %A German, Reinhard %D 2020 %J Energies %N 12 %R 10.3390/en13123253 %T Life Cycle Assessment of a Reversible Heat Pump�Organic Rankine Cycle�Heat Storage System with Geothermal Heat Supply %U https://www.mdpi.com/1996-1073/13/12/3253 %V 13
• FlexAbility - Modeling and Maximizing the Bidirectional Flexibility Availability of Unidirectional Charging of Large Pools of Electric Vehicles Schlund, Jonas; Pruckner, Marco; German, Reinhard in Proceedings of the Eleventh ACM International Conference on Future Energy Systems, e-Energy ’20 (2020). 121�132.
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  @inproceedings{10.1145/3396851.3397697, address = {New York, NY, USA}, author = {Schlund, Jonas and Pruckner, Marco and German, Reinhard}, booktitle = {Proceedings of the Eleventh ACM International Conference on Future Energy Systems}, keywords = {pruckner}, pages = {121�132}, publisher = {Association for Computing Machinery}, series = {e-Energy '20}, title = {FlexAbility - Modeling and Maximizing the Bidirectional Flexibility Availability of Unidirectional Charging of Large Pools of Electric Vehicles}, year = 2020 }

  %0 Conference Paper %1 10.1145/3396851.3397697 %A Schlund, Jonas %A Pruckner, Marco %A German, Reinhard %B Proceedings of the Eleventh ACM International Conference on Future Energy Systems %C New York, NY, USA %D 2020 %I Association for Computing Machinery %P 121�132 %R 10.1145/3396851.3397697 %T FlexAbility - Modeling and Maximizing the Bidirectional Flexibility Availability of Unidirectional Charging of Large Pools of Electric Vehicles %U https://doi.org/10.1145/3396851.3397697 %@ 9781450380096
• A scenario-based study on the impacts of electric vehicles on energy consumption and sustainability in Alberta Doluweera, Ganesh; Hahn, Fabian; Bergerson, Joule; Pruckner, Marco in Applied Energy (2020). 268 114961.
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  @article{DOLUWEERA2020114961, author = {Doluweera, Ganesh and Hahn, Fabian and Bergerson, Joule and Pruckner, Marco}, journal = {Applied Energy}, keywords = {pruckner}, pages = 114961, title = {A scenario-based study on the impacts of electric vehicles on energy consumption and sustainability in Alberta}, volume = 268, year = 2020 }

  %0 Journal Article %1 DOLUWEERA2020114961 %A Doluweera, Ganesh %A Hahn, Fabian %A Bergerson, Joule %A Pruckner, Marco %D 2020 %J Applied Energy %P 114961 %R https://doi.org/10.1016/j.apenergy.2020.114961 %T A scenario-based study on the impacts of electric vehicles on energy consumption and sustainability in Alberta %U https://www.sciencedirect.com/science/article/pii/S0306261920304736 %V 268

• Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids Spitzer, Martin; Schlund, Jonas; Apostolaki-Iosifidou, Elpiniki; Pruckner, Marco in Energies (2019). 12(21)
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  @article{en12214059, author = {Spitzer, Martin and Schlund, Jonas and Apostolaki-Iosifidou, Elpiniki and Pruckner, Marco}, journal = {Energies}, keywords = {pruckner}, number = 21, title = {Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids}, volume = 12, year = 2019 }

  %0 Journal Article %1 en12214059 %A Spitzer, Martin %A Schlund, Jonas %A Apostolaki-Iosifidou, Elpiniki %A Pruckner, Marco %D 2019 %J Energies %N 21 %R 10.3390/en12214059 %T Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids %U https://www.mdpi.com/1996-1073/12/21/4059 %V 12
• Sharing of Energy Among Cooperative Households Using Distributed Multi-Agent Reinforcement Learning. Ebell, Niklas; Gütlein, Moritz; Pruckner, Marco in ISGT Europe (2019). 1–5.
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  @inproceedings{conf/isgteurope/EbellGP19, author = {Ebell, Niklas and Gütlein, Moritz and Pruckner, Marco}, booktitle = {ISGT Europe}, crossref = {conf/isgteurope/2019}, keywords = {pruckner}, pages = {1-5}, publisher = {IEEE}, title = {Sharing of Energy Among Cooperative Households Using Distributed Multi-Agent Reinforcement Learning.}, year = 2019 }

  %0 Conference Paper %1 conf/isgteurope/EbellGP19 %A Ebell, Niklas %A Gütlein, Moritz %A Pruckner, Marco %B ISGT Europe %D 2019 %I IEEE %P 1-5 %T Sharing of Energy Among Cooperative Households Using Distributed Multi-Agent Reinforcement Learning. %U http://dblp.uni-trier.de/db/conf/isgteurope/isgteurope2019.html#EbellGP19 %@ 978-1-5386-8218-0

• Reinforcement Learning Control Algorithm for a PV-Battery-System Providing Frequency Containment Reserve Power. Ebell, Niklas; Heinrich, Felix; Schlund, Jonas; Pruckner, Marco in SmartGridComm (2018). 1–6.
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  @inproceedings{conf/smartgridcomm/EbellHSP18, author = {Ebell, Niklas and Heinrich, Felix and Schlund, Jonas and Pruckner, Marco}, booktitle = {SmartGridComm}, crossref = {conf/smartgridcomm/2018}, keywords = {pruckner}, pages = {1-6}, publisher = {IEEE}, title = {Reinforcement Learning Control Algorithm for a PV-Battery-System Providing Frequency Containment Reserve Power.}, year = 2018 }

  %0 Conference Paper %1 conf/smartgridcomm/EbellHSP18 %A Ebell, Niklas %A Heinrich, Felix %A Schlund, Jonas %A Pruckner, Marco %B SmartGridComm %D 2018 %I IEEE %P 1-6 %T Reinforcement Learning Control Algorithm for a PV-Battery-System Providing Frequency Containment Reserve Power. %U http://dblp.uni-trier.de/db/conf/smartgridcomm/smartgridcomm2018.html#EbellHSP18 %@ 978-1-5386-7954-8
• Coordinating E-Mobility Charging for Frequency Containment Reserve Power Provision. Schlund, Jonas; Steinert, Ronny; Pruckner, Marco in e-Energy, H. Schmeck, V. Hagenmeyer (eds.) (2018). 556–563.
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  @inproceedings{conf/eenergy/SchlundSP18, author = {Schlund, Jonas and Steinert, Ronny and Pruckner, Marco}, booktitle = {e-Energy}, crossref = {conf/eenergy/2018}, editor = {Schmeck, Hartmut and Hagenmeyer, Veit}, keywords = {pruckner}, pages = {556-563}, publisher = {ACM}, title = {Coordinating E-Mobility Charging for Frequency Containment Reserve Power Provision.}, year = 2018 }

  %0 Conference Paper %1 conf/eenergy/SchlundSP18 %A Schlund, Jonas %A Steinert, Ronny %A Pruckner, Marco %B e-Energy %D 2018 %E Schmeck, Hartmut %E Hagenmeyer, Veit %I ACM %P 556-563 %T Coordinating E-Mobility Charging for Frequency Containment Reserve Power Provision. %U http://dblp.uni-trier.de/db/conf/eenergy/eenergy2018.html#SchlundSP18 %@ 978-1-4503-5767-8
• Coordinated Multi-Agent Reinforcement Learning for Swarm Battery Control. Ebell, Niklas; Pruckner, Marco in CCECE (2018). 1–4.
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  @inproceedings{conf/ccece/EbellP18, author = {Ebell, Niklas and Pruckner, Marco}, booktitle = {CCECE}, crossref = {conf/ccece/2018}, keywords = {pruckner}, pages = {1-4}, publisher = {IEEE}, title = {Coordinated Multi-Agent Reinforcement Learning for Swarm Battery Control.}, year = 2018 }

  %0 Conference Paper %1 conf/ccece/EbellP18 %A Ebell, Niklas %A Pruckner, Marco %B CCECE %D 2018 %I IEEE %P 1-4 %T Coordinated Multi-Agent Reinforcement Learning for Swarm Battery Control. %U http://dblp.uni-trier.de/db/conf/ccece/ccece2018.html#EbellP18 %@ 978-1-5386-2410-4
• Including a virtual battery storage into thermal unit commitment. Steber, David; Pruckner, Marco; Schlund, Jonas; Bazan, Peter; German, Reinhard in Comput. Sci. Res. Dev. (2018). 33(1-2) 223–229.
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  @article{journals/ife/SteberPSBG18, author = {Steber, David and Pruckner, Marco and Schlund, Jonas and Bazan, Peter and German, Reinhard}, journal = {Comput. Sci. Res. Dev.}, keywords = {pruckner}, number = {1-2}, pages = {223-229}, title = {Including a virtual battery storage into thermal unit commitment.}, volume = 33, year = 2018 }

  %0 Journal Article %1 journals/ife/SteberPSBG18 %A Steber, David %A Pruckner, Marco %A Schlund, Jonas %A Bazan, Peter %A German, Reinhard %D 2018 %J Comput. Sci. Res. Dev. %N 1-2 %P 223-229 %T Including a virtual battery storage into thermal unit commitment. %U http://dblp.uni-trier.de/db/journals/ife/ife33.html#SteberPSBG18 %V 33
• A comprehensive electricity Market Model using simulation and Optimization Techniques. Steber, David; Hubler, Jakob; Pruckner, Marco in WSC, B. Johansson, S. Jain (eds.) (2018). 2095–2106.
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  @inproceedings{conf/wsc/SteberHP18, author = {Steber, David and Hubler, Jakob and Pruckner, Marco}, booktitle = {WSC}, crossref = {conf/wsc/2018}, editor = {Johansson, Björn and Jain, Sanjay}, keywords = {pruckner}, pages = {2095-2106}, publisher = {IEEE}, title = {A comprehensive electricity Market Model using simulation and Optimization Techniques.}, year = 2018 }

  %0 Conference Paper %1 conf/wsc/SteberHP18 %A Steber, David %A Hubler, Jakob %A Pruckner, Marco %B WSC %D 2018 %E Johansson, Björn %E Jain, Sanjay %I IEEE %P 2095-2106 %T A comprehensive electricity Market Model using simulation and Optimization Techniques. %U http://dblp.uni-trier.de/db/conf/wsc/wsc2018.html#SteberHP18 %@ 978-1-5386-6572-5
• Rebalancing and fleet sizing of Mobility-on-demand Networks with combined simulation, Optimization and Queueing Network Analysis. Bazan, Peter; Djanatliev, Anatoli; Pruckner, Marco; German, Reinhard; Lauer, Christoph in WSC, B. Johansson, S. Jain (eds.) (2018). 1527–1538.
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  @inproceedings{conf/wsc/BazanDPGL18, author = {Bazan, Peter and Djanatliev, Anatoli and Pruckner, Marco and German, Reinhard and Lauer, Christoph}, booktitle = {WSC}, crossref = {conf/wsc/2018}, editor = {Johansson, Björn and Jain, Sanjay}, keywords = {pruckner}, pages = {1527-1538}, publisher = {IEEE}, title = {Rebalancing and fleet sizing of Mobility-on-demand Networks with combined simulation, Optimization and Queueing Network Analysis.}, year = 2018 }

  %0 Conference Paper %1 conf/wsc/BazanDPGL18 %A Bazan, Peter %A Djanatliev, Anatoli %A Pruckner, Marco %A German, Reinhard %A Lauer, Christoph %B WSC %D 2018 %E Johansson, Björn %E Jain, Sanjay %I IEEE %P 1527-1538 %T Rebalancing and fleet sizing of Mobility-on-demand Networks with combined simulation, Optimization and Queueing Network Analysis. %U http://dblp.uni-trier.de/db/conf/wsc/wsc2018.html#BazanDPGL18 %@ 978-1-5386-6572-5
• Reversible Heat Pump Organic Rankine Cycle Systems for the Storage of Renewable Electricity Staub, Sebastian; Bazan, Peter; Braimakis, Konstantinos; Müller, Dominik; Regensburger, Christoph; Scharrer, Daniel; Schmitt, Bernd; Steger, Daniel; German, Reinhard; Karellas, Sotirios; Pruckner, Marco; Schl�cker, Eberhard; Will, Stefan; Karl, J�rgen in Energies (2018). 11(6)
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  @article{en11061352, author = {Staub, Sebastian and Bazan, Peter and Braimakis, Konstantinos and Müller, Dominik and Regensburger, Christoph and Scharrer, Daniel and Schmitt, Bernd and Steger, Daniel and German, Reinhard and Karellas, Sotirios and Pruckner, Marco and Schl�cker, Eberhard and Will, Stefan and Karl, J�rgen}, journal = {Energies}, keywords = {pruckner}, number = 6, title = {Reversible Heat Pump Organic Rankine Cycle Systems for the Storage of Renewable Electricity}, volume = 11, year = 2018 }

  %0 Journal Article %1 en11061352 %A Staub, Sebastian %A Bazan, Peter %A Braimakis, Konstantinos %A Müller, Dominik %A Regensburger, Christoph %A Scharrer, Daniel %A Schmitt, Bernd %A Steger, Daniel %A German, Reinhard %A Karellas, Sotirios %A Pruckner, Marco %A Schl�cker, Eberhard %A Will, Stefan %A Karl, J�rgen %D 2018 %J Energies %N 6 %R 10.3390/en11061352 %T Reversible Heat Pump Organic Rankine Cycle Systems for the Storage of Renewable Electricity %U https://www.mdpi.com/1996-1073/11/6/1352 %V 11

• Analysis of Various Charging Strategies for Electrified Public Bus Transport Utilizing a Lightweight Simulation Model Dicke, Paul; Meyer, Benedikt; Pruckner, Marco in Proceedings of the 1st E-Mobility Power System Integration Symposium (2017).
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  • [ EndNote ]
  @inproceedings{dickeanalysis, address = {Berlin, Germany}, author = {Dicke, Paul and Meyer, Benedikt and Pruckner, Marco}, booktitle = {Proceedings of the 1st E-Mobility Power System Integration Symposium}, keywords = {pruckner}, title = {Analysis of Various Charging Strategies for Electrified Public Bus Transport Utilizing a Lightweight Simulation Model}, year = 2017 }

  %0 Conference Paper %1 dickeanalysis %A Dicke, Paul %A Meyer, Benedikt %A Pruckner, Marco %B Proceedings of the 1st E-Mobility Power System Integration Symposium %C Berlin, Germany %D 2017 %T Analysis of Various Charging Strategies for Electrified Public Bus Transport Utilizing a Lightweight Simulation Model
• Towards an impact study of electric vehicles on the Italian electric power system using simulation techniques. Longo, Michela; Lutz, Nina M.; Daniel, Luca; Zaninelli, Dario; Pruckner, Marco in RTSI (2017). 1–5.
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  @inproceedings{conf/rtsi/LongoLDZP17, author = {Longo, Michela and Lutz, Nina M. and Daniel, Luca and Zaninelli, Dario and Pruckner, Marco}, booktitle = {RTSI}, crossref = {conf/rtsi/2017}, keywords = {pruckner}, pages = {1-5}, publisher = {IEEE}, title = {Towards an impact study of electric vehicles on the Italian electric power system using simulation techniques.}, year = 2017 }

  %0 Conference Paper %1 conf/rtsi/LongoLDZP17 %A Longo, Michela %A Lutz, Nina M. %A Daniel, Luca %A Zaninelli, Dario %A Pruckner, Marco %B RTSI %D 2017 %I IEEE %P 1-5 %T Towards an impact study of electric vehicles on the Italian electric power system using simulation techniques. %U http://dblp.uni-trier.de/db/conf/rtsi/rtsi2017.html#LongoLDZP17 %@ 978-1-5386-3906-1
• Spatial and Temporal Charging Infrastructure Planning Using Discrete Event Simulation. Pruckner, Marco; German, Reinhard; Eckhoff, David in SIGSIM-PADS, W. Cai, Y. M. Teo, P. Wilsey, K. Jin (eds.) (2017). 249–257.
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  @inproceedings{conf/pads/PrucknerGE17, author = {Pruckner, Marco and German, Reinhard and Eckhoff, David}, booktitle = {SIGSIM-PADS}, crossref = {conf/pads/2017}, editor = {Cai, Wentong and Teo, Yong Meng and Wilsey, Philip and Jin, Kevin}, keywords = {pruckner}, pages = {249-257}, publisher = {ACM}, title = {Spatial and Temporal Charging Infrastructure Planning Using Discrete Event Simulation.}, year = 2017 }

  %0 Conference Paper %1 conf/pads/PrucknerGE17 %A Pruckner, Marco %A German, Reinhard %A Eckhoff, David %B SIGSIM-PADS %D 2017 %E Cai, Wentong %E Teo, Yong Meng %E Wilsey, Philip %E Jin, Kevin %I ACM %P 249-257 %T Spatial and Temporal Charging Infrastructure Planning Using Discrete Event Simulation. %U http://dblp.uni-trier.de/db/conf/pads/pads2017.html#PrucknerGE17 %@ 978-1-4503-4489-0
• SWARM � Providing 1 MW FCR power with residential PV-battery energy storage � Simulation and empiric validation Steber, David; Pruckner, Marco; Bazan, Peter; German, Reinhard in 2017 IEEE Manchester PowerTech (2017). 1–6.
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  @inproceedings{7981091, author = {Steber, David and Pruckner, Marco and Bazan, Peter and German, Reinhard}, booktitle = {2017 IEEE Manchester PowerTech}, keywords = {pruckner}, pages = {1-6}, title = {SWARM � Providing 1 MW FCR power with residential PV-battery energy storage � Simulation and empiric validation}, year = 2017 }

  %0 Conference Paper %1 7981091 %A Steber, David %A Pruckner, Marco %A Bazan, Peter %A German, Reinhard %B 2017 IEEE Manchester PowerTech %D 2017 %P 1-6 %R 10.1109/PTC.2017.7981091 %T SWARM � Providing 1 MW FCR power with residential PV-battery energy storage � Simulation and empiric validation
• Electrification of public bus transport under the usage of electricity generated by renewables Dicke, Paul; Meyer, Benedikt; Pruckner, Marco in 2017 2nd IEEE International Conference on Intelligent Transportation Engineering (ICITE) (2017). 314–319.
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  @inproceedings{8056931, author = {Dicke, Paul and Meyer, Benedikt and Pruckner, Marco}, booktitle = {2017 2nd IEEE International Conference on Intelligent Transportation Engineering (ICITE)}, keywords = {pruckner}, pages = {314-319}, title = {Electrification of public bus transport under the usage of electricity generated by renewables}, year = 2017 }

  %0 Conference Paper %1 8056931 %A Dicke, Paul %A Meyer, Benedikt %A Pruckner, Marco %B 2017 2nd IEEE International Conference on Intelligent Transportation Engineering (ICITE) %D 2017 %P 314-319 %R 10.1109/ICITE.2017.8056931 %T Electrification of public bus transport under the usage of electricity generated by renewables

• The impact of electric vehicles on the german energy system. Pruckner, Marco; German, Reinhard in SpringSim (ANSS), J. J. Padilla, A. Tolk, S. Jafer (eds.) (2016). 23.
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  @inproceedings{conf/springsim/PrucknerG16, author = {Pruckner, Marco and German, Reinhard}, booktitle = {SpringSim (ANSS)}, crossref = {conf/springsim/2016-2}, editor = {Padilla, Jose J. and Tolk, Andreas and Jafer, Shafagh}, keywords = {pruckner}, pages = 23, publisher = {ACM}, title = {The impact of electric vehicles on the german energy system.}, year = 2016 }

  %0 Conference Paper %1 conf/springsim/PrucknerG16 %A Pruckner, Marco %A German, Reinhard %B SpringSim (ANSS) %D 2016 %E Padilla, Jose J. %E Tolk, Andreas %E Jafer, Shafagh %I ACM %P 23 %T The impact of electric vehicles on the german energy system. %U http://dblp.uni-trier.de/db/conf/springsim/springsim2016-2.html#PrucknerG16 %@ 978-1-5108-2316-7
• Modeling the impact of electrical energy storage systems on future power systems Pruckner, Marco in 2016 IEEE Electrical Power and Energy Conference (EPEC) (2016). 1–7.
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  @inproceedings{7771724, author = {Pruckner, Marco}, booktitle = {2016 IEEE Electrical Power and Energy Conference (EPEC)}, keywords = {pruckner}, pages = {1-7}, title = {Modeling the impact of electrical energy storage systems on future power systems}, year = 2016 }

  %0 Conference Paper %1 7771724 %A Pruckner, Marco %B 2016 IEEE Electrical Power and Energy Conference (EPEC) %D 2016 %P 1-7 %R 10.1109/EPEC.2016.7771724 %T Modeling the impact of electrical energy storage systems on future power systems

• Hierarchical Simulation of the German Energy System and Houses with PV and Storage Systems. Bazan, Peter; Pruckner, Marco; Steber, David; German, Reinhard in D-A-CH EI, Lecture Notes in Computer Science, S. Gottwalt, L. König, H. Schmeck (eds.) (2015). (Vol. 9424) 12–23.
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  @inproceedings{conf/energieinformatik/BazanPSG15, author = {Bazan, Peter and Pruckner, Marco and Steber, David and German, Reinhard}, booktitle = {D-A-CH EI}, crossref = {conf/energieinformatik/2015}, editor = {Gottwalt, Sebastian and König, Lukas and Schmeck, Hartmut}, keywords = {pruckner}, pages = {12-23}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, title = {Hierarchical Simulation of the German Energy System and Houses with PV and Storage Systems.}, volume = 9424, year = 2015 }

  %0 Conference Paper %1 conf/energieinformatik/BazanPSG15 %A Bazan, Peter %A Pruckner, Marco %A Steber, David %A German, Reinhard %B D-A-CH EI %D 2015 %E Gottwalt, Sebastian %E König, Lukas %E Schmeck, Hartmut %I Springer %P 12-23 %T Hierarchical Simulation of the German Energy System and Houses with PV and Storage Systems. %U http://dblp.uni-trier.de/db/conf/energieinformatik/energieinformatik2015.html#BazanPSG15 %V 9424 %@ 978-3-319-25875-1
• Ein Simulationsmodell f{\"u}r den Energieumstieg in Bayern Pruckner, Marco (2015). Cuvillier Verlag.
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  @book{pruckner2015simulationsmodell, author = {Pruckner, Marco}, keywords = {pruckner}, publisher = {Cuvillier Verlag}, title = {Ein Simulationsmodell f{\"u}r den Energieumstieg in Bayern}, year = 2015 }

  %0 Book %1 pruckner2015simulationsmodell %A Pruckner, Marco %D 2015 %I Cuvillier Verlag %T Ein Simulationsmodell f{\"u}r den Energieumstieg in Bayern

• On the profit enhancement and state estimation services in the smart grid. Awad, Abdalkarim; Pruckner, Marco; Bazan, Peter; German, Reinhard in ISGT (2014). 1–5.
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  @inproceedings{conf/isgt/AwadPBG14, author = {Awad, Abdalkarim and Pruckner, Marco and Bazan, Peter and German, Reinhard}, booktitle = {ISGT}, crossref = {conf/isgt/2014}, keywords = {pruckner}, pages = {1-5}, publisher = {IEEE}, title = {On the profit enhancement and state estimation services in the smart grid.}, year = 2014 }

  %0 Conference Paper %1 conf/isgt/AwadPBG14 %A Awad, Abdalkarim %A Pruckner, Marco %A Bazan, Peter %A German, Reinhard %B ISGT %D 2014 %I IEEE %P 1-5 %T On the profit enhancement and state estimation services in the smart grid. %U http://dblp.uni-trier.de/db/conf/isgt/isgt2014.html#AwadPBG14 %@ 978-1-4799-3652-6
• Modeling country-scale electricity demand profiles. Pruckner, Marco; Eckhoff, David; German, Reinhard in Winter Simulation Conference, S. J. Buckley, J. A. Miller (eds.) (2014). 1084–1095.
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  @inproceedings{conf/wsc/PrucknerEG14, author = {Pruckner, Marco and Eckhoff, David and German, Reinhard}, booktitle = {Winter Simulation Conference}, crossref = {conf/wsc/2014}, editor = {Buckley, Stephen J. and Miller, John A.}, keywords = {pruckner}, pages = {1084-1095}, publisher = {IEEE/ACM}, title = {Modeling country-scale electricity demand profiles.}, year = 2014 }

  %0 Conference Paper %1 conf/wsc/PrucknerEG14 %A Pruckner, Marco %A Eckhoff, David %A German, Reinhard %B Winter Simulation Conference %D 2014 %E Buckley, Stephen J. %E Miller, John A. %I IEEE/ACM %P 1084-1095 %T Modeling country-scale electricity demand profiles. %U http://dblp.uni-trier.de/db/conf/wsc/wsc2014.html#PrucknerEG14
• Modeling and simulation of electricity generated by renewable energy sources for complex energy systems. Pruckner, Marco; German, Reinhard in SpringSim (ANSS) (2014). 4.
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  @inproceedings{conf/springsim/PrucknerG14, author = {Pruckner, Marco and German, Reinhard}, booktitle = {SpringSim (ANSS)}, crossref = {conf/springsim/2014-2}, keywords = {pruckner}, pages = 4, publisher = {SCS/ACM}, title = {Modeling and simulation of electricity generated by renewable energy sources for complex energy systems.}, year = 2014 }

  %0 Conference Paper %1 conf/springsim/PrucknerG14 %A Pruckner, Marco %A German, Reinhard %B SpringSim (ANSS) %D 2014 %I SCS/ACM %P 4 %T Modeling and simulation of electricity generated by renewable energy sources for complex energy systems. %U http://dblp.uni-trier.de/db/conf/springsim/springsim2014-2.html#PrucknerG14
• Gekoppeltes Energiesystemmodell f{\"u}r den Energieumstieg in Bayern Pruckner, Marco; Seifert, Gaby; Luther, Matthias; German, Reinhard in Energiesymposium 2014 (2014).
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  @inproceedings{pruckner2014gekoppeltes, address = {Graz, Austria}, author = {Pruckner, Marco and Seifert, Gaby and Luther, Matthias and German, Reinhard}, booktitle = {Energiesymposium 2014}, keywords = {pruckner}, title = {Gekoppeltes Energiesystemmodell f{\"u}r den Energieumstieg in Bayern}, year = 2014 }

  %0 Conference Paper %1 pruckner2014gekoppeltes %A Pruckner, Marco %A Seifert, Gaby %A Luther, Matthias %A German, Reinhard %B Energiesymposium 2014 %C Graz, Austria %D 2014 %T Gekoppeltes Energiesystemmodell f{\"u}r den Energieumstieg in Bayern

• A simulation model to analyze the residual load during the extension of highly fluctuating renewables in Bavaria, Germany Pruckner, Marco; German, Reinhard in 4th International Conference on Power Engineering, Energy and Electrical Drives (2013). 540–545.
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  @inproceedings{6635666, author = {Pruckner, Marco and German, Reinhard}, booktitle = {4th International Conference on Power Engineering, Energy and Electrical Drives}, keywords = {pruckner}, pages = {540-545}, title = {A simulation model to analyze the residual load during the extension of highly fluctuating renewables in Bavaria, Germany}, year = 2013 }

  %0 Conference Paper %1 6635666 %A Pruckner, Marco %A German, Reinhard %B 4th International Conference on Power Engineering, Energy and Electrical Drives %D 2013 %P 540-545 %R 10.1109/PowerEng.2013.6635666 %T A simulation model to analyze the residual load during the extension of highly fluctuating renewables in Bavaria, Germany
• A hybrid simulation model for large-scaled electricity generation systems. Pruckner, Marco; German, Reinhard in Winter Simulation Conference (2013). 1881–1892.
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  @inproceedings{conf/wsc/PrucknerG13, author = {Pruckner, Marco and German, Reinhard}, booktitle = {Winter Simulation Conference}, crossref = {conf/wsc/2013}, keywords = {pruckner}, pages = {1881-1892}, publisher = {IEEE}, title = {A hybrid simulation model for large-scaled electricity generation systems.}, year = 2013 }

  %0 Conference Paper %1 conf/wsc/PrucknerG13 %A Pruckner, Marco %A German, Reinhard %B Winter Simulation Conference %D 2013 %I IEEE %P 1881-1892 %T A hybrid simulation model for large-scaled electricity generation systems. %U http://dblp.uni-trier.de/db/conf/wsc/wsc2013.html#PrucknerG13

• Towards a simulation model of the Bavarian electrical energy system. Pruckner, Marco; Bazan, Peter; German, Reinhard in GI-Jahrestagung, LNI, U. Goltz, M. A. Magnor, H.-J. Appelrath, H. K. Matthies, W.-T. Balke, L. C. Wolf (eds.) (2012). (Vol. P-208) 597–612.
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  @inproceedings{conf/gi/PrucknerBG12, author = {Pruckner, Marco and Bazan, Peter and German, Reinhard}, booktitle = {GI-Jahrestagung}, crossref = {conf/gi/2012}, editor = {Goltz, Ursula and Magnor, Marcus A. and Appelrath, Hans-Jürgen and Matthies, Herbert K. and Balke, Wolf-Tilo and Wolf, Lars C.}, keywords = {pruckner}, pages = {597-612}, publisher = {GI}, series = {LNI}, title = {Towards a simulation model of the Bavarian electrical energy system.}, volume = {P-208}, year = 2012 }

  %0 Conference Paper %1 conf/gi/PrucknerBG12 %A Pruckner, Marco %A Bazan, Peter %A German, Reinhard %B GI-Jahrestagung %D 2012 %E Goltz, Ursula %E Magnor, Marcus A. %E Appelrath, Hans-Jürgen %E Matthies, Herbert K. %E Balke, Wolf-Tilo %E Wolf, Lars C. %I GI %P 597-612 %T Towards a simulation model of the Bavarian electrical energy system. %U http://dblp.uni-trier.de/db/conf/gi/gi2012.html#PrucknerBG12 %V P-208 %@ 978-3-88579-602-2
• A study on the impact of packet loss and latency on real-time demand response in smart grid. Pruckner, Marco; Awad, Abdalkarim; German, Reinhard in GLOBECOM Workshops (2012). 1486–1490.
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  @inproceedings{conf/globecom/PrucknerAG12, author = {Pruckner, Marco and Awad, Abdalkarim and German, Reinhard}, booktitle = {GLOBECOM Workshops}, crossref = {conf/globecom/2012w}, keywords = {pruckner}, pages = {1486-1490}, publisher = {IEEE}, title = {A study on the impact of packet loss and latency on real-time demand response in smart grid.}, year = 2012 }

  %0 Conference Paper %1 conf/globecom/PrucknerAG12 %A Pruckner, Marco %A Awad, Abdalkarim %A German, Reinhard %B GLOBECOM Workshops %D 2012 %I IEEE %P 1486-1490 %T A study on the impact of packet loss and latency on real-time demand response in smart grid. %U http://dblp.uni-trier.de/db/conf/globecom/globecom2012w.html#PrucknerAG12 %@ 978-1-4673-4942-0
• An approach of a simulation model to analyze the future energy balance of Bavaria Pruckner, Marco; German, Reinhard in 2012 International Conference on Smart Grid Technology, Economics and Policies (SG-TEP) (2012). 1–4.
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  @inproceedings{6642368, author = {Pruckner, Marco and German, Reinhard}, booktitle = {2012 International Conference on Smart Grid Technology, Economics and Policies (SG-TEP)}, keywords = {pruckner}, pages = {1-4}, title = {An approach of a simulation model to analyze the future energy balance of Bavaria}, year = 2012 }

  %0 Conference Paper %1 6642368 %A Pruckner, Marco %A German, Reinhard %B 2012 International Conference on Smart Grid Technology, Economics and Policies (SG-TEP) %D 2012 %P 1-4 %R 10.1109/SG-TEP.2012.6642368 %T An approach of a simulation model to analyze the future energy balance of Bavaria