Leo Strobel M. Sc.

• Benchmarking Aggregation-Disaggregation Pipelines for Smart Charging of Electric Vehicles. Strobel, Leo; Pruckner, Marco. In Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems, of e-Energy ’24, pp. 84–96. Association for Computing Machinery, Singapore, 2024.
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  As the global energy landscape shifts towards renewable energy and the electrification of the transport and heating sectors, national energy systems will include more controllable prosumers. Many future scenarios contain millions of such prosumers with individualistic behavior. This poses a problem for energy system modelers. Memory and runtime limitations often make it impossible to model each prosumer individually. In these cases, it is necessary to model the prosumers with representatives or in aggregated form. Existing literature offers various aggregation methods, each with strengths, drawbacks, and an inherent modeling error. It is difficult to evaluate which of these methods perform best. Each paper presenting a new aggregation method usually includes a performance evaluation. However, what is missing is a direct comparison on the same benchmark, preferably by a neutral third party that is not associated with any of the compared methods. This paper addresses this gap by introducing a benchmark to evaluate the end-to-end performance of multiple aggregation-disaggregation pipelines, specifically focusing on electric vehicles (EVs). Our study assesses the performance of the common representative profile (REP) approach, four different versions of the virtual battery (VB) approach, the Flex Object (FO) method, and the Dependency-based FlexOffer (DFO) method. The results show that each method has a clear use case. Depending on the price signal, additional median charging costs of 2\%-50\% are incurred using an aggregation method, compared to the optimal charging costs (i.e., the charging costs resulting from optimizing the EVs directly, without aggregation). The representative profile approach results in the lowest additional costs (2\%-20\%), while the Flex Object (FO) and Dependency-based FlexOffer (DFO) methods allow for error-free disaggregation, which is advantageous in real-world use cases.

  @inproceedings{10.1145/3632775.3661946, abstract = {As the global energy landscape shifts towards renewable energy and the electrification of the transport and heating sectors, national energy systems will include more controllable prosumers. Many future scenarios contain millions of such prosumers with individualistic behavior. This poses a problem for energy system modelers. Memory and runtime limitations often make it impossible to model each prosumer individually. In these cases, it is necessary to model the prosumers with representatives or in aggregated form. Existing literature offers various aggregation methods, each with strengths, drawbacks, and an inherent modeling error. It is difficult to evaluate which of these methods perform best. Each paper presenting a new aggregation method usually includes a performance evaluation. However, what is missing is a direct comparison on the same benchmark, preferably by a neutral third party that is not associated with any of the compared methods. This paper addresses this gap by introducing a benchmark to evaluate the end-to-end performance of multiple aggregation-disaggregation pipelines, specifically focusing on electric vehicles (EVs). Our study assesses the performance of the common representative profile (REP) approach, four different versions of the virtual battery (VB) approach, the Flex Object (FO) method, and the Dependency-based FlexOffer (DFO) method. The results show that each method has a clear use case. Depending on the price signal, additional median charging costs of 2\%-50\% are incurred using an aggregation method, compared to the optimal charging costs (i.e., the charging costs resulting from optimizing the EVs directly, without aggregation). The representative profile approach results in the lowest additional costs (2\%-20\%), while the Flex Object (FO) and Dependency-based FlexOffer (DFO) methods allow for error-free disaggregation, which is advantageous in real-world use cases.}, address = {New York, NY, USA}, author = {Strobel, Leo and Pruckner, Marco}, booktitle = {Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems}, keywords = {pruckner}, pages = {84–96}, publisher = {Association for Computing Machinery}, series = {e-Energy '24}, title = {Benchmarking Aggregation-Disaggregation Pipelines for Smart Charging of Electric Vehicles}, year = 2024 }

• OMOD: An open-source tool for creating disaggregated mobility demand based on OpenStreetMap. Strobel, Leo; Pruckner, Marco. In Computers, Environment and Urban Systems, 106, p. 102029. Elsevier BV, 2023.
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  @article{Strobel_2023, author = {Strobel, Leo and Pruckner, Marco}, journal = {Computers, Environment and Urban Systems}, keywords = {pruckner}, month = 12, pages = 102029, publisher = {Elsevier BV}, title = {OMOD: An open-source tool for creating disaggregated mobility demand based on OpenStreetMap}, volume = 106, year = 2023 }

• 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), pp. 206–211. 2022.
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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 = {pruckner}, month = 10, pages = {206-211}, title = {Feasibility of completely electrified two-way car sharing}, year = 2022 }
• 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, 315, p. 118945. Elsevier {BV}, 2022.
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  @article{Strobel_2022, author = {Strobel, Leo and Schlund, Jonas and Pruckner, Marco}, journal = {Applied Energy}, keywords = {pruckner}, month = {06}, 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 }

• 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.), pp. 200–215. Springer International Publishing, Cham, 2021.
  • [ 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 = {pruckner}, 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 }