@article{KlemmWieseVennemann2023,
  author    = {Klemm, Christian and Wiese, Frauke and Vennemann, Peter},
  title     = {Model-based run-time and memory reduction for a mixed-use multi-energy system model with high spatial resolution},
  series = {Applied Energy},
  volume    = {334},
  journal   = {Applied Energy},
  issn      = {0306-2619},
  doi       = {10.1016/j.apenergy.2022.120574},
  pages     = {120574},
  year      = {2023},
  abstract  = {Local and regional energy systems are becoming increasingly entangled. Therefore, models for optimizing these energy systems are becoming more and more complex and the required computing resources (run-time and random access memory usage) are increasing rapidly. The computational requirements can basically be reduced solver-based (mathematical optimization of the solving process) or model-based (simplification of the real-world problem in the model). This paper deals with identifying how the required computational requirements for solving optimization models of multi-energy systems with high spatial resolution change with increasing model complexity and which model-based approaches enable to reduce the requirements with the lowest possible model deviations. A total of 12 temporal model reductions (reduction of the number of modeled time steps), nine techno-spatial model reductions (reduction of possible solutions), and five combined reduction schemes were theoretically analyzed and practically applied to a test case. The improvement in reducing the usage of computational resources and the impact on the quality of the results were quantified by comparing the results with a non-simplified reference case. The results show, that the run-time to solve a model increases quadratically and memory usage increases linearly with increasing model complexity. The application of various model adaption methods have enabled a reduction of the run-time by over 99\% and the memory usage by up to 88\%. At the same time, however, some of the methods led to significant deviations of the model results. Other methods require a profound prior knowledge and understanding of the investigated energy systems to be applied. In order to reduce the run-time and memory requirements for investment optimization, while maintaining good quality results, we recommend the application of (1) a pre-model that is used to (1a) perform technological pre-selection and (1b) define reasonable technological boundaries, (2) spatial sub-modeling along network nodes, and 3) temporal simplification by only modeling every nth day (temporal slicing), where at least 20\% of the original time steps are modeled. Further simplifications such as spatial clustering or larger temporal simplification can further reduce the computational effort, but also result in significant model deviations.},
  language  = {en}
}
@article{QuestArendtKlemmetal.2022,
  author    = {Quest, Gemina and Arendt, Rosalie and Klemm, Christian and Bach, Vanessa and Budde, Janik and Vennemann, Peter and Finkbeiner, Matthias},
  title     = {Integrated Life Cycle Assessment (LCA) of Power and Heat Supply for a Neighborhood: A Case Study of Herne, Germany},
  series = {energies},
  volume    = {15},
  journal   = {energies},
  number    = {16},
  issn      = {1996-1073},
  doi       = {10.3390/en15165900},
  pages     = {5900},
  year      = {2022},
  abstract  = {(1) The use of renewable energy for power and heat supply is one of the strategies to reduce greenhouse gas emissions. As only 14\% of German households are supplied with renewable energy, a shift is necessary. This shift should be realized with the lowest possible environmental impact. This paper assesses the environmental impacts of changes in energy generation and distribution, by integrating the life cycle assessment (LCA) method into energy system models (ESM). (2) The integrated LCA is applied to a case study of the German neighborhood of Herne, (i) to optimize the energy supply, considering different technologies, and (ii) to determine the environmental impacts of the base case (status quo), a cost-optimized scenario, and a CO2-optimized scenario. (3) The use of gas boilers in the base case is substituted with CHPs, surface water heat pumps and PV-systems in the CO2-optimized scenario, and five ground-coupled heat pumps and PV-systems for the cost-optimized scenario. This technology shift led to a reduction in greenhouse gas emissions of almost 40\% in the cost-optimized, and more than 50\% in the CO2-optimized, scenario. However, technology shifts, e.g., due to oversized battery storage, risk higher impacts in other categories, such as terrestrial eco toxicity, by around 22\%. Thus, it can be recommended to use smaller battery storage systems. (4) By combining ESM and LCA, additional environmental impacts beyond GHG emissions can be quantified, and therefore trade-offs between environmental impacts can be identified. Furthermore, only applying ESM leads to an underestimation of greenhouse gas emissions of around 10\%. However, combining ESM and LCA required significant effort and is not yet possible using an integrated software.},
  language  = {en}
}
@techreport{KlemmVennemann2019,
  type      = {Working Paper},
  author    = {Klemm, Christian and Vennemann, Peter},
  title     = {Optimierung der Energieeffizienz von Stadtquartieren},
  doi       = {10.25974/fhms-11040},
  url       = {http://nbn-resolving.de/urn:nbn:de:hbz:836-opus-110401},
  year      = {2019},
  language  = {de}
}