@article{KlemmWiese2022,
  author    = {Klemm, Christian and Wiese, Frauke},
  title     = {Indicators for the optimization of sustainable urban energy systems based on energy system modeling},
  series = {Energy, Sustainability and Society},
  volume    = {12},
  journal   = {Energy, Sustainability and Society},
  number    = {3},
  publisher = {Springer Nature},
  doi       = {10.25974/fhms-14513},
  url       = {http://nbn-resolving.de/urn:nbn:de:hbz:836-opus-145136},
  pages     = {1 -- 20},
  year      = {2022},
  abstract  = {Background: Urban energy systems are responsible for 75 \% of the world's energy consumption and for 70 \% of the worldwide greenhouse gas emissions. Energy system models are used to optimize, benchmark and compare such energy systems with the help of energy sustainability indicators. We discuss several indicators for their basic suitability and their response to changing boundary conditions, system structures and reference values. The most suitable parameters are applied to four different supply scenarios of a real-world urban energy system. Results: There is a number of energy sustainability indicators, but not all of them are suitable for the use in urban energy system optimization models. Shortcomings originate from the omission of upstream energy supply chains (secondary energy efficiency), from limited capabilities to compare small energy systems (energy productivity), from excessive accounting expense (regeneration rate), from unsuitable accounting methods (primary energy efficiency), from a questionable impact of some indicators on the overall system sustainability (self-sufficiency), from the lack of detailed information content (share of renewables), and more. On the other hand, indicators of absolute greenhouse gas emissions, energy costs, and final energy demand are well suitable for the use in optimization models. However, each of these indicators only represents partial aspects of energy sustainability; the use of only one indicator in the optimization process increases the risk that other important aspects will deteriorate significantly, eventually leading to suboptimal or even unrealistic scenarios in practice. Therefore, multi-criteria approaches should be used to enable a more holistic optimization and planning of sustainable urban energy systems. Conclusion: We recommend multi-criteria optimization approaches using the indicators of absolute greenhouse gas emissions, absolute energy costs, and absolute energy demand. For benchmarking and comparison purposes, specific indicators should be used and therefore related to the final energy demand, respectively the number of inhabitants. Our example scenarios demonstrate modeling strategies to optimize sustainability of urban energy systems.},
  language  = {en}
}
@techreport{HoernschemeyerSoefkerRienietsNiestenetal.2023,
  author    = {H{\"o}rnschemeyer, Birgitta and S{\"o}fker-Rieniets, Anne and Niesten, Jan and Arendt, Rosalie and Kleckers, Jonas and Stretz, Celestin and Klemm, Christian and Budde, Janik and Wagner, R{\"u}diger and Vonhoegen, Laura and Reicher, Christa and Grimsehl-Schmitz, Winona and Wirbals, Daniel and Stieglitz-Broll, Eva-Maria and Agatz, Kerstin and Bach, Vanessa and Finkbeiner, Matthias and Lewe, Mareike and Henrichs, Malte and Haberkamp, Jens and Walter, Gotthard and Flamme, Sabine and Vennemann, Peter and Zamzow, Malte and Seis, Wolfgang and Matzinger, Andreas and Sonnenberg, Hauke and Rouault, Pascale and Maßmann, Stefanie and Fuchs, Lothar and Plogmeier, Christoph and Steinkamp, Arne and Şereflioğlu, Şenay and M{\"u}ller, Claus and Spital, Matthias and Uhl, Mathias},
  title     = {Leitfaden RessourcenPlan - Teil 1: Konzeption RessourcenPlan. Ergebnisse des Projekts R2Q RessourcenPlan im Quartier},
  publisher = {FH M{\"u}nster},
  address   = {M{\"u}nster},
  organization    = {IWARU Institut f{\"u}r Infrastruktur·Wasser·Ressourcen·Umwelt},
  doi       = {10.25974/fhms-15746},
  url       = {http://nbn-resolving.de/urn:nbn:de:hbz:836-opus-157463},
  year      = {2023},
  language  = {de}
}
@techreport{KlemmBuddeBeckeretal.2023,
  author    = {Klemm, Christian and Budde, Janik and Becker, Gregor and Arendt, Rosalie and Bach, Vanessa and Finkbeiner, Matthias and Vennemann, Peter},
  title     = {Leitfaden RessourcenPlan - Teil 2.4: Ressourcenmanagement Energie. Ergebnisse des Projekts R2Q RessourcenPlan im Quartier},
  doi       = {10.25974/fhms-15756},
  url       = {http://nbn-resolving.de/urn:nbn:de:hbz:836-opus-157560},
  year      = {2023},
  language  = {de}
}
@techreport{HoernschemeyerKleckersStretzetal.2023,
  author    = {H{\"o}rnschemeyer, Birgitta and Kleckers, Jonas and Stretz, Celestin and Klemm, Christian and Budde, Janik and S{\"o}fker-Rieniets, Anne and Vonhoegen, Laura and Zamzow, Malte and Matzinger, Andreas and Maßmann, Stefanie and Plogmeier, Christoph},
  title     = {Leitfaden RessourcenPlan - Teil 3.1: Kurzanleitung RessourcenPlan. Ergebnisse des Projekts R2Q RessourcenPlan im Quartier},
  doi       = {10.25974/fhms-15758},
  url       = {http://nbn-resolving.de/urn:nbn:de:hbz:836-opus-157581},
  year      = {2023},
  language  = {de}
}
@techreport{SoefkerRienietsVonhoegenKlemmetal.2023,
  author    = {S{\"o}fker-Rieniets, Anne and Vonhoegen, Laura and Klemm, Christian and Budde, Janik and H{\"o}rnschemeyer, Birgitta and Lewe, Mareike and Kleckers, Jonas and Stretz, Celestin},
  title     = {Leitfaden RessourcenPlan - Teil 3.2: Lernen von anderen - Booklet „Best-Practice". Ergebnisse des Projekts R2Q RessourcenPlan im Quartier},
  doi       = {10.25974/fhms-15759},
  url       = {http://nbn-resolving.de/urn:nbn:de:hbz:836-opus-157595},
  year      = {2023},
  language  = {de}
}
@techreport{HoernschemeyerKleckersStretzetal.2023,
  author    = {H{\"o}rnschemeyer, Birgitta and Kleckers, Jonas and Stretz, Celestin and Klemm, Christian and Budde, Janik and Arendt, Rosalie and Lewe, Mareike and Albers, Flemming},
  title     = {Leitfaden RessourcenPlan - Teil 3.3: Maßnahmen des Quartiersmanagements: Maßnahmensteckbriefe. Ergebnisse des Projekts R2Q RessourcenPlan im Quartier},
  doi       = {10.25974/fhms-15760},
  url       = {http://nbn-resolving.de/urn:nbn:de:hbz:836-opus-157603},
  year      = {2023},
  language  = {de}
}
@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}
}
@techreport{KlemmVennemann2019,
  type      = {Working Paper},
  author    = {Klemm, Christian and Vennemann, Peter},
  title     = {Optimization of resource efficiency in mixed-use quarters},
  doi       = {10.25974/fhms-11036},
  url       = {http://nbn-resolving.de/urn:nbn:de:hbz:836-opus-110361},
  year      = {2019},
  language  = {en}
}
@article{KlemmVennemannWiese2024,
  author    = {Klemm, Christian and Vennemann, Peter and Wiese, Frauke},
  title     = {Potential-risk and no-regret options for urban energy system design — A sensitivity analysis},
  series = {Sustainable Cities and Society},
  volume    = {102},
  journal   = {Sustainable Cities and Society},
  issn      = {2210-6707},
  doi       = {10.25974/fhms-17568},
  url       = {http://nbn-resolving.de/urn:nbn:de:hbz:836-opus-175686},
  pages     = {105189},
  year      = {2024},
  abstract  = {This study identifies supply options for sustainable urban energy systems, which are robust to external system changes. A multi-criteria optimization model is used to minimize greenhouse gas (GHG) emissions and financial costs of a reference system. Sensitivity analyses examine the impact of changing boundary conditions related to GHG emissions, energy prices, energy demands, and population density. Options that align with both financial and emission reduction and are robust to system changes are called "no-regret" options. Options sensitive to system changes are labeled as "potential-risk" options. There is a conflict between minimizing GHG emissions and financial costs. In the reference case, the emission-optimized scenario enables a reduction of GHG emissions (-93\%), but involves higher costs (+160\%) compared to the financially-optimized scenario. No-regret options include photovoltaic systems, decentralized heat pumps, thermal storages, electricity exchange between sub-systems and with higher-level systems, and reducing energy demands through building insulation, behavioral changes, or the decrease of living space per inhabitant. Potential-risk options include solar thermal systems, natural gas technologies, high-capacity battery storages, and hydrogen for building energy supply. When energy prices rise, financially-optimized systems approach the least-emission system design. The maximum profitability of natural gas technologies was already reached before the 2022 European energy crisis.},
  language  = {en}
}
@misc{TocklothKlemmBeckeretal.2024,
  author    = {Tockloth, Jan N. and Klemm, Christian and Becker, Gregor and Blankenstein, Benjamin and Vennemann, Peter},
  title     = {Spreadsheet Energy System Model Generator (SESMG)},
  series = {16. Steinfurter Bioenergiefachtagung - Tagungsband},
  journal   = {16. Steinfurter Bioenergiefachtagung - Tagungsband},
  doi       = {10.25974/fhms-17820},
  url       = {http://nbn-resolving.de/urn:nbn:de:hbz:836-opus-178209},
  year      = {2024},
  abstract  = {Die Transformation der Energiesysteme im Rahmen der Energiewende macht diese durch zus{\"a}tzliche Komponenten und Wechselwirkungen immer komplexer. Das {\"o}konomische und {\"o}kologische Potenzial, dass sich aus der Nutzung der Synergien dieser Komponenten ergeben kann, erfordert eine gemeinsame Betrachtung des gesamten Energiesystems hinsichtlich s{\"a}mtlicher Energie- und Verbrauchssektoren. Die Energiesystemmodellierung stellt eine geeignete Methode zur Modellierung und Optimierung dieser urbanen Energiesysteme dar. Mit dem „Spreadsheet Energy System Model Generator" (SESMG) hat die FH M{\"u}nster ein Open Source Tool entwickelt, das die Betrachtung urbaner Quartiere erm{\"o}glicht. Diese k{\"o}nnen hinsichtlich verschiedener Zielkriterien wie z. B. monet{\"a}ren Kosten und THG-Emissionen optimiert werden. Die tabellenbasierte Eingabe erfordert keine Programmierkenntnisse. Das implementierte Urban District Upscaling Tool erleichtert die effektive Modellierung auch gr{\"o}ßerer Systeme. Die automatisierte Ergebnisaufbereitung erm{\"o}glicht eine schnelle Analyse der Ergebnisse.},
  language  = {de}
}