@incollection{DiekerhofMontiLebedevaetal., author = {Diekerhof, M. and Monti, A. and Lebedeva, E. and Tkaczyk, A. H. and Y{\"u}ksel-Erg{\"u}n, I. and Zittel, J. and Escudero, L. F. and Soroudi, A. and Helmberg, C. and Kanov{\´i}c, Ž. and Petkovic, M. and Lacalandra, F. and Frangioni, A. and Lee, J. and De Filippo, A. and Lombardi, M. and Milano, M. and Ezran, P. and Haddad, Y.}, title = {Production and Demand Management}, series = {Mathematical Optimization for Efficient and Robust Energy Networks}, volume = {4}, booktitle = {Mathematical Optimization for Efficient and Robust Energy Networks}, publisher = {Springer}, isbn = {978-3-030-57442-0}, doi = {https://doi.org/10.1007/978-3-030-57442-0_1}, abstract = {Demand Side Management (DSM) is usually considered as a process of energy consumption shifting from peak hours to off-peak times. DSM does not always reduce total energy consumption, but it helps to meet energy demand and supply. For example, it balances variable generation from renewables (such as solar and wind) when energy demand differs from renewable generation.}, language = {en} } @incollection{SchwarzLacalandraScheweetal., author = {Schwarz, R. and Lacalandra, F. and Schewe, L. and Bettinelli, A. and Vigo, D. and Bischi, A. and Parriani, T. and Martelli, E. and Vuik, K. and Lenz, R. and Madsen, H. and Blanco, I. and Guericke, D. and Y{\"u}ksel-Erg{\"u}n, I. and Zittel, J.}, title = {Network and Storage}, series = {Mathematical Optimization for Efficient and Robust Energy Networks}, volume = {4}, booktitle = {Mathematical Optimization for Efficient and Robust Energy Networks}, publisher = {Springer}, isbn = {978-3-030-57442-0}, doi = {https://doi.org/10.1007/978-3-030-57442-0_6}, abstract = {Natural gas is considered by many to be the most important energy source for the future. The objectives of energy commodities strategic problems can be mainly related to natural gas and deal with the definition of the "optimal" gas pipelines design which includes a number of related sub problems such as: Gas stations (compression) location and Gas storage locations, as well as compression station design and optimal operation.}, language = {en} } @inproceedings{MuschnerYuekselErguenGehringetal., author = {Muschner, Christoph and Y{\"u}ksel-Erg{\"u}n, Inci and Gehring, Marie-Claire and Bartoszuk, Karolina and Haas, Sabine and Zittel, Janina}, title = {Sensitivity analysis of the energy transition path in the Berlin-Brandenburg area to uncertainties in operational and investment costs of diverse energy production technologies.}, series = {Proceedings of the 37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems - ECOS 2024}, booktitle = {Proceedings of the 37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems - ECOS 2024}, abstract = {The investigation of energy transition paths toward a sustainable and decarbonized future under uncertainty is a critical aspect of contemporary energy planning and policy development. There are numerous methods for analysing uncertainties and sensitivities and many studies on sustainable transformation paths, but there is a lack of combined application to relevant use-cases. In this study, we investigate the sensitivity of energy transition paths to uncertainties in operational and investment costs of power plants in the metropolitan area of Berlin and its rural surroundings. By employing the linear programming energy system model oemof-B3, we extensively focus on the system's energy technologies, such as wind turbines, photovoltaics, hydro and combustion plants, and energy storages. Greenhouse gas reduction and electrification rates per commodity are realized by selected constraints. Our research aims to discern how investments in energy production capacities are influenced by uncertainties of other energy technologies' investment and operational costs in the system. We apply a quantitative approach to investigate such interdependencies of cost variations and their impact on long-term energy planning. Thus, the analysis sheds light on the robustness of energy transition paths in the face of these uncertainties. The region Berlin-Brandenburg serves as a case study and thus reflects on the present space conflicts to meet energy demands in urban and suburban areas and their rural surroundings. An electricity-intensive scenario is selected that assumes a 100 \% reduction in greenhouse gas emissions by 2050. With the results of the case study, we show how our approach enables rural and metropolitan decision-makers to collaborate in achieving sustainable energy. Decision-making in long-term energy planning can be made more robust and flexible by acknowledging the identified sensitivities and enable such regions better to navigate challenges and uncertainties associated with sustainable energy planning.}, language = {en} }