Showing 25 pages using this property.
D | |
DESSTinEE + | T. Bossmann and I. Staffell, 2016. The shape of future electricity demand: Exploring load curves in 2050s Germany and Britain. Energy, 90(20), 1317–1333. |
DIETER + | Zerrahn, A., Schill, W.-P. (2017): Long-run power storage requirements for high shares of renewables: review and a new model. Renewable and Sustainable Energy Reviews 79, 1518-1534 |
Demod + | Barsanti, M., Schwarz, J.S., Gérard Constantin, L.G. et al. Socio-technical modeling of smart energy systems: a co-simulation design for domestic energy demand. Energy Inform 4, 12 (2021). |
Dispa-SET + | Quoilin, S., Hidalgo Gonzalez, I., & Zucker, A. (2017). Modelling Future EU Power Systems Under High Shares of Renewables: The Dispa-SET 2.1 open-source model. Publications Office of the European Union. |
DynPP + | Modelling and simulation of a coal-fired power plant for start-up optimisation |
E | |
ELTRAMOD + | Demand Side Management in Deutschland zur Systemintegration erneuerbarer Energien |
EMLab-Generation + | Richstein et al. 2014, Cross-border electricity market effects due to price caps in an emission trading system: An agent-based approach, Energy Policy Volume 71, August 2014, Pages 139–158 |
EOLES elec + | Shirizadeh, B. & Quirion, P. (2020). Low-carbon options for French power sector: What role for renewables, nuclear energy and carbon capture and storage? Energy Economics, 105004. |
EOLES elecRES + | Shirizadeh, B., Perrier, Q. & Quirion, P. (2022) How sensitive are optimal fully renewable systems to technology cost uncertainty? The Energy Journal, Vol 43, No. 1 |
ESO-X + | Heuberger CF, Rubin ES, Staffell I, Shah N, Mac Dowell Nclose, 2017, Power capacity expansion planning considering endogenous technology cost learning, APPLIED ENERGY, Vol: 204, Pages: 831-845, ISSN: 0306-2619 |
Energy Transition Model + | https://github.com/quintel/documentation |
EnergyScope + | Limpens G, Moret S, Jeanmart H, Maréchal F,EnergyScope TD: a novel open-source model for regional energy systems. Appl Energy 2019; Volume 255. |
F | |
FlexiGIS + | GIS-based urban energy systems models and tools: Introducing a model for the optimisation of flexibilisation technologies in urban areas |
G | |
GAMAMOD-DE + | Hauser, Philipp (2019) : A modelling approach for the German gas gridusing highly resolved spatial, temporal and sectoral data (GAMAMOD-DE), ZBW – LeibnizInformation Centre for Economics, Kiel, Hamburg |
Genesys + | Bussar et. al, 2014, Optimal Allocation and Capacity of Energy Storage Systems in a Future European Power System with 100% Renewable Energy Generation |
H | |
HighRES + | Zeyringer, M., Price, J., Fais, B., Li, P.-H. & Sharp, E. Designing low-carbon power systems for Great Britain in 2050 that are robust to the spatiotemporal and inter-annual variability of weather. Nat. Energy 3, 395–403 (2018) |
M | |
MOCES + | L. Exel, F. Felgner and G. Frey, "Multi-domain modeling of distributed energy systems - The MOCES approach," 2015 IEEE International Conference on Smart Grid Communications (SmartGridComm), Miami, FL, 2015, pp. 774-779. |
Maon + | Maon GmbH, Handbook, https://cloud.maon.eu/handbook. |
Medea + | https://arxiv.org/abs/2006.08009 |
MicroGridsPy + | Sergio Balderrama, Francesco Lombardi, Fabio Riva, Walter Canedo, Emanuela Colombo, Sylvain Quoilin, A two-stage linear programming optimization framework for isolated hybrid microgrids in a rural context: The case study of the “El Espino” community, Energy (2019), 188, |
Mosaik + | A. Ofenloch et al., "MOSAIK 3.0: Combining Time-Stepped and Discrete Event Simulation," 2022 Open Source Modelling and Simulation of Energy Systems (OSMSES), 2022, pp. 1-5 |
MultiMod + | Daniel Huppmann & Ruud Egging (2014). Market power, fuel substitution and infrastructure - A large-scale equilibrium model of global energy markets. Energy, 75, 483–500. |
N | |
NEMO (SEI) + | In preparation |
O | |
OnSSET + | Mentis, Dimitrios; Welsch, Manuel; Fuso Nerini, Francesco; Broad, Oliver; Howells, Mark; Bazilian, Morgan; Rogner, Holger (December 2015). "A GIS-based approach for electrification planning: a case study on Nigeria". Energy for Sustainable Development. 29: 142–150. doi:10.1016/j.esd.2015.09.007. ISSN 0973-0826. |
OpenTUMFlex + | Zade, M.; You, Z.; Kumaran Nalini, B.; Tzscheutschler, P.; Wagner, U. Quantifying the Flexibility of Electric Vehicles in Germany and California—A Case Study. Energies 2020, 13, 5617. |