Showing 25 pages using this property.
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| AMIRIS + | Nitsch, Schimeczek, Wehrle (2021) Back-testing the agent-based model AMIRIS for the Austrian day-ahead electricity market, Working Paper. |
| ASAM + | Glismann (2021), “ Ancillary Services Acquisition Model: considering market interactions in policy design”, preprint Applied Energy Journal. https://arxiv.org/abs/2104.13047 |
| AnyMOD + | Göke (2020), AnyMOD - A graph-based framework for energy system modelling with high levels of renewables and sector integration, Working Paper. |
B | |
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| Backbone + | Helistö, N.; Kiviluoma, J.; Ikäheimo, J.; Rasku, T.; Rinne, E.; O’Dwyer, C.; Li, R.; Flynn, D. Backbone—An Adaptable Energy Systems Modelling Framework. Energies 2019, 12, 3388. |
| Balmorel + | Göransson, L. and Johnsson, F. (2013), Cost-optimized allocation of wind power investments: a Nordic-German perspective, Wind Energy, Vol. 16, Issue 4 |
| Breakthrough Energy Model + | Y. Xu et al., "U.S. Test System with High Spatial and Temporal Resolution for Renewable Integration Studies," 2020 IEEE Power & Energy Society General Meeting (PESGM), 2020, pp. 1-5. |
C | |
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| CAPOW + | Su, Y., Kern, J., Denaro, S., Hill, J., Reed, P., Sun, Y., Cohen, J., Characklis, G. (2020). “An open source model for quantifying risks in bulk electric power systems from spatially and temporally correlated hydrometeorological processes” Environmental Modelling and Software. Vol. 126 |
| CESAR-P + | Leonie Fierz, Urban Energy Systems Lab, Empa. (2021, July 30). hues-platform/cesar-p-core: CESAR-P-V2.0.1 (CESAR-P-V2.0.1). Zenodo. https://doi.org/10.5281/zenodo.5148531 |
| Calliope + | Pfenninger and Pickering, (2018). Calliope: a multi-scale energy systems modelling framework. Journal of Open Source Software, 3(29), 825 |
| CapacityExpansion + | https://joss.theoj.org/papers/10.21105/joss.02034# |
D | |
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| 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 | |
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| 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 | |
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| FlexiGIS + | GIS-based urban energy systems models and tools: Introducing a model for the optimisation of flexibilisation technologies in urban areas |
G | |
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| 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 |
