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| | |text_description=The Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER) has initially been developed in the research project StoRES to study the role of power storage and other flexibility options in a greenfield setting with high shares of renewables. Meanwhile, several model extensions have been developed and applied to different research questions. The model determines cost-minimizing combinations of power generation, demand-side management, and storage capacities as well as their respective dispatch in both the wholesale and the reserve markets. DIETER thus captures multiple system values of energy storage and other flexibility options related to arbitrage, firm capacity, and reserves. DIETER is an open source model which may be freely used and modified by anyone. The code is licensed under the MIT license, and input data is licensed under the Creative Commons Attribution-ShareAlike 4.0 International Public License. The model is implemented in the General Algebraic Modeling System (GAMS). Running the model thus also requires a GAMS system, an LP solver, and respective licenses. | | |text_description=The Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER) has initially been developed in the research project StoRES to study the role of power storage and other flexibility options in a greenfield setting with high shares of renewables. Meanwhile, several model extensions have been developed and applied to different research questions. The model determines cost-minimizing combinations of power generation, demand-side management, and storage capacities as well as their respective dispatch in both the wholesale and the reserve markets. DIETER thus captures multiple system values of energy storage and other flexibility options related to arbitrage, firm capacity, and reserves. DIETER is an open source model which may be freely used and modified by anyone. The code is licensed under the MIT license, and input data is licensed under the Creative Commons Attribution-ShareAlike 4.0 International Public License. The model is implemented in the General Algebraic Modeling System (GAMS). Running the model thus also requires a GAMS system, an LP solver, and respective licenses. |
| | |Primary outputs=Capacities, dispatch (and prices) | | |Primary outputs=Capacities, dispatch (and prices) |
| − | |Framework=GAMS
| |
| | |User documentation=http://www.diw.de/dieter | | |User documentation=http://www.diw.de/dieter |
| | |Code documentation=http://www.diw.de/dieter | | |Code documentation=http://www.diw.de/dieter |
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| | |modelling_software=GAMS; CPLEX | | |modelling_software=GAMS; CPLEX |
| | |processing_software=MS Excel | | |processing_software=MS Excel |
| | + | |External optimizer=CPLEX and others |
| | |GUI=No | | |GUI=No |
| | |model_class=Optimization | | |model_class=Optimization |
| | |sectors=electricity plus sector coupling (EVs, P2Heat) | | |sectors=electricity plus sector coupling (EVs, P2Heat) |
| | |technologies=Renewables, Conventional Generation | | |technologies=Renewables, Conventional Generation |
| − | |Demand sectors=Households | + | |Demand sectors=Households, Transport |
| − | |Energy carriers (Renewable)=Hydro, Sun, Wind | + | |Energy carriers (Solid)=Biomass, Coal, Lignite, Uranium |
| | + | |Energy carriers (Renewable)=Geothermal heat, Hydro, Sun, Wind |
| | |Storage (Electricity)=Battery, CAES, Chemical, PHS | | |Storage (Electricity)=Battery, CAES, Chemical, PHS |
| | |Storage (Gas)=No | | |Storage (Gas)=No |
| − | |Storage (Heat)=No | + | |Storage (Heat)=Yes |
| | + | |User behaviour=DSM: Detailed representation of load shifting and load curtailment |
| | + | |Market models=electricity wholesale and reserve markets |
| | |decisions=dispatch, investment | | |decisions=dispatch, investment |
| | |Changes in efficiency=Exogenous | | |Changes in efficiency=Exogenous |
| − | |georegions=Germany or greenfield, loosely calibrated to Germany, central European version also available | + | |georegions=Initial version: greenfield, loosely calibrated to Germany; central European version also available |
| − | |georesolution=Currently Germany as one node; version with additional central European country nodes available | + | |georesolution=In most applications so far, Germany as one node; version with additional central European country nodes available |
| | |timeresolution=Hour | | |timeresolution=Hour |
| | + | |Additional dimensions (Other)=Solar prosumage |
| | |math_modeltype=Optimization | | |math_modeltype=Optimization |
| | |math_modeltype_shortdesc=Linear cost minimization problem. Decision variables include investment and dispatch of generation, storage, DSM and different sector coupling options including vehicle-grid interactions in both wholesale and balancing markets. | | |math_modeltype_shortdesc=Linear cost minimization problem. Decision variables include investment and dispatch of generation, storage, DSM and different sector coupling options including vehicle-grid interactions in both wholesale and balancing markets. |
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| | |is_suited_for_many_scenarios=Yes | | |is_suited_for_many_scenarios=Yes |
| | |montecarlo=No | | |montecarlo=No |
| − | |computation_time_comments=depends on model specification | + | |computation_time_comments=depends on model specification (seconds to days) |
| | |citation_references=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 | | |citation_references=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 |
| | |citation_doi=https://doi.org/10.1016/j.rser.2016.11.098 | | |citation_doi=https://doi.org/10.1016/j.rser.2016.11.098 |
| − | |report_references=https://doi.org/10.1016/j.rser.2017.05.205 | + | |report_references=https://doi.org/10.1016/j.rser.2017.05.205, |
| − | https://doi.org/10.5547/2160-5890.6.1.wsch | + | https://doi.org/10.5547/2160-5890.6.1.wsch, |
| | https://doi.org/10.1007/s12398-016-0174-7 | | https://doi.org/10.1007/s12398-016-0174-7 |
| − | |example_research_questions=Which capacities of various flexibility / sector coupling options are required for different minimum shares of renewables, and what are their effects on quantities and prices? | + | |example_research_questions=Which capacities of various flexibility / sector coupling options prove to be optimal under different shares of renewables, and what are their effects on quantities and prices? |
| | |Model input file format=No | | |Model input file format=No |
| | |Model file format=No | | |Model file format=No |
| | |Model output file format=No | | |Model output file format=No |
| | }} | | }} |
Which capacities of various flexibility / sector coupling options prove to be optimal under different shares of renewables, and what are their effects on quantities and prices?
