wiki.openmod-initiative.org - User contributions [en]

DIETER

2017-12-13T21:41:09Z

Wolf-Peter Schill:

{{Model
|Full_Model_Name=Dispatch and Investment Evaluation Tool with Endogenous Renewables
|Acronym=DIETER
|author_institution=DIW Berlin
|authors=Wolf-Peter Schill, Alexander Zerrahn
|contact_persons=Wolf-Peter Schill, Alexander Zerrahn
|contact_email=wschill@diw.de
|website=http://www.diw.de/dieter
|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)
|User documentation=http://www.diw.de/dieter
|Code documentation=http://www.diw.de/dieter
|Source of funding=Various research projects
|Number of developers=2 permanent + some temporary ones
|Number of users=unknown
|open_source_licensed=Yes
|license=MIT license (MIT)
|model_source_public=Yes
|data_availability=all
|open_future=No
|modelling_software=GAMS; CPLEX
|processing_software=MS Excel
|External optimizer=CPLEX and others
|GUI=No
|model_class=Optimization
|sectors=electricity plus sector coupling (EVs, P2Heat)
|technologies=Renewables, Conventional Generation
|Demand sectors=Households, Transport
|Energy carriers (Solid)=Biomass, Coal, Lignite, Uranium
|Energy carriers (Renewable)=Geothermal heat, Hydro, Sun, Wind
|Storage (Electricity)=Battery, CAES, Chemical, PHS
|Storage (Gas)=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
|Changes in efficiency=Exogenous
|georegions=Initial version: greenfield, loosely calibrated to Germany; central European version also available
|georesolution=In most applications so far, Germany as one node; version with additional central European country nodes available
|timeresolution=Hour
|Additional dimensions (Other)=Solar prosumage
|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_objective=Cost minimization
|deterministic=- (work in progress)
|is_suited_for_many_scenarios=Yes
|montecarlo=No
|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_doi=https://doi.org/10.1016/j.rser.2016.11.098
|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/10.1007/s12398-016-0174-7
|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 file format=No
|Model output file format=No
}}

DIETER

2017-12-13T20:05:50Z

Wolf-Peter Schill:

{{Model
|Full_Model_Name=Dispatch and Investment Evaluation Tool with Endogenous Renewables
|Acronym=DIETER
|author_institution=DIW Berlin
|authors=Wolf-Peter Schill, Alexander Zerrahn
|contact_persons=Wolf-Peter Schill, Alexander Zerrahn
|contact_email=wschill@diw.de
|website=http://www.diw.de/dieter
|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)
|Framework=GAMS
|User documentation=http://www.diw.de/dieter
|Code documentation=http://www.diw.de/dieter
|Source of funding=Various research projects
|Number of developers=2 permanent + some temporary ones
|Number of users=unknown
|open_source_licensed=Yes
|license=MIT license (MIT)
|model_source_public=Yes
|data_availability=all
|open_future=No
|modelling_software=GAMS; CPLEX
|processing_software=MS Excel
|GUI=No
|model_class=Optimization
|sectors=electricity plus sector coupling (EVs, P2Heat)
|technologies=Renewables, Conventional Generation
|Demand sectors=Households
|Energy carriers (Renewable)=Hydro, Sun, Wind
|Storage (Electricity)=Battery, CAES, Chemical, PHS
|Storage (Gas)=No
|Storage (Heat)=No
|decisions=dispatch, investment
|Changes in efficiency=Exogenous
|georegions=Germany or greenfield, loosely calibrated to Germany, central European version also available
|georesolution=Currently Germany as one node; version with additional central European country nodes available
|timeresolution=Hour
|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_objective=Cost minimization
|deterministic=- (work in progress)
|is_suited_for_many_scenarios=Yes
|montecarlo=No
|computation_time_comments=depends on model specification
|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
|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/10.1007/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?
|Model input file format=No
|Model file format=No
|Model output file format=No
}}

DIETER

2016-02-15T14:32:14Z

Wolf-Peter Schill:

{{Model
|Full_Model_Name=Dispatch and Investment Evaluation Tool with Endogenous Renewables
|author_institution=DIW Berlin
|authors=Alexander Zerrahn, Wolf-Peter Schill
|contact_persons=Alexander Zerrahn, Wolf-Peter Schill
|contact_email=wschill@diw.de
|website=http://www.diw.de/dieter
|text_description=The Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER) has 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. 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 power storage related to arbitrage, firm capacity, and reserves. An extended version also includes grid interactions of electric vehicles. 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.
|open_source_licensed=Yes
|license=MIT license (MIT)
|model_source_public=Yes
|data_availability=all
|open_future=No
|modelling_software=GAMS; CPLEX
|processing_software=MS Excel
|model_class=Optimization
|sectors=electricity
|technologies=Renewables, Conventional Generation
|decisions=dispatch, investment
|georegions=Germany or greenfield, loosely calibrated to Germany
|timeresolution=Hour
|math_modeltype=Optimization
|math_modeltype_shortdesc=Linear cost minimization problem. Decision variables include investment and dispatch of generation, storage, and DSM capacities as ell as vehicle-grid interactions in both wholesale and balancing markets.
|math_objective=Cost minimization
|deterministic=-
|is_suited_for_many_scenarios=Yes
|citation_references=Zerrahn, A., Schill, W.-P. (2015): A greenfield model to evaluate long-run power storage requirements for high shares of renewables. DIW Discussion Paper 1457.
|example_research_questions=Which capacities of storage and/or other flexibility options are required in the long run for different minimum shares of renewables?
}}

DIETER

2015-06-22T11:22:39Z

Wolf-Peter Schill: Created page with "{{Model |Full_Model_Name=Dispatch and Investment Evaluation Tool with Endogenous Renewables |author_institution=DIW Berlin |authors=Alexander Zerrahn, Wolf-Peter Schill |conta..."

{{Model
|Full_Model_Name=Dispatch and Investment Evaluation Tool with Endogenous Renewables
|author_institution=DIW Berlin
|authors=Alexander Zerrahn, Wolf-Peter Schill
|contact_persons=Alexander Zerrahn, Wolf-Peter Schill
|contact_email=wschill@diw.de
|website=http://www.diw.de/dieter
|text_description=The Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER) has 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. 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 power storage related to arbitrage, firm capacity, and reserves. DIETER is an open source model which may be freely shared alike and adapted for non-commercial uses. It is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International 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.
|open_source_licensed=Yes
|license=Creative Commons Attribution Share-Alike 4.0 (CC-BY-SA-4.0)
|model_source_public=Yes
|data_availability=all
|open_future=No
|modelling_software=GAMS; CPLEX
|processing_software=MS Excel
|model_class=Optimization
|sectors=electricity
|technologies=Renewables, Conventional Generation
|decisions=dispatch, investment
|georegions=Greenfield, loosely calibrated to Germany
|timeresolution=Hour
|math_modeltype=Optimization
|math_modeltype_shortdesc=Linear cost minimization problem. Decision variables include investment and dispatch of generation, storage, and DSM capacities in both wholesale and balancing markets.
|math_objective=Cost minimization
|deterministic=-
|is_suited_for_many_scenarios=Yes
|citation_references= Zerrahn, A., Schill, W.-P. (2015): A greenfield model to evaluate long-run power storage requirements for high shares of renewables. DIW Discussion Paper 1457.
|example_research_questions=Which capacities of storage and/or other flexibility options are required in the long run for different minimum shares of renewables?
}}