DIETER - Revision history

Wolf-Peter Schill at 21:41, 13 December 2017

2017-12-13T21:41:09Z

Wolf-Peter Schill at 20:05, 13 December 2017

2017-12-13T20:05:50Z

Wolf-Peter Schill at 14:32, 15 February 2016

2016-02-15T14:32:14Z

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..."

2015-06-22T11:22:39Z

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..."

New page

{{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?
}}

@@ Line 9: / Line 9: @@
 |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
@@ Line 22: / Line 21: @@
 |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
+|Demand sectors=Households, Transport
-|Energy carriers (Renewable)=Hydro, Sun, Wind
+|Energy carriers (Solid)=Biomass, Coal, Lignite, Uranium
 |Storage (Electricity)=Battery, CAES, Chemical, PHS
 |Storage (Gas)=No
-|Storage (Heat)=No
+|Storage (Heat)=Yes
 |decisions=dispatch, investment
 |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
 |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.
@@ Line 42: / Line 46: @@
 |is_suited_for_many_scenarios=Yes
 |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_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
-|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 file format=No
 |Model output file format=No
 }}

@@ Line 1: / Line 1: @@
 {{Model
 |Full_Model_Name=Dispatch and Investment Evaluation Tool with Endogenous Renewables
 |author_institution=DIW Berlin
-|authors=Alexander Zerrahn, Wolf-Peter Schill
+|authors=Wolf-Peter Schill, Alexander Zerrahn
-|contact_persons=Alexander Zerrahn, Wolf-Peter Schill
+|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 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.
+|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.
 |open_source_licensed=Yes
 |license=MIT license (MIT)
@@ Line 14: / Line 22: @@
 |modelling_software=GAMS; CPLEX
 |processing_software=MS Excel
 |model_class=Optimization
-|sectors=electricity
+|sectors=electricity plus sector coupling (EVs, P2Heat)
 |technologies=Renewables, Conventional Generation
 |decisions=dispatch, investment
-|georegions=Germany or greenfield, loosely calibrated to Germany
+|Changes in efficiency=Exogenous
 |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_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=-
+|deterministic=- (work in progress)
 |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.
+|montecarlo=No
-|example_research_questions=Which capacities of storage and/or other flexibility options are required in the long run for different minimum shares of renewables?
+|computation_time_comments=depends on model specification
 }}