Model comparison based on scope and methods: Difference between revisions
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Latest revision as of 17:38, 27 May 2024
This page makes it possible to create a comparison between (a selection of) models and reference card features. The features are ordered by reference card group. You can create a model selection first. This selection will be passed to the 'group features' queries. When you activate a 'group features' button, a new tab will be opened containing the 'run query form' with all features of the reference card group.
Model exploration
After clicking the [+] toggle below a table appears displaying the IAMC models with their scope and methods. You can filter the models based on one or more of the characteristics. This way you can explore the IAMC model set and use this information to inspect IAMC models further by selecting a set of models and comparing their features.
Expand [+}/collapse [-} the scope and method table with filter options to explore the differences.
Note: The 'other' option represents values deviating from the standard options for a feature.
Concept
Method
Model Type
Geographical scope
Solution horizon
| Model | Concept | Method | Model Type | Geographical scope | Solution horizon | State |
|---|---|---|---|---|---|---|
| AIM-Enduse India | Partial equilibrium (fixed demand) | Optimization | Energy system model | Recursive dynamic (myopic) | in preparation | |
| AIM-Enduse Japan | Partial equilibrium (fixed demand) | Optimization | Energy system model | Regional | Recursive dynamic (myopic) | published |
| AIM-Hub | General equilibrium (closed economy) | Simulation | CGE | Global | Recursive dynamic (myopic) | published |
| AIM-Hub Indonesia | General equilibrium (closed economy) | Simulation | CGE | Regional | Recursive dynamic (myopic) | in preparation |
| AIM-Hub Korea | General equilibrium (closed economy) | Simulation | CGE | Regional | Recursive dynamic (myopic) | |
| AIM-Hub Thailand | General equilibrium (closed economy) | Optimization | CGE | Regional | published | |
| AIM-Hub Viet Nam | General equilibrium (closed economy) | Simulation | CGE | Regional | published | |
| BET | General equilibrium (closed economy) | Optimization | Integrated assessment model | Global | Intertemporal optimization (foresight) | published |
| BLUES | General equilibrium (closed economy) | Optimization | Integrated assessment model | Regional | Intertemporal optimization (foresight) | published |
| C3IAM | General equilibrium (closed economy) | Optimization | Integrated assessment model | Global | Intertemporal optimization (foresight) | published |
| CCEM | General equilibrium (closed economy) | Simulation | CGE | Global | published | |
| COFFEE-TEA | General equilibrium (closed economy) | The COFFEE model is solved through Linear Programming (LP). The TEA model is formulated as a mixed complementary problem (MCP) and is solved through Mathematical Programming System for General Equilibrium -- MPSGE within GAMS using the PATH solver. | Integrated assessment model | Global | Intertemporal optimization (foresight) | under review |
| China TIMES | Partial equilibrium (price elastic demand) | Optimization | Energy system model | Regional | Intertemporal optimization (foresight) | published |
| DART | General equilibrium (closed economy) | Optimization | CGE | Global | Recursive dynamic (myopic) | published |
| DNE21+ | published | |||||
| E3ME-FTT | Econometric | Simulation | Integrated assessment model | Global | submitted | |
| ENV-Linkages | General equilibrium (closed economy) | Optimization | CGE | Global | Recursive dynamic (myopic) | in preparation |
| ENVISAGE | in preparation | |||||
| EPPA | General equilibrium (closed economy) | Optimization | Integrated assessment model | Global | Recursive dynamic (myopic) | in preparation |
| Euro-Calliope | Partial equilibrium (fixed demand) | Optimization | Energy system model | Regional | Static | published |
| GCAM | General equilibrium (closed economy)GCAM solves all energy, water, and land markets simultaneously | Recursive dynamic solution method | Integrated assessment model | Global | Recursive dynamic (myopic) | under review |
| GCAM-KAIST | General equilibrium (closed economy) | Integrated assessment model | Global | Recursive dynamic (myopic) | in preparation | |
| GCAM-KSA | Partial equilibrium (price elastic demand)GCAM solves all energy, water, and land markets simultaneously | Recursive dynamic solution method | Integrated assessment model | Global | Recursive dynamic (myopic) | published |
| GEM-E3 | General equilibrium (closed economy) | Optimization | CGE | Global | Recursive dynamic (myopic) | published |
| GENeSYS-MOD | Partial equilibrium (fixed demand) | OptimizationLinear optimisation | Energy system model | Global | Intertemporal optimization (foresight)recursive-dynamic (myopic) | published |
| GMM | Partial equilibrium (fixed demand) | Optimization | Energy system model | Global | Intertemporal optimization (foresight) | in preparation |
| GRACE | General equilibrium (closed economy) | SimulationRecursive dynamic solution method | CGE | Global | Recursive dynamic (myopic) | under review |
| ICES | General equilibrium (closed economy)General Equilibirum (open economy) | Optimization | CGE | Global | Recursive dynamic (myopic) | in preparation |
| IFs | Dynamic recursive with annual time steps through 2100. | under review | ||||
| IMACLIM | General equilibrium (closed economy) | SimulationImaclim-R is implemented in Scilab, and uses the fonction fsolve from a shared C++ library to solve the static equilibrium system of non-linear equations. | CGE | Global | Recursive dynamic (myopic) | published |
| IMACLIM-India | General equilibrium (closed economy) | Optimization | CGE | Regional | Intertemporal optimization (foresight) | in preparation |
| IMACLIM-NLU | General equilibrium (closed economy) | SimulationImaclim-NLU is implemented in Scilab, and uses the fonction fsolve from a shared C++ library to solve the static equilibrium system of non-linear equations. | CGE | Global | Recursive dynamic (myopic) | published |
| IMAGE | Partial equilibrium (price elastic demand) | Simulation | Integrated assessment model | Global | Recursive dynamic (myopic) | published |
| IPAC-AIM technology | Partial equilibrium (fixed demand) | Optimization | Energy system model | Regional | Recursive dynamic (myopic) | in preparation |
| IPAC-Global | Partial equilibrium (price elastic demand) | Optimization | Integrated assessment model | Global | Intertemporal optimization (foresight) | in preparation |
| IPETS | The economic problem is formulated as a three-level nested problem. The solution of these three sub-problems yield the dynamic capital path (investment/consumption trade-off in each simulation year), and factor and output prices which clear all factor and goods markets. | published | ||||
| MARKAL-India | Partial equilibrium (fixed demand) | Optimization | Energy system model | Regional | Intertemporal optimization (foresight) | in preparation |
| MEDEAS | Systems dynamics based approach | Simulation | Integrated assessment model | Global | in preparation | |
| MERGE-ETL | General equilibrium (closed economy) | Optimization | Integrated assessment model | Global | Intertemporal optimization (foresight) | in preparation |
| MESSAGE Korea | Partial equilibrium (fixed demand) | Optimization | Energy system model | Regional | Intertemporal optimization (foresight) | published |
| MESSAGE-GLOBIOM | General equilibrium (closed economy) | Optimization | CGE | Global | published | |
| MIGRATION | Partial equilibrium (fixed demand) | Simulation | Global | Intertemporal optimization (foresight) | published | |
| MUSE | Partial equilibrium (price elastic demand) | Simulation | Energy system model | Global | in preparation | |
| McKinsey | in preparation | |||||
| POLES | Partial equilibrium (price elastic demand) | SimulationRecursive simulation | Integrated assessment model | Global | Recursive dynamic (myopic) | published |
| PRIMES | Partial equilibrium (price elastic demand)The PRIMES model comprises several sub-models (modules), each one representing the behaviour of a specific (or representative) agent, a demander and/or a supplier of energy. The sub-models link with each other through a model integration algorithm, which determines equilibrium prices in multiple markets and equilibrium volumes meets balancing and overall (e.g. emission) constraints. | Mathematically PRIMES solves an EPEC problem (equilibrium problem with equilibrium constraints) which allows prices to be explicitly determined. | Energy system model | Regional | Intertemporal optimization (foresight) | in preparation |
| PROMETHEUS | Partial equilibrium (price elastic demand) | Simulation | Energy system model | Global | Recursive dynamic (myopic) | under review |
| REMIND-MAgPIE | General equilibrium (closed economy)MAgPIE: partial equilibrium model of the agricultural sector; | OptimizationMAgPIE: cost minimization; | CGE | Global | REMIND-MAgPIE: Inter-temporal (foresight); MAgPIE: recursive-dynamic; | published |
| REMod | Partial equilibrium (fixed demand) | OptimizationSimulation-based optimization | Energy system model | Regional | Intertemporal optimization (foresight) | published |
| RICE50+ | General equilibrium (closed economy) | Optimization | CBA-integrated assessment model | Global | Intertemporal optimization (foresight) | published |
Model selection
You can create a model selection based on specific values for model scope and methods.
Current selection is based on filters:
- Method: no filter
- Concept: no filter
- Horizon: no filter
- Model type: CGE
- Geographical scope:Regional
Resulting in model selection : AIM-Hub Indonesia;AIM-Hub Korea;AIM-Hub Thailand;AIM-Hub Viet Nam;IMACLIM-India;VESPA
Feature selection
The buttons below will open a query page in a new tab. It contains a form to select features and run the comparison query.
| About model | Model scope and methods | Socio-economic drivers | Macro-economy | Energy | Land-use | Emission, climate and impacts |
|---|---|---|---|---|---|---|