The rows present the different socio and techno
variables. The columns indicate the available models. Variables are either
considered as outputs
from models, inputs to models or are not represented by the models as any
explicit output or
Global IAMsEnergy System142 is bottom-up type model based on the scenarios of socio-economic, demographic, structural and technological parameters of different countries' development. The outut is energy balances which correspond to the methodology and structure of IEA balances.
Partial Equilibirum (Soft-linked with IMACLIM-India. TIMES-India)0The AIM/End-use Indian model integrates the water module at the resource and technological level into the existing energy and environment systems to capture the impacts of existing and future policies for water, energy, and land systems on the major water- and energy-intensive sectors.
National/Regional Models for EuropeSectoral Focus1The ALADIN model (ALternative Automobiles Diffusion and INfrastructure) is an agent-based simulation of alternative fuel vehicles purchase decision. It uses driving data from several thousand individual vehicles.
Simulation.0Agent-based technology adoption and social innovation diffusion model in the residential sector.
National/Regional Models for EuropeGeneral Equilibrium0CHANCE is a macro-micro model based on a computable general equilibrium (CGE) model that includes a large amount of household microdata. It is a disaggregated multiregional and multisector model that included information for around 200,000 households covering all EU regions, ensuring a large representation of the behaviour of the European households. Therefore, CHANCE is a model designed to analyse the socioeconomic and distributional impacts of public policies that directly affect households and consumers, both economic, energy, environmental or fiscal.
Global IAMsBottom-up optimisation modelling framework (same family as MESSAGE and MARKAL-TIMES). Can be used with partial equilibrium and with myopic setting, but it requires modification and significantly higher computational load0It is not a model application, but a modelling framework. Using OSeMOSYS, a representation of the energy, land and water systems and the links between them can be created. Climate change is an input to the model and it is typically included as variation of temperature (therefore, evaporation and evapotranspiration) and of precipitation patterns. The energy system typically includes representation of several conversion and storage options. The land system includes land cover, water uses and energy uses by built-up environment, water bodies, forest land, grassland and N custom crops. Each crop area is further divided into irrigated and rainfed crop, into different levels of mechanization and inputs, into different levels of productivity dependent on the agro-climatic conditions. The water system includes the whole water cycle: precipitation falls onto the land, it goes through either evaporation, evapotranspiration, runoff or groundwater recharge, and finally all the surface or groundwater that remains is used by different sectors. All water uses for e.g. irrigation, power plants, domsetic uses, industrial uses can be included. The use of resources across the energy, land and water systems is optimised jointly, with an objective to minimise the total systems cost.
Non-EU ModelsSectoral Focus1CONTO - dynamic IO Model of Russian economy is developed for medium- and long-term economic dynamic forecast.
The model based on the official IO tables for Russian economy in 44-industries classification (product-to-product), statistics of SNA, industrial statistics, energy balances etc.
Global IAMsGeneral Equilibrium5The DICE-2013R model is a globally aggregated model. The DICE model views the economics of climate change from the perspective of neoclassical economic growth theory (see particularly Solow 1970). In this approach, economies make investments in capital, education, and technologies, thereby reducing consumption today, in order to increase consumption in the future.
Simulation.0Energy demand and demand-side management modelling in the building sector.
Top-down input output model0DYNERIO is a python-based tool to shape energy transition macroeconomic scenarios and assess their impact on critical materials extraction
Global IAMsMacro-Econometric1The Post Keynesian energy-environment-economy (E3) macroeconometric model (E3ME). Economic growth in E3ME is demand-driven and supply-constrained, with no assumption of the economy being in full-employment equilibrium. Empirically-validated dynamics (the time path of an economy), is a key feature of E3ME.
Global IAMsMacro-econometric E3 model1E3ME is a dynamic, computer-based, global macroeconomic model which represents the three pillars of sustainability: economy, society and environment. E3ME’s detailed sectoral disaggregation is important for assessing interactions between the pillars. The model is highly empirical in its approach.
National/Regional Models for EuropePartial equilibrium gas market model1Partial equilibrium model focusing on EU28 and neighbouring countries' interconnected gas markets.
National/Regional Models for EuropeSimulation model1EnergyPLAN is an input-output model that simulates the annual operation of the entire energy system in hourly time steps. It includes electricity, heating, cooling, transport, industry and desalination demands. For production it includes various types of power plants, variable renewable energy sources and combined heat and power plants. The main focus is to be able to simulate smart energy systems, and therefore includes modelling of electricity, district heating and gas grids. It allows for many types of P2X applications both for heating, gas and liquid fuels.
National/Regional Models for EuropeElectricity sector unit commitment model1The EPMM is a unit commitment and economic dispatch model of the European popwer markets, which during the optimization process satisfies the electricity consumption needs in the modelled countries at minimum system cost considering the different types of costs and capacity constraints of the available power plants and cross-border transmission capacities.
Global IAMsIntegrated Assesment Model1U-ETC Rice is an IAM which investigates how ecological uncertainty affects agents' decisions concerning domestic emissions abatement, physical investments, and R&D expenditures. The model introduces an "hazard rate" function related to the climate change dynamics. The "hazard rate" provides the link between the probability of a catastrophic event and the (endogenous) level of temperature mesured on the planet at a certain moment.
National/Regional Models for EuropeCost-optimisation high-resolution energy system model1Euro Calliope model of the European electricity system built using Calliope, a well-established open-source energy modelling framework
National/Regional Models for EuropeEnergy System12The EU-TIMES model, is the multi-region, European version of TIMES, which is designed for analysing the role of energy technologies and their innovation needs for meeting European policy targets related to energy and climate change. It models technologies uptake and deployment and their interaction with the energy infrastructure in an energy systems perspective.
National/Regional Models for EuropePartial Equilibrium1EXPANSE is a bottom-up, technology-rich electricity system model. Two versions of the model exist depending on the research question: (1) spatially-explicit, single-year model at NUTS-3 spatial resolution and with hourly time step for Europe; and (2) national long-range capacity expansion model with in-depth uncertainty analysis. The unique feature of EXPANSE is that it applies Modelling to Generate Alternatives method (MGA) to compute and analyze large numbers of cost-optimal and near-optimal scenarios with only a single set of assumptions.
National/Regional Models for EuropeSectoral Focus1The FORECAST model is designed as a tool that can be used to support strategic decisions. Its main objective is to support the scenario design and analysis for the long-term development of energy demand and greenhouse gas emissions for the industry, residential and tertiary sectors on country level.
Global IAMsPartial Equilibrium5GCAM is a dynamic-recursive model with technology-rich representations of the economy, energy sector, land use and water linked to a climate model that can be used to explore climate change mitigation policies.
Partial equilibrium0GCAM (v2022) is a dynamic-recursive model with technology-rich representations of the economy, energy sector, land use and water linked to a climate model that can be used to explore climate change mitigation policies including carbon taxes, carbon trading, regulations and accelerated deployment of energy technology. Regional population and labour productivity growth assumptions drive the energy, land-use and water systems employing numerous technology options to produce, transform and provide energy services, as well as to produce agriculture and forest products, and to determine land use and land use cover.
Global IAMsGeneral Equilibrium1GEMINI-E3 is a standard worldwide computable general equilibrium model. The model is based on the assumption of total flexibility in all markets, both the macroeconomic markets such as the capital and the exchange markets (with the associated prices being the real rate of interest and the real exchange rate, which are endogenous) and the microeconomic or sector markets (goods, factors of production).
National/Regional Models for EuropeThe HEB model uses bottom-up approach, to include detailed technological information for building sector.1HEB (High Efficiency Buildings) model analyses building energy use and CO2 emissions. This model is novel in its methodology as compared to earlier global energy analyses and reflects the emerging new paradigm – the performance-oriented approach to buildings energy analysis. As opposed to component-oriented methods, a systemic perspective is taken: the performance of whole systems (e.g. whole buildings) is studied and these performance values are used as inputs in the scenarios.
National/Regional Models for EuropeEnergy sector cost minimization partial equilibrium model1TheHU-TIMES is a social welfare cost minimizing model, which during optimization process satisfies the exogeneous final end-use consumptions in the different energy sectors in Hungary considering the cost of the different energy transformation options and the current and future technologies that are to be used to meet the end-use demand.
Global IAMsGeneral Equilibrium1ICES is a recursive-dynamic computational general equilibrium model. The model describes a stylised world economy where agents optimise their choices (rational agents maximising profit and utility; perfect competition), markets are interconnected by input-output relations in each country and by international trade across countries.
Top-Down (TD) model0A global dynamic recursive CGE model based on the MPSGE language written in GAMS. In the IMACLIM-China model, China’s economy is divided into 18 sectors, including 6 energy sectors and 12 non-energy sectors.
National/Regional Models for EuropeEnergy System1The Long-range Energy Alternatives Planning system (LEAP) is a scenario-based energy-environment modeling tool. Its scenarios are based on comprehensive accounting of how energy is consumed, converted and produced in a given region or economy under a range of alternative assumptions on population, economic development, technology, price and so on.
National/Regional Models for EuropeComputable General Equilibrium1MANAGE is a recursive dynamic single country CGE model designed to focus on energy, emissions and climate change. The model has a detailed specification for the energy sector that allows for capital/labor/energy substitution in production, as well as intra-fuel energy substitution across all demand agents with multi-output and multi-production structure. MANAGE adopts the neo-classical growth specification.
Non-EU ModelsEnergy System5The MAPLE is a bottom-up model based on China national level, including energy supply and demand sectors, around 780 technologies considered.
Non-EU ModelsEnergy System5MARKAL (acronym for MARket ALlocation) is a bottom up dynamic linear programming model and depicts both the energy supply and demand sides of the energy system. The MARKAL family of models is unique, with applications in a wide variety of settings and global technical support from the international research community.
Global IAMsSystem Dynamics and Input Output Tables.1
Policy-simulation dynamic-recursive model which has been designed applying System Dynamics. The model has been developed in Vensim DSS software for Windows, and is also available in Python.
Non-EU ModelsEnergy system model0MENA-EDS is a national energy system model covering in detail the complex interactions between energy demand, supply and energy prices at the national level. Its main objectives are: 1) Assess climate change mitigation pathways and low-emission development strategies for the medium and long-term 2) Analyse the energy system, economic and emission implications of a wide spectrum of energy and climate policy measures, differentiated by region and sector) 3) Explore the economics of fossil fuel production and quantify the impacts of climate policies on the evolution of global energy prices
Global IAMsBottom Up Energy System Optimization Model1MicrogGridsPy is a linear / mixed integer linear optimization model for sizing of rural hybrid microgrids for access to energy. It also exists in its versions "Multi Year Capacity Expansion" and "MicroEnergySystem"
Global IAMsEnergy System10MUSE is a partial equilibrium global integrated assessment model. It uses an agent-based modelling approach to model each sector of the energy system.
Non-EU ModelsEnergy System10NATEM is a particular implementation of the TIMES optimisation modeling approach for Canada, USA and Mexico. NATEM follows a techno-economic modeling approach to describe the energy sector of a given region or country, accounting in particular for a variety of specific energy technologies modeled through both technical parameters and economic parameters.
National/Regional Models for EuropeMacro-Econometric1The NEMESIS model is a detailed sector macroeconomic model for the European Union. It is a system of economic models for every Member State (including UK) devoted to study issues that link economic development, competitiveness, employment and public accounts to economic policies and notably all structural policies involving long term effects.
Bottom Up Energy and resource System Optimization modelling tool0The Open Source energy MOdelling SYStem – OSeMOSYS is a long-term energy and resource planning tool that stands for an open, transparent and accessible approach of energy planning. It is a bottom-up linear optimization modelling system. In the last few years OSeMOSYS has already been used to build regional models like the The Electricity Model Base for Africa – TEMBA, and The open source South American Model Base – SAMBA. In the Horizon 2020 EU REEEM project the Open Source energy Modelling Base for the European Union – OSeMBE was developed. OSeMOSYS has a low learning threshold and is available in three modelling languages (Python, GAMS and GNU MathProg), fitting the needs of different communities of users. That allowed its spread in numerous countries worldwide, for academic research, capacity development and support to national planning processes.
Global IAMsBottom Up Energy System Optimization Model1OSeMBE – OSeMOSYS is a long-term integrated assessment and energy planning tool that stands for an open, transparent and accessible approach of energy planning. It is a bottom-up linear optimization modelling system.
Global IAMsPartial equilibrium Energy1POLES is a dynamic-recursive model with technology-rich representations of the energy secto that can be used to explore climate change mitigation policies including carbon taxes, regulations and accelerated deployment of energy technology. Regional population and GDP growth assumptions drive the energy sector employing numerous technology options to produce, transform and provide energy services.
National/Regional Models for EuropeDeterministic simulation model1PowerPlan is a deterministic bottom-up tool (each plant can be defined separately) for the simulation of electricity demand and production from a centralized planning perspective which allows the exploration of ‘what if’ scenarios. The model provides a flexible and dynamic modelling environment for mid- to long-term electricity supply planning and scenario studies. PowerPlan simulates investment decisions in capacity expansion and produces results including generation costs, system reliability, fuel use and environmental emissions. The core of the PowerPlan model is the production simulation module in which the demand has to be met by the supply using the merit order approach. Calculations are performed on an hourly bases.
Global IAMsEnergy system model0The Prometheus model is a comprehensive world energy model with innovative features: it integrates stochastic relations and so all exogenous variables – parameters are stochastic, following explicit probability distributions, including covariance. Therefore, all model results are also stochastic (probability distributions). Among others, stochastic distributions are used for technology change and learning by doing, as well as for fossil fuel resources, both conventional and unconventional. Prometheus models the world energy system divided into 10 regions and produces yearly projections up to 2050; the update to 2070 is ongoing. The model includes a set of long time series (IEA data mostly) on which econometric estimations are carried out. The model produces projections of energy demand by sector (industry, domestic, transport), power generation (representing about 25 technologies), RES, and hydrogen supply and use. Prometheus puts emphasis on oil and gas resources, while coal is assumed to have rather abundant supplies relative to production prospects in the projection time horizon. The model incorporates uncertainty surrounding the amount of oil and gas resources that are yet to be discovered. Data are mostly calibrated on estimation of resources by USGS. The model produces projections of fossil fuel prices, which depend on demand, supply, technology and resources. As all outputs are probabilistic, fossil fuel price projections take the form of probability distributions. The model includes CO2 emissions and can simulate emission reduction pathways.
National/Regional Models for EuropeBottom-up power system simulation model based on mixed-integer linear programming, partial equilibrium1PSM-EU provides instances of a power system simulation models for (parts of) EU27-3. PSM-EU contains data at a country basis and allows for capacity expansion model runs, to determine, for example, new additions of generation capacity and transmission infrastructure, and hourly Unit Commitment and Economic Dispatch (UCED) model runs considering power plant flexibility limitations and flexible loads.
Non-EU ModelsSectoral Focus1SISGEMA is hybrid environmental-
economic model built to assess economic and environmental impacts of alternative land uses in
Brazil. The model estimates costs of conserving and recovering forest areas, based on, respectively,
land use opportunity costs, and costs of fencing, inputs and labour.
Global IAMsPartial Equilibrium10ETSAP is recalibrating and improving the geographical resolution of the TIAM model. The new version of the model will be available in 2020 and will cover 31 regions, with the same details and general approach of the existing version of the model.
Non-EU ModelsEnergy System6The integrated bottom-up partial-equilibrium energy system model of the Central Asian Caspian Area, titled TIMES-CAC-4R, assembles the 4 separate but structurally-consistent single-region TIMES country models of Azerbaijan, Kazakhstan, Turkmenistan, Uzbekistan (plus 2 "virtual" regions representing the potential of trades with Kyrgyztan and Tajikistan).
Global IAMsIAM, Simulation, System Dynamics, Input Output tables1
Policy-simulation dynamic-recursive integrated assessment model (IMA) which has been designed applying System Dynamics. The model willl be developed in Vensim DSS software for Windows, and will also be available in Python.
Model family including bottom-up calculations, optimization and stock & flow models0The industrial modules of WISEE-EDM described here are used to analyse possible futures of an industrial production system and to derive technically consistent paths to them, starting from the current production system. They are a model family for technologically detailed bottom-up modelling that includes a variety of models and tools that can be combined according to the industrial sub-sector as well as the purpose and level of analysis (see figure 1 below). The models have a high level of technical detail and offer a variety of options for adapting the analysis to scenario-specific assumptions. They are therefore particularly suitable for developing scenarios in exchange with stakeholders. Typical results are energy demand and CO2 emissions differentiated by energy sources, geographical units, years and sectors.
National/Regional Models for EuropeOptimization model for invest and dispatch of energy supply1The energy supply model WISEE-ESM calculates the cost-optimal expansion and use of energy supply plants, infrastructures and sector coupling technologies (e.g. electrolysers or heat pumps) to cover given energy demands. Demands can be taken from the energy demand model (WISEE-EDM) or can be specified externally (e.g. from existing energy scenarios).
Scenario integration and modification tool0WISEE - Global Steel is an Excel and R based scenario development tool for the global steel industry. It supports the development and analysis of Paris-compatible pathways and new value-chains of the global steel industry that may emerge from future trade of directly reduced iron (DRI).
Global IAMsTop-down input output model1The WTMBT optimizes the global international trade patterns within a given set of constraints and by considering the comparative advantage as the only production and trade mechanism for one time period.
AppliancesTechno-economic parameters(Buildings)Characteristics of household appliances in buildings of commercial and residential sectors
AviationTechno-economic parameters(Transport)Characteristics of air transport equipment
Bio-energy market/import pricesEnergy price projectionsPrice projections for the bio-energy market
CCS/NETsTechno-economic parameters(Industry)Characteristics of capital stocks required for Carbon Capture and Storage or Net Emission Technologies
CH4, N2OHistorical emissionsMethane and Nitrous oxide
CHPTechno-economic parameters(Industry)Characteristics of capital stocks for Combined Heat and Power (CHP) generation. CHP is the use of a heat engine to generate electricity and useful heat at the same time.
CO2Historical emissionsCarbon dioxide
Coal market/import pricesEnergy price projectionsPrice projections for the coal market
Commercial building demandDemand driversAmount of resources consumed by buildings in the commercial sector
CoolingTechno-economic parameters(Buildings)Characteristics of equipment to cool spaces in buildings of commercial and residential sectors
Discount rateMacroeconomicRate used to give a present value to costs and benefits occuring at a later date
Education levelDemographyAverage stage of education achieved by a specific portion of the population
Electricity generationTechno-economic parameters(Energy industry)
Characteristics of capital stocks for electricity generation
EmploymentMacroeconomicProportion of a country's population that is employed
Freight transport demandDemand driversDemand for freight transport services
Gas market/import pricesEnergy price projectionsPrice projections for the gas market
GDP/total incomeMacroeconomicTotal monetary or market value of all the finished goods and services produced within a country's borders
Heat generationTechno-economic parameters(Energy industry)
Characteristics of capital stocks for heat generation
HeatingTechno-economic parameters(Buildings)Characteristics of equipment to heat spaces in buildings of commercial and residential sectors
Household sizeDemographyBuilding floorspace in commercial and residential sectors
Hydrogen productionTechno-economic parameters(Energy industry)
Characteristics of capital stocks for hydrogen production. Hydrogen fuel is a zero-emission fuel burned with oxygen
Industrial goodsDemand driversAmount of products manufactured by the industry sector
Interest rateMacroeconomicThe proportion of a loan that is charged as interest to the borrower, expressed as an annual percentage of the loan
Land use change emissionsLand use change emissionsEmissions and removals of greenhouse gases resulting from direct human-induced land use such as settlements and commercial uses, land-use change, and forestry activities
Machine drivesTechno-economic parameters(Industry)Characteristics of capital stocks used for machine drives in industrial processes
Oil market/import pricesEnergy price projectionsPrice projections for the oil market
Passenger transport demandDemand driversDemand for passenger transport services
PopulationDemographyTotal number of people living in the specific country or region
Process heatTechno-economic parameters(Industry)Characteristics of capital stocks used for process heat in industrial processes
RailTechno-economic parameters(Transport)Characteristics of rail transport equipment
Real households incomeMacroeconomicTotal household income minus taxes
Renewable enegy potentialRenewable enegy potentialMaximal potential or supply curve for the production of wind, solar, hydro or geothermal power
Residential Building demandDemand driversAmount of resources consumed by buildings in the residential sector
Road: heavy dutyTechno-economic parameters(Transport)Characteristics of transport vehicles heavier than a specific threshold
Road: light dutyTechno-economic parameters(Transport)Characteristics of transport vehicles lighter than a specific threshold
Sectoral energy mixSectoral energy mixGroup of different primary energy sources from wich secondary energy or final service is produced in a sector
Sectoral value addedMacroeconomicValue of goods and services produced in the sector
SteamTechno-economic parameters(Industry)Characteristics of capital stocks used for steam generation in industrial processes
StorageTechno-economic parameters(Energy industry)
Characteristics of capital stocks for energy storage
Synthetic fuel productionTechno-economic parameters(Energy industry)
Characteristics of capital stocks for synthetic fuel production. Synthetic fuel is a liquid or gaseous fuel, obtained from gasification of solid feedstocks such as coal or biomass or by reforming of natural gas.
UrbanisationDemographyTotal number of people living in urban areas
The I2AM PARIS platform
has been developed within the framework of the PARIS REINFORCE
project, which has received funding from the European Union’s Horizon 2020 Research and Innovation
Programme under grant agreement No. 820846.
The platform is further
supported by the H2020 projects
NDC ASPECTS and
ENCLUDE and the Horizon Europe projects
IAM COMPACT and
DIAMOND, under grant agreements No. 101003866, 101022791, 101056306, and 101081179 respectively.
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is for information purposes only. The European Commission and CINEA do not accept responsibility for any
use made of the information contained therein.