Archive of PROMETHEUS, version: 1.0

Reference card - PROMETHEUS

The reference card is a clearly defined description of model features. The numerous options have been organized into a limited amount of default and model specific (non default) options. In addition some features are described by a short clarifying text.

Legend:

not implemented
implemented
implemented (not default option)

About

Name and version

PROMETHEUS 1.0

Model link

https://e3modelling.com/modelling-tools/prometheus/

Institution

E3Modelling (E3M), Greece, https://e3modelling.com/modelling-tools.

Documentation

PROMETHEUS documentation consists of a referencecard and detailed model documentation

Process state

under review

Model scope and methods

Model documentation: Model scope and methods - PROMETHEUS

Model type

Integrated assessment model
Energy system model
CGE
CBA-integrated assessment model

Geographical scope

Global
Regional

Objective

PROMETHEUS is a global energy system model covering in detail the complex interactions between energy demand, supply and energy prices at the regional and global 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

Solution concept

Partial equilibrium (price elastic demand)
Partial equilibrium (fixed demand)
General equilibrium (closed economy)

Solution horizon

Recursive dynamic (myopic)
Intertemporal optimization (foresight)

Solution method

Simulation
Optimization

Anticipation

Energy system simulation.Foresight is included only is some sub-modules (i.e. electricity generation)

Temporal dimension

Base year:2000, time steps:1, horizon: 2100

Spatial dimension

Number of regions:10

China
India
North America
OECD Pacific
EU-28
Middle East and North Africa
CIS
Emerging Economies
Rest of the world

Time discounting type

Discount rate exogenous
Discount rate endogenous

Policies

Emission tax
Emission pricing
Cap and trade
Fuel taxes
Fuel subsidies
Feed-in-tariff
Portfolio standard
Capacity targets
Emission standards
Energy efficiency standards
Agricultural producer subsidies
Agricultural consumer subsidies
Land protection
Pricing carbon stocks

Socio-economic drivers

Model documentation: Socio-economic drivers - PROMETHEUS

Population

Yes (exogenous)
Yes (endogenous)

Population age structure

Yes (exogenous)
Yes (endogenous)

Education level

Yes (exogenous)
Yes (endogenous)

Urbanization rate

Yes (exogenous)
Yes (endogenous)

GDP

Yes (exogenous)
Yes (endogenous)

Income distribution

Yes (exogenous)
Yes (endogenous)

Employment rate

Yes (exogenous)
Yes (endogenous)

Labor productivity

Yes (exogenous)
Yes (endogenous)

Total factor productivity

Yes (exogenous)
Yes (endogenous)

Autonomous energy efficiency improvements

Yes (exogenous)
Yes (endogenous)

Macro-economy

Model documentation: Macro-economy - PROMETHEUS

Economic sector

Industry

Yes (physical)
Yes (economic)
Yes (physical & economic)

Energy

Yes (physical)
Yes (economic)
Yes (physical & economic)

Transportation

Yes (physical)
Yes (economic)
Yes (physical & economic)

Residential and commercial

Yes (physical)
Yes (economic)
Yes (physical & economic)

Agriculture

Yes (physical)
Yes (economic)
Yes (physical & economic)

Forestry

Yes (physical)
Yes (economic)
Yes (physical & economic)

Macro-economy

Trade

Coal
Oil
Gas
Uranium
Electricity
Bioenergy crops
Food crops
Capital
Emissions permits
Non-energy goods

Cost measures

GDP loss
Welfare loss
Consumption loss
Area under MAC
Energy system cost mark-up

Categorization by group

Income
Urban - rural
Technology adoption
Age
Gender
Education level
Household size

Institutional and political factors

Early retirement of capital allowed
Interest rates differentiated by country/region
Regional risk factors included
Technology costs differentiated by country/region
Technological change differentiated by country/region
Behavioural change differentiated by country/region
Constraints on cross country financial transfers

Resource use

Coal

Yes (fixed)
Yes (supply curve)
Yes (process model)

Conventional Oil

Yes (fixed)
Yes (supply curve)
Yes (process model)

Unconventional Oil

Yes (fixed)
Yes (supply curve)
Yes (process model)

Conventional Gas

Yes (fixed)
Yes (supply curve)
Yes (process model)

Unconventional Gas

Yes (fixed)
Yes (supply curve)
Yes (process model)

Uranium

Yes (fixed)
Yes (supply curve)
Yes (process model)

Bioenergy

Yes (fixed)
Yes (supply curve)
Yes (process model)

Water

Yes (fixed)
Yes (supply curve)
Yes (process model)

Raw Materials

Yes (fixed)
Yes (supply curve)
Yes (process model)

Land

Yes (fixed)
Yes (supply curve)
Yes (process model)

Technological change

Energy conversion technologies

No technological change
Exogenous technological change
Endogenous technological change

Energy End-use

No technological change
Exogenous technological change
Endogenous technological change

Material Use

No technological change
Exogenous technological change
Endogenous technological change

Agriculture (tc)

No technological change
Exogenous technological change
Endogenous technological change

Energy

Model documentation: Energy - PROMETHEUS

Energy technology substitution

Energy technology choice

No discrete technology choices
Logit choice model
Production function
Linear choice (lowest cost)
Lowest cost with adjustment penalties

Energy technology substitutability

Mostly high substitutability
Mostly low substitutability
Mixed high and low substitutability

Energy technology deployment

Expansion and decline constraints
System integration constraints

Energy

Electricity technologies

Coal w/o CCS
Coal w/ CCS
Gas w/o CCS
Gas w/ CCS
Oil w/o CCS
Oil w/ CCS
Bioenergy w/o CCS
Bioenergy w/ CCS
Geothermal power
Nuclear power
Solar power
Solar power-central PV
Solar power-distributed PV
Solar power-CSP
Wind power
Wind power-onshore
Wind power-offshore
Hydroelectric power
Ocean power

Hydrogen production

Coal to hydrogen w/o CCS
Coal to hydrogen w/ CCS
Natural gas to hydrogen w/o CCS
Natural gas to hydrogen w/ CCS
Oil to hydrogen w/o CCS
Oil to hydrogen w/ CCS
Biomass to hydrogen w/o CCS
Biomass to hydrogen w/ CCS
Nuclear thermochemical hydrogen
Solar thermochemical hydrogen
Electrolysis

Refined liquids

Coal to liquids w/o CCS
Coal to liquids w/ CCS
Gas to liquids w/o CCS
Gas to liquids w/ CCS
Bioliquids w/o CCS
Bioliquids w/ CCS
Oil refining

Refined gases

Coal to gas w/o CCS
Coal to gas w/ CCS
Oil to gas w/o CCS
Oil to gas w/ CCS
Biomass to gas w/o CCS
Biomass to gas w/ CCS

Heat generation

Coal heat
Natural gas heat
Oil heat
Biomass heat
Geothermal heat
Solarthermal heat
CHP (coupled heat and power)

Grid Infra Structure

Electricity

Yes (aggregate)
Yes (spatially explicit)

Gas

Yes (aggregate)
Yes (spatially explicit)

Heat

Yes (aggregate)
Yes (spatially explicit)

CO2

Yes (aggregate)
Yes (spatially explicit)

Hydrogen

Yes (aggregate)
Yes (spatially explicit)

Energy end-use technologies

Passenger transportation

Passenger trains
Buses
Light Duty Vehicles (LDVs)
Electric LDVs
Hydrogen LDVs
Hybrid LDVs
Gasoline LDVs
Diesel LDVs
Passenger aircrafts

Freight transportation

Freight trains
Heavy duty vehicles
Freight aircrafts
Freight ships

Industry

Steel production
Aluminium production
Cement production
Petrochemical production
Paper production
Plastics production
Pulp production

Residential and commercial

Space heating
Space cooling
Cooking
Refrigeration
Washing
Lighting

Land-use

Model documentation: Land-use - PROMETHEUS

Land cover

Cropland
Cropland irrigated
Cropland food crops
Cropland feed crops
Cropland energy crops
Forest
Managed forest
Natural forest
Pasture
Shrubland
Built-up area

Agriculture and forestry demands

Agriculture food
Agriculture food crops
Agriculture food livestock
Agriculture feed
Agriculture feed crops
Agriculture feed livestock
Agriculture non-food
Agriculture non-food crops
Agriculture non-food livestock
Agriculture bioenergy
Agriculture residues
Forest industrial roundwood
Forest fuelwood
Forest residues

Agricultural commodities

Wheat
Rice
Other coarse grains
Oilseeds
Sugar crops
Ruminant meat
Non-ruminant meat and eggs
Dairy products

Emission, climate and impacts

Model documentation: Emissions - PROMETHEUS, Climate - PROMETHEUS, Non-climate sustainability dimension - PROMETHEUS

Greenhouse gases

CO2 fossil fuels
CO2 cement
CO2 land use
CH4 energy
CH4 land use
CH4 other
N2O energy
N2O land use
N2O other
CFCs
HFCs
SF6
PFCs

Pollutants

CO energy
CO land use
CO other
NOx energy
NOx land use
NOx other
VOC energy
VOC land use
VOC other
SO2 energy
SO2 land use
SO2 other
BC energy
BC land use
BC other
OC energy
OC land use
OC other
NH3 energy
NH3 land use
NH3 other

Climate indicators

Concentration: CO2
Concentration: CH4
Concentration: N2O
Concentration: Kyoto gases
Radiative forcing: CO2
Radiative forcing: CH4
Radiative forcing: N2O
Radiative forcing: F-gases
Radiative forcing: Kyoto gases
Radiative forcing: aerosols
Radiative forcing: land albedo
Radiative forcing: AN3A
Radiative forcing: total
Temperature change
Sea level rise
Ocean acidification

Carbon dioxide removal

Bioenergy with CCS
Reforestation
Afforestation
Soil carbon enhancement
Direct air capture
Enhanced weathering

Climate change impacts

Agriculture
Energy supply
Energy demand
Economic output
Built capital
Inequality

Co-Linkages

Energy security: Fossil fuel imports & exports (region)
Energy access: Household energy consumption
Air pollution & health: Source-based aerosol emissions
Air pollution & health: Health impacts of air Pollution
Food access
Water availability
Biodiversity

Model Documentation - PROMETHEUS

The PROMETHEUS model provides detailed projections of energy demand, supply, power generation mix, energy-related carbon emissions, energy prices and investment to the future covering the global energy system. PROMETHEUS is a fully fledged energy demand and supply simulation model aiming at addressing energy system analysis, energy price projections, power generation planning and climate change mitigation policies. PROMETHEUS contains relations and/or exogenous variables for all the main quantities, which are of interest in the context of general energy systems analysis. These include demographic and economic activity indicators, primary and final energy consumption by main fuel, fuel resources and prices, CO2 emissions, greenhouse gases concentrations and technology dynamics (for power generation, road transport, hydrogen production and industrial and residential end-use technologies).

PROMETHEUS quantifies CO2 emissions and incorporates environmentally oriented emission abatement technologies (like RES, electric vehicles, CCS, energy efficiency) and policy instruments. The latter include both market based instruments such as cap and trade systems with differential application per region and sector specific policies and measures focusing on specific carbon emitting activities. Key characteristics of the model, that are particularly pertinent for performing the analysis of the implications of alternative climate abatement scenarios, include world supply/demand resolution for determining the prices of internationally traded fuels and technology dynamics mechanisms for simulating spill-over effects for technological improvements (increased uptake of a new technology in one part of the world leads to improvements through learning by experience which eventually benefits the energy systems in other parts of the World).

PROMETHEUS is designed to provide medium and long term energy system projections and system restructuring up to 2050, both in the demand and the supply sides. The model produces analytical quantitative results in the form of detailed energy balances in the period 2015 to 2050 annually. The model can support impact assessment of specific energy and environment policies and measures, applied at regional and global level, including price signals, such as taxation, subsidies, technology and energy efficiency promoting policies, RES supporting policies, environmental policies and technology standards.

PROMETHEUS is a self-contained large-scale world energy demand and supply model consisting of a large set of equations describing the time evolution of key variables, which are of interest in the context of a general analysis of the energy-environment-economic system. The model can be used either in its deterministic or in its stochastic mode. Equations in PROMETHEUS represent the model’s endogenous variables as a function of other endogenous variables, exogenous variables, parameters and residual terms. PROMETHEUS incorporates a recursive dynamic (partial equilibrium energy system) model with annual resolution currently serviced to run up to the year 2050 (the process to extend model horizon to 2100 is ongoing). The PROMETHEUS model has a triangular structure in order to avoid contemporaneous simultaneity. On the other hand, simultaneity is modelled through lagged instances of endogenous variables. Most of the model equations are specified in difference terms in order to avoid excessive early variability and adequately represent accumulation of uncertainty in the longer term.

The model simulates both demand and supply of energy, interacting with each other to form market equilibrium at different regional scales: detailed regional balances are aggregated in order to simulate world energy markets. Apart from international fuel prices, regional energy systems influence each other particularly through trade, technical progress and network effects including changing patterns of consumption and spillover effects with regard to technology diffusion.

The geographical representation is based on the importance of countries in energy consumption and GHG emissions. PROMETHEUS describes full energy and emissions balances for 10 geographical units, in particular for: China, India, North America (USA and Canada), OECD Pacific (Japan, S. Korea, Australia, New Zealand), EU-28, CIS (Russian Federation and other Commonwealth of Independent States), MENA (Middle East and North Africa), EMRG (Emerging economies) and RESTW (Rest of the world). The model runs with a 1 year time step, usually from 2018 to 2050, the 2015-2018 period being almost entirely set by data and used for calibration. The model horizon will be expanded to 2100.

PROMETHEUS model is organized in sub-models (modules), each one representing the behaviour of a representative agent, a demander and/or a supplier of energy. The figure below presents a simplified summary flow chart of the PROMETHEUS model. The main modules are:

1) The demographic and economic activity module, which projects population and activity growth for each region.

2) The fossil fuel supply module that includes oil and gas resources, while coal is assumed to have abundant supplies relative to production prospects at least for the projection time horizon

3) The biomass supply module, which contains technical and economic potential for biomass per region and their effects on biomass costs.

4) The cost-supply curves for renewable energy sources (RES) module.

5) The fuel prices module projecting both international and final consumer prices, with the latter being differentiated for each demand sector. Global fossil fuel prices are determined from the equilibrium of demand and supply of each fuel at the global level.

6) The final energy demand module, projecting energy demand and fuel mix in three main sectors; industry, transport and residential/services/agriculture sector. The following energy forms are considered as options in the final demand sectors: natural gas, oil, coal, biofuels, electricity, steam and hydrogen. The private passenger cars sector is modelled in detail, by distinguishing the following types of passenger cars: internal combustion engine cars (using gasoline, diesel, biofuels or hydrogen as a fuel), conventional and plug-in hybrids, electric cars and fuel-cell cars (using hydrogen or gasoline as a fuel).

7) The electricity generation module, identifying 26 power generation technologies and their competition to cover electricity demand for base, medium and peak load.

8) The hydrogen production sub-model, identifying 18 hydrogen production options

9)The hydrogen storage and delivery module, including 16 different technological options in order to represent in detail the development of hydrogen infrastructure.

10) The technology dynamics module, which endogenises technical progress through both learning by research and learning by experience (“learning by doing”) mechanisms.

12) The technology diffusion module incorporating network effects accelerating spillovers between regions in cases where technology uptake attains critical levels

PROMETHEUS modules

1) Model scope and methods - PROMETHEUS

The PROMETHEUS model provides detailed projections of energy demand, supply, power generation mix, energy-related carbon emissions, energy prices and investment to the future covering the global energy system. PROMETHEUS is a fully fledged energy demand and supply simulation model aiming at addressing energy system analysis, energy price projections, power generation planning and climate change mitigation policies. PROMETHEUS contains relations and/or exogenous variables for all the main quantities, which are of interest in the context of general energy systems analysis. These include demographic and economic activity indicators, primary and final energy consumption by main fuel, fuel resources and prices, CO2 emissions, greenhouse gases concentrations and technology dynamics (for power generation, road transport, hydrogen production and industrial and residential end-use technologies).

PROMETHEUS quantifies CO2 emissions and incorporates environmentally oriented emission abatement technologies (including renewable energy, electric vehicles, Carbon Capture and Storage, energy efficiency, electrification, green hydrogen, advanced biofuels) and energy and climate policy instruments. The latter include both market based instruments such as cap and trade systems with differential application per region and sector specific policies and measures focusing on specific carbon emitting activities. Key characteristics of the model, that are particularly pertinent for performing the analysis of the implications of alternative climate abatement scenarios, include world supply/demand resolution for determining the prices of internationally traded fuels and technology dynamics mechanisms for simulating spill-over effects for technological improvements (increased uptake of a new technology in one part of the world leads to improvements through learning by experience which eventually benefits the energy systems in other parts of the World). PROMETHEUS is designed to provide medium and long term energy system projections and system restructuring up to 2050 (and 2100), both in the energy demand and the supply sides. The model produces analytical quantitative results in the form of detailed energy balances in the period 2015 to 2050 annually (to be expanded to 2100). The model can support impact assessment of specific energy and environment policies and measures, applied at regional and global level, including price signals, such as taxation, subsidies, technology and energy efficiency promoting policies, RES supporting policies, environmental policies and technology standards.

The PROMETHEUS model is organized in sub-models (modules), each one representing the behaviour of a representative agent, a demander and/or a supplier of energy. The figure below presents a simplified summary flow chart of the PROMETHEUS model. The main modules are:

1) The demographic and economic activity module, which projects population and activity growth for each region.

2) The fossil fuel supply module that includes oil and gas resources, while coal is assumed to have abundant supplies relative to production prospects at least for the projection time horizon

3) The biomass supply module, which contains technical and economic potential for biomass per region and their effects on biomass costs.

4) The cost-supply curves for renewable energy sources (RES) module.

5) The fuel prices module projecting both international and final consumer prices, with the latter being differentiated for each demand sector. Global fossil fuel prices are determined from the equilibrium of fuel demand and supply at the global level.

6) The final energy demand module, projecting energy demand and fuel mix in three main sectors; industry, transport and residential/services/agriculture sector. The following energy forms are considered as options in the final demand sectors: natural gas, oil, coal, biofuels, electricity, steam and hydrogen. The private passenger cars sector is modelled in detail, by distinguishing the following types of passenger cars: internal combustion engine cars (using gasoline, diesel, biofuels or hydrogen as a fuel), conventional and plug-in hybrids, electric cars and fuel-cell cars (using hydrogen or gasoline as a fuel).

7) The electricity generation module, identifying 26 power generation technologies and their competition to cover electricity demand for base, medium and peak load.

8) The hydrogen production sub-model, identifying 18 hydrogen production options

9)The hydrogen storage and delivery module, including 16 different technological options in order to represent in detail the development of hydrogen infrastructure.

10) The technology dynamics module, which endogenises technical progress through both learning by research and learning by experience (“learning by doing”) mechanisms.

11) The technology diffusion module incorporating network effects accelerating spillovers between regions in cases where technology uptake attains critical levels

PROMETHEUS flow chart

1.1) Model concept, solver and details - PROMETHEUS

PROMETHEUS is a recursive dynamic energy system simulation model. Variables are either calculated directly or are calculated based on the previous years' values, to which are applied the evolution of explanatory variables and other exogenous parameters.

The economic decisions regarding the investment and operation of the energy system are based on the current state of knowledge of parameters (costs and performance of technologies, prices, ...) or with a myopic anticipation of future costs and constraints.

The model does not use foresight but myopic anticipation. Some foresight can be forced in the electricity production sector.

The model is developed on the EVIEWS software.

1.3) Temporal dimension - PROMETHEUS

The model runs with a 1 year time step, usually from 2000 to 2050, the 2000-2018 period being almost entirely set by data and used for calibration. The model is currently expanded to 2100.

1.4) Spatial dimension - PROMETHEUS

PROMETHEUS describes full energy system and CO2 emissions balances for 10 geographical regions covering the World, including:

EU28 Member States (slpit into the new Member States that entered the Union after 2004, and the previous 15 EU Member States) +Norway and Switzerland
China
India
North America (USA and Canada)
Western Pacific (Japan, S. Korea. Australia, New Zealand)
Commonwealth of Independent States (e.g. the Former Soviet Union excluding the Baltic Republics)
Middle East and North Africa: the Middle East (from the Mediterranean to the Iranian border with Afghanistan and Pakistan) and North Africa (Egypt, Libya, Tunisia , Algeria, Morocco)
Emerging Economies: Including all other countries that had more than 4000 ($11) PPPs per capita in 2005. Broadly speaking this region includes Turkey, almost the whole of Latin America, Southeast Asia (excluding Indonesia and Indochina) and Southern Africa.
Rest of world: All other countries, mostly in Africa and South East Asia

Fossil fuel production and renewable energies potentials (wind, solar, biomass) follow the geographical representation of the energy balances.

The international air and maritime bunkers are represented separately.

Energy demand and related emissiosn at World level is the sum of all regions and bunkers.

1.5) Policy - PROMETHEUS

The PROMETHEUS model is used to simulate the implications of various energy and climate policy instruments, including:

GHG policies
- Regional emission reduction objective: Implementation of carbon pricing schemes
- Cumulated CO2 buget: Regional differentiation of emission constraints and carbon pricing to reduce emissions within budget (iterative calculation)
Energy pricing policies
- Carbon pricing (either carbon taxation in ETS sectors or carbon values non-ETS sectors)
- other environmental taxes (e.g. introduction of taxes on fossil fuel production and/or consumption or environmental tax on non-conventional fuels production)
- Subsidies to renewable energy, electric cars and energy efficiency
- fossil fuel subsidies (including the possibility to phase out)
Support policies for specific technologies
- Electricity generation feed-in tariffs (especially for renewable energy technologies)
- Acceleration of deployment of low-emission vehicles (e.g. through direct subsidies or low interest loans)
- Low interest loans or subsidies to capital cost to purchase energy appliances and equipment or to perform energy retrofitting
Efficiency standards
- fuel efficiency standards in vehicles and in buildings
- penetration of low-energy consuming buildings
Openness to investment, especially in low-carbon technologies
- Discount rates in low-carbon technology investment
- Lower discount rates (subsidies to capital) for low-carbon and energy efficient technologies

The PROMETHEUS model calculates several indicators that can be used to inform energy and climate policy impact assessment at regional or global level. These include:

Energy Demand

Energy intensity of GDP (primary and final energy)
Energy intensity per unit of value added in industry
Energy intensity of households’ income
Energy intensity per inhabitant
Energy intensity per passenger car
Electricity consumption per capita in residential sector
Electricity generated per capita
Transport fuels per capita
Performance against overall energy efficiency targets (primary energy and final energy)
Number of passenger cars per capita

Renewables

Overall share of RES in primary energy demand
Share of RES in total power generation
Share of bio-fuels in fuels used in the transport sector

Power sector

Share of renewable energy in power generation
Share of electricity produced by CCS
Share of intermittent RES in power generation
Share of nuclear in power generation
Power generation per capita
Average load factor of power generation
Average rate of use of power plant capacities (by type)

Security of Energy Supply

Overall energy dependence indicator in each region
Evolution of import fossil fuel prices for the EU
Developments of global fossil fuel markets for oil, natural gas and coal
Share of unconventional oil (extra heavy oil and tar sands) in global oil supply
Share of Middle East production in global oil production and reserves
Development of unconventional gas resources (shale, tight and CBM)

Emissions

Carbon intensity of GDP
Carbon intensity of households
Carbon intensity of the transport sector
Carbon emissions per capita
Carbon intensity of power generation
Share of emissions captured in power generation
Carbon intensity per unit of final energy in industry/transport/buildings
Carbon intensity per unit of primary energy

Costs and Prices

Prices for internationally traded fossil fuels (coal, oil and natural gas)
Electricity prices for industries and households (for all regions)
Unit costs of electricity production
Investments in the power generation sector and in energy efficiency
Consumer expenditures on final energy
Carbon prices

2) Socio-economic drivers - PROMETHEUS

The two main socio-economic drivers, population and GDP, are exogenous in PROMETHEUS.

The key marco-economic assumptions are derived from population and GDP projections.

Starting from historical data, sectoral economic activity variables are calculated (capturing regional differentiation):

sectoral value added by sector (industries, services, agriculture): depends on the level of development of the region, given by GDP per capita (industrialization phase followed by service-based economy);
industrial physical production: depends on the evolution of sectoral value added, which depends on the level of development;
mobility (for passengers and for goods): depends on the evolution of GDP per capita and transport activity (measured in terms of passenger-km/cars per capita or tonne-km) as well as the average cost of transport compared to income
buildings surfaces: depend on households size and surface per dwelling, both depending on personal income.

2.1) Population - PROMETHEUS

Population is an exogenous driver in PROMETHEUS. The model distinguishes only one population group.

Population projections by region are derived from the latest EC Ageing Report (for EU countries) and from the UN World Population Prospects, medium fertility scenario (for non-EU countries).

Alternative assumptions for population developments can be used to simulate different futures/ scenarios (e.g. including the Shared Socio-economic Pathways)

2.2) Economic activity - PROMETHEUS

GDP is exogenous in PROMETHEUS and is derived from various international sources, including:

latest IMF forecasts (for the short run)
EU Ageing Report (for EU countries)
IEA and OECD forecasts (for non-EU countries in the longer term)

The consistency of GDP assumptions with population is checked for each region, in terms of robust development of GDP per capital indicator.

PROMETHEUS can also use the macro-economic projections of the CGE model GEM-E3 for the specific regions, while it can also incorporate different GDP projections (as those described in the Shared Socioeconomic Pathways)

All other economic activities variables (industrial value added, mobility, incomes, cars per capita) are endogenously calculated in PROMETHEUS, as a function of historic development patterns and the future development of GDP per capital and energy costs in various sectors.

4) Energy - PROMETHEUS

PROMETHEUS describes the world energy system, covering all energy carriers and their trade across regions.

The model includes the following modules:

Energy supply: production and international trade of fossil fuels (coal, oil, natural gas)
Energy transformation: electricity production, refining of fuels, production of synthetic fuels (e.g. liquid biofuels, hydrogen)
Final energy demand: industry, buildings, transport, agriculture

PROMETHEUS produces Excel reports containing detailed energy demand and supply balances for each region identified in the model up to 2050 (the extension of model horizon to 2100 is ongoing). The projection figures come from the various PROMETHEUS modules. The focus of the model lies in the detailed representation of energy consumption dynamics (by sector and by energy carrier) combined with power generation sector which is modelled in great detail with explicit representation of distinct technologies, load duration curve patterns and a mechanism to calculate utilization of each plant in each time segment (power plant dispatching).

Scenario results based on the PROMETHEUS model include:

Energy demand by sector and energy product
Primary production of fossil fuels
Net imports of energy (fossil fuels, biomass and electricity)
Detailed power generation mix by technology
Energy supply by energy carrier
Projection of energy system costs and fossil fuel prices
Evolution of electricity prices in each region
Energy system investments in demand and supply sectors
Calculation of CO2 energy related emissions by sector and by fuel
Energy, economy and emissions indicators
System performance against energy and climate objectives (e.g. emission reduction, renewable energy penetration, energy efficiency improvements)

4.1) Energy resource endowments - PROMETHEUS

In PROMETHEUS model, energy supply is linked to energy consumption via trade across the ten regions identified in the model:

Oil: all oil producers export to single global market "pool", identifying one global market for crude oil
Gas: trade and price dynamics are modelled focusing on core regional gas markets (e.g. Europe, the USA, Asia/Japan, LNG). The gas markets are modelled to capture rents and other mark-up costs to reflect different formulations of the gas market, ranging from long-term contracts (Japan), to gas-to-gas competiton (USA) and their combination (Europe). Import gas prices in each region depend on the evolution of international gas price and the cost of gas extraction and transport from the most important producing regions (mark-up cost).
Coal: trade and price dynamics are modelled focusing on three core markets (e.g. Europe, China, Asia)
Biofuels and biomass: regional-specific cost-supply curves
Uranium: single global supply cost curve
Renewable electricity (hydro, solar, wind): country-specific renewables potentials for power generation to cover domestic electricity demand

4.1.1) Fossil energy resources - PROMETHEUS

The PROMETHEUS model differentiates various types of fossil fuels:

oil: conventional, tar, heavy and oil shale, deepwater;
gas: conventional, shale gas, tight gas, coalbed methane;
coal: one generic type is identified.

The uncertainty surrounding the evolution of oil and gas resources and reserves is one of the most crucial drivers of the world energy system. Conventional and non-conventional oil are distinguished in PROMETHEUS analysis. The former are differentiated between Gulf and non-Gulf oil, while the latter are distinguished between Venezuela’s extra heavy oil, Canada’s tar sands and light tight oil. The uncertainty that surrounds the amount of oil and natural gas that is yet to be discovered has been incorporated into PROMETHEUS. Using studies conducted by USGS, comprehensive analysis has been carried out in order to obtain robust estimates for the yet to be discovered oil and gas conventional resources (endowments) at the starting year of the simulation procedure.

The rate of discovery as well as the rate of recovery of petroleum are endogenous in the model, they are both positively correlated with the international oil price and are subject to their own specific uncertainties. Gross additions to reserves of conventional oil are a function of the yet to be discovered oil in each region, the international oil price and world oil production, while the recovery rates of unconventional oil sources are pricedependent and act as a “backstop” preventing the persistence of very high oil prices. Gross additions to conventional gas reserves are a function of the yet to be discovered natural gas and the gross additions to oil reserves, as the exploration for conventional oil increases the likelihood of gas discoveries. In addition to conventional gas, unconventional gas (shale, tight and coal bed methane) is considered in the PROMETHEUS model, the resource base of which and the uncertainty surrounding it, is derived from a variety of assessments.

Oil and gas reserves are supplemented by reserve growth arising from known deposits following assessments by USGS. Apart from statistical dependence arising from geological factors, exploration and extraction technologies, hydrocarbon reserves are also linked through their dependence on the relevant prices which are incorporated in the equations. Oil production in the Gulf is influenced by the (lagged) reserves to production ratio in the Middle East and the world oil demand, while oil production capacity in the Middle East is driven by petroleum demand but it is also subject to random disruptions, whose variance is determined using historical data. Conventional oil production in the Rest of the world is driven by the world demand, the international oil price and reserves of this region.

Non-conventional oil production is driven by world oil demand, the international oil price and the R/P (reserves to production) ratio of conventional oil. When the international oil price exceeds a threshold, the production from non-conventional oil sources increases substantially, as more and more non-conventional deposits become economically recoverable. Besides the statistical dependence due to geological factors and due to hydrocarbon exploration and extraction technologies, fossil fuel reserves are also correlated through the statistical dependence of their prices. International fossil fuel prices (for oil, natural gas and coal) are endogenous in PROMETHEUS; this is a distinctive feature of the model, as energy price development is a crucial factor determining the future evolution of the global energy system. On the other hand, global hydrocarbon prices are exogenous in several energy-economy models. The deterministic version of PROMETHEUS has been extensively used by the European Commission (e.g. EU Reference scenario 2016, Energy trends to 2050, EU Energy Roadmap 2050) to provide aquantitative assessment for fuel import prices in EU under alternative scenario assumptions.

PROMETHEUS enables an integrated assessment of the global energy system with international prices influenced by global energy demand for fossil fuels, energy and climate policies, hydrocarbon reserves and resources (both conventional and unconventional), production capacity and probability of disruption of hydrocarbon production in the Middle East and the assumed extraction costs for different hydrocarbon resources.

International fuel prices (for oil, natural gas and coal) are endogenous in PROMETHEUS. The international oil price is driven by the complex dynamics of energy supply and demand and depends on the oil production to capacity ration in the Middle East and on the global Reserves to Production ratio. International gas prices depend on the evolution of the global oil price (oil price indexing) and on the reserves to production ratio of gas in different regions.

Import gas prices in each region depend on the evolution of international gas price and the cost of gas extraction and transport from the most important producing regions (mark-up cost). The importance of Reserve to Productio ratios in the oil and gas price equations is a clear reflection of the oligopolistic nature of themarkets for the respective fuels. At any rate, the equations have been estimated econometrically over periods when cartel power has been much in evidence and rents and other oligopolistic mark-ups are captured in all equation parameters including constants. The latter can be varied in order to reflect different formulations of the fossil fuel market and especially different structures in the gas market ranging from oil price indexing with long-term contracts (as in Japan) to gas-to-gas competition (in the USA) and their combinations (as in the EU and other emerging markets).

The international price of coal is driven by the coal demand and supply dynamics at the regional and global levels and is also partly linked to the international oil price, as it is usually observed in international markets mainly due to oil price indexing and coal transportation costs influenced by global oil price.

PROMETHEUS demand-supply interactions

4.1.2) Uranium and other fissile resources - PROMETHEUS

Uranium resources used in LWRs are represented at World level only, based on data from IAEA. The uranium price is derived from a global cost supply curve, constrained by the amount of remaining resources.

4.1.3) Bioenergy - PROMETHEUS

The biomass supply module of PROMETHEUS includes detailed estimates of technical and economic potential for biomass per region and their effects on biomass costs.

Primary biomass resources for energy uses are modelled through region-specific cost-supply curves.

The conversion into liquid biofuels distinguishes first generation (agricultural energy crops) and second generation (cellulosic).

4.1.4) Non-biomass renewables - PROMETHEUS

The potential for various renewable energy sources is represented by nonlinear cost-supply curves distinguished by type of source (wind onshore, photovoltaics, solar thermal, wind offshore, hydro and biomass).

In particular:

Hydro resources are defined for all regions. They constrain the development of hydro power (which depends on average power production costs and already implemented investment).
Solar resources are defined as the maximum amount of solar energy that can harvested for the energy system in terms of technical and economic potential. The resource is then used in the energy system depending on the economic conditions, considering network constraints.
Wind resources: The model distinguishes between total resource and technical potential that is considered as harvestable, based on prevailing market conditions (economic potential). It fully distinguishes between onshore and offshore wind resources.Total wind resources (technical potential) come from NREL estimates. This potential is then used in the energy system depending on the economic conditions, considering network constraints.

4.2) Energy conversion - PROMETHEUS

The model distinguishes the following energy conversion processes:

Electricity production: detailed representation of investment and operation of the electricity system, including power generation capacities and production by technology
Gaseous fuels: natural gas, hydrogen production
Liquid fuels: crude oil refineries; liquid fuels production from coal, gas and solid biomass

4.2.1) Electricity - PROMETHEUS

PROMETHEUS incorporates a detailed module for the representation of the investment and operation of the power sector. Total electricity generation is determined by electricity demand for the industrial, residential and transportation sectors, own-consumption of power plants and transmission and distribution losses in each region identified in the model. Electricity trade between regions is exogenous in the model.

PROMETHEUS is equipped with an enhanced portfolio of power generation technologies that compete to satisfy electricity requirements. The power sector model includes the following technologies: coal-firing, lignite-firing, open cycle oil, open cycle gas, gas turbines, Gas combined cycle (CCGT), nuclear, CCS-coal, CCS-gas, biomass-firing, CCS-biomass, wind onshore, hydro (large and small), solar photovoltaic, wind offshore, concentrated solar power (CSP) and others. The option of solar thermal power station combining solar power with natural gas is also included in the model.

Plant scrapping (normal and premature) and competition of alternative technologies in new capacity installations follow the pattern of the substitution mechanism. PROMETHEUS also accounts for already decided investments in specific power plants and the firmly adopted plans for decommissioning of old and inefficient ones in each region, as obtained from a wide literature review.

New generation capacity in each region is determined by the evolution of electricity demand in the various sectors, scrapping of power plants, firmly adopted plans for decommissioning of old and inefficient plants, the already decided investments in specific power plants for the period until 2015 (especially for nuclear and RES) and the security of supply margin. The allocation of new investments in power generation technologies is determined by the overall cost of the competing options, which includes capital, fixed and variable O&M and fuel costs as well as additional costs for integrating intermittent RES in the power grid or additional costs for capture and storage of CO2 for CCS technologies. The utilisation of the capacity of power plants for each time segment (dispatching of power plants) is endogenous in the model and is determined by the annual load duration curve in combination with variable O&M and fuel costs and the installed capacities of the different technologies.

The model associates a demand fluctuating profile to every use of electricity included in the demand sector modules (industry, transport, households). Regional load profiles change over time and in scenarios, depending on the relative shares of various electricity uses, the prices (which are higher for sectors with low load factors), the degree of energy savings (and the use of more efficient equipment) and special demand side management measures including smart metering, which in the transport sector are supposed to motivate battery recharging at off peak hours. When load profiles become smoother, capital intensive power technologies are favoured (like RES and nuclear) and reserve power requirements are lower, implying lower overall costs. Consumer prices of electricity are derived based on wholesale market prices, grid tariffs, subsidization of electricity prices and taxation including carbon emission pricing. Targets for renewables, penetration of natural gas and CO2 emissions are reflected in the model influencing both dispatching of plants and the choices in investment decision making. All economic/choice modeling (e.g. investment choice, fuel switching, dispatching) in PROMETHEUS reflects the financial perspective of power plant project developers and includes all costs, subsidies and taxes as well as other financial incentives that directly affect investment decisions. These financial instrument can potentially include feed-in tariffs, RES promoting policies, fuel standards, strategy for cleaner electricity dispatch and risk premiums differentiated by technology. The potential for RES is represented by nonlinear cost-supply curves distinguished by type of source (wind onshore, photovoltaics, solar thermal, wind offshore, hydro and biomass).

Electricity prices are determined by the long term average generation costs and are calculated separately for the final electricity demand sectors (industry and domestic sectors). Differences in electricity prices between sectors mostly arise from the fact that different technologies supply different segments of the load duration curve and from differential distribution and grid costs. The electricity prices in PROMETHEUS are calculated in order to recuperate all costs, including capital and operating costs, costs related to schemes supporting renewables, grid costs and supply costs. The power sector model simulates a wholesale market subject to technical plant operation constraints and reserve requirements, represents dispatching of power plants and can simulate investment in new power plants. The market bidding of power plants aims at recovering fixed and capital costs. Power grids are implicitly represented as capital assets evolving based on investment, which in turn depends on demand evolution and the penetration of variable decentralized RES sources (that increase grid requirements and hence grid costs).

Investment in RES based electricity is dominated by the consideration of capital costs. On the other hand such technologies are generally characterised by limitations as to their potential. In most cases this is taken into account by incorporating reductions in availability as such potentials are approached (i.e. the most suitable sites being exploited earlier and less suitable ones increasingly sought). This effectively results in a supply curve where costs increase non-linearly with the gradual exhaustion of potential. The cost-supply curve implies that additional RES deployment is accompanied by a reduction in availability and hence increase in RES costs for electricity production due to the depletion of suitable sites, the difficulty of getting access to resource and grid connection difficulties. In establishing such curves, a wide range of bibliography is used. The modelling also simulates the site retaining factor, i.e. the cost incentive to install a new renewable power plant in the same place where an old one existed.

PROMETHEUS can take into account support for RES technologies in each of the ten regions identified in the model by assuming different levels of feed-in tariff and other supporting schemes for renewables in the alternative scenarios simulated. The main RES facilitation policies that can be simulated with the PROMETHEUS model include subsidies for RES technologies, feed-in tariffs and obligation/target for specific RES deployment. In constructing the supply curves for biomass, a number of studies were taken into account which include technical and economic assessment of biomass potential. However, their estimates vary significantly, implying high uncertainty regarding biomass economic potential. Such uncertainty is introduced explicitly in the specification of the biomass cost equations, according to which the deployment of biomass technologies is constrained by limited land and waste energy resource availability. Driven by emission reduction targets or by carbon pricing, CCS competes with other emissions reduction options, such as carbon free power generation (renewable energy, nuclear), the fuel switching towards low emitting forms and the reduction of energy consumption. The power plants that are equipped with CCS are more expensive in terms of capital and O&M costs and have lower net thermal efficiency compared to similar plants without carbon capture. Non-linear cost-supply curves are simulated for underground storage of carbon dioxide. Public acceptance issues can be modelled through parameters lowering CCS potential and making the technology more expensive.

Nuclear deployment depends on the evolution electricity demand, load profiles, economic features of competing technologies and carbon prices (and other energy and climate policies assumed in each of the ten regions identified in the model). The unit cost of investment depends on the nuclear technology: nuclear PWR and fourth generation technologies are represented in the model. The unit cost of investment take into account costs for future decommissioning (15% provision). Variable and fuel costs of nuclear power take into account waste recycling and disposal costs. Nuclear costs have been revised upwards following the Fukushima accident. Due to the long construction times for new nuclear power plants, the increasing public acceptability concerns and the difficulty to licence and build new nuclear plants, the development of nuclear power is calibrated until 2025 taking into account the already decided investments and the firmly adopted plans for decommissioning of nuclear power plants in each region identified in the model. The building of a power generation plant usually requires several years (especially with regard to nuclear and hydro technologies). This has important implications for cost evaluation of alternative technologies that influence power system planning and choice of plant type. The model considers the financial costs associated with the construction period of each power generation technology, which can be significant in the case of nuclear power plants.

4.2.2) Heat - PROMETHEUS

PROMETHEUS represents the steam produced by Combined Heat and Power (CHP) cogeneration plants and steam-only plants, the inputs of which are accounted for within the "own use" of the energy sector. The production of steam is not simulated explicitly.

4.2.3) Gaseous fuels - PROMETHEUS

Natural gas domestic production and imports directly supply gas for consumption, either for use in power plants or in final energy consumption (industries, buildings, transport).

Hydrogen

PROMETHEUS includes a detailed module to represent hydrogen production, transport, storage and use in various sectors: transport (fuel cells or thermal use), but also in stationary uses in industry and buildings (fuel cells or blending with natural gas). PROMETHEUS includes various hydrogen (H2) production options, which compete for the centralised production of hydrogen. Investments in hydrogen-supply technologies are based on the production cost of each technology. In each year, the model determines the required new investments, by taking into account both normal and pre-mature scrapping rates of technologies, and then calculates their shares in new investments (using a quasi cost-minimising Weibull function similar to the one used in the power generation module) . These H2 production technologies include the currently most promising options towards decarbonisation: water electrolysis, gas steam reforming (with or without CCS), but also other innovative solutions including biomass gasification (with or without CCS), nuclear or solar high-temperature thermochemical cycles. On the demand side, hydrogen is introduced in the competitive market of distributed electricity production (through stationary fuel cells) and in the road transport sector. The hydrogen and electricity systems are connected and interact within the overall energy system in two points: in the hydrogen production through the electricity price in grid electrolysis and in the demand side through the competition between the decentralized fuel cell electricity production and the electricity from grid and the competition between electric and fuel cell private cars. The major end uses of hydrogen in PROMETHEUS are for vehicle propulsion and for production of steam or heat and electricity. Two kinds of vehicle propulsion engines that use hydrogen are included in PROMETHEUS: fuel cells and internal combustion engines. The fuel cell engine is further differentiated into stack and system components. Moreover, the stacks and systems themselves are varying depending on the fuel used in the fuel cell cars (hydrogen or gasoline). On the other hand, the internal combustion engines technically are not different from the internal combustion engines that are used today in oil-powered vehicles.

For automotive on-board hydrogen storage, two options are included in the model: hydrogen in liquid form and hydrogen in gaseous form. These two options compete in the model, since each of them needs its own specific infrastructure to support it. On-board gasoline reformers are also included in PROMETHEUS, in order to allow for on-board hydrogen production. These reformers are used in the fuel cell vehicles, bypassing in this way the need for hydrogen distribution infrastructure. In total, the hydrogen related technologies incorporated in PROMETHEUS for mobile applications are two types of fuel cell stacks, two types of fuel cell systems, two types of on board hydrogen storage, one type of on-board reformer and a hydrogen IC engine. The above components result in eight different hydrogen related technologies in road transport. These components are combined together to define five vehicle types in the model:

Fuel cell cars powered with liquid hydrogen
Fuel cell cars powered with gaseous hydrogen
Fuel cell cars with on-board reformer powered with gasoline
Internal combustion engine cars fuelled with liquid hydrogen
Internal combustion engine cars fuelled with gaseous hydrogen

The hydrogen powered cars compete with the rest of the car types included in the model (conventional, hybrid, plug-in hybrid and electric cars) in order to gain share in the market. The decision is based on the total cost per vehicle kilometre of each car type, which includes the costs to purchase car, the operation and maintenance cost and the cost to purchase fuels.

In PROMETHEUS hydrogen is also used for the combined production of heat and electricity. The fuel cell CHP plants are distinguished according to their size and the fuel that they use. Small scale stationary fuel cell CHP plants (1- 5Kw) are directly linked with low voltage grid (small scale applications), while fuel cell CHP plants of a size of up to 300KW are used for the combined production of low enthalpy steam and electricity in the industrial sectors (medium voltage). Regarding the fuel that they use, two types are considered, one which is fuelled directly with hydrogen and one that uses natural gas and onsite steam reforming. For a more accurate characterisation of the fuel cell CHP plants, the fuel cell stacks, the fuel cell systems and the onsite reformers are defined individually.

In total, six hydrogen related technologies are considered for stationary applications in the residential/commercial and industrial sectors:

Fuel cell stacks and fuel cell systems for small scale CHP
Fuel cell stacks and fuel cell systems for large scale CHP
Onsite natural gas reformers

The eventual development of hydrogen economy must be accompanied by the development of an extensive hydrogen storage and delivery infrastructure system. A great number of configurations of such infrastructure are possible. The PROMETHEUS technology database contains several options for liquid and gaseous hydrogen storage and distribution (pipelines, trucks, service stations) providing flexibility in the choice of the components of a future hydrogen infrastructure system as a result of the work performed in the common information base of the EU-funded CASCADE MINTS project. However, complete modelling of the hydrogen storage and distribution system is a very complex task, since it is a “chicken-egg” problem; it is not possible to have infrastructure developments without demand and vice-versa. Network effects, which are implicitly modelled, play a crucial role in development of such infrastructure. Therefore, a vision is needed about the future development of hydrogen infrastructure system, in which its main components will be identified and fully characterised in terms of their technical and economic performance.

The stylized configuration of PROMETHEUS refers to an “average” region supplied with hydrogen during a “take-off” period for hydrogen and contains a plant connected to a turnpike pipeline, which is used as storage medium, load management tool and emergency supply in cases of production disruption. The turnpike pipeline crosses the region and is connected with similar turnpike pipelines in neighbouring regions. Moreover, other pipelines of smaller capacity connect the plant with the urban and industrial areas (high-demand areas) of the region. The model identifies two kinds of service stations: rural stations along the roads crossing the region and urban service stations mostly concentrated on the outside ring of the urban area. It can be reasonably assumed that all rural stations will be supplied by trucks carrying gaseous or liquid hydrogen. On site hydrogen production and distribution facilities can be built where demand is high enough (i.e. near urban cities). Hydrogen can be stored either in gaseous or in liquid form. PROMETHEUS also incorporates competition between gaseous or liquid storage options and between pipelines and trucks. The detailed hydrogen infrastructure system of PROMETHEUS is described in figure below

Hydrogen representation in PROMETHEUS

4.2.4) Liquid fuels - PROMETHEUS

Oil products

Crude oil production is transformed into oil products based on a refineries efficiency, differentiated by region. The refined oil products can then be used in final energy consumption sectors (transport, industry, buildings) and in power plants

Biomass to Liquid

The PROMETHEUS model differentiates 4 biomass-to-liquids production technologies (1st and 2nd generation bioethanol and biodiesel), each described by costs, technical efficiency and use of feedstock type:

The use of the different liquid biofuels is restricted by blending constraints (with oil products) in the various sectors.

Coal to Liquid

The Coal-to-liquid production (Fischer Tropsch) is described by one generic technology (cost and efficiency) to which a CCS module can be added.

Gas to Liquid Similarly to CTL process, the gas-to-liquids production is described by one generic technology (cost and efficiency) to which a CCS module can be added.

The development of GTL depends on the distance between production cost and the oil price.

4.2.5) Solid fuels - PROMETHEUS

Coal primary supply (imported or domestically produced) is directly fed to consumption, both to final energy consumption (industries, buildings) and to power generation plants.

Biomass

Biomass primary supply (imported or domestically produced; in energy units) is directly fed to consumption, both to final energy consumption (industries, buildings) and to power generation plants.

Solid biomass can be used to produce liquid biofuels or electricity in energy transformation; or in direct combustion in final demand.

4.2.6) Grid, pipelines and other infrastructure - PROMETHEUS

PROMETHEUS model represents gas and electricity grids implicitly, in particular through the energy transportation and distribution costs, which depend on the provision of infrastructure (e.g. electricity interconnectors, gas pipelines, LNG)

Own use of the energy sector

Fossil fuel extraction

PROMETHEUS describes own energy use related to fossil fuel extraction is through one single factor, expressed by fuel as a % of the energy production, differentiated by fuel type (conventional oil, tar sands, extra heavy oil, coal, lignite, conventional gas, shale gas, tight gas and coalbed methane).The future development of these factors follows the historical patterns.

Refineries

The energy use in the refining sector is captured through a coefficient, expressed as a % of the demand for oil product, which can be kept constant in the future or implement some energy efficiency improvements.

Others

Other own-energy uses are captured through a coefficient, expressed by fuel as a % of primary energy demand.

Losses in Transport & Distribution

Grids and pipelines are not modelled explicitly. Pipelines are captured through transport costs as compared to other trade routes.

Losses in T&D are expressed by fuel as a % of final energy use, and can be kept constant at the last historical value or adjusted depending on the scenario (for instance to capture a decrease in electricity losses through improvements in grids, ..).

4.3) Energy end-use - PROMETHEUS

In PROMETHEUS, useful energy demand (services from energy such as temperature in a house, lighting, industrial production, passenger-km etc.) is determined at a level of a sector/subsector. Demand for energy services is assumed to be a function of macroeconomic drivers (GDP, population, household income, industrial activity) and the average costs of meeting energy services based on econometrically estimated elasticities. Energy demand is modelled in terms of useful energy services (such as heating, electric appliances, mobility, industrial steam) and in terms of final energy commodities, ensuring energy balance between useful and final energies at all times.

Energy end-use is distinguished in demand for:

industrial sectors;
buildings (residential, services and agriculture);
transport (road, rail, water, air);
Demand for non-energy uses

4.3.1) Transport - PROMETHEUS

The transport sector is one of the most important energy related GHG emitters, while the emission reduction options in this sector are rather limited, especially in specific models like aviation and freight transport. A detailed representation of the transport sector allowing projection of activity, final energy consumption, technology deployment and carbon dioxide emissions to the future and policy and impact analysis is thus very important. The PROMETHEUS transport module projects to the future (up to 2050 and 2100) the road transport sector for each region identified in the model. The module projects the evolution of passenger car stocks and demand for transport, based on economic and technology choices of transportation; PROMETHEUS also projects the derived fuel consumption (diesel, gasoline, natural gas, biofuels, electricity and hydrogen) and CO2 emissions from fuel combustion.

The PROMETHEUS model is equipped with a detailed bottom-up mechanism to project the evolution of passenger car stock in each region, which depends on exogenous socio-economic projections (population and GDP growth) and on the average cost of passenger transportation (depending on the evolution of prices for trannsport fuels). The formulation used in PROMETHEUS can also capture changes in consumption patterns (when a developing region reaches income levels typical for a developed one) and the possible saturation effects in developed regions (in case that passenger vehicles per inhabitant reach a certain high threshold).

The private passenger cars sector is modelled in great detail in PROMETHEUS model, by distinguishing thirteen types of passenger cars (figure below):

Internal combustion engine cars, using gasoline, diesel, hydrogen (liquid or gaseous) or bio-fuels
Hybrid cars (conventional hybrids, plug-in hybrids, hybrids using biofuels, plug-in hybrids using bio-fuels)
Battery electric cars
Fuel cell cars, using hydrogen (gaseous or liquid) or gasoline (with onboard reformer).

The road transport module projects transport activity, in terms of car ownership per capita, car utilisation rates, and the penetration of new car types in the market. The model first determines the total car stock that is necessary to satisfy the increased transport activity, by using equations depending on GDP growth and average fuel price for road transport. PROMETHEUS then calculates the new registrations required to meet the increased demand by taking into account the scrapping of the cars reaching the end of their lifetime.

Short term, long term and very long term effects on road transport activity are thoroughly modelled, in order to project transport activity in a realistic manner. Very long term equations are estimated using a pool of developed countries that have already reached or they are approaching saturation levels. Transitions from one specification to another are modelled using weights.

Market penetration of road passenger transport technologies is not predefined but is a result of the model depending on economics of alternative car options and behaviour of private consumers. The share of each car type in new registrations is determined by its total cost per km (that includes capital, fixed O&M, variable O&M and fuel costs) and maturity factors through a Weibull specification (already described in the “Energy demand section). Fuel consumption (gasoline, diesel, bio-fuels, electricity or hydrogen) is then calculated using efficiencies, which are determined endogenously by the two factor learning curves module, and average mileages (endogenously derived based on vehicle utilisation rates). Infrastructure and social network effects are modelled and play a crucial role, especially for the penetration of new low-carbon technologies, like electric and fuel cell cars. Improvements in energy efficiency also impact final energy consumption in the road transport sector. Reduction in energy intensity of road transport activity can be a result of increases in fuel prices, technological choices (e.g. hybrid vehicles substituting for gasoline internal combustion cars), reduction in the utilisation rates of vehicles as motorisation increases, changes in consumption patterns, technological improvements and imposition of energy efficiency (or CO2) standards.

The rest sub-sectors of transport (including aviation, rail transport and inland navigation) are modelled in PROMETHEUS, albeit in a more aggregate manner relative to the road passenger sector. The model incorporates equations for the calculation of final energy consumption for non-road transport activity, which is assumed to be influenced by GDP growth, trade dynamics and average fuel price. The main technologies that compete to satisfy non-road transport demand are oil products (diesel, gasoline, heavy fuel oil and kerosene for aviation) and biofuels, as there are only limited opportunities for electricity and hydrogen to penetrate in the non-road transport sector. Competition between technologies to cover non-road transport demand occurs in terms of shares in new demand and heavily depends on the relative competitiveness of oil products with biofuels. GTL (Gas-to-Liquids) and CTL (Coal-to-Liquids) technologies are also modelled in PROMETHEUS to cover both road and non-road transport demand, while recently the model has been expanded to cover clean synthetic fuels.

Marine bunkers are treated separately at the world level, due to the fact that CO2 emissions from international marine and aviation bunkers are not included in climate policy targets of specific regions/countries, as described in national climate poliies and in Nationally Determined Contributions (NDCs). Oil products dominate in final energy demand for marine bunkers, but the model also includes biofuels and clean synthetic fuels as an alternative to petroleum products.

Transport modelling in PROMETHEUS

4.3.2) Residential and commercial sectors - PROMETHEUS

The residential sector in PROMETHEUS includes households, services and agricultural sectors. In the residential sector, energy is consumed as input in processes that provide services to the households, such as space heating, water heating, cooking, cooling, specific electricity uses, lighting and other needs. The model distinguishes ⁡between ⁡residential⁡ sector’s demand for specific electric uses (e.g. electric appliances for non-heating purposes, air-conditioning, lighting, electronic equipment etc.) and useful energy demand for space and water heating. Demand for non-substitutable electricity is driven by growth in economic activity and disposable income of households and residential electricity price, while useful energy demand for heating purposes is related to income growth and the evolution of fuel prices.

Residential and tertiary consumers decide about the level of energy consumption taking into account their need for heating, which is further related to changes in income and fuel prices. Different iso-elastic demand equations are estimated for each type of residential sector’s demand and for each region. As the pattern of energy consumption is not usually controlled directly by the consumer, but is determined by the installed technology and is largely embodied in the characteristics of the durable equipment, responses to price shifts and environmental policies usually involve long lags. Changes in consumption patterns for developing regions are also modelled through a gradual convergence procedure to developed countries’ consumption patterns.

The competition between technologies to cover energy demand for space and water heating is modelled using the substitution specification, based on the notion of "gap" (as described in previous sections) and the competition of technologies to satisfy new energy requirements, based on their total production costs (including capital, operation and maintenance, carbon and fuel costs) and in other non-market factors, like technology maturity, mimetism, TRL levels, information, uncertainty etc. The model differentiates between “cold” and “warm” regions based on their climatic conditions, as in the latter (India, Emerging economies, the Middle East and North Africa and the Rest of the World region) energy demand for space heating is relatively insignificant, i.e. energy demand for water heating dominates. The evolution of useful energy demand is also assumed to depend on income levels, costs for energy services, consumer behaviour and regional climatic characteristics.

Energy demand for heating purposes is covered by natural gas, oil, coal, electric resistances, fuel cells (using hydrogen or natural gas as a fuel) and heat-pumps. Substitution between fuels and technologies is triggered by their total production cost, which includes capital, fixed O&M, variable O&M and fuel cost, their transformation efficiency, the scrapping rates of their equipment and their relative “technology maturity” factors. Technological trends, infrastructure and social network effects are assumed to influence technologies’ maturities, especially for fuel cells and heat-pumps, are incorporated in the decision mechanism, in order to represent in a realistic way the consumption patterns, the evolution of technology and fuel mix and the rigidities involved in the decision mechanism.

Energy performance of buildings largely depends on the characteristics of the dwelling (thermal integrity) and the technology of the equipment which uses energy. Individual energy consumers can spend money to improve energy efficiency and select solutions with upfront costs and utilisation performance leading to reasonable pay-back periods (e.g. deep retrofitting strategies in buildings). Energy efficiency progress implies high upfront cost but saves on variable and energy purchase costs during the lifetime of the energy equipment.

Energy meets fundamental needs of households. In developed economies (like North America, OECD Western Pacific and the EU) income elasticity is expected to be less than one, while in developing regions income elasticity can exceed one. Econometrics are used to estimate such elasticity value in all PROMETHEUS regions.

4.3.3) Industrial sector - PROMETHEUS

The industry is represented in PROMETHEUS through different sectors and processes. The general modeling describes energy requirements per sector dependent on an activity variable and energy prices. Total demand of energy depends on the developments of activity variables (e.g. industrial production or value added) and energy prices.

PROMETHEUS models separately industrial demand for electric and nonelectric uses in each region. The model can also distinguish between energy intensive and non-energy intensive industrial ones depending on data availability. The evolution of industrial demand for electricity is assumed to be a function of electricity prices for industry and industrial value added in each region (that is exogenously specified using the GEM-E3 model). Demand for industrial electricity is covered by the electricity grid or combined heat and power (CHP) facilities or, finally, by fuel cells that use hydrogen. The gap in supply is calculated (with the substitution mechanism to be described below) and the ensuing competition between the above options determines their shares in electricity demand for industries. The total non-electric energy demand for industrial processes requiring steam and heat is determined by industry value-added⁡ and⁡ the average cost to provide energy services to industries, which is defined as the weighted average of fuel prices (coal, oil, gas, CHP, fuel cells) for industry consumers (using their shares in non-electric industrial energy demand of the previous year as weights). Coal, natural gas and oil together with CHP facilities and fuel cells (that can use hydrogen or natural gas) compete for gaining shares in the demand-supply gap for industrial non-electric uses. The inclusion of CHP and fuel cells in the set of competing technologies for non-electric uses is based on the rationale that their utilization for electricity production results in the co-production of a certain amount of heat which is subtracted from the gap for non-electric uses.

Industrial energy demand in PROMETHEUS is modelled in terms of useful energy services (such as industrial processes, heating, steam) and in terms of final energy commodities, ensuring energy balance between useful and final energies at all times. Demand for industrial energy services is assumed to be a function of macroeconomic drivers (GDP, industrial activity) and the average costs of meeting energy services based on econometrically estimated elasticities. Central to the energy technology substitution mechanism is the notion of the “gap”, which is defined in terms of the difference between energy demand and the amount of energy that can be satisfied using existing equipment (separately for electric and non-electric uses). The scrapping rate of technology includes normal scrapping, due to plants reaching the end of their lifetimes, and premature scrapping, due to changes in variable and fuel costs which render the continuation of the plant's operation economically unsustainable.Competition between technologies occurs in terms of market shares within the gap (separately for electric and non-electric uses). The allocation of new investments is modelled as a quasi cost-minimizing function (based on the Weibull specification) and is driven by the total cost of the competing options, including capital expenditures, operation & maintenance costs, carbon costs and costs to purchase energy carriers.

Energy efficiency improvement is induced by increases in energy prices, technology/fuel choice at the energy use level and can be also obtained by direct investment on energy savings (e.g. industrial energy management). The saving possibilities are seen as cost-quantity curves which have limited potential and non-linear increasing costs. PROMETHEUS explicitly takes into account fossil fuel subsidies and taxes in the ten regions identified in the model and can simulate changes in end-user prices for individual energy consumers, e.g. removal of fossil fuel subsidies directed to industrial sectors in the Middle East and North Africa (MENA) region. Emission constraints, energy efficiency goals, and regulations/standards are represented in PROMETHEUS and can influence the choice of technology for investment, the choice of final energy products and the overall energy efficiency investment. The accounting of costs (CAPEX, OPEX), and the performances in terms of emissions, renewables and energy efficiency are reported.

The choices of energy use technologies involve a variety of possibilities which differ in upfront investment costs and in variable costs depending on energy performance and efficiency. The scope of the industrial demand submodel of PROMETHEUS is to represent simultaneously:

the mix of technologies and fuels, including the use of CHP and fuel cells
the links to self-supply of energy forms (e.g. cogeneration of electricity and steam);
the explicit representation of energy saving possibilities;
the satisfaction of constraints through emission abatement, pollution permits and/or energy savings, and
Possible substitutions between energy forms, technologies and energy savings

4.3.4) Other end-use - PROMETHEUS

The evolution of energy use of the agriculture and forestry sector depends on the value added of agriculture sector in each PROMETHEUS region.

4.4) Energy demand - PROMETHEUS

In PROMETHEUS energy demand is modelled in terms of useful energy services (such as space and water heating, electric appliances, mobility, industrial steam) and in terms of final energy commodities, ensuring energy balance between useful and final energies at all times. The model follows an econometric top-down approach to estimate overall energy demand by sector. Demand for energy services is assumed to be a function of macroeconomic drivers (GDP, population, household income, industrial activity) and the average costs of meeting energy services based on econometrically estimated elasticities.

Final energy demand in PROMETHEUS comes from three main sectors: industry, domestic (which includes households, services and agriculture) and transport (which includes both various transport models of both freight and passenger transport). Within these broad categories the model identifies subsectors: in industry heat, electricity and non-energy uses of fuels; in the domestic sector demand that is subject to fuel substitution (space and water heating, cooking) and specific electricity demand; in the transport sector road (passenger and freight), air (aviation) and marine bunkers. For each energy demand sector a representative decision making agent is assumed to operate.

In PROMETHEUS useful energy demand (services from energy such as temperature in a house, lighting, industrial production, passenger-km etc.) is determined at a level of a sector/subsector. In the typical useful energy demand equation, the main explanatory variables are activity and income indicators and energy costs.

Energy efficiency investment can be triggered by increased energy prices as well as by dedicated policy measures and investments, i.e. investments in retrofitting and insulation improvement in buildings. Energy efficiency investments reduce demand for energy services addressed to final energy products but the costs are included in the accounting for energy service costs. The choice of energy commodities (gas, electricity, oil products, coal, biomass and other RES) to satisfy demand for energy services depends on the stock of energy conversion equipment which evolves over time driven by investment decisions in each demand sector. The latter are driven by technology progress and relative costs of competing options.

Emission constraints, energy efficiency goals, and regulations/standards are represented in PROMETHEUS and can influence the choice of technology for investment, the choice of final energy products and the overall energy efficiency investment. The accounting of costs (CAPEX, OPEX), and the performances in terms of emissions, renewables and energy efficiency are reported for every energy demand sector. The PROMETHEUS model also considers saturation dynamics in energy consumption that depend on the income of households and the saturation factor exhibits a sigmoid curve which indicates income elasticity of energy above one if useful energy at low levels (developing regions) and elasticity values lower than one (and decreasing) when income and useful energy levels are high (developed regions).

Activity indicators are derived from the demographic and economic activity module of PROMETHEUS which estimates various economic activity indicators (including industrial value added, household disposable income, passenger-km, tonne-km, building floor space, car ownerhip rates) based on the evolution of GDP in each country. The demographic module is relatively simple and it is calibrated to reproduce the latest UN medium fertility variant scenario.

Useful energy requirements at the level of sectors and sub-sectors (e.g. space heating, water heating, specific electricity uses, industrial steam, mobility etc.) have to be met by consumption of final energy carriers. The representative agent in each sector or subsector is formulated to choose among fuels, technologies and energy savings. Final energy demand is met by a number of options characterised by the fuel used and specific technologies. Notable among the latter are: for space heating fossil fuel boilers, electrical options (resistance and heat pumps) and hydrogen fuel cells; for road transport conventional vehicles (using gasoline, diesel, biofuels or hydrogen), hybrids (both stand-alone and plug-in), electric vehicles and fuel-cell powered (with or without reformer).

Energy demand from the various end-uses (industry, buildings, transport) is aggregated into totals that have to be supplied by the energy transformation module, for each energy carrier, including: oil products, natural gas, coal, biofuels (traditional and advanced biofuels), electricity, heat and hydrogen. Total demand of energy depends on the relevant activity variable (industrial production, household income, mobility) and energy costs by sector. Competition across fuels takes place based on the total costs for the user (also considering the lifetime of existing equipment) and is also influenced by technological trends and by policy measures (e.g. energy effiiency standards, carbon pricing etc).

4.5) Technological change in energy - PROMETHEUS

The substitution between different fuels/technological options and technological change in PROMETHEUS is modelled through a mechanism that is similar for both final energy demand and energy supply (power generation and hydrogen production). Central to this mechanism is the notion of the “gap”, which is defined in terms of the difference between energy demand and the amount of energy that can be satisfied using existing equipment from the previous year, which is not scrapped. The overall scrapping rate of each technology includes normal scrapping, due to plants reaching the end of their lifetimes, and premature scrapping, due to changes in variable and fuel costs which render the continuation of the plant's operation economically unsustainable. The inclusion of the latter form of scrapping is important in order to enable the modelling of rapid technical transformation in case of strong climate action or rapidly increasing fossil fuel prices, as the renewal of equipment stock accelerates.

Competition between technologies to cover energy demand in each sector occurs in terms of market shares within the gap. The allocation of new investments is modelled as a quasi cost-minimizing function (based on the Weibul specification) and is driven by the total cost of the competing options, which includes the discounted and annualised capital costs, fixed and variable Operating and Maintenance costs, carbon costs and costs to purchase the required energy carriers. Technology diffusion therefore depends both on economic considerations (e.g. the relative costs and competitiveness of alternative technological options) but also on various other factors including mimetism, information, trade, infrastructure development, TRL levels, and network effects, which are captured by the "maturity" parameters,reflecting⁡ the ⁡relative⁡“maturity” ⁡factor⁡ of⁡ each⁡ technology in terms of readiness of consumers to adopt them.

Traditional technology dynamics has long recognised the importance of learning by experience in the improvement of the cost and technical performance of technologies. However, it is also widely accepted that (public and private) R&D can contribute directly to technological improvement and in order to address policy questions concerning the efficacy of R&D, it is clear that R&D must figure explicitly in the technology dynamics specification. The core in the endogenous technological change modelling adopted in PROMETHEUS is the two factors learning curve (TFLC) specification and the endogenisation of the technical progress through both learning by research and learning by experience. Under this scheme, an R&D action leads directly to technological improvement, which in turn enhances competitiveness of a particular option and leads to increased technology take-up. This latter increase sets in motion learning by experience, which results in further technological improvement, further up-take etc. In this sense, learning by doing acts as an accelerator of the impact of initial R&D effects. Clearly, the cycle is characterised by dampening effects that result in finite overall impacts. This dampening notwithstanding, the inclusion of such mechanisms in the model does tend to introduce elements of instability, in particular “lock-in” effects –massive R&D funding on some technological options may lockout other options that fail to benefit from the learning by experience they could have enjoyed, had such initial R&D infusion not taken place. There is sufficient evidence that this scheme is an accurate representation of the way technical progress has occurred in the past. PROMETHEUS also incorporates the notion of technical potential (floor costs), as they emerge from perspective technological analysis.

Taking into account the fact that technological change is a process characterized by fundamental uncertainty, critical parameters for the effects of R&D effort, technology adoption and cost efficiency are explicitly modelled enabling the quantification of the variance and covariance associated with the adoption of particular technologies. The parameters of the two factor learning curves in PROMETHEUS are jointly distributed random variables and they covary. The PROMETHEUS outlook also incorporates modelling of the size and direction of R&D, which are endogenous to the model. By analysing historical observations of R&D on energy technologies and utilizing perspective analysis, relations have been established, linking R&D to economic factors and particularly measures of energy cost.

PROMETHEUS augments the traditional TFLC specification (i.e. technology costs depend on the accumulated technology production/capacity and on cumulative R&D expenditire) by incorporating clustering effects, which are essential in cases of a rapid energy system transformation.The idea is that technological progress in a specific direction enhances cost efficiency of similar technologies, to a degree which depends on the “proximity” of the corresponding technologies. A technology cluster is a group of technologies that share a common component. A technology can belong to different clusters when it is composed of different components, e.g. a natural gas combined cycle is part of the gas turbine, recovery boiler and steam turbine clusters. The common component is assumed to be the learning technology and each component has its own learning curve specifications. Technical progress leads to the improvement of different cost components, i.e. capital, fixed O&M and variable O&M cost and technical efficiency. Thus learning parameters have been estimated for each of the above components. The improvement in different cost components leads to a reduction of the overall cost of the technology and hence to increased competitiveness, in particular for low-carbon technologies (that are currently immature and have a high innovation and deployment potential).

In PROMETHEUS technology dynamics for 51 technological options for electricity production, hydrogen production/storage/delivery and passenger cars were estimated. These include:

Capital costs parameters for 44 technological options
Fixed O&M costs for 34 technologies; although they are basically labour costs, technical progress has been assumed based on the increased automation, reliability and the economies of scale
Variable cost parameters for 12 technologies, adjusted for efficiency.
Efficiency parameters for 20 technologies

Technology dynamics representation in PROMETHEUS

5) Land-use - PROMETHEUS

Land use (and associated emissions) are not included in PROMETHEUS

5.1) Agriculture - PROMETHEUS

5.2) Forestry - PROMETHEUS

5.3) Land-use change - PROMETHEUS

5.4) Bioenergy land-use - PROMETHEUS

5.5) Other land-use - PROMETHEUS

5.6) Agricultural demand - PROMETHEUS

5.7) Technological change in land-use - PROMETHEUS

6) Emissions - PROMETHEUS

The PROMETHEUS model estimates in detail carbon dioxide emissions, as emerging from fossil fuel combustion and industrial processes.

The model directly covers all emissions from the energy sector and the industry sector and can split CO2 emissions by sector (transport, industry, buildings, power generation, refineries, international bunkers, other) and by fuel (coal, oil, natural gas).

6.1) GHGs - PROMETHEUS

The PROMETHEUS model estimates in detail carbon dioxide emissions, as emerging from fossil fuel combustion and industrial processes.

The model directly covers all emissions from the energy sector and the industry sector and can split CO2 emissions by sector (transport, industry, buildings, power generation, refineries, international bunkers, other) and by fuel (coal, oil, natural gas). The model is currently expanded to represent non-CO2 GHG emissions (including CH₄, N₂O and F-gases) through specific marginal abatement cost curves per region and sector.

Energy and climate policies affect these emissions: energy CO₂ is derived from the changes in the energy sector induced by the policy, other emissions are affected by marginal abatement cost curves.

The model has been used extensively to study climate change mitigation scenarios, see References section for more examples.

6.2) Pollutants and non-GHG forcing agents - PROMETHEUS

The PROMETHEUS model does not include air pollutants and non-GHG forcing agents.

6.3) Carbon dioxide removal (CDR) options - PROMETHEUS

The following carbon dioxide removal options are modelled in PROMETHEUS:

CCS in power generation: used in power plants with coal, gas, biomass
CCS in hydrogen production: used in hydrogen production plants with coal, gas, biomass
CCS in industry: with combustion of coal, biomass
Direct Air Capture

For a recent discussion on CDR options and strategies in PROMETHEUS, please see (Fragkos, 2020) in Energy Technology Journal: Global Energy System Transformations to 1.5 degrees C: The Impact of Revised Intergovernmental Panel on Climate Change Carbon Budgets

Category:

7) Climate - PROMETHEUS

The model produces annual carbon dioxide emissions from energy combustion and indsustrial processes.

The climate effects are calculated thanks to the MAGICC diagnostics toolbox using model outputs.

The model does not assess the impacts of climate change on energy use and comfort in the residential sector.

7.1) Modelling of climate indicators - PROMETHEUS

7.2) Climate damages, temperature changes - PROMETHEUS

8) Non-climate sustainability dimension - PROMETHEUS

Currently, the PROMETHEUS model does not incorporate non-climate sustainability dimensions.

Ongoing work is implemented to add a representation of the water sector in the model. In particular, water use associated with the production of electricity will be modelled. Specific water use indicators are associated with each power generation technology and PROMETHEUS will provide projections of water needs based on installed capacities per technology and per region.

8.1) Air pollution and health - PROMETHEUS

8.2) Water - PROMETHEUS

8.3) Other materials - PROMETHEUS

8.4) Other sustainability dimensions - PROMETHEUS

9) Appendices - PROMETHEUS

9.1) Mathematical model description - PROMETHEUS

9.2) Data - PROMETHEUS

As a global energy-economy-environment model, PROMETHEUS has extensive requirements for data. A wide variety of databases and other sources have been used to provide the required energy, technology and economic data. PROMETHEUS uses energy system and power generation data from international widely-used databases (mainly from the IEA and ENERDATA databases); in particular, data for final energy demand by sector and fuel, primary production by energy form, input and output from energy transformation processes, electricity demand, power generation mix and energy imports and exports. Detailed data for power plant stations are also collected from the Enerdata Power Plant Tracker or from the Platts World Electric Power Plants database

Energy prices by fuel and type of consumer are collected from ENERDATA and IEA databases (final consumer prices, import prices, spot prices). Data for global and EU import fuel prices are gathered from a variety of sources, including DG ENER, IMF and Platts database. CO2 emissions data are collected from the IEA, CDIAC and the WorldBank databases. Hydrocarbon reserves and resources are collected from USGS and BGR databases, while an extensive literature review has been conducted for unconventional hydrocarbon resources and technology learning rates.

Population data and projections are based on UN Population Prospects. Data for economic drivers are derived from the GTAP and World Bank databases.\ Macro-economic projections are usually based on GEM-E3 projections or on IEA WEO estimates combined with IMF projections for the short term. A wide literature review has been conducted to estimate costs for all energy system technologies, which are mainly based on costs derived from the PRIMES database and the TECHPOL database (developed in the context of the FP7 EU-funded ADVANCE project). The PROMETHEUS modelling framework ensures consistency between all data sources used, as data collection and reconciliation constitute important procedures in the overall modelling.

Variable: Data Source

Population: UN Population Prospects
GDP and value added: World Bank database, IMF, IEA, EC Ageing Report
Hydrocarbon reserves and resources: USGS, BGR
Biomass potentials : Moreira
Wind and solar resources: NREL
Energy reserves and production: Enerdata, IEA
Energy demand by sector and fuel: Enerdata, IEA
Energy transformation processes: Enerdata
Power generation by technology:Enerdata
Power generation capacities: Enerdata
Global and consumer energy prices: Enerdata, IEA
CO2 emissions: Enerdata, IEA, EDGAR
Technology costs: WEC, IEA, EC
Car stock: OICA
Import dependence: Enerdata
Policy Assessment indicators: Enerdata, IEA

10) References - PROMETHEUS

PROMETHEUS model documentation, available at: https://e3modelling.com/modelling-tools/prometheus/

P. Fragkos (2020), Global Energy System Transformations to 1.5 degrees C: The Impact of Revised Intergovernmental Panel on Climate Change Carbon Budgets, Energy Technology

A.Marcucci, E. Panos, S. Kypreos, P.Fragkos (2019), Probabilistic assessment of realizing the 1.5° C climate target, Applied Energy, Volume 239, Pages 239-251

P. Fragkos, N. Kouvaritakis (2018), Model-based analysis of Intended Nationally Determined Contributions and 2° C pathways for major economies, Energy, Volume 160, Pages 965-978

P. Fragkos, N. Kouvaritakis (2019), Investments in Power Generation Under Uncertainty—a MIP Specification and Large-Scale Application for EU, Environmental Modeling & Assessment, Volume 23, Issue 5, Pages 511-527

P. Capros, A. De Vita et al (2016), EU Reference Scenario 2016-Energy, transport and GHG emissions Trends to 2050, European Commission Directorate-General for Energy, Directorate-General for Climate Action and Directorate-General for Mobility and Transport

P. Fragkos, N. Kouvaritakis, P. Capros (2015), Incorporating uncertainty into world energy modelling: the PROMETHEUS Model, Environmental Modeling & Assessment, Volume 20, Issue 5, Pages 549-569

P. Capros, A. De Vita., P. Fragkos et al (2015), The impact of hydrocarbon resources and GDP growth assumptions for the evolution of the EU energy system for the medium and long term. Energy Strategy Reviews, Volume 6, Pages 64-79

Snapshot of - PROMETHEUS

Reference card - PROMETHEUS

About

Model scope and methods

Socio-economic drivers

Macro-economy

Energy

Land-use

Emission, climate and impacts

Model Documentation - PROMETHEUS

1) Model scope and methods - PROMETHEUS

1.1) Model concept, solver and details - PROMETHEUS

1.3) Temporal dimension - PROMETHEUS

1.4) Spatial dimension - PROMETHEUS

1.5) Policy - PROMETHEUS

2) Socio-economic drivers - PROMETHEUS

2.1) Population - PROMETHEUS

2.2) Economic activity - PROMETHEUS

4) Energy - PROMETHEUS

4.1) Energy resource endowments - PROMETHEUS

4.1.1) Fossil energy resources - PROMETHEUS

4.1.2) Uranium and other fissile resources - PROMETHEUS

4.1.3) Bioenergy - PROMETHEUS

4.1.4) Non-biomass renewables - PROMETHEUS

4.2) Energy conversion - PROMETHEUS

4.2.1) Electricity - PROMETHEUS

4.2.2) Heat - PROMETHEUS

4.2.3) Gaseous fuels - PROMETHEUS

Hydrogen

4.2.4) Liquid fuels - PROMETHEUS

4.2.5) Solid fuels - PROMETHEUS

Biomass

4.2.6) Grid, pipelines and other infrastructure - PROMETHEUS

Own use of the energy sector

Fossil fuel extraction

Refineries

Others

Losses in Transport & Distribution

4.3) Energy end-use - PROMETHEUS

4.3.1) Transport - PROMETHEUS

4.3.2) Residential and commercial sectors - PROMETHEUS

4.3.3) Industrial sector - PROMETHEUS

4.3.4) Other end-use - PROMETHEUS

4.4) Energy demand - PROMETHEUS

4.5) Technological change in energy - PROMETHEUS

5) Land-use - PROMETHEUS

5.1) Agriculture - PROMETHEUS

5.2) Forestry - PROMETHEUS

5.3) Land-use change - PROMETHEUS

5.4) Bioenergy land-use - PROMETHEUS

5.5) Other land-use - PROMETHEUS

5.6) Agricultural demand - PROMETHEUS

5.7) Technological change in land-use - PROMETHEUS

6) Emissions - PROMETHEUS

6.1) GHGs - PROMETHEUS

6.2) Pollutants and non-GHG forcing agents - PROMETHEUS

6.3) Carbon dioxide removal (CDR) options - PROMETHEUS

7) Climate - PROMETHEUS

7.1) Modelling of climate indicators - PROMETHEUS

7.2) Climate damages, temperature changes - PROMETHEUS

8) Non-climate sustainability dimension - PROMETHEUS

8.1) Air pollution and health - PROMETHEUS

8.2) Water - PROMETHEUS

8.3) Other materials - PROMETHEUS

8.4) Other sustainability dimensions - PROMETHEUS

9) Appendices - PROMETHEUS

9.1) Mathematical model description - PROMETHEUS

9.2) Data - PROMETHEUS

10) References - PROMETHEUS

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