IAMC-Documentation - User contributions [en]

PRIMES

2023-05-10T09:50:36Z

Maria Kannavou:

{{ModelTemplate}}
{{ModelInfoTemplate
|Name=PRIMES
|Version=PRIMES 2022
|ModelLink=https://e3modelling.com/modelling-tools/primes/
|participation=reference card only
|processState=in preparation
}}
{{InstitutionTemplate
|abbr=E3M
|institution=E3Modelling
|link=https://e3modelling.com/
|country=Greece
}}
{{ScopeMethodTemplate
|ModelTypeOption=Energy system model
|GeographicalScopeOption=Regional
|Objective=PRIMES provides detailed projections of energy demand, supply, prices and
investment to the future, covering the entire energy system including
emissions for each individual European country and for Europe-wide trade of
energy commodities.
PRIMES model design is suitable for medium- and long-term energy system
projections and system restructuring up to 2070, both in demand and supply. The model can support an impact assessment of specific energy and
environment policies and measures, applied at the Member State or EU level,
including price signals, such as taxation, subsidies, ETS, technology-promoting
policies, RES-supporting policies, efficiency-promoting policies, environmental
policies and technology standards. PRIMES is sufficiently detailed to represent
concrete policy measures in various sectors, including market design options
for the EU internal electricity and gas markets. Policy analysis draws on
comparing the results of scenarios against a reference projection
|SolutionConceptOption=Partial equilibrium (price elastic demand)
|SolutionConcept=The PRIMES model comprises several sub-models (modules), each one representing the behaviour of a specific (or representative) agent, a demander and/or a supplier of energy. The sub-models link with each other through a model integration algorithm, which determines equilibrium prices in multiple markets and equilibrium volumes meets balancing and overall (e.g. emission) constraints.
|SolutionHorizonOption=Intertemporal optimization (foresight)
|SolutionMethod=Mathematically PRIMES solves an EPEC problem (equilibrium problem with equilibrium constraints) which allows prices to be explicitly determined.
|Anticipation=The PRIMES model is fully dynamic and has options regarding future
anticipation by agents in decision-making. Usually, PRIMES assumes perfect
foresight over a short time horizon for demand sectors and perfect foresight
over a long time horizon for supply sectors. The sub-models solve over the
entire projection period in each cycle of interaction between demand and
supply and so market equilibrium is dynamic and not static. Other options are
available allowing the model user to specify shorter time horizons for
foresight.
|BaseYear=2015
|TimeSteps=5 year
|Horizon=2015 to 2070
|Nr=28
|Region=EU27, UK. Primes has also used for providing projections for the Energy Community Contracting Parties, Turkey, Iceland, Switzerland.
|TimeDiscountingTypeOption=Discount rate exogenous
|PoliciesOption=Emission tax; Emission pricing; Cap and trade; Fuel taxes; Fuel subsidies; Feed-in-tariff; Emission standards; Energy efficiency standards
|Policies=Eco-design standars, Best Available Technology regulations, Energy Performance standards; Emission standards or efficiency standards or CO2 standards on vehicles and other transport means,; Phase-out regarulations, Large Combustion Plant Directive; Additionality rules for the production of renewable hydrogen and synthetic fuels (e-fuels)
}}
{{Socio-economicTemplate
|PopulationOption=Yes (exogenous)
|PopulationAgeStructureOption=Yes (exogenous)
|UrbanizationRateOption=Yes (exogenous)
|GDPOption=Yes (exogenous)
|IncomeDistributionOption=Yes (exogenous)
|EmploymentRateOption=Yes (exogenous)
|AutonomousEnergyEfficiencyImprovementsOption=Yes (endogenous)
}}
{{Macro-economyTemplate
|TradeOption=Electricity; Emissions permits
|CategorizationByGroupOption=Income; Age; Household size
|InstitutionalAndPoliticalFactorsOption=Interest rates differentiated by country/region; Technology costs differentiated by country/region; Technological change differentiated by country/region; Behavioural change differentiated by country/region
|CoalRUOption=Yes (supply curve)
|ConventionalOilRUOption=Yes (supply curve)
|UnconventionalOilRUOption=Yes (supply curve)
|ConventionalGasRUOption=Yes (supply curve)
|UnconventionalGasRUOption=Yes (supply curve)
|UraniumRUOption=Yes (supply curve)
|BioenergyRUOption=Yes (supply curve)
|IndustryESOption=Yes (physical & economic)
|EnergyESOption=Yes (physical & economic)
|TransportationESOption=Yes (physical & economic)
|ResidentialAndCommercialESOption=Yes (physical & economic)
|AgricultureESOption=Yes (economic)
|EnergyConversionTechnologyTCOption=Exogenous technological change
|EnergyEnd-useTCOption=Endogenous technological change
|AgricultureTCOption=Exogenous technological change
}}
{{EnergyTemplate
|EnergyTechnologyChoiceOption=Logit choice model
|EnergyTechnologySubstitutabilityOption=Mixed high and low substitutability
|EnergyTechnologyDeploymentOption=System integration constraints
|ElectricityTechnologyOption=Coal w/o CCS; Coal w/ CCS; Gas w/o CCS; Gas w/ CCS; Oil w/o 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
|HydrogenProductionOption=Electrolysis
|RefinedLiquidsOption=Oil refining
|RefinedGasesOption=Coal to gas w/o CCS; Oil to gas w/o CCS
|HeatGenerationOption=Coal heat; Natural gas heat; Oil heat; Biomass heat; Geothermal heat; Solarthermal heat; CHP (coupled heat and power)
|ElectricityGIOption=Yes (aggregate)
|GasGIOption=Yes (aggregate)
|HeatGIOption=Yes (aggregate)
|CO2GIOption=Yes (aggregate)
|HydrogenGIOption=Yes (aggregate)
|PassengerTransportationOption=Passenger trains; Buses; Light Duty Vehicles (LDVs); Electric LDVs; Hydrogen LDVs; Hybrid LDVs; Gasoline LDVs; Diesel LDVs; Passenger aircrafts
|PassengerTransportation=Private road passenger (cars, powered 2 wheelers), public road passenger (buses and coaches), road freight (HDVs, LDVs), passenger rail (slow and high-speed trains, metro), freight rail, passenger aviation (split into distance classes), freight and passenger inland navigation and short sea shipping, bunkers. Numerous classes of vehicles and transport means with tracking of technology vintages.
|FreightTransportationOption=Freight trains; Heavy duty vehicles; Freight ships
|IndustryOption=Steel production; Aluminium production; Cement production; Petrochemical production; Paper production; Plastics production; Pulp production
|ResidentialAndCommercialOption=Space heating; Space cooling; Cooking; Refrigeration; Washing; Lighting
}}
{{Land-useTemplate}}
{{EmissionClimateTemplate
|GHGOption=CO2 fossil fuels
|PollutantOption=NOx energy; SO2 energy
|ClimateIndicatorOption=Concentration: CO2
|CarbonDioxideRemovalOption=Bioenergy with CCS; Direct air capture
|ClimateChangeImpactsOption=Energy supply; Energy demand
|Co-LinkagesOption=Energy security: Fossil fuel imports & exports (region); Energy access: Household energy consumption; Air pollution & health: Health impacts of air Pollution; Water availability
}}

PRIMES

2023-05-10T05:12:59Z

Maria Kannavou:

{{ModelTemplate}}
{{ModelInfoTemplate}}
{{ScopeMethodTemplate
|ModelTypeOption=Energy system model
|GeographicalScopeOption=Regional
|Objective=PRIMES provides detailed projections of energy demand, supply, prices and
investment to the future, covering the entire energy system including
emissions for each individual European country and for Europe-wide trade of
energy commodities.
PRIMES model design is suitable for medium- and long-term energy system
projections and system restructuring up to 2070, both in demand and supply. The model can support an impact assessment of specific energy and
environment policies and measures, applied at the Member State or EU level,
including price signals, such as taxation, subsidies, ETS, technology-promoting
policies, RES-supporting policies, efficiency-promoting policies, environmental
policies and technology standards. PRIMES is sufficiently detailed to represent
concrete policy measures in various sectors, including market design options
for the EU internal electricity and gas markets. Policy analysis draws on
comparing the results of scenarios against a reference projection
|SolutionConceptOption=Partial equilibrium (price elastic demand)
|SolutionConcept=The PRIMES model comprises several sub-models (modules), each one representing the behaviour of a specific (or representative) agent, a demander and/or a supplier of energy. The sub-models link with each other through a model integration algorithm, which determines equilibrium prices in multiple markets and equilibrium volumes meets balancing and overall (e.g. emission) constraints.
|SolutionHorizonOption=Intertemporal optimization (foresight)
|SolutionMethod=Mathematically PRIMES solves an EPEC problem (equilibrium problem with equilibrium constraints) which allows prices to be explicitly determined.
|Anticipation=The PRIMES model is fully dynamic and has options regarding future
anticipation by agents in decision-making. Usually, PRIMES assumes perfect
foresight over a short time horizon for demand sectors and perfect foresight
over a long time horizon for supply sectors. The sub-models solve over the
entire projection period in each cycle of interaction between demand and
supply and so market equilibrium is dynamic and not static. Other options are
available allowing the model user to specify shorter time horizons for
foresight.
|BaseYear=2015
|TimeSteps=5 year
|Horizon=2015 to 2070
|Nr=28
|Region=EU27, UK. Primes has also used for providing projections for the Energy Community Contracting Parties, Turkey, Iceland, Switzerland.
|TimeDiscountingTypeOption=Discount rate exogenous
|PoliciesOption=Emission tax; Emission pricing; Cap and trade; Fuel taxes; Fuel subsidies; Feed-in-tariff; Emission standards; Energy efficiency standards
|Policies=Eco-design standars, Best Available Technology regulations, Energy Performance standards; Emission standards or efficiency standards or CO2 standards on vehicles and other transport means,; Phase-out regarulations, Large Combustion Plant Directive; Additionality rules for the production of renewable hydrogen and synthetic fuels (e-fuels)
}}
{{Socio-economicTemplate
|PopulationOption=Yes (exogenous)
|PopulationAgeStructureOption=Yes (exogenous)
|UrbanizationRateOption=Yes (exogenous)
|GDPOption=Yes (exogenous)
|IncomeDistributionOption=Yes (exogenous)
|EmploymentRateOption=Yes (exogenous)
|AutonomousEnergyEfficiencyImprovementsOption=Yes (endogenous)
}}
{{Macro-economyTemplate
|TradeOption=Electricity; Emissions permits
|CategorizationByGroupOption=Income; Age; Household size
|InstitutionalAndPoliticalFactorsOption=Interest rates differentiated by country/region; Technology costs differentiated by country/region; Technological change differentiated by country/region; Behavioural change differentiated by country/region
|CoalRUOption=Yes (supply curve)
|ConventionalOilRUOption=Yes (supply curve)
|UnconventionalOilRUOption=Yes (supply curve)
|ConventionalGasRUOption=Yes (supply curve)
|UnconventionalGasRUOption=Yes (supply curve)
|UraniumRUOption=Yes (supply curve)
|BioenergyRUOption=Yes (supply curve)
|IndustryESOption=Yes (physical & economic)
|EnergyESOption=Yes (physical & economic)
|TransportationESOption=Yes (physical & economic)
|ResidentialAndCommercialESOption=Yes (physical & economic)
|AgricultureESOption=Yes (economic)
|EnergyConversionTechnologyTCOption=Exogenous technological change
|EnergyEnd-useTCOption=Endogenous technological change
|AgricultureTCOption=Exogenous technological change
}}
{{EnergyTemplate
|EnergyTechnologyChoiceOption=Logit choice model
|EnergyTechnologySubstitutabilityOption=Mixed high and low substitutability
|EnergyTechnologyDeploymentOption=System integration constraints
|ElectricityTechnologyOption=Coal w/o CCS; Coal w/ CCS; Gas w/o CCS; Gas w/ CCS; Oil w/o 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
|HydrogenProductionOption=Electrolysis
|RefinedLiquidsOption=Oil refining
|RefinedGasesOption=Coal to gas w/o CCS; Oil to gas w/o CCS
|HeatGenerationOption=Coal heat; Natural gas heat; Oil heat; Biomass heat; Geothermal heat; Solarthermal heat; CHP (coupled heat and power)
|ElectricityGIOption=Yes (aggregate)
|GasGIOption=Yes (aggregate)
|HeatGIOption=Yes (aggregate)
|CO2GIOption=Yes (aggregate)
|HydrogenGIOption=Yes (aggregate)
|PassengerTransportationOption=Passenger trains; Buses; Light Duty Vehicles (LDVs); Electric LDVs; Hydrogen LDVs; Hybrid LDVs; Gasoline LDVs; Diesel LDVs; Passenger aircrafts
|PassengerTransportation=Private road passenger (cars, powered 2 wheelers), public road passenger (buses and coaches), road freight (HDVs, LDVs), passenger rail (slow and high-speed trains, metro), freight rail, passenger aviation (split into distance classes), freight and passenger inland navigation and short sea shipping, bunkers. Numerous classes of vehicles and transport means with tracking of technology vintages.
|FreightTransportationOption=Freight trains; Heavy duty vehicles; Freight ships
|IndustryOption=Steel production; Aluminium production; Cement production; Petrochemical production; Paper production; Plastics production; Pulp production
|ResidentialAndCommercialOption=Space heating; Space cooling; Cooking; Refrigeration; Washing; Lighting
}}
{{Land-useTemplate}}
{{EmissionClimateTemplate
|GHGOption=CO2 fossil fuels
|PollutantOption=NOx energy; SO2 energy
|ClimateIndicatorOption=Concentration: CO2
|CarbonDioxideRemovalOption=Bioenergy with CCS; Direct air capture
|ClimateChangeImpactsOption=Energy supply; Energy demand
|Co-LinkagesOption=Energy security: Fossil fuel imports & exports (region); Energy access: Household energy consumption; Air pollution & health: Health impacts of air Pollution; Water availability
}}
{{InstitutionTemplate}}

PRIMES

2023-05-10T05:11:19Z

Maria Kannavou:

PRIMES

2023-05-10T05:03:02Z

Maria Kannavou:

PRIMES

2023-05-10T05:00:12Z

Maria Kannavou:

PRIMES

2023-05-10T04:56:02Z

Maria Kannavou:

PRIMES

2023-05-10T04:48:05Z

Maria Kannavou:

PRIMES

2023-05-10T04:47:32Z

Maria Kannavou:

{{ModelTemplate}}
{{ModelInfoTemplate
|Name=PRIMES
|Version=2022
|ModelLink=https://e3modelling.com/modelling-tools/primes/
|participation=reference card only
|processState=in preparation
}}
{{ScopeMethodTemplate
|ModelTypeOption=Energy system model
|GeographicalScopeOption=Regional
|Objective=PRIMES provides detailed projections of energy demand, supply, prices and
investment to the future, covering the entire energy system including
emissions for each individual European country and for Europe-wide trade of
energy commodities.
PRIMES model design is suitable for medium- and long-term energy system
projections and system restructuring up to 2070, both in demand and supply. The model can support an impact assessment of specific energy and
environment policies and measures, applied at the Member State or EU level,
including price signals, such as taxation, subsidies, ETS, technology-promoting
policies, RES-supporting policies, efficiency-promoting policies, environmental
policies and technology standards. PRIMES is sufficiently detailed to represent
concrete policy measures in various sectors, including market design options
for the EU internal electricity and gas markets. Policy analysis draws on
comparing the results of scenarios against a reference projection
|SolutionConceptOption=Partial equilibrium (price elastic demand)
|SolutionConcept=The PRIMES model comprises several sub-models (modules), each one representing the behaviour of a specific (or representative) agent, a demander and/or a supplier of energy. The sub-models link with each other through a model integration algorithm, which determines equilibrium prices in multiple markets and equilibrium volumes meets balancing and overall (e.g. emission) constraints.
|SolutionHorizonOption=Intertemporal optimization (foresight)
|SolutionMethod=Mathematically PRIMES solves an EPEC problem (equilibrium problem with equilibrium constraints) which allows prices to be explicitly determined.
|Anticipation=The PRIMES model is fully dynamic and has options regarding future
anticipation by agents in decision-making. Usually, PRIMES assumes perfect
foresight over a short time horizon for demand sectors and perfect foresight
over a long time horizon for supply sectors. The sub-models solve over the
entire projection period in each cycle of interaction between demand and
supply and so market equilibrium is dynamic and not static. Other options are
available allowing the model user to specify shorter time horizons for
foresight.
|BaseYear=2015
|TimeSteps=5 year
|Horizon=2015 to 2070
|Nr=28
|Region=EU27, UK. Primes has also used for providing projections for the Energy Community Contracting Parties, Turkey, Iceland, Switzerland.
|TimeDiscountingTypeOption=Discount rate exogenous
|PoliciesOption=Emission tax; Emission pricing; Cap and trade; Fuel taxes; Fuel subsidies; Feed-in-tariff; Emission standards; Energy efficiency standards
}}
{{Socio-economicTemplate
|PopulationOption=Yes (exogenous)
|PopulationAgeStructureOption=Yes (exogenous)
|UrbanizationRateOption=Yes (exogenous)
|GDPOption=Yes (exogenous)
|IncomeDistributionOption=Yes (exogenous)
|AutonomousEnergyEfficiencyImprovementsOption=Yes (endogenous)
}}
{{Macro-economyTemplate}}
{{EnergyTemplate
|EnergyTechnologyChoice=The agents’ behaviours are sector-specific. The modelling draws on structural microeconomics: each demand module formulates a representative agent who maximises benefits (profit, utility, etc.) from energy demand and non-energy inputs (commodities, production factors) subject to prices, budget and other constraints. The submodels use either discrete technology choices or linear choice.
|ElectricityTechnologyOption=Coal w/o CCS; Coal w/ CCS; Gas w/o CCS; Gas w/ CCS; Oil w/o 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
|HydrogenProductionOption=Electrolysis
|RefinedGasesOption=Coal to gas w/o CCS
|HeatGenerationOption=Coal heat; Natural gas heat; Oil heat; Biomass heat; Geothermal heat; Solarthermal heat; CHP (coupled heat and power)
|ElectricityGIOption=Yes (aggregate)
|GasGIOption=Yes (aggregate)
|HeatGIOption=Yes (aggregate)
|CO2GIOption=Yes (aggregate)
|HydrogenGIOption=Yes (aggregate)
|PassengerTransportationOption=Passenger trains; Buses; Light Duty Vehicles (LDVs); Electric LDVs; Hydrogen LDVs; Hybrid LDVs; Gasoline LDVs; Diesel LDVs; Passenger aircrafts
|FreightTransportationOption=Freight trains; Heavy duty vehicles; Freight aircrafts; Freight ships
|IndustryOption=Steel production; Aluminium production; Cement production; Petrochemical production; Paper production; Plastics production; Pulp production
|ResidentialAndCommercialOption=Space heating; Space cooling; Cooking; Refrigeration; Washing; Lighting
}}
{{Land-useTemplate}}
{{EmissionClimateTemplate
|GHGOption=CO2 fossil fuels
|PollutantOption=NOx energy; SO2 energy
|ClimateIndicatorOption=Concentration: CO2
|CarbonDioxideRemovalOption=Bioenergy with CCS; Direct air capture
|ClimateChangeImpactsOption=Energy supply; Energy demand
|Co-LinkagesOption=Energy security: Fossil fuel imports & exports (region); Energy access: Household energy consumption; Air pollution & health: Health impacts of air Pollution; Water availability
}}
{{InstitutionTemplate
|abbr=E3M
|institution=E3Modelling
|link=https://e3modelling.com/modelling-tools/primes/
|country=Greece
}}

PRIMES

2023-05-10T04:41:29Z

Maria Kannavou:

{{ModelTemplate}}
{{ModelInfoTemplate
|Name=PRIMES
|Version=2022
|ModelLink=https://e3modelling.com/modelling-tools/primes/
|participation=reference card only
|processState=in preparation
}}
{{ScopeMethodTemplate
|ModelTypeOption=Energy system model
|GeographicalScopeOption=Regional
|SolutionConceptOption=Partial equilibrium (price elastic demand)
|SolutionConcept=The PRIMES model comprises several sub-models (modules), each one representing the behaviour of a specific (or representative) agent, a demander and/or a supplier of energy. The sub-models link with each other through a model integration algorithm, which determines equilibrium prices in multiple markets and equilibrium volumes meets balancing and overall (e.g. emission) constraints.
|SolutionHorizonOption=Intertemporal optimization (foresight)
|Anticipation=The PRIMES model is fully dynamic and has options regarding future
anticipation by agents in decision-making. Usually, PRIMES assumes perfect
foresight over a short time horizon for demand sectors and perfect foresight
over a long time horizon for supply sectors. The sub-models solve over the
entire projection period in each cycle of interaction between demand and
supply and so market equilibrium is dynamic and not static. Other options are
available allowing the model user to specify shorter time horizons for
foresight.
|TimeSteps=5 year
|TimeDiscountingTypeOption=Discount rate exogenous
|PoliciesOption=Emission tax; Emission pricing; Cap and trade; Fuel taxes; Fuel subsidies; Feed-in-tariff; Emission standards; Energy efficiency standards
}}
{{Socio-economicTemplate
|PopulationOption=Yes (exogenous)
|PopulationAgeStructureOption=Yes (exogenous)
|UrbanizationRateOption=Yes (exogenous)
|GDPOption=Yes (exogenous)
|IncomeDistributionOption=Yes (exogenous)
|AutonomousEnergyEfficiencyImprovementsOption=Yes (endogenous)
}}
{{Macro-economyTemplate}}
{{EnergyTemplate
|EnergyTechnologyChoice=The agents’ behaviours are sector-specific. The modelling draws on structural microeconomics: each demand module formulates a representative agent who maximises benefits (profit, utility, etc.) from energy demand and non-energy inputs (commodities, production factors) subject to prices, budget and other constraints. The submodels use either discrete technology choices or linear choice.
|ElectricityTechnologyOption=Coal w/o CCS; Coal w/ CCS; Gas w/o CCS; Gas w/ CCS; Oil w/o 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
|HydrogenProductionOption=Electrolysis
|RefinedGasesOption=Coal to gas w/o CCS
|HeatGenerationOption=Coal heat; Natural gas heat; Oil heat; Biomass heat; Geothermal heat; Solarthermal heat; CHP (coupled heat and power)
|ElectricityGIOption=Yes (aggregate)
|GasGIOption=Yes (aggregate)
|HeatGIOption=Yes (aggregate)
|CO2GIOption=Yes (aggregate)
|HydrogenGIOption=Yes (aggregate)
|PassengerTransportationOption=Passenger trains; Buses; Light Duty Vehicles (LDVs); Electric LDVs; Hydrogen LDVs; Hybrid LDVs; Gasoline LDVs; Diesel LDVs; Passenger aircrafts
|FreightTransportationOption=Freight trains; Heavy duty vehicles; Freight aircrafts; Freight ships
|IndustryOption=Steel production; Aluminium production; Cement production; Petrochemical production; Paper production; Plastics production; Pulp production
|ResidentialAndCommercialOption=Space heating; Space cooling; Cooking; Refrigeration; Washing; Lighting
}}
{{Land-useTemplate}}
{{EmissionClimateTemplate
|GHGOption=CO2 fossil fuels
|PollutantOption=NOx energy; SO2 energy
|ClimateIndicatorOption=Concentration: CO2
|CarbonDioxideRemovalOption=Bioenergy with CCS; Direct air capture
|ClimateChangeImpactsOption=Energy supply; Energy demand
|Co-LinkagesOption=Energy security: Fossil fuel imports & exports (region); Energy access: Household energy consumption; Air pollution & health: Health impacts of air Pollution; Water availability
}}
{{InstitutionTemplate
|abbr=E3M
|institution=E3Modelling
|link=https://e3modelling.com/modelling-tools/primes/
|country=Greece
}}

PRIMES

2023-05-10T04:38:33Z

Maria Kannavou:

{{ModelTemplate}}
{{ModelInfoTemplate
|Name=PRIMES
|Version=2022
|ModelLink=https://e3modelling.com/modelling-tools/primes/
|participation=reference card only
|processState=in preparation
}}
{{InstitutionTemplate
|abbr=E3M
|institution=E3Modelling
|link=https://e3modelling.com/modelling-tools/primes/
|country=Greece
}}
{{ScopeMethodTemplate
|ModelTypeOption=Energy system model
|GeographicalScopeOption=Regional
|SolutionConceptOption=Partial equilibrium (price elastic demand)
|SolutionConcept=The PRIMES model comprises several sub-models (modules), each one representing the behaviour of a specific (or representative) agent, a demander and/or a supplier of energy. The sub-models link with each other through a model integration algorithm, which determines equilibrium prices in multiple markets and equilibrium volumes meets balancing and overall (e.g. emission) constraints.
|SolutionHorizonOption=Intertemporal optimization (foresight)
|Anticipation=The PRIMES model is fully dynamic and has options regarding future
anticipation by agents in decision-making. Usually, PRIMES assumes perfect
foresight over a short time horizon for demand sectors and perfect foresight
over a long time horizon for supply sectors. The sub-models solve over the
entire projection period in each cycle of interaction between demand and
supply and so market equilibrium is dynamic and not static. Other options are
available allowing the model user to specify shorter time horizons for
foresight.
|TimeSteps=5 year
|TimeDiscountingTypeOption=Discount rate exogenous
|PoliciesOption=Emission tax; Emission pricing; Cap and trade; Fuel taxes; Fuel subsidies; Feed-in-tariff; Emission standards; Energy efficiency standards
}}
{{Socio-economicTemplate
|PopulationOption=Yes (exogenous)
|PopulationAgeStructureOption=Yes (exogenous)
|UrbanizationRateOption=Yes (exogenous)
|GDPOption=Yes (exogenous)
|IncomeDistributionOption=Yes (exogenous)
|AutonomousEnergyEfficiencyImprovementsOption=Yes (endogenous)
}}
{{Macro-economyTemplate}}
{{EnergyTemplate
|EnergyTechnologyChoice=The agents’ behaviours are sector-specific. The modelling draws on structural microeconomics: each demand module formulates a representative agent who maximises benefits (profit, utility, etc.) from energy demand and non-energy inputs (commodities, production factors) subject to prices, budget and other constraints. The submodels use either discrete technology choices or linear choice.
|ElectricityTechnologyOption=Coal w/o CCS; Coal w/ CCS; Gas w/o CCS; Gas w/ CCS; Oil w/o 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
|HydrogenProductionOption=Electrolysis
|RefinedGasesOption=Coal to gas w/o CCS
|HeatGenerationOption=Coal heat; Natural gas heat; Oil heat; Biomass heat; Geothermal heat; Solarthermal heat; CHP (coupled heat and power)
|ElectricityGIOption=Yes (aggregate)
|GasGIOption=Yes (aggregate)
|HeatGIOption=Yes (aggregate)
|CO2GIOption=Yes (aggregate)
|HydrogenGIOption=Yes (aggregate)
|PassengerTransportationOption=Passenger trains; Buses; Light Duty Vehicles (LDVs); Electric LDVs; Hydrogen LDVs; Hybrid LDVs; Gasoline LDVs; Diesel LDVs; Passenger aircrafts
|FreightTransportationOption=Freight trains; Heavy duty vehicles; Freight aircrafts; Freight ships
|IndustryOption=Steel production; Aluminium production; Cement production; Petrochemical production; Paper production; Plastics production; Pulp production
|ResidentialAndCommercialOption=Space heating; Space cooling; Cooking; Refrigeration; Washing; Lighting
}}
{{Land-useTemplate}}
{{EmissionClimateTemplate
|GHGOption=CO2 fossil fuels
|ClimateIndicatorOption=Concentration: CO2
|CarbonDioxideRemovalOption=Bioenergy with CCS; Direct air capture
|Co-LinkagesOption=Energy security: Fossil fuel imports & exports (region); Energy access: Household energy consumption
}}

PRIMES

2023-05-10T04:37:54Z

Maria Kannavou:

{{ModelTemplate}}
{{ModelInfoTemplate
|Name=PRIMES
|Version=2022
|ModelLink=http://www.e3mlab.eu/e3mlab/index.php?option=com_content&view=category&id=35
|participation=reference card only
|processState=in preparation
}}
{{ScopeMethodTemplate
|ModelTypeOption=Energy system model
|GeographicalScopeOption=Regional
|SolutionConceptOption=Partial equilibrium (price elastic demand)
|SolutionConcept=The PRIMES model comprises several sub-models (modules), each one representing the behaviour of a specific (or representative) agent, a demander and/or a supplier of energy. The sub-models link with each other through a model integration algorithm, which determines equilibrium prices in multiple markets and equilibrium volumes meets balancing and overall (e.g. emission) constraints.
|SolutionHorizonOption=Intertemporal optimization (foresight)
|Anticipation=The PRIMES model is fully dynamic and has options regarding future
anticipation by agents in decision-making. Usually, PRIMES assumes perfect
foresight over a short time horizon for demand sectors and perfect foresight
over a long time horizon for supply sectors. The sub-models solve over the
entire projection period in each cycle of interaction between demand and
supply and so market equilibrium is dynamic and not static. Other options are
available allowing the model user to specify shorter time horizons for
foresight.
|TimeSteps=5 year
|TimeDiscountingTypeOption=Discount rate exogenous
|PoliciesOption=Emission tax; Emission pricing; Cap and trade; Fuel taxes; Fuel subsidies; Feed-in-tariff; Emission standards; Energy efficiency standards
}}
{{Socio-economicTemplate
|PopulationOption=Yes (exogenous)
|PopulationAgeStructureOption=Yes (exogenous)
|UrbanizationRateOption=Yes (exogenous)
|GDPOption=Yes (exogenous)
|IncomeDistributionOption=Yes (exogenous)
|AutonomousEnergyEfficiencyImprovementsOption=Yes (endogenous)
}}
{{Macro-economyTemplate}}
{{EnergyTemplate
|EnergyTechnologyChoice=The agents’ behaviours are sector-specific. The modelling draws on structural microeconomics: each demand module formulates a representative agent who maximises benefits (profit, utility, etc.) from energy demand and non-energy inputs (commodities, production factors) subject to prices, budget and other constraints. The submodels use either discrete technology choices or linear choice.
|ElectricityTechnologyOption=Coal w/o CCS; Coal w/ CCS; Gas w/o CCS; Gas w/ CCS; Oil w/o 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
|HydrogenProductionOption=Electrolysis
|RefinedGasesOption=Coal to gas w/o CCS
|HeatGenerationOption=Coal heat; Natural gas heat; Oil heat; Biomass heat; Geothermal heat; Solarthermal heat; CHP (coupled heat and power)
|ElectricityGIOption=Yes (aggregate)
|GasGIOption=Yes (aggregate)
|HeatGIOption=Yes (aggregate)
|CO2GIOption=Yes (aggregate)
|HydrogenGIOption=Yes (aggregate)
|PassengerTransportationOption=Passenger trains; Buses; Light Duty Vehicles (LDVs); Electric LDVs; Hydrogen LDVs; Hybrid LDVs; Gasoline LDVs; Diesel LDVs; Passenger aircrafts
|FreightTransportationOption=Freight trains; Heavy duty vehicles; Freight aircrafts; Freight ships
|IndustryOption=Steel production; Aluminium production; Cement production; Petrochemical production; Paper production; Plastics production; Pulp production
|ResidentialAndCommercialOption=Space heating; Space cooling; Cooking; Refrigeration; Washing; Lighting
}}
{{Land-useTemplate}}
{{EmissionClimateTemplate
|GHGOption=CO2 fossil fuels
|ClimateIndicatorOption=Concentration: CO2
|CarbonDioxideRemovalOption=Bioenergy with CCS; Direct air capture
|Co-LinkagesOption=Energy security: Fossil fuel imports & exports (region); Energy access: Household energy consumption
}}
{{InstitutionTemplate
|abbr=E3M
|institution=E3Modelling
|link=http://www.e3mlab.eu/e3mlab/index.php
|country=Greece
}}

PRIMES

2023-02-14T13:49:45Z

Maria Kannavou:

{{ModelTemplate}}
{{ModelInfoTemplate}}
{{ScopeMethodTemplate}}
{{Socio-economicTemplate
|PopulationOption=Yes (exogenous)
|PopulationAgeStructureOption=Yes (exogenous)
|UrbanizationRateOption=Yes (exogenous)
|GDPOption=Yes (exogenous)
|IncomeDistributionOption=Yes (exogenous)
|AutonomousEnergyEfficiencyImprovementsOption=Yes (endogenous)
}}
{{Macro-economyTemplate}}
{{EnergyTemplate
|EnergyTechnologyChoice=The agents’ behaviours are sector-specific. The modelling draws on structural microeconomics: each demand module formulates a representative agent who maximises benefits (profit, utility, etc.) from energy demand and non-energy inputs (commodities, production factors) subject to prices, budget and other constraints. The submodels use either discrete technology choices or linear choice.
|ElectricityTechnologyOption=Coal w/o CCS; Coal w/ CCS; Gas w/o CCS; Gas w/ CCS; Oil w/o 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
|HydrogenProductionOption=Electrolysis
|RefinedGasesOption=Coal to gas w/o CCS
|HeatGenerationOption=Coal heat; Natural gas heat; Oil heat; Biomass heat; Geothermal heat; Solarthermal heat; CHP (coupled heat and power)
|ElectricityGIOption=Yes (aggregate)
|GasGIOption=Yes (aggregate)
|HeatGIOption=Yes (aggregate)
|CO2GIOption=Yes (aggregate)
|HydrogenGIOption=Yes (aggregate)
|PassengerTransportationOption=Passenger trains; Buses; Light Duty Vehicles (LDVs); Electric LDVs; Hydrogen LDVs; Hybrid LDVs; Gasoline LDVs; Diesel LDVs; Passenger aircrafts
|FreightTransportationOption=Freight trains; Heavy duty vehicles; Freight aircrafts; Freight ships
|IndustryOption=Steel production; Aluminium production; Cement production; Petrochemical production; Paper production; Plastics production; Pulp production
|ResidentialAndCommercialOption=Space heating; Space cooling; Cooking; Refrigeration; Washing; Lighting
}}
{{Land-useTemplate}}
{{EmissionClimateTemplate
|GHGOption=CO2 fossil fuels
|ClimateIndicatorOption=Concentration: CO2
|CarbonDioxideRemovalOption=Bioenergy with CCS; Direct air capture
|Co-LinkagesOption=Energy security: Fossil fuel imports & exports (region); Energy access: Household energy consumption
}}
{{InstitutionTemplate}}

PRIMES

2023-02-14T13:48:43Z

Maria Kannavou:

{{ModelTemplate}}
{{ModelInfoTemplate}}
{{ScopeMethodTemplate}}
{{Socio-economicTemplate}}
{{Macro-economyTemplate}}
{{EnergyTemplate
|EnergyTechnologyChoice=The agents’ behaviours are sector-specific. The modelling draws on structural microeconomics: each demand module formulates a representative agent who maximises benefits (profit, utility, etc.) from energy demand and non-energy inputs (commodities, production factors) subject to prices, budget and other constraints. The submodels use either discrete technology choices or linear choice.
|ElectricityTechnologyOption=Coal w/o CCS; Coal w/ CCS; Gas w/o CCS; Gas w/ CCS; Oil w/o 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
|HydrogenProductionOption=Electrolysis
|RefinedGasesOption=Coal to gas w/o CCS
|HeatGenerationOption=Coal heat; Natural gas heat; Oil heat; Biomass heat; Geothermal heat; Solarthermal heat; CHP (coupled heat and power)
|ElectricityGIOption=Yes (aggregate)
|GasGIOption=Yes (aggregate)
|HeatGIOption=Yes (aggregate)
|CO2GIOption=Yes (aggregate)
|HydrogenGIOption=Yes (aggregate)
|PassengerTransportationOption=Passenger trains; Buses; Light Duty Vehicles (LDVs); Electric LDVs; Hydrogen LDVs; Hybrid LDVs; Gasoline LDVs; Diesel LDVs; Passenger aircrafts
|FreightTransportationOption=Freight trains; Heavy duty vehicles; Freight aircrafts; Freight ships
|IndustryOption=Steel production; Aluminium production; Cement production; Petrochemical production; Paper production; Plastics production; Pulp production
|ResidentialAndCommercialOption=Space heating; Space cooling; Cooking; Refrigeration; Washing; Lighting
}}
{{Land-useTemplate}}
{{EmissionClimateTemplate
|GHGOption=CO2 fossil fuels
|ClimateIndicatorOption=Concentration: CO2
|CarbonDioxideRemovalOption=Bioenergy with CCS; Direct air capture
|Co-LinkagesOption=Energy security: Fossil fuel imports & exports (region); Energy access: Household energy consumption
}}
{{InstitutionTemplate}}

PRIMES

2023-02-14T12:31:51Z

Maria Kannavou:

{{ModelTemplate}}
{{ModelInfoTemplate}}
{{ScopeMethodTemplate}}
{{Socio-economicTemplate}}
{{Macro-economyTemplate}}
{{EnergyTemplate
|EnergyTechnologyChoice=The agents’ behaviours are sector-specific. The modelling draws on structural microeconomics: each demand module formulates a representative agent who maximises benefits (profit, utility, etc.) from energy demand and non-energy inputs (commodities, production factors) subject to prices, budget and other constraints. The submodels use either discrete technology choices or linear choice.
|ElectricityTechnologyOption=Coal w/o CCS; Coal w/ CCS; Gas w/o CCS; Gas w/ CCS; Oil w/o 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
|HydrogenProductionOption=Electrolysis
|RefinedGasesOption=Coal to gas w/o CCS
|HeatGenerationOption=Coal heat; Natural gas heat; Oil heat; Biomass heat; Geothermal heat; Solarthermal heat; CHP (coupled heat and power)
|ElectricityGIOption=Yes (aggregate)
|GasGIOption=Yes (aggregate)
|HeatGIOption=Yes (aggregate)
|CO2GIOption=Yes (aggregate)
|HydrogenGIOption=Yes (aggregate)
|PassengerTransportationOption=Passenger trains; Buses; Light Duty Vehicles (LDVs); Electric LDVs; Hydrogen LDVs; Hybrid LDVs; Gasoline LDVs; Diesel LDVs; Passenger aircrafts
|FreightTransportationOption=Freight trains; Heavy duty vehicles; Freight aircrafts; Freight ships
|IndustryOption=Steel production; Aluminium production; Cement production; Petrochemical production; Paper production; Plastics production; Pulp production
|ResidentialAndCommercialOption=Space heating; Space cooling; Cooking; Refrigeration; Washing; Lighting
}}
{{Land-useTemplate}}
{{EmissionClimateTemplate
|GHGOption=CO2 fossil fuels
|CarbonDioxideRemovalOption=Bioenergy with CCS; Direct air capture
|Co-LinkagesOption=Energy security: Fossil fuel imports & exports (region); Energy access: Household energy consumption
}}
{{InstitutionTemplate}}

PRIMES

2023-02-14T12:27:14Z

Maria Kannavou:

PRIMES

2023-02-14T12:16:37Z

Maria Kannavou:

{{ModelTemplate}}
{{ModelInfoTemplate}}
{{ScopeMethodTemplate
|ModelTypeOption=Energy system model
|GeographicalScopeOption=Regional
|Objective=The PRIMES (Price-Induced Market Equilibrium System) is a large-scale applied energy system model that provides detailed projections of energy demand, supply, prices and investment in the future, covering the entire energy system including emissions. The distinctive feature of PRIMES is the combination of behavioural modelling (following a microeconomic foundation) with engineering aspects, covering all energy sectors and markets. The model has a detailed representation of instruments for policy impact assessment related to energy markets and climate, including market drivers, standards, and targets by sector or overall. It handles multiple policy objectives, such as GHG emissions reductions, energy efficiency, and renewable energy targets and provides pan-European simulation of internal markets for electricity and gas.
|SolutionConceptOption=Partial equilibrium (price elastic demand)
|SolutionHorizonOption=Intertemporal optimization (foresight)
|SolutionHorizon=The PRIMES model comprises several sub-models (modules), each one representing the behaviour of a specific (or representative) agent, a demander and/or a supplier of energy. The sub-models link with each other through a model integration algorithm, which determines equilibrium prices in multiple markets and equilibrium volumes meets balancing and overall (e.g. emission) constraints. Mathematically PRIMES solves an EPEC problem (equilibrium problem with equilibrium constraints) which allows prices to be explicitly determined.
|SolutionMethodOption=Optimization
|Anticipation=The PRIMES model is fully dynamic and has options regarding future
anticipation by agents in decision-making. Usually, PRIMES assumes perfect
foresight over a short time horizon for demand sectors and perfect foresight
over long time horizon for supply sectors. The sub-models solve over the
entire projection period in each cycle of interaction between demand and
supply and so market equilibrium is dynamic and not static. Other options are
available allowing the model user to specify shorter time horizons for
foresight.
|BaseYear=2015
|TimeSteps=5-year
|Horizon=2070
|Nr=40
|SpatialText=EU27 MS individually, UK, Energy Community Contracting Parties and PRIMES has also provided in the past detailed outlooks for Switzerland, Norway, Turkey and Iceland
|TimeDiscountingTypeOption=Discount rate exogenous
|PoliciesOption=Emission tax; Emission pricing; Cap and trade; Fuel taxes; Fuel subsidies; Feed-in-tariff; Capacity targets; Emission standards; Energy efficiency standards
|Policies=Eco-design standards, Best Available Technology regulations, Efficiency standards on vehicles and other transport means; Large Combustion plants directives and other phase-out policies or policies permitting power plant technologies at a national level (e.g. CCS); Energy performance standards
}}
{{Socio-economicTemplate
|PopulationOption=Yes (exogenous)
|PopulationAgeStructureOption=Yes (exogenous)
|UrbanizationRateOption=Yes (exogenous)
|GDPOption=Yes (exogenous)
|IncomeDistributionOption=Yes (exogenous)
|AutonomousEnergyEfficiencyImprovementsOption=Yes (endogenous)
}}
{{Macro-economyTemplate
|TradeOption=Gas; Electricity; Bioenergy crops; Emissions permits
|InstitutionalAndPoliticalFactorsOption=Interest rates differentiated by country/region; Technology costs differentiated by country/region; Behavioural change differentiated by country/region
|EnergyConversionTechnologyTCOption=Exogenous technological change
|EnergyEnd-useTCOption=Exogenous technological change
}}
{{EnergyTemplate}}
{{Land-useTemplate}}
{{EmissionClimateTemplate}}
{{InstitutionTemplate}}

PRIMES

2023-02-14T12:09:48Z

Maria Kannavou:

{{ModelTemplate}}
{{ModelInfoTemplate}}
{{ScopeMethodTemplate
|ModelTypeOption=Energy system model
|GeographicalScopeOption=Regional
|Objective=The PRIMES (Price-Induced Market Equilibrium System) is a large-scale applied energy system model that provides detailed projections of energy demand, supply, prices and investment in the future, covering the entire energy system including emissions. The distinctive feature of PRIMES is the combination of behavioural modelling (following a microeconomic foundation) with engineering aspects, covering all energy sectors and markets. The model has a detailed representation of instruments for policy impact assessment related to energy markets and climate, including market drivers, standards, and targets by sector or overall. It handles multiple policy objectives, such as GHG emissions reductions, energy efficiency, and renewable energy targets and provides pan-European simulation of internal markets for electricity and gas.
|SolutionConceptOption=Partial equilibrium (price elastic demand)
|SolutionHorizonOption=Intertemporal optimization (foresight)
|SolutionHorizon=The PRIMES model comprises several sub-models (modules), each one representing the behaviour of a specific (or representative) agent, a demander and/or a supplier of energy. The sub-models link with each other through a model integration algorithm, which determines equilibrium prices in multiple markets and equilibrium volumes meets balancing and overall (e.g. emission) constraints. Mathematically PRIMES solves an EPEC problem (equilibrium problem with equilibrium constraints) which allows prices to be explicitly determined.
|SolutionMethodOption=Optimization
|Anticipation=The PRIMES model is fully dynamic and has options regarding future
anticipation by agents in decision-making. Usually, PRIMES assumes perfect
foresight over a short time horizon for demand sectors and perfect foresight
over long time horizon for supply sectors. The sub-models solve over the
entire projection period in each cycle of interaction between demand and
supply and so market equilibrium is dynamic and not static. Other options are
available allowing the model user to specify shorter time horizons for
foresight.
|BaseYear=2015
|TimeSteps=5-year
|Horizon=2070
|Nr=40
|SpatialText=EU27 MS individually, UK, Energy Community Contracting Parties and PRIMES has also provided in the past detailed outlooks for Switzerland, Norway, Turkey and Iceland
|TimeDiscountingTypeOption=Discount rate exogenous
|PoliciesOption=Emission tax; Emission pricing; Cap and trade; Fuel taxes; Fuel subsidies; Feed-in-tariff; Capacity targets; Emission standards; Energy efficiency standards
|Policies=Eco-design standards, Best Available Technology regulations, Efficiency standards on vehicles and other transport means; Large Combustion plants directives and other phase-out policies or policies permitting power plant technologies at a national level (e.g. CCS); Energy performance standards
}}
{{Socio-economicTemplate
|PopulationOption=Yes (exogenous)
|PopulationAgeStructureOption=Yes (exogenous)
|UrbanizationRateOption=Yes (exogenous)
|GDPOption=Yes (exogenous)
|IncomeDistributionOption=Yes (exogenous)
|AutonomousEnergyEfficiencyImprovementsOption=Yes (endogenous)
}}
{{Macro-economyTemplate}}
{{EnergyTemplate}}
{{Land-useTemplate}}
{{EmissionClimateTemplate}}
{{InstitutionTemplate}}

PRIMES

2023-02-14T12:05:00Z

Maria Kannavou:

{{ModelTemplate}}
{{ModelInfoTemplate}}
{{ScopeMethodTemplate
|ModelTypeOption=Energy system model
|GeographicalScopeOption=Regional
|Objective=The PRIMES (Price-Induced Market Equilibrium System) is a large-scale applied energy system model that provides detailed projections of energy demand, supply, prices and investment in the future, covering the entire energy system including emissions. The distinctive feature of PRIMES is the combination of behavioural modelling (following a microeconomic foundation) with engineering aspects, covering all energy sectors and markets. The model has a detailed representation of instruments for policy impact assessment related to energy markets and climate, including market drivers, standards, and targets by sector or overall. It handles multiple policy objectives, such as GHG emissions reductions, energy efficiency, and renewable energy targets and provides pan-European simulation of internal markets for electricity and gas.
|SolutionConceptOption=Partial equilibrium (price elastic demand)
|SolutionHorizonOption=Intertemporal optimization (foresight)
|SolutionHorizon=The PRIMES model comprises several sub-models (modules), each one representing the behaviour of a specific (or representative) agent, a demander and/or a supplier of energy. The sub-models link with each other through a model integration algorithm, which determines equilibrium prices in multiple markets and equilibrium volumes meets balancing and overall (e.g. emission) constraints. Mathematically PRIMES solves an EPEC problem (equilibrium problem with equilibrium constraints) which allows prices to be explicitly determined.
|SolutionMethodOption=Optimization
|Anticipation=The PRIMES model is fully dynamic and has options regarding future
anticipation by agents in decision-making. Usually, PRIMES assumes perfect
foresight over a short time horizon for demand sectors and perfect foresight
over long time horizon for supply sectors. The sub-models solve over the
entire projection period in each cycle of interaction between demand and
supply and so market equilibrium is dynamic and not static. Other options are
available allowing the model user to specify shorter time horizons for
foresight.
|BaseYear=2015
|TimeSteps=5-year
|Horizon=2070
|Nr=40
|SpatialText=EU27 MS individually, UK, Energy Community Contracting Parties and PRIMES has also provided in the past detailed outlooks for Switzerland, Norway, Turkey and Iceland
|TimeDiscountingTypeOption=Discount rate exogenous
|PoliciesOption=Emission tax; Emission pricing; Cap and trade; Fuel taxes; Fuel subsidies; Feed-in-tariff; Capacity targets; Emission standards; Energy efficiency standards
|Policies=Eco-design standards, Best Available Technology regulations, Efficiency standards on vehicles and other transport means; Large Combustion plants directives and other phase-out policies or policies permitting power plant technologies at a national level (e.g. CCS); Energy performance standards
}}
{{Socio-economicTemplate}}
{{Macro-economyTemplate}}
{{EnergyTemplate}}
{{Land-useTemplate}}
{{EmissionClimateTemplate}}
{{InstitutionTemplate}}