IAMC-Documentation - User contributions [en]

Gaseous fuels - TIAM-UCL

2016-12-15T21:26:08Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Gaseous fuels
}}
=== Alternative fuels ===

Table 3.2.4 contains technologies for the production of alternative fuels. The technologies are split into two groups: 1) Ethanol and methanol production, either from coal or biomass and 2) Fischer-Tropsch processes, producing oil products from coal, gas and biomass.

'''Table 3.2.4: Alternative fuel technologies'''

{| class="wikitable"
|width="100%"|'''Model Technology Description'''
|-
|Ethanol from biomass
|-
|Cellulose ethanol plant
|-
|Methanol from Bioliquids
|-
|Methanol from coal
|-
|Methanol from coal with CO2 capture
|-
|Methanol from natural gas
|-
|Methanol from natural gas with CCS
|-
|FT fuels from natural gas
|-
|FT fuels from natural gas with CCS
|-
|FT fuels from coal
|-
|FT fuels from coal with CCS
|-
|FT fuels from coal low biomass and coal co production
|-
|FT fuels low biomass and coal co production with CCS
|-
|FT fuels high biomass and coal co production
|-
|FT fuels high biomass and coal co production with CCS
|-
|FT fuels solid biomass
|-
|FT fuels solid biomass with CCS
|}

=== Hydrogen ===

New technologies include those used for hydrogen production and demand technologies in the transport sector that consume hydrogen. Production technologies are generic in nature and are defined by the type of fuel used - coal, natural gas, electricity and biomass.

There are also technologies, available from 2020, that allow for mixing of hydrogen into the natural gas supply to different sectors. This mix is fixed at 15% hydrogen / 85% natural gas. A single distribution technology allows for hydrogen transport, with costs developed on the basis of unit of energy transported (using VAROM).

'''Table 3.2.5: Hydrogen production and supply technologies'''

{| class="wikitable"
|width="100%"|'''Model Technology Description'''
|-
|Hydrogen from Brown coal
|-
|Hydrogen from Hard coal
|-
|Electrolysis
|-
|Hydrogen from NGA
|-
|Hydrogen from NGA - Decentralized
|-
|Hydrogen from biomass gasification
|-
|Mix of Gas and Hydrogen - For COM
|-
|Mix of Gas and Hydrogen - For IND
|-
|Mix of Gas and Hydrogen - For RES
|-
|Distribution of hydrogen
|}

Hydrogen technologies for cars and light duty trucks are included in the model, with different types based on the use of combustion, hybrid or fuel cell technology. The associated Trans file puts different hurdle rates on these technologies, assuming 15% for developed regions and 30% for developing regions such as Africa. The Trans file is also used to adjust efficiencies and costs across all regions, for both transport and production technologies.

=== Sequestration ===

Sequestration technologies and storage options mainly relate to the electricity sector, and are described in the relevant sector chapter of this report.

There are two technologies that allow for the capture of CO2 emissions (process-based) in the upstream sector. The costs of such 'dummy' capture technologies are modelled simply, using variable costs of 0.001 (equivalent to $1/tCO2).

Another set of important technologies for integrated climate modelling are those that relate to emissions and removals by the forestry sector. Labelled SINKAF*. The levels of emissions and removals and the associated costs are controlled by the Trans file and are based on assumptions used in the EMF analysis. Finally, atmospheric CO2 may be partly absorbed and fixed by biological sinks such as forests; the model has six options for forestation and avoided deforestation, as described in Sathaye et al. (2005) and adopted by the Energy Modelling Forum, EMF-21 and 22 groups.

=== Land-use CO2 ===

The SubRes file ''LUCO2'' defines a single technology that emits fixed levels of emissions by region each period. It is net CO2 emissions from deforestation and forest degradation. It does not include emissions from land use. The levels are calculated in the associated Trans file. The global emission level in 2005 is estimated at 2.7 GtCO2 per year, which decreases to 0.1 GtCO2 by 2100.Allocation by region is based on distribution of agricultural managed land. It is assumed that LULUCF emissions for UK is zero and therefore, WEU region's LULUCF emission has not been changed. There are scenarios in the model with reduced emissions from deforestation based on the EMF 21 study scenarios.

== Grid and infrastructure ==
No representation of grids in TIAM-UCL except Electricity generation can be centralised or decentralised (CEN or DCN). A generic cost and efficiency loss associated with distribution are included for Gas pipelines and electricity.

The range of CO2 storage technologies in the model are listed below.

'''Table 3.2.6: Types of storage technologies'''

{| class ="wikitable"
|width="100%"|'''Model Technology Description'''
|-
|Removal by Enhanced Coalbed Meth recov <1000 m
|-
|Removal by Enhanced Coalbed Meth recov >1000 m
|-
|Removal by Depl gas fields (offshore)
|-
|Removal by Depl gas fields (onshore)
|-
|Removal by Storage in the deep ocean
|-
|Removal by Depl oil fields (offshore)
|-
|Removal by Depl oil fields (onshore)
|-
|Removal by Deep saline aquifers
|-
|Removal by Enhanced Oil Recovery
|-
|Mineralization for CO2 storage
|}

Gaseous fuels - TIAM-UCL

2016-12-15T21:24:56Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Gaseous fuels
}}
=== Alternative fuels ===

Table 3.2.4 contains technologies for the production of alternative fuels. The technologies are split into two groups: 1) Ethanol and methanol production, either from coal or biomass and 2) Fischer-Tropsch processes, producing oil products from coal, gas and biomass.

'''Table 3.2.4: Alternative fuel technologies'''

{| class="wikitable"
|width="100%"|'''Model Technology Description'''
|-
|Ethanol from biomass
|-
|Cellulose ethanol plant
|-
|Methanol from Bioliquids
|-
|Methanol from coal
|-
|Methanol from coal with CO2 capture
|-
|Methanol from natural gas
|-
|Methanol from natural gas with CCS
|-
|FT fuels from natural gas
|-
|FT fuels from natural gas with CCS
|-
|FT fuels from coal
|-
|FT fuels from coal with CCS
|-
|FT fuels from coal low biomass and coal co production
|-
|FT fuels low biomass and coal co production with CCS
|-
|FT fuels high biomass and coal co production
|-
|FT fuels high biomass and coal co production with CCS
|-
|FT fuels solid biomass
|-
|FT fuels solid biomass with CCS
|}

=== Hydrogen ===

New technologies include those used for hydrogen production and demand technologies in the transport sector that consume hydrogen. Production technologies (name starting 'H') are generic in nature and are defined by the type of fuel used - coal, natural gas, electricity and biomass.

There are also technologies, available from 2020, that allow for mixing of hydrogen into the natural gas supply to different sectors (name starting 'UP'). This mix is fixed at 15% hydrogen / 85% natural gas. A single distribution technology allows for hydrogen transport, with costs developed on the basis of unit of energy transported (using VAROM).

'''Table 3.2.5: Hydrogen production and supply technologies'''

{| class="wikitable"
|width="100%"|'''Model Technology Description'''
|-
|Hydrogen from Brown coal
|-
|Hydrogen from Hard coal
|-
|Electrolysis
|-
|Hydrogen from NGA
|-
|Hydrogen from NGA - Decentralized
|-
|Hydrogen from biomass gasification
|-
|Mix of Gas and Hydrogen - For COM
|-
|Mix of Gas and Hydrogen - For IND
|-
|Mix of Gas and Hydrogen - For RES
|-
|Distribution of hydrogen
|}

Hydrogen technologies for cars and light duty trucks are included in the model, with different types based on the use of combustion, hybrid or fuel cell technology. The associated Trans file puts different hurdle rates on these technologies, assuming 15% for developed regions and 30% for developing regions such as Africa. The Trans file is also used to adjust efficiencies and costs across all regions, for both transport and production technologies.

=== Sequestration ===

Sequestration technologies and storage options mainly relate to the electricity sector, and are described in the relevant sector chapter of this report.

There are two technologies that allow for the capture of CO2 emissions (process-based) in the upstream sector. The costs of such 'dummy' capture technologies are modelled simply, using variable costs of 0.001 (equivalent to $1/tCO2).

Another set of important technologies for integrated climate modelling are those that relate to emissions and removals by the forestry sector. Labelled SINKAF*. The levels of emissions and removals and the associated costs are controlled by the Trans file and are based on assumptions used in the EMF analysis. Finally, atmospheric CO2 may be partly absorbed and fixed by biological sinks such as forests; the model has six options for forestation and avoided deforestation, as described in Sathaye et al. (2005) and adopted by the Energy Modelling Forum, EMF-21 and 22 groups.

=== Land-use CO2 ===

The SubRes file ''LUCO2'' defines a single technology that emits fixed levels of emissions by region each period. It is net CO2 emissions from deforestation and forest degradation. It does not include emissions from land use. The levels are calculated in the associated Trans file. The global emission level in 2005 is estimated at 2.7 GtCO2 per year, which decreases to 0.1 GtCO2 by 2100.Allocation by region is based on distribution of agricultural managed land. It is assumed that LULUCF emissions for UK is zero and therefore, WEU region's LULUCF emission has not been changed. There are scenarios in the model with reduced emissions from deforestation based on the EMF 21 study scenarios.

== Grid and infrastructure ==
No representation of grids in TIAM-UCL except Electricity generation can be centralised or decentralised (CEN or DCN). A generic cost and efficiency loss associated with distribution are included for Gas pipelines and electricity.

The range of CO2 storage technologies in the model are listed below.

'''Table 3.2.6: Types of storage technologies'''

{| class ="wikitable"
|width="100%"|'''Model Technology Description'''
|-
|Removal by Enhanced Coalbed Meth recov <1000 m
|-
|Removal by Enhanced Coalbed Meth recov >1000 m
|-
|Removal by Depl gas fields (offshore)
|-
|Removal by Depl gas fields (onshore)
|-
|Removal by Storage in the deep ocean
|-
|Removal by Depl oil fields (offshore)
|-
|Removal by Depl oil fields (onshore)
|-
|Removal by Deep saline aquifers
|-
|Removal by Enhanced Oil Recovery
|-
|Mineralization for CO2 storage
|}

Gaseous fuels - TIAM-UCL

2016-12-15T21:21:18Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Gaseous fuels
}}
=== Alternative fuels ===

Table 3.2.4 contains technologies for the production of alternative fuels. The technologies are split into two groups: 1) Ethanol and methanol production, either from coal or biomass and 2) Fischer-Tropsch processes, producing oil products from coal, gas and biomass.

'''Table 3.2.4: Alternative fuel technologies'''

{| class="wikitable"
|width="100%"|'''Model Technology Description'''
|-
|Ethanol from biomass
|-
|Cellulose ethanol plant
|-
|Methanol from Bioliquids
|-
|Methanol from coal
|-
|Methanol from coal with CO2 capture
|-
|Methanol from natural gas
|-
|Methanol from natural gas with CCS
|-
|FT fuels from natural gas
|-
|FT fuels from natural gas with CCS
|-
|FT fuels from coal
|-
|FT fuels from coal with CCS
|-
|FT fuels from coal low biomass and coal co production
|-
|FT fuels low biomass and coal co production with CCS
|-
|FT fuels high biomass and coal co production
|-
|FT fuels high biomass and coal co production with CCS
|-
|FT fuels solid biomass
|-
|FT fuels solid biomass with CCS
|}

=== Hydrogen ===

New technologies include those used for hydrogen production and demand technologies in the transport sector that consume hydrogen. Production technologies (name starting 'H') are generic in nature and are defined by the type of fuel used - coal, natural gas, electricity and biomass.

There are also technologies, available from 2020, that allow for mixing of hydrogen into the natural gas supply to different sectors (name starting 'UP'). This mix is fixed at 15% hydrogen / 85% natural gas. A single distribution technology allows for hydrogen transport, with costs developed on the basis of unit of energy transported (using VAROM).

'''Table 3.2.5: Hydrogen production and supply technologies'''

{| class="wikitable"
|width="100%"|'''Model Technology Description'''
|-
|Hydrogen from Brown coal
|-
|Hydrogen from Hard coal
|-
|Electrolysis
|-
|Hydrogen from NGA
|-
|Hydrogen from NGA - Decentralized
|-
|Hydrogen from biomass gasification
|-
|Mix of Gas and Hydrogen - For COM
|-
|Mix of Gas and Hydrogen - For IND
|-
|Mix of Gas and Hydrogen - For RES
|-
|Distribution of hydrogen
|}

Hydrogen technologies for cars and light duty trucks are included in the model, with different types based on the use of combustion, hybrid or fuel cell technology. The associated Trans file puts different hurdle rates on these technologies, assuming 15% for developed regions and 30% for developing regions such as Africa. The Trans file is also used to adjust efficiencies and costs across all regions, for both transport and production technologies.

=== Sequestration ===

Sequestration technologies and storage options mainly relate to the electricity sector, and are described in the relevant sector chapter of this report.

There are two technologies that allow for the capture of CO2 emissions (process-based) in the upstream sector. The costs of such 'dummy' capture technologies are modelled simply, using variable costs of 0.001 (equivalent to $1/tCO2).

Another set of important technologies for integrated climate modelling are those that relate to emissions and removals by the forestry sector. Labelled SINKAF*. The levels of emissions and removals and the associated costs are controlled by the Trans file and are based on assumptions used in the EMF analysis. Finally, atmospheric CO2 may be partly absorbed and fixed by biological sinks such as forests; the model has six options for forestation and avoided deforestation, as described in Sathaye et al. (2005) and adopted by the Energy Modelling Forum, EMF-21 and 22 groups.

=== Land-use CO2 ===

The SubRes file ''LUCO2'' defines a single technology that emits fixed levels of emissions by region each period. It is net CO2 emissions from deforestation and forest degradation. It does not include emissions from land use. The levels are calculated in the associated Trans file. The global emission level in 2005 is estimated at 2.7 GtCO2 per year, which decreases to 0.1 GtCO2 by 2100.Allocation by region is based on distribution of agricultural managed land. It is assumed that LULUCF emissions for UK is zero and therefore, WEU region?s LULUCF emission has not been changed. There are scenarios in the model with reduced emissions from deforestation based on the EMF 21 study scenarios.

== Grid and infrastructure ==
No representation of grids in TIAM-UCL except Electricity generation can be centralised or decentralised (CEN or DCN). A generic cost and efficiency loss associated with distribution are included for Gas pipelines and electricity.

The range of CO2 storage technologies in the model are listed below.

'''Table 3.2.6: Types of storage technologies'''

{| class ="wikitable"
|width="100%"|'''Model Technology Description'''
|-
|Removal by Enhanced Coalbed Meth recov <1000 m
|-
|Removal by Enhanced Coalbed Meth recov >1000 m
|-
|Removal by Depl gas fields (offshore)
|-
|Removal by Depl gas fields (onshore)
|-
|Removal by Storage in the deep ocean
|-
|Removal by Depl oil fields (offshore)
|-
|Removal by Depl oil fields (onshore)
|-
|Removal by Deep saline aquifers
|-
|Removal by Enhanced Oil Recovery
|-
|Mineralization for CO2 storage
|}

Heat - TIAM-UCL

2016-12-15T21:19:18Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Heat
}}
Heat technologies are respresented as

* Public CHP plant, providing electricity to the grid and heat to local distict heating networks
* Sector CHP plant (autoproducers), providing electricity and heat to specific industries.
* Public heat generation plant (heat only plants), providing heat to local distribution networks

Energy conversion - TIAM-UCL

2016-12-15T21:17:48Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Energy conversion
}}
Energy conversion technologies in TIAM-UCL are undertaken by various distinct processes and are generally characterized by a number of data inputs including:

- investment costs

- operation and maintenance costs

- lifetime

- efficiency

- environmental outputs (CO2)

- growth constraints

Also, electricity grids are not explicitly modelled, with no capacity limits or investment requirements for system infrastructure. Two commodities are produced to represent generation from centralised (ELCC) and decentralised (ELCD) technologies. Distribution losses are modelled by commodity efficiency for ELCC (using parameter COM_IE). They reflect regional differences in the base year but by 2100 are the same across all regions. Electricity supply is tracked at a DAYNITE timeslice resolution. This allows for simplistic modelling of the load curve, representing when consumers demand electricity (see section 3 on demand drivers for more information). DAYNITE time-slices total 6 periods, representing day and night in the three (equal length) seasons (summer, winter, intermediate).

Electricity - TIAM-UCL

2016-12-15T21:16:22Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Electricity
}}
== Conversion ==
The electricity and heat generation sector represents many different technology types, using a wide range of fossil-based and renewables resources. The existing system is represented in generic terms whilst the options for future investments are characterised in more detail. Annual electricity and heat supply is temporally disaggregated across six periods (or ''time slices''), based on three season and two diurnal periods (Day / night) to represent changes in load based on sector demand profiles.

Electricity generation plant are additionally categorised as providing electricity to the centralised or decentralised grid (CEN or DCN). Decentralised producers tend to be small scale, connected to the distribution network or serving local grids, and produce one commodity in the model while centralised producers, connected to transmission network, produce a seperate commodity.

The electricity sector Base-Year template is used to calibrate the base-year electricity and heat generation. In the Base-Year template (providing information on existing plant), characterisation of plants is fairly generic, with all production of electricity categorised as ELC-CEN. Off-grid production (via micro-generation technologies) is not explicitly captured in the model, with small-scale generation represented in the decentralised producer group.

[[File:35815674.png]]

'''Figure: Existing Electricity Generation Capacity by Region in 2005 (Model base year), GW'''

[[File:35815675.png]]

'''Figure: Existing Electricity Generation Capacity by Type in 2005 (Model base year), GW'''

== New technologies ==

=== Key technology options ===

New electricity generation technologies are listed in Table.

'''Table: New technology options for electricity'''

{| class= "wikitable"
|width="50%"|'''Technology Group'''
|width="50%"|'''Model Technology Description'''
|-
|'''Coal'''
|Atmospheric Fl Bed.
|-
|''' '''
|Air Blown IGCC.
|-
|''' '''
|Oxygen Blown IGCC.
|-
|''' '''
|Pressurized Fl Bed.
|-
|''' '''
|Pulverized Coal.
|-
|'''Gas'''
|Gas Steam.
|-
|''' '''
|Fuel Cells.
|-
|'''Dual gas / oil'''
|Gas_Oil Comb Cycle.
|-
|''' '''
|Advanced Gas_Oil Turbine.
|-
|'''Oil'''
|Oil Steam.
|-
|''' '''
|Generic Dist Gen for Base Load.
|-
|''' '''
|Generic Dist Gen for Peak Load.
|-
|'''Nuclear'''
|Advanced Nuclear.
|-
|''' '''
|Fusion Nuclear.
|-
|''' '''
|Advanced Nuclear LWR.
|-
|''' '''
|Advanced Nuclear PBMR.
|-
|'''Hydro*'''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic ROR Hydro.
|-
|'''Biomass'''
|Crop Direct Combustion.
|-
|''' '''
|Crop Gasification.
|-
|''' '''
|Biogas from Waste.
|-
|''' '''
|MSW Direct Combustion.
|-
|''' '''
|Sld Biomass Direct Combustion.
|-
|''' '''
|Sld Biomass Gasification.
|-
|''' '''
|Sld Biomass Direct Combustion.Decentralized
|-
|''' '''
|Sld Biomass Gasification.Decentralized
|-
|'''Geothermal'''
|Shallow.
|-
|''' '''
|Deep.
|-
|''' '''
|Very deep.
|-
|'''Solar PV*'''
|CEN.PV.T0
|-
|''' '''
|CEN.PV.
|-
|''' '''
|CEN.PV.T1
|-
|''' '''
|CEN.PV.T2
|-
|''' '''
|CEN.PV.T3
|-
|''' '''
|CEN.PV.T4
|-
|''' '''
|CEN.PV.T5
|-
|''' '''
|DCN.PV.T0
|-
|''' '''
|DCN.PV.
|-
|''' '''
|DCN.PV.T1
|-
|''' '''
|DCN.PV.T2
|-
|''' '''
|PV.T3
|-
|''' '''
|PV.T4
|-
|''' '''
|PV.T5
|-
|'''Solar thermal'''
|CEN.Thermal.
|-
|'''Wind*'''
|CEN.
|-
|''' '''
|CEN.Offshore.
|-
|''' '''
|CEN.Onshore.
|-
|''' '''
|DCN.Onshore.
|}

* Different tranches of renewable technologies represent differences in the cost of resources (hydro) or quality of the resource (wind, solar).

An important element is the transformation element which allows for regional differences to be introduced without having to duplicate technologies. For the electricity sector, the following parameters are controlled, and varied by region:

* Costs parameters (INVCOST, FIXOM and VAROM)''.'' Operation and maintenance costs tend to be lower in developing regions, as do investment cost where those regions have a technology manufacturing base e.g. China.
* Technology discount rate set to 10%, except for solar technologies, where the rate is higher for some regions. Higher rates are typically used for developing regions.
* Seasonal AFs are set by region for solar technologies, accounting for different insolation values.
* Construction time is provided for hydro and nuclear technologies - 10 years for nuclear and hydro (dam) and 5 years for hydro (run-of-river). No differentiation is made between regions.

Further work is required to include new CHP technologies, which are not available for public system or industry investment.

An overview of the key parameters for the different technology groups is shown in below.

'''Table: Overview of technology characteristics by technology group (for WEU region)'''

{|class= "wikitable"
|width="16%"|'''Technology Group'''
|width="16%"|'''Efficiency % (range)'''
|width="16%"|
|width="16%"|'''Investment cost $/kW (range)'''
|width="16%"|
|width="16%"|'''Comment'''
|-
|''' '''
|'''2005'''
|'''2050'''
|'''2005'''
|'''2050'''
| 
|-
|'''Coal'''
|40-49
|40-49
|1430-1870
|1265-1662
| 
|-
|'''Gas / Dual'''
|37-57
|37-57
|360-1000
|300-1000
|Lower cost and higher efficiency values represent combined cycle technology
|-
|'''Oil'''
|31-35
|31-35
|660-1045
|660-1045
| 
|-
|'''Nuclear'''
|
| 
|1760-1870
|1760-1870
|Fusion costs set at 3300 $/kW
|-
|'''Hydro'''
|
| 
|1650-6050
|1540-5400
|Five dam-based technologies reflecting different cost of resource
|-
|'''Biomass'''
|33-34
|33-34
|1870-2200
|1870-2200
|MSW plant significantly higher at 3850 $/kW
|-
|'''Geothermal'''
|
| 
|1925-2780
|1650-2310
|Three geothermal technologies reflecting different cost of resource
|-
|'''Solar PV'''
|
| 
|7150-11000
|1485-3025
|Low cost is centralised plant and high cost decentralised plant. Technology resource tranched on basis of AFs
|-
|'''Solar thermal'''
|
| 
|13321
|13321
|Single technology with no evolution on costs
|-
|'''Wind'''
|
| 
|1065-1650
|880-1310
|One backstop, one offshore (CEN) and 2 onshore (one is CEN and one is DCN) technologies. Offshore tech. represents the high costs.
|}

== Power plants with CCS technologies ==

For low carbon analyses, sequestration technologies in the electricity generation sector are very important.
The first five technologies listed have vintages for 2010, 2020 and 2030.

'''Table: Overview of Power plant with CCS technology characteristics'''

{| class= "wikitable"
|width="33%"|'''Model Technology Description'''
|width="33%"|'''Investment cost ($/kW)'''
|width="33%"|'''Efficiency (%)'''
|-
|NGCC+Oxyfueling
|950-1250
|48-55
|-
|NGCC+CO2 removal from flue gas
|800-1000
|49-57
|-
|IGCC+CO2 removal from input gas
|1800-2300
|40-48
|-
|Conventional Pulverized Coal+Oxyfueling
|1900-2400
|37-44
|-
|Conventional Pulverized Coal+CO2 removal from flue gas
|1850-2250
|38-44
|-
|SOFC (COAL) +CO2 removal - 2030
|2200
|48
|-
|SOFC (GAS) +CO2 removal - 2020
|1600
|58
|-
|Crop Direct Combustion. With CCS
|2125
|33
|-
|Crop Gasification.with CCS
|2500
|34
|-
|Sld Biomass Direct Combustion.with CCS
|1700
|33
|-
|Sld Biomass Gasification.with CCS
|2420
|34
|}

The fossil-based plants produce SNKELCCO2, a 'dummy' commodity which then goes to the different storage technologies. Biomass plants with sequestration produce SNKTOTCO2, differentiated as technologies that capture CO2 from the atmosphere (negative emissions). The range of storage technologies in the model are listed below.

'''Types of storage technologies'''

Removal by Enhanced Coalbed Meth recov <1000 m

Removal by Enhanced Coalbed Meth recov >1000 m

Removal by Depl gas fields (offshore)

Removal by Depl gas fields (onshore)

Removal by Storage in the deep ocean

Removal by Depl oil fields (offshore)

Removal by Depl oil fields (onshore)

Removal by Deep saline aquifers

Removal by Enhanced Oil Recovery

Mineralization for CO2 storage

Electricity - TIAM-UCL

2016-12-15T21:15:18Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Electricity
}}
== Conversion ==
The electricity and heat generation sector represents many different technology types, using a wide range of fossil-based and renewables resources. The existing system is represented in generic terms whilst the options for future investments are characterised in more detail. Annual electricity and heat supply is temporally disaggregated across six periods (or ''time slices''), based on three season and two diurnal periods (Day / night) to represent changes in load based on sector demand profiles.

Electricity generation plant are additionally categorised as providing electricity to the centralised or decentralised grid (CEN or DCN). Decentralised producers tend to be small scale, connected to the distribution network or serving local grids, and produce one commodity in the model while centralised producers, connected to transmission network, produce a seperate commodity.

The electricity sector Base-Year template is used to calibrate the base-year electricity and heat generation. In the Base-Year template (providing information on existing plant), characterisation of plants is fairly generic, with all production of electricity categorised as ELC-CEN. Off-grid production (via micro-generation technologies) is not explicitly captured in the model, with small-scale generation represented in the decentralised producer group.

[[File:35815674.png]]

'''Figure: Existing Electricity Generation Capacity by Region in 2005 (Model base year), GW'''

[[File:35815675.png]]

'''Figure: Existing Electricity Generation Capacity by Type in 2005 (Model base year), GW'''

== New technologies ==

=== Key technology options ===

New electricity generation technologies are listed in Table.

'''Table: New technology options for electricity'''

{| class= "wikitable"
|width="50%"|'''Technology Group'''
|width="50%"|'''Model Technology Description'''
|-
|'''Coal'''
|Atmospheric Fl Bed.
|-
|''' '''
|Air Blown IGCC.
|-
|''' '''
|Oxygen Blown IGCC.
|-
|''' '''
|Pressurized Fl Bed.
|-
|''' '''
|Pulverized Coal.
|-
|'''Gas'''
|Gas Steam.
|-
|''' '''
|Fuel Cells.
|-
|'''Dual gas / oil'''
|Gas_Oil Comb Cycle.
|-
|''' '''
|Advanced Gas_Oil Turbine.
|-
|'''Oil'''
|Oil Steam.
|-
|''' '''
|Generic Dist Gen for Base Load.
|-
|''' '''
|Generic Dist Gen for Peak Load.
|-
|'''Nuclear'''
|Advanced Nuclear.
|-
|''' '''
|Fusion Nuclear.
|-
|''' '''
|Advanced Nuclear LWR.
|-
|''' '''
|Advanced Nuclear PBMR.
|-
|'''Hydro*'''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic ROR Hydro.
|-
|'''Biomass'''
|Crop Direct Combustion.
|-
|''' '''
|Crop Gasification.
|-
|''' '''
|Biogas from Waste.
|-
|''' '''
|MSW Direct Combustion.
|-
|''' '''
|Sld Biomass Direct Combustion.
|-
|''' '''
|Sld Biomass Gasification.
|-
|''' '''
|Sld Biomass Direct Combustion.Decentralized
|-
|''' '''
|Sld Biomass Gasification.Decentralized
|-
|'''Geothermal'''
|Shallow.
|-
|''' '''
|Deep.
|-
|''' '''
|Very deep.
|-
|'''Solar PV*'''
|CEN.PV.T0
|-
|''' '''
|CEN.PV.
|-
|''' '''
|CEN.PV.T1
|-
|''' '''
|CEN.PV.T2
|-
|''' '''
|CEN.PV.T3
|-
|''' '''
|CEN.PV.T4
|-
|''' '''
|CEN.PV.T5
|-
|''' '''
|DCN.PV.T0
|-
|''' '''
|DCN.PV.
|-
|''' '''
|DCN.PV.T1
|-
|''' '''
|DCN.PV.T2
|-
|''' '''
|PV.T3
|-
|''' '''
|PV.T4
|-
|''' '''
|PV.T5
|-
|'''Solar thermal'''
|CEN.Thermal.
|-
|'''Wind*'''
|CEN.
|-
|''' '''
|CEN.Offshore.
|-
|''' '''
|CEN.Onshore.
|-
|''' '''
|DCN.Onshore.
|}

* Different tranches of renewable technologies represent differences in the cost of resources (hydro) or quality of the resource (wind, solar).

An important element is the transformation element which allows for regional differences to be introduced without having to duplicate technologies. For the electricity sector, the following parameters are controlled, and varied by region:

* Costs parameters (INVCOST, FIXOM and VAROM)''.'' Operation and maintenance costs tend to be lower in developing regions, as do investment cost where those regions have a technology manufacturing base e.g. China.
* Technology discount rate set to 10%, except for solar technologies, where the rate is higher for some regions. Higher rates are typically used for developing regions.
* Seasonal AFs are set by region for solar technologies, accounting for different insolation values.
* Construction time is provided for hydro and nuclear technologies - 10 years for nuclear and hydro (dam) and 5 years for hydro (run-of-river). No differentiation is made between regions.

Further work is required to include new CHP technologies, which are not available for public system or industry investment.

An overview of the key parameters for the different technology groups is shown in below.

'''Table: Overview of technology characteristics by technology group (for WEU region)'''

{|class= "wikitable"
|width="16%"|'''Technology Group'''
|width="16%"|'''Efficiency % (range)'''
|width="16%"|
|width="16%"|'''Investment cost $/kW (range)'''
|width="16%"|
|width="16%"|'''Comment'''
|-
|''' '''
|'''2005'''
|'''2050'''
|'''2005'''
|'''2050'''
| 
|-
|'''Coal'''
|40-49
|40-49
|1430-1870
|1265-1662
| 
|-
|'''Gas / Dual'''
|37-57
|37-57
|360-1000
|300-1000
|Lower cost and higher efficiency values represent combined cycle technology
|-
|'''Oil'''
|31-35
|31-35
|660-1045
|660-1045
| 
|-
|'''Nuclear'''
|
| 
|1760-1870
|1760-1870
|Fusion costs set at 3300 $/kW
|-
|'''Hydro'''
|
| 
|1650-6050
|1540-5400
|Five dam-based technologies reflecting different cost of resource
|-
|'''Biomass'''
|33-34
|33-34
|1870-2200
|1870-2200
|MSW plant significantly higher at 3850 $/kW
|-
|'''Geothermal'''
|
| 
|1925-2780
|1650-2310
|Three geothermal technologies reflecting different cost of resource
|-
|'''Solar PV'''
|
| 
|7150-11000
|1485-3025
|Low cost is centralised plant and high cost decentralised plant. Technology resource tranched on basis of AFs
|-
|'''Solar thermal'''
|
| 
|13321
|13321
|Single technology with no evolution on costs
|-
|'''Wind'''
|
| 
|1065-1650
|880-1310
|One backstop, one offshore (CEN) and 2 onshore (one is CEN and one is DCN) technologies. Offshore tech. represents the high costs.
|}

== Power plants with CCS technologies ==

For low carbon analyses, sequestration technologies in the electricity generation sector are very important.
The first five technologies listed have vintages for 2010, 2020 and 2030.

'''Table: Overview of Power plant with CCS technology characteristics'''

{| class= "wikitable"
|width="33%"|'''Model Technology Description'''
|width="33%"|'''Investment cost ($/kW)'''
|width="33%"|'''Efficiency (%)'''
|-
|NGCC+Oxyfueling
|950-1250
|48-55
|-
|NGCC+CO2 removal from flue gas
|800-1000
|49-57
|-
|IGCC+CO2 removal from input gas
|1800-2300
|40-48
|-
|Conventional Pulverized Coal+Oxyfueling
|1900-2400
|37-44
|-
|Conventional Pulverized Coal+CO2 removal from flue gas
|1850-2250
|38-44
|-
|SOFC (COAL) +CO2 removal - 2030
|2200
|48
|-
|SOFC (GAS) +CO2 removal - 2020
|1600
|58
|-
|Crop Direct Combustion. With CCS
|2125
|33
|-
|Crop Gasification.with CCS
|2500
|34
|-
|Sld Biomass Direct Combustion.with CCS
|1700
|33
|-
|Sld Biomass Gasification.with CCS
|2420
|34
|}

The fossil-based plants produce SNKELCCO2, a 'dummy' commodity which then goes to the different storage technologies. Biomass plants with sequestration produce SNKTOTCO2, differentiated as technologies that capture CO2 from the atmosphere (negative emissions). The range of storage technologies in the model are listed below.

'''Types of storage technologies'''

Removal by Enhanced Coalbed Meth recov <1000 m
Removal by Enhanced Coalbed Meth recov >1000 m
Removal by Depl gas fields (offshore)
Removal by Depl gas fields (onshore)
Removal by Storage in the deep ocean
Removal by Depl oil fields (offshore)
Removal by Depl oil fields (onshore)
Removal by Deep saline aquifers
Removal by Enhanced Oil Recovery
Mineralization for CO2 storage

Technologies listed above capture SNKELCCO2.

Electricity - TIAM-UCL

2016-12-15T21:10:48Z

Matthew Winning:

Electricity - TIAM-UCL

2016-12-15T21:05:30Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Electricity
}}
== Conversion ==
The electricity and heat generation sector represents many different technology types, using a wide range of fossil-based and renewables resources. The existing system is represented in generic terms whilst the options for future investments are characterised in more detail. Annual electricity and heat supply is temporally disaggregated across six periods (or ''time slices''), based on three season and two diurnal periods (Day / night) to represent changes in load based on sector demand profiles.

Electricity generation plant are additionally categorised as providing electricity to the centralised or decentralised grid (CEN or DCN). Decentralised producers tend to be small scale, connected to the distribution network or serving local grids, and produce one commodity in the model while centralised producers, connected to transmission network, produce a seperate commodity.

The electricity sector Base-Year template is used to calibrate the base-year electricity and heat generation. In the Base-Year template (providing information on existing plant), characterisation of plants is fairly generic, with all production of electricity categorised as ELC-CEN. Off-grid production (via micro-generation technologies) is not explicitly captured in the model, with small-scale generation represented in the decentralised producer group.

[[File:35815674.png]]

'''Figure: Existing Electricity Generation Capacity by Region in 2005 (Model base year), GW'''

[[File:35815675.png]]

'''Figure: Existing Electricity Generation Capacity by Type in 2005 (Model base year), GW'''

== New technologies ==

=== Key technology options ===

New electricity generation technologies are listed in Table.

'''Table: New technology options for electricity'''

{| class= "wikitable"
|width="50%"|'''Technology Group'''
|width="50%"|'''Model Technology Description'''
|-
|'''Coal'''
|Atmospheric Fl Bed.
|-
|''' '''
|Air Blown IGCC.
|-
|''' '''
|Oxygen Blown IGCC.
|-
|''' '''
|Pressurized Fl Bed.
|-
|''' '''
|Pulverized Coal.
|-
|'''Gas'''
|Gas Steam.
|-
|''' '''
|Fuel Cells.
|-
|'''Dual gas / oil'''
|Gas_Oil Comb Cycle.
|-
|''' '''
|Advanced Gas_Oil Turbine.
|-
|'''Oil'''
|Oil Steam.
|-
|''' '''
|Generic Dist Gen for Base Load.
|-
|''' '''
|Generic Dist Gen for Peak Load.
|-
|'''Nuclear'''
|Advanced Nuclear.
|-
|''' '''
|Fusion Nuclear.
|-
|''' '''
|Advanced Nuclear LWR.
|-
|''' '''
|Advanced Nuclear PBMR.
|-
|'''Hydro*'''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic ROR Hydro.
|-
|'''Biomass'''
|Crop Direct Combustion.
|-
|''' '''
|Crop Gasification.
|-
|''' '''
|Biogas from Waste.
|-
|''' '''
|MSW Direct Combustion.
|-
|''' '''
|Sld Biomass Direct Combustion.
|-
|''' '''
|Sld Biomass Gasification.
|-
|''' '''
|Sld Biomass Direct Combustion.Decentralized
|-
|''' '''
|Sld Biomass Gasification.Decentralized
|-
|'''Geothermal'''
|Shallow.
|-
|''' '''
|Deep.
|-
|''' '''
|Very deep.
|-
|'''Solar PV*'''
|CEN.PV.T0
|-
|''' '''
|CEN.PV.
|-
|''' '''
|CEN.PV.T1
|-
|''' '''
|CEN.PV.T2
|-
|''' '''
|CEN.PV.T3
|-
|''' '''
|CEN.PV.T4
|-
|''' '''
|CEN.PV.T5
|-
|''' '''
|DCN.PV.T0
|-
|''' '''
|DCN.PV.
|-
|''' '''
|DCN.PV.T1
|-
|''' '''
|DCN.PV.T2
|-
|''' '''
|PV.T3
|-
|''' '''
|PV.T4
|-
|''' '''
|PV.T5
|-
|'''Solar thermal'''
|CEN.Thermal.
|-
|'''Wind*'''
|CEN.
|-
|''' '''
|CEN.Offshore.
|-
|''' '''
|CEN.Onshore.
|-
|''' '''
|DCN.Onshore.
|}

* Different tranches of renewable technologies represent differences in the cost of resources (hydro) or quality of the resource (wind, solar).

An important element is the transformation element which allows for regional differences to be introduced without having to duplicate technologies. For the electricity sector, the following parameters are controlled, and varied by region:

* Costs parameters (INVCOST, FIXOM and VAROM)''.'' Operation and maintenance costs tend to be lower in developing regions, as do investment cost where those regions have a technology manufacturing base e.g. China.
* Technology discount rate set to 10%, except for solar technologies, where the rate is higher for some regions. Higher rates are typically used for developing regions.
* Seasonal AFs are set by region for solar technologies, accounting for different insolation values.
* Construction time is provided for hydro and nuclear technologies - 10 years for nuclear and hydro (dam) and 5 years for hydro (run-of-river). No differentiation is made between regions.

Further work is required to include new CHP technologies, which are not available for public system or industry investment.

An overview of the key parameters for the different technology groups is shown in below.

'''Table: Overview of technology characteristics by technology group (for WEU region)'''

{|class= "wikitable"
|width="16%"|'''Technology Group'''
|width="16%"|'''Efficiency % (range)'''
|width="16%"|
|width="16%"|'''Investment cost $/kW (range)'''
|width="16%"|
|width="16%"|'''Comment'''
|-
|''' '''
|'''2005'''
|'''2050'''
|'''2005'''
|'''2050'''
| 
|-
|'''Coal'''
|40-49
|40-49
|1430-1870
|1265-1662
| 
|-
|'''Gas / Dual'''
|37-57
|37-57
|360-1000
|300-1000
|Lower cost and higher efficiency values represent combined cycle technology
|-
|'''Oil'''
|31-35
|31-35
|660-1045
|660-1045
| 
|-
|'''Nuclear'''
|
| 
|1760-1870
|1760-1870
|Fusion costs set at 3300 $/kW
|-
|'''Hydro'''
|
| 
|1650-6050
|1540-5400
|Five dam-based technologies reflecting different cost of resource
|-
|'''Biomass'''
|33-34
|33-34
|1870-2200
|1870-2200
|MSW plant significantly higher at 3850 $/kW
|-
|'''Geothermal'''
|
| 
|1925-2780
|1650-2310
|Three geothermal technologies reflecting different cost of resource
|-
|'''Solar PV'''
|
| 
|7150-11000
|1485-3025
|Low cost is centralised plant and high cost decentralised plant. Technology resource tranched on basis of AFs
|-
|'''Solar thermal'''
|
| 
|13321
|13321
|Single technology with no evolution on costs
|-
|'''Wind'''
|
| 
|1065-1650
|880-1310
|One backstop, one offshore (CEN) and 2 onshore (one is CEN and one is DCN) technologies. Offshore tech. represents the high costs.
|}

== Power plants with CCS technologies ==

For low carbon analyses, sequestration technologies in the electricity generation sector are very important.

'''Table: Overview of Power plant with CCS technology characteristics'''

{| class= "wikitable"
|width="33%"|'''Model Technology Description'''
|width="33%"|'''Investment cost ($/kW)'''
|width="33%"|'''Efficiency (%)'''
|-
|NGCC+Oxyfueling
|950-1250
|48-55
|-
|NGCC+CO2 removal from flue gas
|800-1000
|49-57
|-
|IGCC+CO2 removal from input gas
|1800-2300
|40-48
|-
|Conventional Pulverized Coal+Oxyfueling
|1900-2400
|37-44
|-
|Conventional Pulverized Coal+CO2 removal from flue gas
|1850-2250
|38-44
|-
|SOFC (COAL) +CO2 removal - 2030
|2200
|48
|-
|SOFC (GAS) +CO2 removal - 2020
|1600
|58
|-
|Crop Direct Combustion. With CCS
|2125
|33
|-
|Crop Gasification.with CCS
|2500
|34
|-
|Sld Biomass Direct Combustion.with CCS
|1700
|33
|-
|Sld Biomass Gasification.with CCS
|2420
|34
|}

* The first five technologies listed have vintages for 2010, 2020 and 2030.

Electricity - TIAM-UCL

2016-12-15T20:53:03Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Electricity
}}
== Conversion ==
The electricity and heat generation sector represents many different technology types, using a wide range of fossil-based and renewables resources. The existing system is represented in generic terms whilst the options for future investments are characterised in more detail. Annual electricity and heat supply is temporally disaggregated across six periods (or ''time slices''), based on three season and two diurnal periods (Day / night) to represent changes in load based on sector demand profiles.

Electricity generation plant are additionally categorised as providing electricity to the centralised or decentralised grid (CEN or DCN). Decentralised producers tend to be small scale, connected to the distribution network or serving local grids, and produce one commodity in the model while centralised producers, connected to transmission network, produce a seperate commodity.

The electricity sector Base-Year template is used to calibrate the base-year electricity and heat generation. In the Base-Year template (providing information on existing plant), characterisation of plants is fairly generic, with all production of electricity categorised as ELC-CEN. Off-grid production (via micro-generation technologies) is not explicitly captured in the model, with small-scale generation represented in the decentralised producer group.

[[File:35815674.png]]

'''Figure: Existing Electricity Generation Capacity by Region in 2005 (Model base year), GW'''

[[File:35815675.png]]

'''Figure: Existing Electricity Generation Capacity by Type in 2005 (Model base year), GW'''

== New technologies ==

=== Key technology options ===

New electricity generation technologies are listed in Table.

'''Table: New technology options for electricity'''

{| class= "wikitable"
|width="50%"|'''Technology Group'''
|width="50%"|'''Model Technology Description'''
|-
|'''Coal'''
|Atmospheric Fl Bed.
|-
|''' '''
|Air Blown IGCC.
|-
|''' '''
|Oxygen Blown IGCC.
|-
|''' '''
|Pressurized Fl Bed.
|-
|''' '''
|Pulverized Coal.
|-
|'''Gas'''
|Gas Steam.
|-
|''' '''
|Fuel Cells.
|-
|'''Dual gas / oil'''
|Gas_Oil Comb Cycle.
|-
|''' '''
|Advanced Gas_Oil Turbine.
|-
|'''Oil'''
|Oil Steam.
|-
|''' '''
|Generic Dist Gen for Base Load.
|-
|''' '''
|Generic Dist Gen for Peak Load.
|-
|'''Nuclear'''
|Advanced Nuclear.
|-
|''' '''
|Fusion Nuclear.
|-
|''' '''
|Advanced Nuclear LWR.
|-
|''' '''
|Advanced Nuclear PBMR.
|-
|'''Hydro*'''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic ROR Hydro.
|-
|'''Biomass'''
|Crop Direct Combustion.
|-
|''' '''
|Crop Gasification.
|-
|''' '''
|Biogas from Waste.
|-
|''' '''
|MSW Direct Combustion.
|-
|''' '''
|Sld Biomass Direct Combustion.
|-
|''' '''
|Sld Biomass Gasification.
|-
|''' '''
|Sld Biomass Direct Combustion.Decentralized
|-
|''' '''
|Sld Biomass Gasification.Decentralized
|-
|'''Geothermal'''
|Shallow.
|-
|''' '''
|Deep.
|-
|''' '''
|Very deep.
|-
|'''Solar PV*'''
|CEN.PV.T0
|-
|''' '''
|CEN.PV.
|-
|''' '''
|CEN.PV.T1
|-
|''' '''
|CEN.PV.T2
|-
|''' '''
|CEN.PV.T3
|-
|''' '''
|CEN.PV.T4
|-
|''' '''
|CEN.PV.T5
|-
|''' '''
|DCN.PV.T0
|-
|''' '''
|DCN.PV.
|-
|''' '''
|DCN.PV.T1
|-
|''' '''
|DCN.PV.T2
|-
|''' '''
|PV.T3
|-
|''' '''
|PV.T4
|-
|''' '''
|PV.T5
|-
|'''Solar thermal'''
|CEN.Thermal.
|-
|'''Wind*'''
|CEN.
|-
|''' '''
|CEN.Offshore.
|-
|''' '''
|CEN.Onshore.
|-
|''' '''
|DCN.Onshore.
|}

* Different tranches of renewable technologies represent differences in the cost of resources (hydro) or quality of the resource (wind, solar).

The other important file is the transformation file, which allows for regional differences to be introduced without having to duplicate technologies. For the electricity sector, the following parameters are controlled, and varied by region:

* Costs parameters (INVCOST, FIXOM and VAROM)''.'' Operation and maintenance costs tend to be lower in developing regions, as do investment cost where those regions have a technology manufacturing base e.g. China.
* Technology discount rate set to 10%, except for solar technologies, where the rate is higher for some regions. Higher rates are typically used for developing regions.
* Seasonal AFs are set by region for solar technologies, accounting for different insolation values.
* Construction time is provided for hydro and nuclear technologies - 10 years for nuclear and hydro (dam) and 5 years for hydro (run-of-river). No differentiation is made between regions.

Further work is required to include new CHP technologies, which are not available for public system or industry investment.

An overview of the key parameters for the different technology groups is shown in below.

'''Table: Overview of technology characteristics by technology group (for WEU region)'''

{|class= "wikitable"
|width="16%"|'''Technology Group'''
|width="16%"|'''Efficiency % (range)'''
|width="16%"|
|width="16%"|'''Investment cost $/kW (range)'''
|width="16%"|
|width="16%"|'''Comment'''
|-
|''' '''
|'''2005'''
|'''2050'''
|'''2005'''
|'''2050'''
| 
|-
|'''Coal'''
|40-49
|40-49
|1430-1870
|1265-1662
| 
|-
|'''Gas / Dual'''
|37-57
|37-57
|360-1000
|300-1000
|Lower cost and higher efficiency values represent combined cycle technology
|-
|'''Oil'''
|31-35
|31-35
|660-1045
|660-1045
| 
|-
|'''Nuclear'''
|
| 
|1760-1870
|1760-1870
|Fusion costs set at 3300 $/kW
|-
|'''Hydro'''
|
| 
|1650-6050
|1540-5400
|Five dam-based technologies reflecting different cost of resource
|-
|'''Biomass'''
|33-34
|33-34
|1870-2200
|1870-2200
|MSW plant significantly higher at 3850 $/kW
|-
|'''Geothermal'''
|
| 
|1925-2780
|1650-2310
|Three geothermal technologies reflecting different cost of resource
|-
|'''Solar PV'''
|
| 
|7150-11000
|1485-3025
|Low cost is centralised plant and high cost decentralised plant. Technology resource tranched on basis of AFs
|-
|'''Solar thermal'''
|
| 
|13321
|13321
|Single technology with no evolution on costs
|-
|'''Wind'''
|
| 
|1065-1650
|880-1310
|One backstop, one offshore (CEN) and 2 onshore (one is CEN and one is DCN) technologies. Offshore tech. represents the high costs.
|}

== Power plants with CCS technologies ==

For low carbon analyses, sequestration technologies in the electricity generation sector are very important.

'''Table: Overview of Power plant with CCS technology characteristics'''

{| class= "wikitable"
|width="33%"|'''Model Technology Description'''
|width="33%"|'''Investment cost ($/kW)'''
|width="33%"|'''Efficiency (%)'''
|-
|NGCC+Oxyfueling
|950-1250
|48-55
|-
|NGCC+CO2 removal from flue gas
|800-1000
|49-57
|-
|IGCC+CO2 removal from input gas
|1800-2300
|40-48
|-
|Conventional Pulverized Coal+Oxyfueling
|1900-2400
|37-44
|-
|Conventional Pulverized Coal+CO2 removal from flue gas
|1850-2250
|38-44
|-
|SOFC (COAL) +CO2 removal - 2030
|2200
|48
|-
|SOFC (GAS) +CO2 removal - 2020
|1600
|58
|-
|Crop Direct Combustion. With CCS
|2125
|33
|-
|Crop Gasification.with CCS
|2500
|34
|-
|Sld Biomass Direct Combustion.with CCS
|1700
|33
|-
|Sld Biomass Gasification.with CCS
|2420
|34
|}

* The first five technologies listed have vintages for 2010, 2020 and 2030.

Electricity - TIAM-UCL

2016-12-15T20:52:10Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Electricity
}}
== Conversion ==
The electricity and heat generation sector represents many different technology types, using a wide range of fossil-based and renewables resources. The existing system is represented in generic terms whilst the options for future investments are characterised in more detail. Annual electricity and heat supply is temporally disaggregated across six periods (or ''time slices''), based on three season and two diurnal periods (Day / night) to represent changes in load based on sector demand profiles.

Electricity generation plant are additionally categorised as providing electricity to the centralised or decentralised grid (CEN or DCN). Decentralised producers tend to be small scale, connected to the distribution network or serving local grids, and produce one commodity in the model while centralised producers, connected to transmission network, produce a seperate commodity.

The electricity sector Base-Year template is used to calibrate the base-year electricity and heat generation. In the Base-Year template (providing information on existing plant), characterisation of plants is fairly generic, with all production of electricity categorised as ELC-CEN. Off-grid production (via micro-generation technologies) is not explicitly captured in the model, with small-scale generation represented in the decentralised producer group.

[[File:35815674.png]]

'''Figure: Existing Electricity Generation Capacity by Region in 2005 (Model base year), GW'''

[[File:35815675.png]]

'''Figure: Existing Electricity Generation Capacity by Type in 2005 (Model base year), GW'''

== New technologies ==

=== Key technology options ===

New electricity generation technologies are listed in Table.

'''Table: New technology options for electricity'''

{| class= "wikitable"
|width="50%"|'''Technology Group'''
|width="50%"|'''Model Technology Description'''
|-
|'''Coal'''
|Atmospheric Fl Bed.
|-
|''' '''
|Air Blown IGCC.
|-
|''' '''
|Oxygen Blown IGCC.
|-
|''' '''
|Pressurized Fl Bed.
|-
|''' '''
|Pulverized Coal.
|-
|'''Gas'''
|Gas Steam.
|-
|''' '''
|Fuel Cells.
|-
|'''Dual gas / oil'''
|Gas_Oil Comb Cycle.
|-
|''' '''
|Advanced Gas_Oil Turbine.
|-
|'''Oil'''
|Oil Steam.
|-
|''' '''
|Generic Dist Gen for Base Load.
|-
|''' '''
|Generic Dist Gen for Peak Load.
|-
|'''Nuclear'''
|Advanced Nuclear.
|-
|''' '''
|Fusion Nuclear.
|-
|''' '''
|Advanced Nuclear LWR.
|-
|''' '''
|Advanced Nuclear PBMR.
|-
|'''Hydro*'''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic ROR Hydro.
|-
|'''Biomass'''
|Crop Direct Combustion.
|-
|''' '''
|Crop Gasification.
|-
|''' '''
|Biogas from Waste.
|-
|''' '''
|MSW Direct Combustion.
|-
|''' '''
|Sld Biomass Direct Combustion.
|-
|''' '''
|Sld Biomass Gasification.
|-
|''' '''
|Sld Biomass Direct Combustion.Decentralized
|-
|''' '''
|Sld Biomass Gasification.Decentralized
|-
|'''Geothermal'''
|Shallow.
|-
|''' '''
|Deep.
|-
|''' '''
|Very deep.
|-
|'''Solar PV*'''
|CEN.PV.T0
|-
|''' '''
|CEN.PV.
|-
|''' '''
|CEN.PV.T1
|-
|''' '''
|CEN.PV.T2
|-
|''' '''
|CEN.PV.T3
|-
|''' '''
|CEN.PV.T4
|-
|''' '''
|CEN.PV.T5
|-
|''' '''
|DCN.PV.T0
|-
|''' '''
|DCN.PV.
|-
|''' '''
|DCN.PV.T1
|-
|''' '''
|DCN.PV.T2
|-
|''' '''
|PV.T3
|-
|''' '''
|PV.T4
|-
|''' '''
|PV.T5
|-
|'''Solar thermal'''
|CEN.Thermal.
|-
|'''Wind*'''
|CEN.
|-
|''' '''
|CEN.Offshore.
|-
|''' '''
|CEN.Onshore.
|-
|''' '''
|DCN.Onshore.
|}

* Different tranches of renewable technologies represent differences in the cost of resources (hydro) or quality of the resource (wind, solar).

The other important file is the transformation file, which allows for regional differences to be introduced without having to duplicate technologies. For the electricity sector, the following parameters are controlled, and varied by region:

* Costs parameters (INVCOST, FIXOM and VAROM)''.'' Operation and maintenance costs tend to be lower in developing regions, as do investment cost where those regions have a technology manufacturing base e.g. China.
* Technology discount rate set to 10%, except for solar technologies, where the rate is higher for some regions. Higher rates are typically used for developing regions.
* Seasonal AFs are set by region for solar technologies, accounting for different insolation values.
* Construction time is provided for hydro and nuclear technologies - 10 years for nuclear and hydro (dam) and 5 years for hydro (run-of-river). No differentiation is made between regions.

Further work is required to include new CHP technologies, which are not available for public system or industry investment.

An overview of the key parameters for the different technology groups is shown in below.

'''Table 3.2.2: Overview of technology characteristics by technology group (for WEU region)'''

{|class= "wikitable"
|width="16%"|'''Technology Group'''
|width="16%"|'''Efficiency % (range)'''
|width="16%"|
|width="16%"|'''Investment cost $/kW (range)'''
|width="16%"|
|width="16%"|'''Comment'''
|-
|''' '''
|'''2005'''
|'''2050'''
|'''2005'''
|'''2050'''
| 
|-
|'''Coal'''
|40-49
|40-49
|1430-1870
|1265-1662
| 
|-
|'''Gas / Dual'''
|37-57
|37-57
|360-1000
|300-1000
|Lower cost and higher efficiency values represent combined cycle technology
|-
|'''Oil'''
|31-35
|31-35
|660-1045
|660-1045
| 
|-
|'''Nuclear'''
|
| 
|1760-1870
|1760-1870
|Fusion costs set at 3300 $/kW
|-
|'''Hydro'''
|
| 
|1650-6050
|1540-5400
|Five dam-based technologies reflecting different cost of resource
|-
|'''Biomass'''
|33-34
|33-34
|1870-2200
|1870-2200
|MSW plant significantly higher at 3850 $/kW
|-
|'''Geothermal'''
|
| 
|1925-2780
|1650-2310
|Three geothermal technologies reflecting different cost of resource
|-
|'''Solar PV'''
|
| 
|7150-11000
|1485-3025
|Low cost is centralised plant and high cost decentralised plant. Technology resource tranched on basis of AFs
|-
|'''Solar thermal'''
|
| 
|13321
|13321
|Single technology with no evolution on costs
|-
|'''Wind'''
|
| 
|1065-1650
|880-1310
|One backstop, one offshore (CEN) and 2 onshore (one is CEN and one is DCN) technologies. Offshore tech. represents the high costs.
|}

== Power plants with CCS technologies ==

For low carbon analyses, sequestration technologies in the electricity generation sector are very important.

'''Table 3.2.3: Overview of Power plant with CCS technology characteristics'''

{| class= "wikitable"
|width="33%"|'''Model Technology Description'''
|width="33%"|'''Investment cost ($/kW)'''
|width="33%"|'''Efficiency (%)'''
|-
|NGCC+Oxyfueling
|950-1250
|48-55
|-
|NGCC+CO2 removal from flue gas
|800-1000
|49-57
|-
|IGCC+CO2 removal from input gas
|1800-2300
|40-48
|-
|Conventional Pulverized Coal+Oxyfueling
|1900-2400
|37-44
|-
|Conventional Pulverized Coal+CO2 removal from flue gas
|1850-2250
|38-44
|-
|SOFC (COAL) +CO2 removal - 2030
|2200
|48
|-
|SOFC (GAS) +CO2 removal - 2020
|1600
|58
|-
|Crop Direct Combustion. With CCS
|2125
|33
|-
|Crop Gasification.with CCS
|2500
|34
|-
|Sld Biomass Direct Combustion.with CCS
|1700
|33
|-
|Sld Biomass Gasification.with CCS
|2420
|34
|}

* The first five technologies listed have vintages for 2010, 2020 and 2030.

Electricity - TIAM-UCL

2016-12-15T20:48:30Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Electricity
}}
== Conversion ==
The electricity and heat generation sector represents many different technology types, using a wide range of fossil-based and renewables resources. The existing system is represented in generic terms whilst the options for future investments are characterised in more detail. Annual electricity and heat supply is temporally disaggregated across six periods (or ''time slices''), based on three season and two diurnal periods (Day / night) to represent changes in load based on sector demand profiles.

Electricity generation plant are additionally categorised as providing electricity to the centralised or decentralised grid (CEN or DCN). Decentralised producers tend to be small scale, connected to the distribution network or serving local grids, and produce one commodity in the model while centralised producers, connected to transmission network, produce a seperate commodity.

The electricity sector Base-Year template is used to calibrate the base-year electricity and heat generation. In the Base-Year template (providing information on existing plant), characterisation of plants is fairly generic, with all production of electricity categorised as ELC-CEN. Off-grid production (via micro-generation technologies) is not explicitly captured in the model, with small-scale generation represented in the decentralised producer group.

[[File:35815674.png]]

'''Figure: Existing Electricity Generation Capacity by Region in 2005 (Model base year), GW'''

[[File:35815675.png]]

'''Figure: Existing Electricity Generation Capacity by Type in 2005 (Model base year), GW'''

== New technologies ==

=== Key technology options ===

New electricity generation technologies are listed in Table 3.2.1. Further work is required to include new CHP technologies, which are not available for public system or industry investment.

'''Table: New technology options for electricity'''

{| class= "wikitable"
|width="50%"|'''Technology Group'''
|width="50%"|'''Model Technology Description'''
|-
|'''Coal'''
|Atmospheric Fl Bed.
|-
|''' '''
|Air Blown IGCC.
|-
|''' '''
|Oxygen Blown IGCC.
|-
|''' '''
|Pressurized Fl Bed.
|-
|''' '''
|Pulverized Coal.
|-
|'''Gas'''
|Gas Steam.
|-
|''' '''
|Fuel Cells.
|-
|'''Dual gas / oil'''
|Gas_Oil Comb Cycle.
|-
|''' '''
|Advanced Gas_Oil Turbine.
|-
|'''Oil'''
|Oil Steam.
|-
|''' '''
|Generic Dist Gen for Base Load.
|-
|''' '''
|Generic Dist Gen for Peak Load.
|-
|'''Nuclear'''
|Advanced Nuclear.
|-
|''' '''
|Fusion Nuclear.
|-
|''' '''
|Advanced Nuclear LWR.
|-
|''' '''
|Advanced Nuclear PBMR.
|-
|'''Hydro*'''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic ROR Hydro.
|-
|'''Biomass'''
|Crop Direct Combustion.
|-
|''' '''
|Crop Gasification.
|-
|''' '''
|Biogas from Waste.
|-
|''' '''
|MSW Direct Combustion.
|-
|''' '''
|Sld Biomass Direct Combustion.
|-
|''' '''
|Sld Biomass Gasification.
|-
|''' '''
|Sld Biomass Direct Combustion.Decentralized
|-
|''' '''
|Sld Biomass Gasification.Decentralized
|-
|'''Geothermal'''
|Shallow.
|-
|''' '''
|Deep.
|-
|''' '''
|Very deep.
|-
|'''Solar PV*'''
|CEN.PV.T0
|-
|''' '''
|CEN.PV.
|-
|''' '''
|CEN.PV.T1
|-
|''' '''
|CEN.PV.T2
|-
|''' '''
|CEN.PV.T3
|-
|''' '''
|CEN.PV.T4
|-
|''' '''
|CEN.PV.T5
|-
|''' '''
|DCN.PV.T0
|-
|''' '''
|DCN.PV.
|-
|''' '''
|DCN.PV.T1
|-
|''' '''
|DCN.PV.T2
|-
|''' '''
|PV.T3
|-
|''' '''
|PV.T4
|-
|''' '''
|PV.T5
|-
|'''Solar thermal'''
|CEN.Thermal.
|-
|'''Wind*'''
|CEN.
|-
|''' '''
|CEN.Offshore.
|-
|''' '''
|CEN.Onshore.
|-
|''' '''
|DCN.Onshore.
|}

* Different tranches of renewable technologies represent differences in the cost of resources (hydro) or quality of the resource (wind, solar).

The other important file is the transformation file, which allows for regional differences to be introduced without having to duplicate technologies. For the electricity sector, the following parameters are controlled, and varied by region:

* Costs parameters (INVCOST, FIXOM and VAROM)''.'' Operation and maintenance costs tend to be lower in developing regions, as do investment cost where those regions have a technology manufacturing base e.g. China.
* Technology discount rate set to 10%, except for solar technologies, where the rate is higher for some regions. Higher rates are typically used for developing regions.
* Seasonal AFs are set by region for solar technologies, accounting for different insolation values.
* Construction time is provided for hydro and nuclear technologies - 10 years for nuclear and hydro (dam) and 5 years for hydro (run-of-river). No differentiation is made between regions.

An overview of the key parameters for the different technology groups is shown in below.

'''Table 3.2.2: Overview of technology characteristics by technology group (for WEU region)'''

{|class= "wikitable"
|width="16%"|'''Technology Group'''
|width="16%"|'''Efficiency % (range)'''
|width="16%"|
|width="16%"|'''Investment cost $/kW (range)'''
|width="16%"|
|width="16%"|'''Comment'''
|-
|''' '''
|'''2005'''
|'''2050'''
|'''2005'''
|'''2050'''
| 
|-
|'''Coal'''
|40-49
|40-49
|1430-1870
|1265-1662
| 
|-
|'''Gas / Dual'''
|37-57
|37-57
|360-1000
|300-1000
|Lower cost and higher efficiency values represent combined cycle technology
|-
|'''Oil'''
|31-35
|31-35
|660-1045
|660-1045
| 
|-
|'''Nuclear'''
|
| 
|1760-1870
|1760-1870
|Fusion costs set at 3300 $/kW
|-
|'''Hydro'''
|
| 
|1650-6050
|1540-5400
|Five dam-based technologies reflecting different cost of resource
|-
|'''Biomass'''
|33-34
|33-34
|1870-2200
|1870-2200
|MSW plant significantly higher at 3850 $/kW
|-
|'''Geothermal'''
|
| 
|1925-2780
|1650-2310
|Three geothermal technologies reflecting different cost of resource
|-
|'''Solar PV'''
|
| 
|7150-11000
|1485-3025
|Low cost is centralised plant and high cost decentralised plant. Technology resource tranched on basis of AFs
|-
|'''Solar thermal'''
|
| 
|13321
|13321
|Single technology with no evolution on costs
|-
|'''Wind'''
|
| 
|1065-1650
|880-1310
|One backstop, one offshore (CEN) and 2 onshore (one is CEN and one is DCN) technologies. Offshore tech. represents the high costs.
|}

== Power plants with CCS technologies ==

For low carbon analyses, sequestration technologies in the electricity generation sector are very important.

'''Table 3.2.3: Overview of Power plant with CCS technology characteristics'''

{| class= "wikitable"
|width="33%"|'''Model Technology Description'''
|width="33%"|'''Investment cost ($/kW)'''
|width="33%"|'''Efficiency (%)'''
|-
|NGCC+Oxyfueling
|950-1250
|48-55
|-
|NGCC+CO2 removal from flue gas
|800-1000
|49-57
|-
|IGCC+CO2 removal from input gas
|1800-2300
|40-48
|-
|Conventional Pulverized Coal+Oxyfueling
|1900-2400
|37-44
|-
|Conventional Pulverized Coal+CO2 removal from flue gas
|1850-2250
|38-44
|-
|SOFC (COAL) +CO2 removal - 2030
|2200
|48
|-
|SOFC (GAS) +CO2 removal - 2020
|1600
|58
|-
|Crop Direct Combustion. With CCS
|2125
|33
|-
|Crop Gasification.with CCS
|2500
|34
|-
|Sld Biomass Direct Combustion.with CCS
|1700
|33
|-
|Sld Biomass Gasification.with CCS
|2420
|34
|}

* The first five technologies listed have vintages for 2010, 2020 and 2030.

File:Elec.png

2016-12-15T20:47:32Z

Matthew Winning:

Electricity - TIAM-UCL

2016-12-15T20:46:00Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Electricity
}}
== Conversion ==
The electricity and heat generation sector represents many different technology types, using a wide range of fossil-based and renewables resources. The existing system is represented in generic terms whilst the options for future investments are characterised in more detail. Annual electricity and heat supply is temporally disaggregated across six periods (or ''time slices''), based on three season and two diurnal periods (Day / night) to represent changes in load based on sector demand profiles.

Electricity generation plant are additionally categorised as providing electricity to the centralised or decentralised grid (CEN or DCN). Decentralised producers tend to be small scale, connected to the distribution network or serving local grids, and produce one commodity in the model while centralised producers, connected to transmission network, produce a seperate commodity.

The electricity sector Base-Year template is used to calibrate the base-year electricity and heat generation. In the Base-Year template (providing information on existing plant), characterisation of plants is fairly generic, with all production of electricity categorised as ELC-CEN. Off-grid production (via micro-generation technologies) is not explicitly captured in the model, with small-scale generation represented in the decentralised producer group.

[[File:35815674.png]]

'''Figure 3.2.1: Existing Electricity Generation Capacity by Region in 2005 (Model base year), GW'''

[[File:35815675.png]]

'''Figure 3.2.2: Existing Electricity Generation Capacity by Type in 2005 (Model base year), GW'''

== New technologies ==

=== Key technology options ===

New electricity generation technologies are listed in Table 3.2.1. Further work is required to include new CHP technologies, which are not available for public system or industry investment.

'''Table 3.2.1: New technology options for electricity'''

{| class= "wikitable"
|width="50%"|'''Technology Group'''
|width="50%"|'''Model Technology Description'''
|-
|'''Coal'''
|Atmospheric Fl Bed.
|-
|''' '''
|Air Blown IGCC.
|-
|''' '''
|Oxygen Blown IGCC.
|-
|''' '''
|Pressurized Fl Bed.
|-
|''' '''
|Pulverized Coal.
|-
|'''Gas'''
|Gas Steam.
|-
|''' '''
|Fuel Cells.
|-
|'''Dual gas / oil'''
|Gas_Oil Comb Cycle.
|-
|''' '''
|Advanced Gas_Oil Turbine.
|-
|'''Oil'''
|Oil Steam.
|-
|''' '''
|Generic Dist Gen for Base Load.
|-
|''' '''
|Generic Dist Gen for Peak Load.
|-
|'''Nuclear'''
|Advanced Nuclear.
|-
|''' '''
|Fusion Nuclear.
|-
|''' '''
|Advanced Nuclear LWR.
|-
|''' '''
|Advanced Nuclear PBMR.
|-
|'''Hydro*'''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic ROR Hydro.
|-
|'''Biomass'''
|Crop Direct Combustion.
|-
|''' '''
|Crop Gasification.
|-
|''' '''
|Biogas from Waste.
|-
|''' '''
|MSW Direct Combustion.
|-
|''' '''
|Sld Biomass Direct Combustion.
|-
|''' '''
|Sld Biomass Gasification.
|-
|''' '''
|Sld Biomass Direct Combustion.Decentralized
|-
|''' '''
|Sld Biomass Gasification.Decentralized
|-
|'''Geothermal'''
|Shallow.
|-
|''' '''
|Deep.
|-
|''' '''
|Very deep.
|-
|'''Solar PV*'''
|CEN.PV.T0
|-
|''' '''
|CEN.PV.
|-
|''' '''
|CEN.PV.T1
|-
|''' '''
|CEN.PV.T2
|-
|''' '''
|CEN.PV.T3
|-
|''' '''
|CEN.PV.T4
|-
|''' '''
|CEN.PV.T5
|-
|''' '''
|DCN.PV.T0
|-
|''' '''
|DCN.PV.
|-
|''' '''
|DCN.PV.T1
|-
|''' '''
|DCN.PV.T2
|-
|''' '''
|PV.T3
|-
|''' '''
|PV.T4
|-
|''' '''
|PV.T5
|-
|'''Solar thermal'''
|CEN.Thermal.
|-
|'''Wind*'''
|CEN.
|-
|''' '''
|CEN.Offshore.
|-
|''' '''
|CEN.Onshore.
|-
|''' '''
|DCN.Onshore.
|}

* Different tranches of renewable technologies represent differences in the cost of resources (hydro) or quality of the resource (wind, solar).

The other important file is the transformation file, which allows for regional differences to be introduced without having to duplicate technologies. For the electricity sector, the following parameters are controlled, and varied by region:

* Costs parameters (INVCOST, FIXOM and VAROM)''.'' Operation and maintenance costs tend to be lower in developing regions, as do investment cost where those regions have a technology manufacturing base e.g. China.
* Technology discount rate set to 10%, except for solar technologies, where the rate is higher for some regions. Higher rates are typically used for developing regions.
* Seasonal AFs are set by region for solar technologies, accounting for different insolation values.
* Construction time is provided for hydro and nuclear technologies - 10 years for nuclear and hydro (dam) and 5 years for hydro (run-of-river). No differentiation is made between regions.

An overview of the key parameters for the different technology groups is shown in below.

'''Table 3.2.2: Overview of technology characteristics by technology group (for WEU region)'''

{|class= "wikitable"
|width="16%"|'''Technology Group'''
|width="16%"|'''Efficiency % (range)'''
|width="16%"|
|width="16%"|'''Investment cost $/kW (range)'''
|width="16%"|
|width="16%"|'''Comment'''
|-
|''' '''
|'''2005'''
|'''2050'''
|'''2005'''
|'''2050'''
| 
|-
|'''Coal'''
|40-49
|40-49
|1430-1870
|1265-1662
| 
|-
|'''Gas / Dual'''
|37-57
|37-57
|360-1000
|300-1000
|Lower cost and higher efficiency values represent combined cycle technology
|-
|'''Oil'''
|31-35
|31-35
|660-1045
|660-1045
| 
|-
|'''Nuclear'''
|
| 
|1760-1870
|1760-1870
|Fusion costs set at 3300 $/kW
|-
|'''Hydro'''
|
| 
|1650-6050
|1540-5400
|Five dam-based technologies reflecting different cost of resource
|-
|'''Biomass'''
|33-34
|33-34
|1870-2200
|1870-2200
|MSW plant significantly higher at 3850 $/kW
|-
|'''Geothermal'''
|
| 
|1925-2780
|1650-2310
|Three geothermal technologies reflecting different cost of resource
|-
|'''Solar PV'''
|
| 
|7150-11000
|1485-3025
|Low cost is centralised plant and high cost decentralised plant. Technology resource tranched on basis of AFs
|-
|'''Solar thermal'''
|
| 
|13321
|13321
|Single technology with no evolution on costs
|-
|'''Wind'''
|
| 
|1065-1650
|880-1310
|One backstop, one offshore (CEN) and 2 onshore (one is CEN and one is DCN) technologies. Offshore tech. represents the high costs.
|}

== Power plants with CCS technologies ==

For low carbon analyses, sequestration technologies in the electricity generation sector are very important.

'''Table 3.2.3: Overview of Power plant with CCS technology characteristics'''

{| class= "wikitable"
|width="33%"|'''Model Technology Description'''
|width="33%"|'''Investment cost ($/kW)'''
|width="33%"|'''Efficiency (%)'''
|-
|NGCC+Oxyfueling
|950-1250
|48-55
|-
|NGCC+CO2 removal from flue gas
|800-1000
|49-57
|-
|IGCC+CO2 removal from input gas
|1800-2300
|40-48
|-
|Conventional Pulverized Coal+Oxyfueling
|1900-2400
|37-44
|-
|Conventional Pulverized Coal+CO2 removal from flue gas
|1850-2250
|38-44
|-
|SOFC (COAL) +CO2 removal - 2030
|2200
|48
|-
|SOFC (GAS) +CO2 removal - 2020
|1600
|58
|-
|Crop Direct Combustion. With CCS
|2125
|33
|-
|Crop Gasification.with CCS
|2500
|34
|-
|Sld Biomass Direct Combustion.with CCS
|1700
|33
|-
|Sld Biomass Gasification.with CCS
|2420
|34
|}

* The first five technologies listed have vintages for 2010, 2020 and 2030.

Energy conversion - TIAM-UCL

2016-12-15T20:44:46Z

Matthew Winning:

Electricity - TIAM-UCL

2016-12-15T20:28:35Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Electricity
}}
== Conversion ==
The electricity and heat generation sector represents many different technology types, using a wide range of fossil-based and renewables resources. The existing system is represented in generic terms whilst the options for future investments are characterised in more detail. Annual electricity and heat supply is temporally disaggregated across six periods (or ''time slices''), based on three season and two diurnal periods (Day / night) to represent changes in load based on sector demand profiles.

Electricity generation plant are additionally categorised as providing electricity to the centralised or decentralised grid (CEN or DCN). Decentralised producers tend to be small scale, connected to the distribution network or serving local grids, and produce one commodity in the model while centralised producers, connected to transmission network, produce a seperate commodity.

The electricity sector Base-Year template is used to calibrate the base-year electricity and heat generation. In the Base-Year template (providing information on existing plant), characterisation of plants is fairly generic, with all production of electricity categorised as ELCC. Off-grid production (via micro-generation technologies) is not explicitly captured in the model, with small-scale generation represented in the decentralised producer group.

[[File:35815674.png]]

'''Figure 3.2.1: Existing Electricity Generation Capacity by Region in 2005 (Model base year), GW'''

[[File:35815675.png]]

'''Figure 3.2.2: Existing Electricity Generation Capacity by Type in 2005 (Model base year), GW'''

== New technologies ==

=== Key technology options ===

New electricity generation technologies are listed in Table 3.2.1. Further work is required to include new CHP technologies, which are not available for public system or industry investment.

'''Table 3.2.1: New technology options for electricity'''

{| class= "wikitable"
|width="50%"|'''Technology Group'''
|width="50%"|'''Model Technology Description'''
|-
|'''Coal'''
|Atmospheric Fl Bed.
|-
|''' '''
|Air Blown IGCC.
|-
|''' '''
|Oxygen Blown IGCC.
|-
|''' '''
|Pressurized Fl Bed.
|-
|''' '''
|Pulverized Coal.
|-
|'''Gas'''
|Gas Steam.
|-
|''' '''
|Fuel Cells.
|-
|'''Dual gas / oil'''
|Gas_Oil Comb Cycle.
|-
|''' '''
|Advanced Gas_Oil Turbine.
|-
|'''Oil'''
|Oil Steam.
|-
|''' '''
|Generic Dist Gen for Base Load.
|-
|''' '''
|Generic Dist Gen for Peak Load.
|-
|'''Nuclear'''
|Advanced Nuclear.
|-
|''' '''
|Fusion Nuclear.
|-
|''' '''
|Advanced Nuclear LWR.
|-
|''' '''
|Advanced Nuclear PBMR.
|-
|'''Hydro*'''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic Impoundment Hydro.
|-
|''' '''
|Generic ROR Hydro.
|-
|'''Biomass'''
|Crop Direct Combustion.
|-
|''' '''
|Crop Gasification.
|-
|''' '''
|Biogas from Waste.
|-
|''' '''
|MSW Direct Combustion.
|-
|''' '''
|Sld Biomass Direct Combustion.
|-
|''' '''
|Sld Biomass Gasification.
|-
|''' '''
|Sld Biomass Direct Combustion.Decentralized
|-
|''' '''
|Sld Biomass Gasification.Decentralized
|-
|'''Geothermal'''
|Shallow.
|-
|''' '''
|Deep.
|-
|''' '''
|Very deep.
|-
|'''Solar PV*'''
|CEN.PV.T0
|-
|''' '''
|CEN.PV.
|-
|''' '''
|CEN.PV.T1
|-
|''' '''
|CEN.PV.T2
|-
|''' '''
|CEN.PV.T3
|-
|''' '''
|CEN.PV.T4
|-
|''' '''
|CEN.PV.T5
|-
|''' '''
|DCN.PV.T0
|-
|''' '''
|DCN.PV.
|-
|''' '''
|DCN.PV.T1
|-
|''' '''
|DCN.PV.T2
|-
|''' '''
|PV.T3
|-
|''' '''
|PV.T4
|-
|''' '''
|PV.T5
|-
|'''Solar thermal'''
|CEN.Thermal.
|-
|'''Wind*'''
|CEN.
|-
|''' '''
|CEN.Offshore.
|-
|''' '''
|CEN.Onshore.
|-
|''' '''
|DCN.Onshore.
|}

* Different tranches of renewable technologies represent differences in the cost of resources (hydro) or quality of the resource (wind, solar).

The other important file is the transformation file, which allows for regional differences to be introduced without having to duplicate technologies. For the electricity sector, the following parameters are controlled, and varied by region:

* Costs parameters (INVCOST, FIXOM and VAROM)''.'' Operation and maintenance costs tend to be lower in developing regions, as do investment cost where those regions have a technology manufacturing base e.g. China.
* Technology discount rate set to 10%, except for solar technologies, where the rate is higher for some regions. Higher rates are typically used for developing regions.
* Seasonal AFs are set by region for solar technologies, accounting for different insolation values.
* Construction time is provided for hydro and nuclear technologies - 10 years for nuclear and hydro (dam) and 5 years for hydro (run-of-river). No differentiation is made between regions.

An overview of the key parameters for the different technology groups is shown in below.

'''Table 3.2.2: Overview of technology characteristics by technology group (for WEU region)'''

{|class= "wikitable"
|width="16%"|'''Technology Group'''
|width="16%"|'''Efficiency % (range)'''
|width="16%"|
|width="16%"|'''Investment cost $/kW (range)'''
|width="16%"|
|width="16%"|'''Comment'''
|-
|''' '''
|'''2005'''
|'''2050'''
|'''2005'''
|'''2050'''
| 
|-
|'''Coal'''
|40-49
|40-49
|1430-1870
|1265-1662
| 
|-
|'''Gas / Dual'''
|37-57
|37-57
|360-1000
|300-1000
|Lower cost and higher efficiency values represent combined cycle technology
|-
|'''Oil'''
|31-35
|31-35
|660-1045
|660-1045
| 
|-
|'''Nuclear'''
|
| 
|1760-1870
|1760-1870
|Fusion costs set at 3300 $/kW
|-
|'''Hydro'''
|
| 
|1650-6050
|1540-5400
|Five dam-based technologies reflecting different cost of resource
|-
|'''Biomass'''
|33-34
|33-34
|1870-2200
|1870-2200
|MSW plant significantly higher at 3850 $/kW
|-
|'''Geothermal'''
|
| 
|1925-2780
|1650-2310
|Three geothermal technologies reflecting different cost of resource
|-
|'''Solar PV'''
|
| 
|7150-11000
|1485-3025
|Low cost is centralised plant and high cost decentralised plant. Technology resource tranched on basis of AFs
|-
|'''Solar thermal'''
|
| 
|13321
|13321
|Single technology with no evolution on costs
|-
|'''Wind'''
|
| 
|1065-1650
|880-1310
|One backstop, one offshore (CEN) and 2 onshore (one is CEN and one is DCN) technologies. Offshore tech. represents the high costs.
|}

== Power plants with CCS technologies ==

For low carbon analyses, sequestration technologies in the electricity generation sector are very important.

'''Table 3.2.3: Overview of Power plant with CCS technology characteristics'''

{| class= "wikitable"
|width="33%"|'''Model Technology Description'''
|width="33%"|'''Investment cost ($/kW)'''
|width="33%"|'''Efficiency (%)'''
|-
|NGCC+Oxyfueling
|950-1250
|48-55
|-
|NGCC+CO2 removal from flue gas
|800-1000
|49-57
|-
|IGCC+CO2 removal from input gas
|1800-2300
|40-48
|-
|Conventional Pulverized Coal+Oxyfueling
|1900-2400
|37-44
|-
|Conventional Pulverized Coal+CO2 removal from flue gas
|1850-2250
|38-44
|-
|SOFC (COAL) +CO2 removal - 2030
|2200
|48
|-
|SOFC (GAS) +CO2 removal - 2020
|1600
|58
|-
|Crop Direct Combustion. With CCS
|2125
|33
|-
|Crop Gasification.with CCS
|2500
|34
|-
|Sld Biomass Direct Combustion.with CCS
|1700
|33
|-
|Sld Biomass Gasification.with CCS
|2420
|34
|}

* The first five technologies listed have vintages for 2010, 2020 and 2030.

Bioenergy - TIAM-UCL

2016-12-15T20:08:16Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Bioenergy
}}
Biofuels impact on land-use emissions are not considered and neither are life-cycle impacts of biofuels i.e. completely carbon neutral.

Biomass used in the electricity sector is provided by two different commodities - ELCSLD (from BIOSLD) and ELCCRP (from BIOCRP). Both originate from domestic (MIN) processes: MINBIOCRP0 (producing BIOCRP) and MINBIOSLD1,2 and 3 (producing BIOSLD). In this module biomass availability is modelled for energy crops and solid biomass (Table 11 5). Energy crops and solid biomass availability data is taken from TIAM-WORLD (www.kanors.com) and some adjustment made to match the regions in the TIAM-UCL. These two biomass resources are traded, transportation cost is presented in trade module. The domestic production bounds for 2005 can be found in the BY UPS templates. Concerning costs, all regions have the same COST for the three tranches of BIOSLD (at 0.63, 1.88 and 3.13). For BIOCRP, resource costs differ between regions although the basis for this differential is not clear. They range between 1.38 in India to 3.65 in ODA. All costs remain the same over the time horizon.

Production system and representation of economic sectors - TIAM-UCL

2016-12-15T20:05:04Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Production system and representation of economic sectors
}}
We have added a simplified general equilibrium macroeconomic growth module developed by Kypreos and Lehtila (2013). Macro Stand-Alone (MSA) is a single agent; single sector, multi-regional, general equilibrium optimal growth model which maximises discounted utility of a single consumer-producer agent. GDP is comprised of consumption, investment and energy system costs. Total economic production is determined by a combination of energy, capital and labour where energy substitutes with a capital-labour composite via an elasticity of substitution parameter. Quadratic cost functions and demand decoupling factors (essentially elasticity parameters for each period and demand)are estimated from the calibration routine are fed from TIAM-UCL to MSA. MSA is then solved and the new energy demands are given back into TIAM-UCL which is then solved again. The iteration continues until the model converges, defined by the change in energy service demand variation between interactions slowing to within a specified tolerance.

Macro-economy - TIAM-UCL

2016-12-15T19:54:53Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Macro-economy
}}
The economy is represented for each region by hard-linking TIAM-UCL with Macro Stand Alone (MSA) module to allow consideration of the rest of the economy beyond energy i.e. general not partial equilibrium, and endogenises demand changes.

Energy resource endowments - TIAM-UCL

2016-12-15T19:52:19Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Energy resource endowments
}}
Fossil reserves and mining technologies are presented in the Table below on Non-renewable primary resources. A supply curve for each type of the sources shown is defined within region. Each time step is characterised by the cost of the resource and the total amount of energy available at this cost.

The Resource Module contains the data which separately characterises resources which are situated in regions with members of OPEC and those resources found in all other Non-OPEC regions. The module was originally based upon that provided in ETSAP-TIAM although significant changes have been made to their characterisation and dynamics of production including: adding Arctic oil and gas, shale gas and separately considering natural bitumen and kerogen oil produced by mining and by in situ methods. Geological constraints are also imposed upon oil and gas production that represent empirical depletion rate constraints.

'''Table: Non-renewable primary resources'''

{| class="wikitable"
|width="100%"|'''Technology Description'''
|-
|'''Oil'''
|-
|Existing proved plus probable reserves 
|-
|Reserve growth 
|-
|Undiscovered oil
|-
|Arctic oil 
|-
|Natural bitumen ('oil sands') by in situ means of production 
|-
|Natural bitumen ('oil sands') by mining 
|-
|Extra-heavy oil 
|-
|Kerogen oil by in situ means of production
|-
|Kerogen oil by mining
|-
|Natural gas liquids 
|-
|'''Natural gas''' 
|-
|Existing proved plus probable reserves
|-
|Reserve growth
|-
|Undiscovered gas
|-
|Arctic gas 
|-
|Tight gas 
|-
|Coal bed methane 
|-
|Shale gas 
|-
|Associated gas 
|-
|'''Coal'''
|-
|Existing reserves 
|-
|Additional resources 
|-
|'''Uranium'''
|-
|Uranium (dummy) - Reserves
|}

Trade - TIAM-UCL

2016-12-15T19:43:32Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Trade
}}
=== Energy Trade ===

Regional trade is modelled in the trade module. In the current version of TIAM-UCL, regional trade is allowed for coal, natural gas, LNG, natural gas liquid, uranium oil and oil products such as heavy fuel oil, gasoline, naphtha, diesel, energy crops and solid biomass. Emission trading under cap-and-trade policy is also modelled and the level of trading can be constrained. Trading in the base-year 2005 is calibrated to the actual energy import and export data. Base-year energy trade (import and export of fossil resources) for the UK is taken from DUKES (2010).

'''Table 2-3: Resources traded in the 16 region TIAM-UCL global model'''

{| class="wikitable"
|width="100%"|'''Resource'''
|-
|Crude oil
|-
|Hard coal
|-
|Natural gas
|-
|Heavy fuel oil
|-
|Naphtha
|-
|Gasoline
|-
|Natural gas liquid
|-
|Distillates (diesel)
|-
|Liquefied natural gas
|-
|Uranium
|-
|Biomass 
|-
|Bio-Fuels 
|-
|Emissions permits 
|}

References - TIAM-UCL

2016-12-15T19:26:20Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=References
}}
Clarke, L., J. Edmonds, H. D. Jacoby, H. Pitcher, J. M. Reilly and R. Richels (2007): Scenarios of Greenhouse Gas Emissions and Atmospheric Concentrations. Sub-report 2.1A of Synthesis and Assessment Product 2.1 by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. Department of Energy / Office of Biological & Environmental Research. Washington, DC.: 154.

Dessens O. and Anandarajah G. (2012) Soft coupling between the integrated assessment models PAGE and TIAM-UCL: climate change damage function and greenhouse gas emissions abatement costs. IEW2012, Cape Town, South Africa, June 19-21.

Forster, P., V. Ramaswamy, P. Artaxo, T. Berntsen, R. Betts, D.W. Fahey, J. Haywood, J. Lean, D.C. Lowe, G. Myhre, J. Nganga, R. Prinn, G. Raga, M. Schulz and R. Van Dorland, 2007: Changes in Atmospheric Constituents and in Radiative Forcing. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Hope, C. (2011) The PAGE09 integrated assessment model: A technical description. Cambridge Judge Business School Working Paper. Cambridge, UK.

International Energy Agency (IEA), ''World Energy Balances, 2009'', ESDS International, (Mimas) University of Manchester

Kypreos, S. and A. Lehtila (2013), TIMES-Macro: Decomposition into Hard-Linked LP and NLP problems, ETSAP TIMES 3.4 User Note, 25 March 2015

Lehtila A., Loulou R. (2005) TIMES Damage Functions. ETSAP TIMES Version 2.0 User Note. IEA-ETSAP.

Loulou, R., and M. Labriet (2007), ?ETSAP-TIAM: The TIMES Integrated Assessment Model --Part I: Model Structure?, ''Computational Management Science special issue on Energy and Environment'', Vol. 5, No 1-2, pp. 7-40

Loulou, R., Lehtila, A., Labriet, M. (2010): ?TIMES Climate Module (Nov. 2010)?, ETSAP, [http://www.etsap.org/documentation.asp http://www.etsap.org/documentation.asp]

Morita, Tsuneyuki (1999) Emission Scenario Database prepared for IPCC Special Report on Emission Scenarios convened by Dr. Nebosja Nakicenovic, National Institute for Environmental Studies Centre for Global Environmental Research

Meinshausen M., Raper S. C. B. and Wigley T. M. L. (2011) Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 ? Part 1: Model description and calibration. Atmospheric Chemistry and Physics 11(4): 1417-1456.

Nordhaus, W.D., Boyer, J. (1999): ?Roll the DICE Again: Economic Models of Global Warming?, Yale University, manuscript edition.

Prinn R., S. Paltsev, A. Sokolov, M. Sarofim, J. Reilly, and H. Jacoby (2008). The Influence on Climate Change of Differing Scenarios for Future Development Analyzed Using the MIT Integrated Global System Model. Report nยบ163, MIT Joint Program on the Science and Policy of Global Change, 32 p.

Ramaswamy, V., Boucher, O., Haigh, J., Hauglustaine, D., Haywood, J., Myhre, G., Nakajima, T., Shi, G.W., Solomon, S. 2007: Radiative Forcing of Climate Change. In: Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change [Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der Linden, P.J., Dai, X., Maskell, K., Johnson, C.A. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

UN (2009): ''World Population Prospects: The 2008 Revision,'' ''Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat, '' [http://esa.un.org/unpp_ http://esa.un.org/unpp_], February 10, 2010_

Production system and representation of economic sectors - TIAM-UCL

2016-12-15T19:25:53Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Production system and representation of economic sectors
}}
We have added a simplified general equilibrium macroeconomic growth module developed by Kypreos and Lehtila (2013). Macro Stand-Alone (MSA) is a single agent; single sector, multi-regional, general equilibrium optimal growth model which maximises discounted utility of a single consumer-producer agent. GDP is comprised of consumption, investment and energy system costs. Total economic production is determined by a combination of energy, capital and labour where energy substitutes with a capital-labour composite via an elasticity of substitution parameter. Quadratic cost functions and demand decoupling factors are estimated from the calibration routine are fed from TIAM-UCL to MSA. MSA is then solved and the new energy demands are given back into TIAM-UCL which is then solved again. The iteration continues until the model converges, defined by the change in energy service demand variation between interactions slowing to within a specified tolerance.

Macro-economy - TIAM-UCL

2016-12-15T19:21:20Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Macro-economy
}}
The economy is represented for each region by linking TIAM-UCL with Macro Stand Alone (MSA) module to allow consideration of the rest of the economy beyond energy i.e. general not partial equilibrium, and endogenises demand changes.

Economic activity - TIAM-UCL

2016-12-15T19:18:48Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Economic activity
}}
=== GDP ===
Estimations of future economic growth are much more uncertain than future population growth. Few studies exist that forecast GDP up to 2100 and so unlike population assumptions, GDP figures in TIAM-UCL are not based on a single source. Economic growth rates have been compared to assumptions made for scenarios in the 4th assessment report of the IPCC (Tsuneyuki 1999) and Clarke et al. (2007).
Global GDP is assumed to grow from $50 trillion in 2010 to $155 trillion in 2050 and $350 trillion in 2100 (all GDP are in 2005 US$). Current figures for 2010 have been taken from the IMF (2009).

Figures for future economic growth are based on an approximate assumption of economic convergence between regions (see Figure 3 5), i.e. that low income regions grow faster compared to high income regions. The figure shows this convergence of per capita income among world regions. The GDP per person is calculated as the ratio of GDP and population.
The economic convergence is a central point in the assumptions on socio-economic drivers. The effect becomes clear when one compares the GDP per head in different regions. In 2005 India is the poorest region with a GDP per head of 10% of the world average and the USA is the richest region with 600% of the world average. In 2100 this picture changes with India having a GDP per head that has now grown to 55% of the world average and the USA being the richest country with 350% of the world average.

GDP growth rates are expected to decline over the course of the 21st century, while they remain higher for developing countries than for developed countries. Owing to the shrinking population, the growth rates for South Korea and Japan are very low and turn negative at the end of the 21st century. Growth rates for Western Europe, the UK and the United States are assumed to drop from an average of 2.2% to 1.3% p.a. in 2050. The only region that is expected to increase GDP growth rates over the first decades is Africa based on a growing population and its current low income levels.
Global economic growth is approximately in the mid-range of the growth in the SSP scenarios

<figure id="fig:GDP per capita">
[[File:Pop vs SSPs.png|400px|<caption>GDP per capita</caption>]]
</figure>

=== Sectoral drivers ===

The industrial, services and agricultural sectors have different growth drivers from all other sectors i.e. they are not directly related to growth in GDP and a decoupling factor. There are a number of reasons for this, but key is that there is expected to be a decoupling of growth in, for example, production of steel and growth in GDP that is cannot be trivially estimated by a single decoupling factor. Additionally, the industrial service demands can be interpreted as represent the production of physical quantities e.g. tonnes of steel, tonnes of aluminium etc. Projections of future production are provided by various sources, who look in detail at the array of factors that affect production and consumption levels on regional basis. These sources therefore likely provide more robust estimates of future production while also providing a more tangible projection of what is being estimated.

The projections of steel, aluminium and cement, paper and chemicals production globally used in TIAM-UCL are provided in the Figures below. These figures also shows how these compare with the projections used in ETSAP-TIAM.
These quantities have been estimated using the regional per-capita consumption and productions projections from IEA up to 2050 ensuring that these balance on a global level). A single provider was used for this estimation to ensure consistency across the different metallic and non-metallic sectors. Consumption from 2050 to 2100 was then based on historical trends in per-capita consumption from 2000 to 2050, so, for example, annual aluminium consumption is assumed to trend towards 35 kg/person and steel towards 500 kg/capita as regions increase their GDP/capita. Energy-service demands rely on production and not consumption levels, which are not equal because of trade. Production to satisfy this increasing demand was thus estimated by projecting trends in production between 2010 and 2050 whilst again ensuring that consumption and production matched on a global level.

It can be seen that the new projections are in general lower than those used previously, particularly in the case of cement. These projections can be easily modified to account for different socio-economic scenarios, for example if it is assumed that material intensity will be greater or lower in the future (included within the main assumptions of the SSPs for example).
The energy-service demand for agriculture is derived in a similar manner. A relationship is given between crop caloric demand/capita, protein demand/capita, and GDP/capita. This suggests that both follow an approximate square root relationship with GDP/capita (so if GDP/capita doubles protein demand and crop calorie demand increase by 41%).

TIAM-UCL requires the energy-service demand and the energy intensity of protein and crop calories are very different. However, because both crop and protein demand follow a similar relationship to GDP/capita, the GDP/capita assumption shown in the crop Figure can be used to estimate how total consumption within each region will change in the future demand. This therefore assumes a constant ratio of crop to meat calories in all regions in the future, although clearly because GDP/capita increases, the absolute level of each also increases over time.
Again production levels are required for energy-service demands and not consumption. A strong assumption is therefore made whch is that the current (2005) ratio of production to consumption would remain constant in the future, a ratio that varies significantly between different regions. This assumption and projections of consumption and production can be easily modified to account for different socio-economic scenarios, say if it is assumed that global trade of agricultural goods will increase or decrease in the future.

<figure id="fig:steel">
[[File:steel.png|400px|<caption>Steel</caption>]]
</figure>

<figure id="fig:aluminium">
[[File:aluminium.png|400px|<caption>aluminium</caption>]]
</figure>

<figure id="fig:cement">
[[File:cement.png|400px|<caption>cement</caption>]]
</figure>

<figure id="fig:paper">
[[File:Paper.png|400px|<caption>Paper</caption>]]
</figure>

<figure id="fig:Chemical">
[[File:Chemical.png|400px|<caption>Chemical</caption>]]
</figure>

<figure id="fig:Crop calorie production">
[[File:Crop_calorie_production.png|400px|<caption>Crop Calorie Production</caption>]]
</figure>

File:Crop calorie production.png

2016-12-15T19:15:34Z

Matthew Winning:

File:Chemical.png

2016-12-15T19:14:41Z

Matthew Winning:

File:Paper.png

2016-12-15T19:12:48Z

Matthew Winning:

File:Cement.png

2016-12-15T19:11:43Z

Matthew Winning:

File:Aluminium.png

2016-12-15T19:08:49Z

Matthew Winning:

File:Steel.png

2016-12-15T19:07:52Z

Matthew Winning:

Population - TIAM-UCL

2016-12-15T19:00:11Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Population
}}
=== Population ===

Population figures up to 2050 are based on UN estimations (UN, 2009). It is assumed that world population will increase from 6.7 billion people in 2005 to 9.3 billion people in 2050, reach the peak in 2090 with 9.8 billion and then decline slightly.

The biggest population increase over the 21st century is expected to happen in Africa, India, Other Developing Asia and the Middle East .

Under the given assumptions China, Eastern Europe, Former Soviet Union, Japan, Mexico, South Korea and Western Europe experience negative population growth rates in the second half of the 21st century.

Especially for South Korea and Japan, it is assumed that the population will shrink significantly over the course of the 21st century.

We are also able to run the various Shared Socio-economic (SSP) pathway scenarios [[CiteRef::nakicenovic2014a]] in TIAM-UCL. The standard TIAM-UCL population assumption is around halfway between SSP3 and SSP2 for population.
<figure id="fig:Population SSPs">
[[File:Pop vs SSPs.png|400px|<caption>TIAM-UCL population vs SSPs</caption>]]
</figure>

=== Households ===

The number of households is based on population estimates and occupancy rate. There exists no database for the occupancy rate for each region in the TIAM-UCL model. Therefore, the numbers in this section rely on national statistics. There are forecasts for the average household occupancy for some countries for the near future (up to 2030) from which it is possible estimate the number of households (given assumptions on population).
For the longer term, it is assumed that the occupancy rate will increase in line with historic data to 1.7 to 3 persons per household, depending on the region. The reason for this range is the difference in current average persons per household, e.g. in 2005 the average Indian household consisted of 5.3 persons, while the average Western European household consisted of 2.1 persons per household.

Given these assumptions, the total number of households globally increases from 1.9 billion in 2005 to 3.4 billion in 2050 to 5.1 billion in 2100.

In order to simplify the data needed for the calculation, characteristic countries have been chosen for regions that consist of more than two countries. Those are South Africa for Africa, Brazil for Central and South America, Poland for Eastern Europe, Russia for Former Soviet Union, Iran for Middle East, Indonesia for Other Developing Asia and Germany for Western Europe.

[[File:Households.png|400px|Households growth rate]]

File:Households.png

2016-12-15T18:57:01Z

Matthew Winning:

Socio-economic drivers - TIAM-UCL

2016-12-15T18:52:09Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Socio-economic drivers
}}
There are 42 energy-service demands for the five different end-use sectors in TIAM-UCL.

A driver is allocated to each energy service demand to project demand for future years throughout the model horizon (2005 to 2100).
The driver is linked to the energy-service demand by a constant and an elasticity. Demand drivers include population, GDP, number of households, GDP per capita, GDP per household and agricultural, service and industrial drivers.

Assumptions on the development of drivers are based on several sources, which are explained in the following subsections. Assumptions on demand drivers have been substantially updated from the ESTAP-TIAM model.

Economic activity - TIAM-UCL

2016-12-15T18:51:08Z

Matthew Winning:

Economic activity - TIAM-UCL

2016-12-15T18:45:00Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Economic activity
}}
=== GDP ===

Estimations of future economic growth are much more uncertain than future population growth. In TIAM-UCL future regional economic growth are based on an assumption of economic convergence between regions.

In detail, this means that per capita income is assumed to converge between different regions, i.e. that low income regions grow faster compared to high income regions. GDP is calculated in 2005 USD and in PPP terms.

The figure, which has a logarithmic scale, shows this convergence of per capita income among world regions. The GDP per capita is calculated as the ratio of GDP and population. The economic convergence is a central point in the assumptions on socio-economic drivers. The effect becomes clear when one compares the GDP per capita in different regions.

India is the poorest region with a GDP per head of 10% of the world average and the USA is the richest region with 608% of the world average in 2005.

In 2100 this changes to India still being the poorest country with GDP per head but with 47% of the world average and the USA being the richest country with 303% of the world average.

<figure id="fig:GDP per capita">
[[File:GDP per capita.png|400px|<caption>GDP per capita</caption>]]
</figure>

=== Sectoral drivers ===

Industrial production is subdivided into chemical industry, iron & steel and non-ferrous metals, pulp & paper and non-metallic minerals, and other industries. Initial numbers are based on number from ETSAP-TIAM published by KANORS (2010).

The development of sectoral growth rates are geared to the GDP numbers and imply a shift in GDP composition towards the service sector, so that agriculture and industry will become less important for the whole economy over the 21st century. To this end, the GDP composition of the most important regions has been extracted from national statistics according to the sectoral aggregation in TIAM.

Sectoral drivers have been calibrated in such a way that they yield a more service-orientated economy.

In addition, the driver for the iron & steel industry is geared to historical data on steel production obtained from statistics of the World Steel Association.

Economic activity - TIAM-UCL

2016-12-15T18:43:58Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Economic activity
}}
=== GDP ===

Estimations of future economic growth are much more uncertain than future population growth. In TIAM-UCL future regional economic growth are based on an assumption of economic convergence between regions.

In detail, this means that per capita income is assumed to converge between different regions, i.e. that low income regions grow faster compared to high income regions. GDP is calculated in 2005 USD and in PPP terms.

The figure, which has a logarithmic scale, shows this convergence of per capita income among world regions. The GDP per capita is calculated as the ratio of GDP and population. The economic convergence is a central point in the assumptions on socio-economic drivers. The effect becomes clear when one compares the GDP per capita in different regions.

India is the poorest region with a GDP per head of 10% of the world average and the USA is the richest region with 608% of the world average in 2005.

In 2100 this changes to India still being the poorest country with GDP per head but with 47% of the world average and the USA being the richest country with 303% of the world average.

<figure id="fig:GDP per capita">
[[File:GDP per capita.png|400px|<caption>GDP per capita</caption>]]
</figure>

=== Sectoral drivers ===

There exist no reliable data for the forecast of industrial production, agricultural or service output for the next 90 years.

Industrial production is subdivided into chemical industry, iron & steel and non-ferrous metals, pulp & paper and non-metallic minerals, and other industries. Initial numbers are based on number from ETSAP-TIAM published by KANORS (2010).

The development of sectoral growth rates are geared to the GDP numbers and imply a shift in GDP composition towards the service sector, so that agriculture and industry will become less important for the whole economy over the 21st century. To this end, the GDP composition of the most important regions has been extracted from national statistics according to the sectoral aggregation in TIAM.

Sectoral drivers have been calibrated in such a way that they yield a more service-orientated economy.

In addition, the driver for the iron & steel industry is geared to historical data on steel production obtained from statistics of the World Steel Association.

Economic activity - TIAM-UCL

2016-12-15T18:41:22Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Economic activity
}}
=== GDP ===

Estimations of future economic growth are much more uncertain than future population growth. Figures for future economic growth are based on an assumption of economic convergence between regions.

In detail, this means that per capita income is assumed to converge between different regions, i.e. that low income regions grow faster compared to high income regions. GDP is calculated in 2005 USD and in PPP terms.

The figure, which has a logarithmic scale, shows this convergence of per capita income among world regions. The GDP per person is calculated as the ratio of GDP and population. The economic convergence is a central point in the assumptions on socio-economic drivers. The effect becomes clear when one compares the GDP per head in different regions.

India is the poorest region with a GDP per head of 10% of the world average and the USA is the richest region with 608% of the world average in 2005.

In 2100 this picture changes to India still being the poorest country with GDP per head but with 47% of the world average and the USA being the richest country with 303% of the world average.

<figure id="fig:GDP per capita">
[[File:GDP per capita.png|400px|<caption>GDP per capita</caption>]]
</figure>

=== Sectoral drivers ===

There exist no reliable data for the forecast of industrial production, agricultural or service output for the next 90 years.

Industrial production is subdivided into chemical industry, iron & steel and non-ferrous metals, pulp & paper and non-metallic minerals, and other industries. Initial numbers are based on number from ETSAP-TIAM published by KANORS (2010).

The development of sectoral growth rates are geared to the GDP numbers and imply a shift in GDP composition towards the service sector, so that agriculture and industry will become less important for the whole economy over the 21st century. To this end, the GDP composition of the most important regions has been extracted from national statistics according to the sectoral aggregation in TIAM.

In a next step, the sectoral drivers have been calibrated in such a way that they yield a more service orientated economy.

In addition, the driver for the iron & steel industry is geared to historical data on steel production obtained from statistics of the World Steel Association.

Economic activity - TIAM-UCL

2016-12-15T18:40:19Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Economic activity
}}
=== GDP ===

Estimations of future economic growth are much more uncertain than future population growth. Figures for future economic growth are based on an assumption of economic convergence between regions.

In detail, this means that per capita income is assumed to converge between different regions, i.e. that low income regions grow faster compared to high income regions. GDP is calculated in 2005 USD and in PPP terms.

The figure, which has a logarithmic scale, shows this convergence of per capita income among world regions. The GDP per person is calculated as the ratio of GDP and population. The economic convergence is a central point in the assumptions on socio-economic drivers. The effect becomes clear when one compares the GDP per head in different regions.

India is the poorest region with a GDP per head of 10% of the world average and the USA is the richest region with 608% of the world average in 2005.

In 2100 this picture changes to India still being the poorest country with GDP per head but with 47% of the world average and the USA being the richest country with 303% of the world average.

<figure id="fig:GDP per capita">
[[File:Pop vs SSPs.png|400px|<caption>GDP per capita</caption>]]
</figure>

=== Sectoral drivers ===

There exist no reliable data for the forecast of industrial production, agricultural or service output for the next 90 years.

Industrial production is subdivided into chemical industry, iron & steel and non-ferrous metals, pulp & paper and non-metallic minerals, and other industries. Initial numbers are based on number from ETSAP-TIAM published by KANORS (2010).

The development of sectoral growth rates are geared to the GDP numbers and imply a shift in GDP composition towards the service sector, so that agriculture and industry will become less important for the whole economy over the 21st century. To this end, the GDP composition of the most important regions has been extracted from national statistics according to the sectoral aggregation in TIAM.

In a next step, the sectoral drivers have been calibrated in such a way that they yield a more service orientated economy.

In addition, the driver for the iron & steel industry is geared to historical data on steel production obtained from statistics of the World Steel Association.

File:GDP per capita.png

2016-12-15T18:09:28Z

Matthew Winning:

File:GDPvsSSPs.png

2016-12-15T18:01:00Z

Matthew Winning:

Population - TIAM-UCL

2016-12-15T18:00:23Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Population
}}
=== Population ===

Population figures up to 2050 are based on UN estimations (UN, 2009). It is assumed that world population will increase from 6.7 billion people in 2005 to 9.3 billion people in 2050, reach the peak in 2090 with 9.8 billion and then decline slightly.

The biggest population increase over the 21st century is expected to happen in Africa, India, Other Developing Asia and the Middle East .

Under the given assumptions China, Eastern Europe, Former Soviet Union, Japan, Mexico, South Korea and Western Europe experience negative population growth rates in the second half of the 21st century.

Especially for South Korea and Japan, it is assumed that the population will shrink significantly over the course of the 21st century.

We are also able to run the various Shared Socio-economic (SSP) pathway scenarios [[CiteRef::nakicenovic2014a]] in TIAM-UCL. The standard TIAM-UCL population assumption is around halfway between SSP3 and SSP2 for population.
<figure id="fig:Population SSPs">
[[File:Pop vs SSPs.png|400px|<caption>TIAM-UCL population vs SSPs</caption>]]
</figure>

=== Households ===

The growth rate of household numbers during 2005-2100 for different regions are represented in the model. The number of households is based on population estimates and occupancy rate. There exists no database for the occupancy rate for each region in the TIAM-UCL model.

Therefore, the numbers in this section rely on national statistics. For some countries, there exist forecasts for the near future (up to 2030) concerning the development of the average number of people in a household. These have been used where available in order to determine the household growth for the near future.

For the longer term, it is assumed that the occupancy rate will increase in line with historic data from 1.7 to 3 persons per household, depending on the region. The reason for this range is the difference in current average persons per household, e.g. in 2005 the average Indian household consisted of 5.3 persons, while the average Western European household consisted of 2.1 persons per household. 

In order to simplify the data needed for the calculation, characteristic countries have been chosen for regions that consist of more than two countries. Those are South Africa for Africa, Brazil for Central and South America, Poland for Eastern Europe, Russia for Former Soviet Union, Iran for Middle East, Indonesia for Other Developing Asia and Germany for Western Europe. Numbers for the driver 'GDP per household' have been calculated as the ratio of GDP and number of households for each given region.

Population - TIAM-UCL

2016-12-15T17:53:14Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Population
}}
=== Population ===

Population figures up to 2050 are based on UN estimations (UN, 2009). It is assumed that world population will increase from 6.7 billion people in 2005 to 9.3 billion people in 2050, reach the peak in 2090 with 9.8 billion and then decline slightly.

The biggest population increase over the 21st century is expected to happen in Africa, India, Other Developing Asia and the Middle East .

Under the given assumptions China, Eastern Europe, Former Soviet Union, Japan, Mexico, South Korea and Western Europe experience negative population growth rates in the second half of the 21st century.

Especially for South Korea and Japan, it is assumed that the population will shrink significantly over the course of the 21st century.

We are also able to run the various Shared Socio-economic (SSP) pathway scenarios [[CiteRef::nakicenovic2014a]] in TIAM-UCL. The standard TIAM-UCL population assumption is around halfway between SSP3 and SSP2 for population.

=== Households ===

The growth rate of household numbers during 2005-2100 for different regions are represented in the model. The number of households is based on population estimates and occupancy rate. There exists no database for the occupancy rate for each region in the TIAM-UCL model.

Therefore, the numbers in this section rely on national statistics. For some countries, there exist forecasts for the near future (up to 2030) concerning the development of the average number of people in a household. These have been used where available in order to determine the household growth for the near future.

For the longer term, it is assumed that the occupancy rate will increase in line with historic data from 1.7 to 3 persons per household, depending on the region. The reason for this range is the difference in current average persons per household, e.g. in 2005 the average Indian household consisted of 5.3 persons, while the average Western European household consisted of 2.1 persons per household. 

In order to simplify the data needed for the calculation, characteristic countries have been chosen for regions that consist of more than two countries. Those are South Africa for Africa, Brazil for Central and South America, Poland for Eastern Europe, Russia for Former Soviet Union, Iran for Middle East, Indonesia for Other Developing Asia and Germany for Western Europe. Numbers for the driver 'GDP per household' have been calculated as the ratio of GDP and number of households for each given region.

File:Pop vs SSPs.png

2016-12-15T17:50:24Z

Matthew Winning:

Population - TIAM-UCL

2016-12-15T16:35:41Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Population
}}
=== Population ===

Population figures up to 2050 are based on UN estimations (UN, 2009). It is assumed that world population will increase from 6.7 billion people in 2005 to 9.3 billion people in 2050, reach the peak in 2090 with 9.8 billion and then decline slightly.

The biggest population increase over the 21st century is expected to happen in Africa, India, Other Developing Asia and the Middle East .

Under the given assumptions China, Eastern Europe, Former Soviet Union, Japan, Mexico, South Korea and Western Europe experience negative population growth rates in the second half of the 21st century.

Especially for South Korea and Japan, it is assumed that the population will shrink significantly over the course of the 21st century.

We are also able to run the various Shared Socio-economic (SSP) pathway scenarios in TIAM-UCL. The standard TIAM-UCL population assumption is around halfway between SSP3 and SSP2 for population.

=== Households ===

The growth rate of household numbers during 2005-2100 for different regions are represented in the model. The number of households is based on population estimates and occupancy rate. There exists no database for the occupancy rate for each region in the TIAM-UCL model.

Therefore, the numbers in this section rely on national statistics. For some countries, there exist forecasts for the near future (up to 2030) concerning the development of the average number of people in a household. These have been used where available in order to determine the household growth for the near future.

For the longer term, it is assumed that the occupancy rate will increase in line with historic data from 1.7 to 3 persons per household, depending on the region. The reason for this range is the difference in current average persons per household, e.g. in 2005 the average Indian household consisted of 5.3 persons, while the average Western European household consisted of 2.1 persons per household. 

In order to simplify the data needed for the calculation, characteristic countries have been chosen for regions that consist of more than two countries. Those are South Africa for Africa, Brazil for Central and South America, Poland for Eastern Europe, Russia for Former Soviet Union, Iran for Middle East, Indonesia for Other Developing Asia and Germany for Western Europe. Numbers for the driver 'GDP per household' have been calculated as the ratio of GDP and number of households for each given region.

Population - TIAM-UCL

2016-12-14T19:47:27Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Population
}}
=== Population ===

Population figures up to 2050 are based on UN estimations (UN, 2009). It is assumed that world population will increase from 6.7 billion people in 2005 to 9.3 billion people in 2050, reach the peak in 2090 with 9.8 billion and then decline slightly.

The biggest population increase over the 21st century is expected to happen in Africa, India, Other Developing Asia and the Middle East .

Under the given assumptions China, Eastern Europe, Former Soviet Union, Japan, Mexico, South Korea and Western Europe experience negative population growth rates in the second half of the 21st century.

Especially for South Korea and Japan, it is assumed that the population will shrink significantly over the course of the 21st century.

We are also able to run Shared Socio-economic (SSP) pathway scenarios in TIAM-UCL

=== Households ===

The growth rate of household numbers during 2005-2100 for different regions are represented in the model. The number of households is based on population estimates and occupancy rate. There exists no database for the occupancy rate for each region in the TIAM-UCL model.

Therefore, the numbers in this section rely on national statistics. For some countries, there exist forecasts for the near future (up to 2030) concerning the development of the average number of people in a household. These have been used where available in order to determine the household growth for the near future.

For the longer term, it is assumed that the occupancy rate will increase in line with historic data from 1.7 to 3 persons per household, depending on the region. The reason for this range is the difference in current average persons per household, e.g. in 2005 the average Indian household consisted of 5.3 persons, while the average Western European household consisted of 2.1 persons per household. 

In order to simplify the data needed for the calculation, characteristic countries have been chosen for regions that consist of more than two countries. Those are South Africa for Africa, Brazil for Central and South America, Poland for Eastern Europe, Russia for Former Soviet Union, Iran for Middle East, Indonesia for Other Developing Asia and Germany for Western Europe. Numbers for the driver 'GDP per household' have been calculated as the ratio of GDP and number of households for each given region.

Policy - TIAM-UCL

2016-12-14T19:42:38Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Policy
}}
A variety of energy and climate policies can be implemented, depending on the approach, usually by creating specific scenario files to incorporate the policy elements.

A number of general or specific policy choices can be modelled including:

* Emissions taxes,
* permit trading,
* specific technology subsidies
* Technology and/or resource constraints
* Technology and/or resource targets

Spatial dimension - TIAM-UCL

2016-12-14T19:39:30Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Spatial dimension
}}
TIAM-UCL is a global model with 16 regions listed in the table below, each of which has their own energy system.

The TIAM-UCL model has been developed at UCL since 2010 and differs from the ETSAP-TIAM model in two ways: the first is breaking out the UK from the 15 region ETSAP-TIAM model; the second is enhancing TIAM-UCL by revising/adding new drivers and resources for all regions and adding new features.

In order to break out the UK from Western Europe (WEU) region, separate Base-Year templates were created for end-use sectors, upstream and power sectors for the UK and calibrated final energy consumption to the actual base year data 2005 for the UK and the WEU regions. The underlying data for the base year calibration in TIAM-UCL is the IEA Extended Energy Balances of OECD and non-OECD countries. This data can be accessed through the online portal https://www.ukdataservice.ac.uk/ in the UK. A database of the IEA Extended Energy Balances has been developed to import the IEA data into the data tables on the base year templates in the TIAM-UCL with a software application which allows easy aggregation of country data into regions. Energy services demands for different end-use sectors and drivers of projections of demands during the model period 2005-2100 were created for the UK region. Besides the calibration of resource and trade modules of the UK and the WEU regions, all other scenario files were also updated and calibrated.

Once the 16 region TIAM-UCL had been successfully calibrated, the model was enhanced through technical improvements such as adding new drivers, new resources, climate change policies (cap-and-trade, carbon tax), supply resource cost curves etc. Development of the database of the IEA Extended Energy Balances helped to recalibrate all 16 regions in the TIAM model to the IEA primary energy production/consumption, final consumption and electricity generation (and heat) data.

'''''Table 1.1: Regions in TIAM-UCL'''''

{| class="wikitable"
|width="20%"|'''Region'''
|width="80%"|'''Countries'''
|-
|'''Africa (AFR)'''
|Algeria, Angola, Benin, Cameroon, Congo, Congo Republic, Egypt, Ethiopia, Gabon, Ghana, Ivory Coast, Kenya, Libya, Morocco, Mozambique, Nigeria, Other Africa, Senegal, South Africa, Sudan, Tanzania, Tunisia, Zambia, Zimbabwe
|-
|'''Australia (AUS)'''
|Australia and New Zealand
|-
|'''Canada (CAN)'''
|Canada
|-
|'''Central and South America (CSA)'''
|Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Jamaica, Netherlands Antilles, Nicaragua, Other Latin America, Panama, Paraguay, Peru, Trinidad-Tobago, Uruguay, Venezuela
|-
|'''China (CHI)'''
|China
|-
|'''Eastern Europe (EEU)'''
|Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Czech Republic, Hungary, Macedonia, Poland, Romania, Slovakia, Slovenia, Yugoslavia
|-
|'''Former Soviet Union (FSU)'''
|Armenia, Azerbaijan, Belarus, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine, Uzbekistan
|-
|'''India (IND)'''
|India
|-
|'''Japan (JAP)'''
|Japan
|-
|'''Mexico (MEX)'''
|Mexico
|-
|'''Middle-east (MEA)'''
|Bahrain, Cyprus, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, Turkey, United Arab Emirates, Yemen
|-
|'''Other Developing Asia (ODA)'''
|Bangladesh, Brunei, Chinese Taipei, Indonesia, North Korea, Malaysia, Myanmar, Nepal, Other Asia, Pakistan, Philippines, Singapore, Sri Lanka, Thailand, Vietnam
|-
|'''South Korea (SKO)'''
|South Korea
|-
|'''United Kingdom (UK)'''
|United Kingdom
|-
|'''USA (USA)'''
|United States of America
|-
|'''Western Europe (WEU)'''
|Austria, Belgium, Denmark, Finland, France, Germany, Gibraltar, Greece, Greenland, Iceland, Ireland, Italy, Luxembourg, Malta, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland
|}

Spatial dimension - TIAM-UCL

2016-12-14T19:37:03Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Spatial dimension
}}
TIAM-UCL is a global model with 16 regions listed in the table below, each of which has their own energy system.

The TIAM-UCL model has been developed at UCL since 2010 and differs from the ETSAP-TIAM model in two ways: the first is breaking out the UK from the 15 region ETSAP-TIAM model; the second is enhancing TIAM-UCL by revising/adding new drivers and resources for all regions and adding new features.

In order to break out the UK from Western Europe (WEU) region, separate Base-Year templates were created for end-use sectors, upstream and power sectors for the UK and calibrated final energy consumption to the actual base year data 2005 for the UK and the WEU regions. The underlying data for the base year calibration in TIAM-UCL is the IEA Extended Energy Balances of OECD and non-OECD countries. This data can be accessed through the online portal https://www.ukdataservice.ac.uk/ in the UK. A database of the IEA Extended Energy Balances has been developed to import the IEA data into the data tables on the base year templates in the TIAM-UCL with a software application which allows easy aggregation of country data into regions. Energy services demands for different end-use sectors and drivers of projections of demands during the model period 2005-2100 were created for the UK region. Besides the calibration of resource and trade modules of the UK and the WEU regions, all other scenario files were also updated and calibrated.

Once the 16R TIAM-UCL had been successfully calibrated, the model was enhanced through technical improvements such as adding new drivers, new resources, climate change policies (cap-and-trade, carbon tax), supply resource cost curves etc. Development of the database of the IEA Extended Energy Balances helped to recalibrate all 16 regions in the TIAM model to the IEA primary energy production/consumption, final consumption and electricity generation (and heat) data.

'''''Table 1.1: Regions in TIAM-UCL'''''

{| class="wikitable"
|width="20%"|'''Region'''
|width="80%"|'''Countries'''
|-
|'''Africa (AFR)'''
|Algeria, Angola, Benin, Cameroon, Congo, Congo Republic, Egypt, Ethiopia, Gabon, Ghana, Ivory Coast, Kenya, Libya, Morocco, Mozambique, Nigeria, Other Africa, Senegal, South Africa, Sudan, Tanzania, Tunisia, Zambia, Zimbabwe
|-
|'''Australia (AUS)'''
|Australia and New Zealand
|-
|'''Canada (CAN)'''
|Canada
|-
|'''Central and South America (CSA)'''
|Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Jamaica, Netherlands Antilles, Nicaragua, Other Latin America, Panama, Paraguay, Peru, Trinidad-Tobago, Uruguay, Venezuela
|-
|'''China (CHI)'''
|China
|-
|'''Eastern Europe (EEU)'''
|Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Czech Republic, Hungary, Macedonia, Poland, Romania, Slovakia, Slovenia, Yugoslavia
|-
|'''Former Soviet Union (FSU)'''
|Armenia, Azerbaijan, Belarus, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine, Uzbekistan
|-
|'''India (IND)'''
|India
|-
|'''Japan (JAP)'''
|Japan
|-
|'''Mexico (MEX)'''
|Mexico
|-
|'''Middle-east (MEA)'''
|Bahrain, Cyprus, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, Turkey, United Arab Emirates, Yemen
|-
|'''Other Developing Asia (ODA)'''
|Bangladesh, Brunei, Chinese Taipei, Indonesia, North Korea, Malaysia, Myanmar, Nepal, Other Asia, Pakistan, Philippines, Singapore, Sri Lanka, Thailand, Vietnam
|-
|'''South Korea (SKO)'''
|South Korea
|-
|'''United Kingdom (UK)'''
|United Kingdom
|-
|'''USA (USA)'''
|United States of America
|-
|'''Western Europe (WEU)'''
|Austria, Belgium, Denmark, Finland, France, Germany, Gibraltar, Greece, Greenland, Iceland, Ireland, Italy, Luxembourg, Malta, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland
|}

Temporal dimension - TIAM-UCL

2016-12-14T19:21:39Z

Matthew Winning:

{{ModelDocumentationTemplate
|IsEmpty=No
|IsDocumentationOf=TIAM-UCL
|DocumentationCategory=Temporal dimension
}}
The model base year is 2005 with data taken from IEA Energy Balances.

The model time horizon is 95 years (2005-2100) with 5 year time steps up to 2070 and with 10 year time steps beyond.
Each year is divided to six time slices + an additional peaking constraint.

Demand fractions (see Table 1.2) determine the fraction of service demand to be met during a specific period of the day in a given season (or timeslice).

The temporal resolution is determined by three seasons, summer, winter and intermediate. Each of the seasons accounts for a third of the whole year or 4 month. These timeslices are again split into night and day, where day represents 16 hours and night 8 hours (Table 1-2).

Therefore there a six timeslice possibilities of:

* summer-day,
* summer-night,
* intermediary day,
* intermediary-night,
* winter-day,
* winter-night

'''Table 1.2: Fraction of energy-service demands'''

{| class="wikitable"
|width="25%"|'''Time slice'''
|width="25%"|'''Month share'''
|width="25%"|'''Day share'''
|width="25%"|'''Fraction'''
|-
|'''ID'''
|0.333 (4 months)
|0.666 (16 hours)
|0.223
|-
|'''IN'''
| 
|0.333 (8 hours)
|0.111
|-
|'''SD'''
|0.333
|0.666
|0.223
|-
|'''SN'''
| 
|0.333
|0.111
|-
|'''WD'''
|0.333
|0.666
|0.221
|-
|'''WN'''
| 
|0.333
|0.111
|}

The model is generally run with perfect foresight but can be run as myopic or stochastic though this is generally not the case.