Energy demand - TIAM-UCL

Model Documentation - TIAM-UCL
Model scope and methods - TIAM-UCL Model concept, solver and details - TIAM-UCL Temporal dimension - TIAM-UCL Spatial dimension - TIAM-UCL Policy - TIAM-UCL Socio-economic drivers - TIAM-UCL Population - TIAM-UCL Economic activity - TIAM-UCL Macro-economy - TIAM-UCL Production system and representation of economic sectors - TIAM-UCL Trade - TIAM-UCL Energy - TIAM-UCL Energy resource endowments - TIAM-UCL Bioenergy - TIAM-UCL Non-biomass renewables - TIAM-UCL Energy conversion - TIAM-UCL Electricity - TIAM-UCL Heat - TIAM-UCL Gaseous fuels - TIAM-UCL Energy end-use - TIAM-UCL Transport - TIAM-UCL Residential and commercial sectors - TIAM-UCL Industrial sector - TIAM-UCL Other end-use - TIAM-UCL Energy demand - TIAM-UCL Technological change in energy - TIAM-UCL Land-use - TIAM-UCL Emissions - TIAM-UCL GHGs - TIAM-UCL Pollutants and non-GHG forcing agents - TIAM-UCL Climate - TIAM-UCL Non-climate sustainability dimension - TIAM-UCL Appendices - TIAM-UCL References - TIAM-UCL
Corresponding documentation
AIM-Hub BLUES C3IAM COFFEE-TEA DNE21+ GCAM GEM-E3 GRACE IFs IMACLIM IMAGE MESSAGE-GLOBIOM POLES PROMETHEUS REMIND-MAgPIE TIAM-UCL WITCH
Previous versions
Archive of TIAM-UCL version 3.1.5
Model information
Model link	https://www.ucl.ac.uk/energy-models/models/tiam-ucl
Institution	University College London (UCL), UK, https://www.ucl.ac.uk.
Solution concept	Partial equilibrium (price elastic demand)
Solution method	Linear optimisation
Anticipation	Perfect Foresight (Stochastic and myopic runs are also possible)

Demand drivers (population, GDP, family units, etc.) are obtained externally, via other models or from other sources (e.g. UN statistics, World Bank, IEA). Energy-service demands and respective drivers in the TIAM-UCL are presented in Table 2-1. The demands for energy services are linked to the drivers' projections via elasticities, see bellow. These elasticities of demands are intended to reflect changing patterns in energy service demands in relation to socio-economic growth, such as saturation in some energy end-use demands, increased urbanization, or changes in consumption patterns once the basic needs are satisfied. The energy-service demands for future years are projected using the following relationship:

Where k is a constant equal to 1 for most of the energy services demand. The constant k is population and number of households when the driver is GDP per Person (GDPP) and GDP per Household (GDPPHOU) respectively.

Table 2-1: Energy-services demand and respective drivers

Code	Description	Unit	Driver
ICH	Chemicals	PJ	PCHEM
IIS	Iron and Steel	Mt	PISNF
INF	Non-ferrous metals	Mt	PISNF
INM	Non Metals	PJ	POEI
ILP	Pulp and Paper	Mt	POEI
IOI	Other Industries	PJ	POI
I00	Other Industrial consumption	PJ	Constant
NEO	Industrial and Other Non Energy Uses	PJ	GDP
ONO	Other non-specified consumption	PJ	GDP
AGR	Agricultural demand	PJ	PAGR
CC1	Commercial Cooling - Region 1	PJ	PSER
CCK	Commercial Cooking	PJ	PSER
CH1	Commercial Space Heat - Region 1	PJ	PSER
CHW	Commercial Hot Water	PJ	PSER
CLA	Commercial Lighting	PJ	PSER
COE	Commercial Office Equipment	PJ	PSER
CRF	Commercial Refrigeration	PJ	PSER
RC1	Residential Cooling - Region 1	PJ	HOU/GDPPHOU*
RCD	Residential Clothes Drying	PJ	HOU/GDPPHOU*
RCW	Residential Clothes Washing	PJ	HOU/GDPPHOU*
RDW	Residential Dishwashing	PJ	HOU/GDPPHOU*
REA	Residential Other Electric	PJ	HOU/GDPPHOU*
RH1	Residential Space Heat - Region 1	PJ	HOU
RHW	Residential Hot Water	PJ	POP
RK1	Residential Cooking - Region 1	PJ	POP
RL1	Residential Lighting - Region 1	PJ	GDPP
RRF	Residential Refrigeration	PJ	HOU/GDPPHOU*
NEU	Non Energy Uses	PJ	GDP
TAD	Domestic Aviation	PJ	GDP
TAI	International Aviation	PJ	GDP
TRB	Road Bus Demand	Bv-km	POP
TRC	Road Commercial Trucks Demand	Bv-km	GDP
TRE	Road Three Wheels Demand	Bv-km	POP
TRH	Road Heavy Trucks Demand	Bv-km	GDP
TRL	Road Light Vehicle Demand	Bv-km	GDP
TRM	Road Medium Trucks Demand	Bv-km	GDP
TRT	Road Auto Demand	Bv-km	GDPP
TRW	Road Two Wheels Demand	Bv-km	POP
TTF	Rail-Freight	PJ	GDP
TTP	Rail-Passengers	PJ	POP
TWD	Domestic Internal Navigation	PJ	GDP
TWI	International Navigation	PJ	GDP

• The driver is GDPPHOU for AFR, CHI, CSA, EEU, FSU, IND, MEA, MEX, ODA and SKO

Driver Elasticity

Driver elasticities determine the sensitivity of changes in energy-service demand to changes in the underlying driver. An elasticity of 1 means that a change of the underlying driver is exactly reflected in the energy-service demand. Energy-service demands with an elasticity below 1 are demand inelastic, while those with an elasticity of one or higher are demand elastic. In general it is assumed that energy-service demands grow slower than the underlying driver, such as GDP, GDP per capita or number of household. This decoupling of energy demand and economic growth is expected to increase during the 21^st century so that all elasticities fall. Residential space heating (RH1), for example, has an elasticity of 0.8 in 2010, which drops to 0.5 in 2100. This means that initially the energy demand for space heating increases at 80% of household number growth, the specific underlying driver, and in the 2^nd half of the century at only 50% of the household number growth rate.

Table 2-2: Driver elasticities for the United Kingdom

Energy-service demand	2010	2020	2030	2040	2050	2100
AGR	0.8	0.8	0.8	0.8	0.8	0.6
CC1	0.8	0.8	0.8	0.8	0.7	0.4
CCK	0.5	0.5	0.5	0.5	0.5	0.4
CH1	0.5	0.5	0.5	0.5	0.5	0.3
CHW	0.5	0.5	0.5	0.5	0.5	0.4
CLA	0.5	0.5	0.5	0.5	0.5	0.4
COE	0.5	0.5	0.5	0.5	0.5	0.4
COT	0.5	0.5	0.5	0.5	0.5	0.4
CRF	0.5	0.5	0.5	0.5	0.5	0.4
I00	0.6	0.6	0.6	0.6	0.6	0.5
ICH	0.8	0.8	0.8	0.8	0.7	0.5
IIS	0.7	0.7	0.7	0.7	0.7	0.5
ILP	0.8	0.8	0.8	0.8	0.7	0.5
INF	0.8	0.8	0.8	0.8	0.7	0.5
INM	0.8	0.8	0.8	0.8	0.7	0.5
IOI	0.8	0.8	0.8	0.8	0.8	0.6
NEO	0.6	0.6	0.6	0.6	0.6	0.5
NEU	1	1	1	1	0.9	0.5
ONO	0.6	0.6	0.6	0.6	0.6	0.5
RCD	1	1	1	1	1	0.8
RCW	1	1	1	1	1	0.8
RDW	1	1	1	1	1	0.8
REA	1	1	1	1	1	0.8
RH1	0.8	0.8	0.8	0.8	0.8	0.5
RK1	0.7	0.7	0.7	0.7	0.7	0.5
RL1	1	1	1	1	0.9	0.7
ROT	1	1	1	1	1	0.8
RRF	1	1	1	1	1	0.8
RHW	1	1	1	1	1	0.8
TAD	1.2	1.2	1.1	1.1	0.9	0.1
TAI	1.2	1.2	1.1	1.1	0.9	0.1
TRB	0.7	0.7	0.7	0.7	0.7	0.8
TRC	0.7	0.7	0.7	0.7	0.7	0.4
TRE	0.7	0.7	0.7	0.7	0.7	0.7
TRH	0.7	0.7	0.7	0.7	0.7	0.4
TRL	0.7	0.7	0.7	0.7	0.7	0.4
TRM	0.7	0.7	0.7	0.7	0.7	0.4
TRT	1.2	1.2	1.2	1.2	1	0.5
TRW	0.7	0.7	0.7	0.7	0.7	0.7
TTF	1	1	1	0.8	0.6	0.1
TTP	0.8	0.8	0.8	0.8	0.8	0.7
TWD	0.8	0.8	0.8	0.6	0.5	0.1
TWI	0.8	0.8	0.8	0.6	0.5	0.1

Non-energy demands are not explicitly considered.

Regional GDP per capita is a driver for the model, but there are no income distribution within a given region. Access issues are not considered either.

Regions can be split to additional subregions for the demand level, thus allowing to model demand separately for, for example, urban and rural areas in the Residential sector. Currently, USA and CAN have four and three geographic regions, respectively, while AFR, CHI, IND, MEA and MEX each have two ?sub-regions?, corresponding to rural and urban areas.

Behavioural change

Behaviour and heterogeneous agents are mostly not explicitly considered but are represented via price mechanisms e.g. there is no modal shift in the transport sector. With the exceptions of technology and region specific discount rates and price responsive energy service demands i.e. see Residential sector. Diffusion constraints can be implemented to simulate behavioural inertia (among the other barriers that are not explicitly included in the model).