Energy demand - TIAM-UCL: Difference between revisions
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== Behavioural change == | == Behavioural change == | ||
Behaviour and heterogeneous agents | 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). | ||
Diffusion constraints can be | |||
Latest revision as of 18:46, 14 December 2016
| Corresponding documentation | |
|---|---|
| Previous versions | |
| Model information | |
| Model link | |
| 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 21st 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 2nd 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).