Energy demand - MESSAGE-GLOBIOM

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Model Documentation - MESSAGE-GLOBIOM

Corresponding documentation
Previous versions
Model information
Model link
Institution International Institute for Applied Systems Analysis (IIASA), Austria, http://data.ene.iiasa.ac.at.
Solution concept General equilibrium (closed economy)
Solution method Optimization
Anticipation

Baseline energy service demands are provided exogenously to MESSAGE, though they can be adjusted endogenously based on energy prices using the MESSAGE-MACRO link. There are seven energy service demands that are provided to MESSAGE, including:

  1. Residential/commercial thermal
  2. Residential/commercial specific
  3. Industrial thermal
  4. Industrial specific
  5. Industrial feedstock (non-energy)
  6. Transportation
  7. Non-commercial biomass.

These demands are generated using a so-called scenario generator which is implemented in the script language [[1]]. The scenario generator uses country-level historical data of GDP per capita (PPP) and final energy use as well as projections of GDP (PPP) and population to extrapolate the seven energy service demands into the future. The sources for the historical and projected datasets are the following:

  1. Historical GDP (PPP) – World Bank (World Development Indicators 2012 MSG-GLB_world_bank_group_world_2012)
  2. Historical Population – UN Population Division (World Population Projection 2010 MSG-GLB_un_population_division_world_2010)
  3. Historical Final Energy – International Energy Agency Energy Balances (IEA 2012 MSG-GLB_international_energy_agency_energy_2012)
  4. Projected GDP (PPP) – Dellink et al (2015 MSG-GLB_dellink_long-term_2015), see Shared Socio-Economic Pathways database (scenarios)
  5. Projected Population – KC and Lutz (2014 MSG-GLB_kc_human_2014), see Shared Socio-Economic Pathways database(scenarios)

The scenario generator runs regressions on the historical datasets to establish the relationship between the independent variable (GDP (PPP) per capita) and several dependent variables, including total final energy intensity (MJ/2005USD) and the shares of final energy in several energy sectors (%). In the case of final energy intensity, the relationship is best modeled by a power function so both variables are log-transformed. In the case of most sectoral shares, only the independent variable is log-transformed. The exception is the industrial share of final energy, which uses a hump-shaped function inspired by Schäfer (2005) MSG-GLB_schafer_structural_2005. This portion of the model provides the historical relationships between GDP per capita and the dependent variables for each of the eleven MESSAGE regions.

The historical data are also used in regressions to develop global trend lines that represent each percentile of the cumulative distribution function (CDF) of each regressed variable. Given the regional regressions and global trend lines, final energy intensity and sectoral shares can be extrapolated based on projected GDP per capita, or average income. Several user-defined inputs allow the user to tailor the extrapolations to individual socio-economic scenarios. In the case of final energy intensity (FEI), the extrapolation is produced for each region by defining the quantile at which FEI converges (e.g., the 20th percentile) and the income at which the convergence occurs. For example, while final energy intensity converges quickly to the lowest quantile (0.001) in SSP1, it converges more slowly to a larger quantile (0.5 to 0.7 depending on the region) in SSP3. Convergence quantiles and incomes are provided for each SSP and region in <xr id="tab:MESSAGE-GLOBIOM_quantssp1"/>, <xr id="tab:MESSAGE-GLOBIOM_quantssp2"/> and <xr id="tab:MESSAGE-GLOBIOM_quantssp3"/>. The convergence quantile allows one to identify the magnitude of FEI while the convergence income establishes the rate at which the quantile is approached. For the sectoral shares, the user can specify the global quantile at which the extrapolation should converge, the income at which the extrapolation diverges from the regional regression line and turns parallel to the specified convergence quantile (i.e., how long the sectoral share follows the historical trajectory), and the income at which the extrapolation converges to the quantile. Given these input parameters, the user can extrapolate both FEI and sectoral shares.

The total final energy in each region is then calculated by multiplying the extrapolated final energy intensity by the projected GDP (PPP) in each time period. Next, the extrapolated shares are multiplied by the total final energy to identify final energy demand for each of the seven energy service demands used in MESSAGE. Finally, final energy is converted to useful energy in each region by using the average final-to-useful energy efficiencies reported by the IEA for each country.

<figtable id="tab:MESSAGE-GLOBIOM_quantssp1">

Convergence quantile and income for each parameter and region for SSP1 (for region descriptions, see: Spatial dimension of MESSAGE-GLOBIOM)
SSP1 AFR CPA EEU FSU LAM MEA NAM PAO PAS SAS WEU
Convergence Quantile
Final Energy Intensity (FEI) 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001
Share NC Biomass 0.01 0.25 0.01 0.75 0.01 0.3 0.01 0.01 0.01 0.01 0.01
Share Transport 0.05 0.02 0.2 0.05 0.2 0.05 0.2 0.2 0.04 0.03 0.2
Share Res/Com 0.25 0.25 0.2 0.2 0.28 0.3 0.25 0.2 0.28 0.3 0.2
Share Industry 0.1 0.2 0.1 0.5 0.28 0.2 0.3 0.3 0.28 0.2 0.3
Elec Share Res/Com 0.45 0.45 0.45 0.45 0.63 0.62 0.4 0.63 0.62 0.64 0.43
Feedstock Share Industry 0.18 0.2 0.24 0.24 0.2 0.26 0.26 0.23 0.26 0.22 0.24
Elec Share Industry 0.4 0.4 0.42 0.36 0.4 0.33 0.36 0.36 0.4 0.4 0.4
Convergence Income
Final Energy Intensity (FEI) 112295 98603 299177 112307 100188 113404 112356 112261 106323 112300 107636
Share NC Biomass 5981 46015 34405 40951 20038 34894 112356 112261 16357 11105 48153
Share Transport 99676 32868 112341 71664 112310 113404 123018 94337 112293 97169 141627
Share Res/Com 119611 112276 179506 153565 112310 112270 123018 157229 112293 112300 141627
Share Industry 39870 105177 164547 92139 40075 112270 123018 112261 126769 83288 127464
Elec Share Res/Com 112295 112276 112341 112307 112310 87234 131219 132072 112293 112300 112168
Feedstock Share Industry 112295 112276 112341 112307 112310 112270 123018 125783 112293 112300 112168
Elec Share Industry 112295 98603 299177 112307 100188 113404 112356 112261 106323 112300 107636

</figtable>

<figtable id="tab:MESSAGE-GLOBIOM_quantssp2">

Convergence quantile and income for each parameter and region for SSP2 (for region descriptions, see: Spatial dimension of MESSAGE-GLOBIOM)
SSP2 AFR CPA EEU FSU LAM MEA NAM PAO PAS SAS WEU
Convergence Quantile
Final Energy Intensity (FEI) 0.03 0.03 0.03 0.04 0.04 0.04 0.05 0.02 0.03 0.03 0.02
Share NC Biomass 0.6 0.6 0.75 0.75 0.25 0.75 0.75 0.75 0.6 0.6 0.75
Share Transport 0.05 0.04 0.15 0.1 0.5 0.3 0.5 0.14 0.2 0.05 0.15
Share Res/Com 0.15 0.28 0.5 0.5 0.3 0.5 0.3 0.35 0.3 0.28 0.33
Share Industry 0.25 0.4 0.15 0.25 0.15 0.25 0.25 0.25 0.25 0.6 0.25
Elec Share Res/Com 0.42 0.4 0.35 0.22 0.58 0.6 0.14 0.57 0.6 0.51 0.18
Feedstock Share Industry 0.15 0.22 0.26 0.26 0.18 0.27 0.32 0.27 0.3 0.22 0.27
Elec Share Industry 0.39 0.38 0.4 0.45 0.35 0.4 0.4 0.4 0.4 0.43 0.35
Convergence Income
Final Energy Intensity (FEI) 200009 200033 299177 266179 199975 139574 246036 141506 199968 200002 199977
Share NC Biomass 19935 26294 77786 40951 20038 94649 94724 132072 12268 18046 48153
Share Transport 49838 105177 94540 94596 80150 94649 94724 94652 81787 27763 99139
Share Res/Com 119611 65735 89753 71664 94577 69787 94724 110060 81787 83288 113301
Share Industry 31896 105177 44877 102377 100188 78511 94724 141506 98144 13881 94607
Elec Share Res/Com 69773 94593 94540 102377 94577 87234 123018 141506 94627 55525 113301
Feedstock Share Industry 19935 94593 94540 94596 94577 94649 94724 94652 94627 94615 94607
Elec Share Industry 200009 200033 299177 266179 199975 139574 246036 141506 199968 200002 199977

</figtable>


<figtable id="tab:MESSAGE-GLOBIOM_quantssp3">

Convergence quantile and income for each parameter and region for SSP3 (for region descriptions, see: Spatial dimension of MESSAGE-GLOBIOM)
SSP2 AFR CPA EEU FSU LAM MEA NAM PAO PAS SAS WEU
Convergence Quantile
Final Energy Intensity (FEI) 0.6 0.55 0.5 0.7 0.7 0.5 0.7 0.5 0.5 0.7 0.6
Share NC Biomass 0.9 0.6 0.75 0.75 0.25 0.75 0.75 0.75 0.6 0.9 0.75
Share Transport 0.1 0.05 0.7 0.2 0.45 0.5 0.7 0.25 0.5 0.1 0.7
Share Res/Com 0.25 0.25 0.55 0.55 0.3 0.5 0.35 0.6 0.25 0.2 0.5
Share Industry 0.1 0.6 0.2 0.1 0.2 0.2 0.1 0.1 0.6 0.2 0.1
Elec Share Res/Com 0.4 0.6 0.45 0.4 0.9 0.9 0.25 0.65 0.9 0.6 0.33
Feedstock Share Industry 0.2 0.22 0.26 0.24 0.2 0.3 0.32 0.29 0.3 0.22 0.27
Elec Share Industry 0.3 0.43 0.37 0.45 0.3 0.4 0.35 0.45 0.4 0.35 0.4
Convergence Income
Final Energy Intensity (FEI) 200009 200033 200000 200044 199975 200027 200109 199995 199968 200002 199977
Share NC Biomass 13955 26294 80927 40951 12023 80953 80782 132072 12268 12771 48153
Share Transport 13955 46015 59835 51188 70131 69787 80782 132072 32715 55525 81010
Share Res/Com 23922 65735 59835 61426 80952 52340 80782 80816 199968 80512 81010
Share Industry 5981 52588 200000 122852 18034 43617 200109 199995 81787 30539 198277
Elec Share Res/Com 80976 80986 80927 61426 80952 69787 80782 80816 80969 80956 81010
Feedstock Share Industry 19935 26294 80927 80980 80952 80953 80782 80816 80969 80956 81010
Elec Share Industry 200009 200033 200000 200044 199975 200027 200109 199995 199968 200002 199977

</figtable>

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