Energy demand

Baseline energy service demands are provided exogenously to MESSAGEix, though they can be adjusted endogenously based on energy prices using the MESSAGEix-MACRO link. There are seven energy service demands that are provided to MESSAGEix, 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 R. The scenario generator relates historical country-level GDP per capita (PPP) to final energy and, using projections of GDP (PPP) and population, 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 [117])

  2. Historical Population – UN Population Division (World Population Projection, 2010 [10])

  3. Historical Final Energy – International Energy Agency Energy Balances (IEA, 2012 [1])

  4. Projected GDP (PPP) – Dellink et al. (2015) [9], also see Shared Socio-Economic Pathways database (SSP scenarios)

  5. Projected Population – KC and Lutz (2014) [40], also see Shared Socio-Economic Pathways database (SSP scenarios)

The scenario generator runs regressions on the historical datasets to establish the relationship for each of the eleven MESSAGEix regions between the independent variable (GDP (PPP) per capita) and the following dependent variables:

  1. Total final energy intensity (MJ/2005USD)

  2. Shares of final energy among several energy end-use sectors (transport, residential/commercial and industry)

  3. Shares of electricity use between the industrial and residential/commercial 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 Schafer (2005) [98].

In parallel, the same historical data are used, now globally, in quantile regressions to develop global trend lines that represent each percentile of the cumulative distribution function (CDF) of each dependent 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.

A basic assumption here is that the regional trends derived above will converge to certain quantiles of the global trend when each region reaches a certain income level. Hence, two key user-defined inputs allow users to tailor the extrapolations to individual socio-economic scenarios: convergence quantile and the corresponding income. 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 within the global trend) 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 Table 21, Table 22, Table 23. 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, users 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, users 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 used in the MESSAGE model for each model region (Regions).

Table 21 Convergence quantile and income for each quantity and region for SSP1 (for region descriptions, see: Regions)

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

Table 22 Convergence quantile and income for each quantity and region for SSP2 (for region descriptions, see: Regions)

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

Table 23 Convergence quantile and income for each quantity and region for SSP3 (for region descriptions, see: Regions)

SSP3

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