HYBTEP HYBRID TECHNOLOGICAL ECONOMIC … fortes_etsap.pdf · 600 800 900 No Link (It. 0) TIMES-ELAS...

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HYBTEP HYBRID TECHNOLOGICAL ECONOMIC

PLATFORM

Patrícia Fortes, Júlia Seixas

63rd Semi-annual ETSAP meeting, Paris

Motivation

Top-down models

+ Describe the interaction between the energy system and the economy as a whole

− Do not contain technological detail, representing the energy sector in aggregate form

Bottom-up models

+ Represent the energy system with great detail

− Ignore the full macroeconomic feedbacks of different energy system pathways

Policy makers need clear and consistent information concerning the real impact of policies in the economy and the most cost-efficient technology portfolio to achieve a low carbon future

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Context

Hybrid approaches to assess economic, environmental and technological impacts of

long term low carbon scenarios - The Portuguese case:

The objective of HybCO2 research project is to advance on modelling tools and improve impact assessment and energy and climate policy design: • HYBTEP (HYBrid Technological Economic Platform) supported by a soft-link

between the bottom-up model, TIMES_PT and the top-down GEM-E3_PT;

• HYBGED (HYBrid General Equilibrium Dynamic) model sustained by Mixed Complementarity Problem.

HybCO2 is a research project funded by:

HybTEP - Hybrid Technological Economic Platform

Goal:

Obtain a modelling platform with the detailed technological information of TIMES_PT;

Explicit representation of economy and its factors (production, consumption, labour) from GEM-E3_PT.

Approach

Fuel substitution and energy prices are driven by technological decisions within the framework of the TIMES-PT model.

GEM-E3_PT model receives energy demand and the resulting changes in economic output growth are used as adjusted exogenous drivers to the TIMES-PT model.

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Models Harmonization

Defining correspondent sectors and energy commodities

GEM-E3_PT productive sectors/household expenditure category

TIMES_PT sectors

01. Agriculture Agriculture 02. Oil Oil Refinery 03. Coal

Other energy supply 04. Natural Gas 05. Power sector Electricity 06. Ferrous and non-ferrous metals Iron and Steel; Non-ferrous metals 07. Chemical Ammonia; Chlorine; Other chemicals

08. Energy intensive sector Cement; lime; hollow glass; flat glass; other non-

metallic minerals; high quality paper; low quality paper

09. Electric and Other equipment goods; 10. Transport equipment; Other Industries; 11. Consumer Goods Industries; 12. Food and textile; 13. Construction

Other industries

14. Land transport; Road freight, rail freight; buses, intercity coaches,

heavy rail passengers, subway 15. Other transport; Aviation; navigation 16. Services of credit and insurances; 17. Other Market Services; 18. Non Market Services

Services (space heating and cooling, water heating, cooking, refrigeration, electric appliances,

public lighting)

Households operation of transport associated with Operation of transport

Car short distance; car long distance; moto

Households Fuels and power associated with Heating and cooking appliances

Residential (heating, cooling and water heating, lighting, refrigeration, cooking, electric appliances)

Domestic Output

Capital Labor-Energy-Materials

CES

CES

Labor Energy Materials

01.AGR 06.IIS

CES

... 18.COM3

Coal

Electricity

Oil

Gas

Leontief

Biomass

GEM-E3 changes

Original

HybTEP modified version

i. Energy consumption and fuel mix defined exogenously;

ii. New energy commodity: biomass;

iii. Energy prices evolution defined exogenously;

Domestic Output

Capital Labor - Energy - Materials

CES

CES

Labor

Electricity Fuels

En ergy

CES

Materials

01. AGR 06. IIS

CES

Coal Oil

CES

Gas

... 18.COM3 07. ICH

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Coupling Framework

• Sector domestic production growth • GDP growth • Private consumption growth • Sector energy services demand

• Energy consumption per sector/energy carrier

• Energy costs per sector (incl. CO2e price in Policy scenarios)

• Energy consumption in volume (€) • Energy mix (%) • Energy price evolution • Energy efficiency evolution

Demand generator

Linking Process

𝑫𝑬𝑴𝒊,𝒕 = 𝑫𝑬𝑴𝒊,𝒕−𝟏 ∙ 𝟏 + 𝑫𝑹𝑮𝑹𝒊,𝒕 × 𝐄𝐋𝐀𝐒𝒊,𝒕 𝒑𝒆𝒓𝒊𝒐𝒅 𝒍𝒆𝒏𝒈𝒕𝒉

∙ (𝟏 − 𝐀𝐄𝐄𝐈𝒊)

Each cycle represents 1 iteration

Convergence criteria: Min energy services demand difference (Euclidean function)

HYTEP

DG

DG

LP

Reference scenario: no energy/climate policy

Policy scenario: CO2 tax to induce a GHG emissions reduction in line

with EU goal (EU Energy Roadmap: 2020: 25€7ton, 2030: 52€/ton, 2050: >265€/ton )

50 000

100 000

150 000

200 000

250 000

300 000

350 000

400 000

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

M€ 2

00

5

Scenarios

2.9%pa

GDP

Private Consumption 2.8%pa

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Reference Scenario

Demand Convergence: achived after 5 linking cycles

0

2

4

6

8

10

12

14

16

2005 2020 2030 2050

Mt

ICM

It.0

It.1

It.2

It.3

It.4

0

0.5

1

1.5

2

2.5

3

3.5

2005 2020 2030 2050

Mt

IIS

It.0

It.1

It.2

It.3

It.4

0

50

100

150

200

250

300

2005 2020 2030 2050

PJ

Services

It.0

It.1

It.2

It.3

It.4

0

50

100

150

2005 2020 2030 2050

PJ

Residential

It.0

It.1

It.2

It.3

It.4

Reference scenario - GHG

In 2050 the difference between TIMES it.0 and GEM-E3 GHG emissions is 93%

GEM-E3 reduces energy intensity less than 1% per year and no significant change in the fuel mix is observed

TIMES reduces energy intensity at around 2% per year and increases the share of electricity (+9%) from 2005 to 2050

0

20 000

40 000

60 000

80 000

100 000

120 000

2005 2020 2030 2050

kt C

O2e

It.0 / TIMES

It.1

It.2

It.3

It.4

GEM-E3

+93%

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Convergence is achieved after 4 linking cycles

In 2050 the national GHG emissions are reduce: 80.4% with no Link, 83.7% with full iteration (HybTEP) and 84% with TIMES-ELAS, comparing with 1990

Policy scenario

-85.2% / -87.7%

-21.6% / -27.6% -9.8% / -14.3%

Policy Scenario - GHG

No linking versus Hytep versus TIMES-ELAS

0

5

10

15

20

25

30

35

0

200

400

600

800

1 000

1 200

1 400

2005 2020 2030 2050

PJ

kt C

O2

ICH

0.0

1.0

2.0

3.0

4.0

5.0

0

50

100

150

200

2005 2020 2030 2050

Mt

kt C

O2

IPP

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0

50

100

150

200

250

2005 2020 2030 2050

Mt

kt C

O2

IIS

No Link (It. 0)

TIMES-ELAS

HybTEP (It. 3)

No Link (It. 0)

TIMES-ELAS

HybTEP (It. 3)

0

50

100

150

200

250

300

0

500

1 000

1 500

2 000

2 500

3 000

3 500

2005 2020 2030 2050

PJ

kt C

O2

COM

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Policy Scenario – Final Energy

In 2050, TIMES-ELAS reduces more the final energy consumption than HybTEP

The fossil fuels consumption between TIMES-ELAS and HybTEP is almost the same justifying the close GHG emissions

0

100

200

300

400

500

600

700

800

900

No Link(It. 0)

TIMES-ELAS HybTEP(It. 3)

No Link(It. 0)

TIMES-ELAS HybTEP(It. 3)

No Link(It. 0)

TIMES-ELAS HybTEP(It. 3)

2005 2030 2050

PJ

Other (incl. RES)

Biomass

Electricity

Gas

Oil

Coal

-14% -9%

100 000

150 000

200 000

250 000

300 000

350 000

400 000

2020 2030 2040 2050

M€ 2

00

5

GDP impact

REF GDP

Policy GDP

Economic Impact

2020: -3.6%

2030: -3.0%

2050: -6.4%

Policy scenario induces a reduction of annual GDP around 4.5% between 2020 and 2050

Chemical is the industry with higher domestic production reduction comparing with Reference scenario

Domestic Demand: -8% in 2050

Imports: +13% in 2050.

Exports: -69% in 2050

Reduction of Domestic Production

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Conclusions

Modelling energy and/or climate policies with HybTEP allows to:

Obtain the most cost-effective technology portfolio and simultaneously;

Understand in a clear way the macroeconomic impact of such policies (e.g. in production, domestic demand, exports, imports)

Further Work

Replicate energy technologies investment patterns of TIMES_PT on GEM-E3_PT

Include other energy carriers on GEM-E3_PT (e.g. H2);

Thanks for your attention

Patrícia Fortes: p.fs@fct.unl.pt