A N N A K R O O K R I E K K O L A , L U L E Å U N I V E R S I T Y O F T E C H N O L O G Y ( L T U )

C H A R L O T T E B E R G ,

N A T I O N A L I N S T I T U T E O F E C O N O M I C R E S E A R C H ( N I E R )

E R I K A H L G R E N , C H A L M E R S U N I V E R S I T Y O F T E C H N O L O G Y ( C H A L M E R S )

P A T R I K S Ö D E R H O L M ,

L U L E Å U N I V E R S I T Y O F T E C H N O L O G Y ( L T U )

Challenges in Top-down and Bottom-up Soft Linking: The Case

of EMEC and TIMES-Sweden

T H E P R O J E C T I S F I N A N C E D B Y T H E S W E D I S H E N E R G Y A G E N C Y

1

Why, Aim and Philosophy

Why: The development of the future energy system depend on the future demand of energy. The future demand of energy partly depend on the economic development. The sector development partly depend on the energy prices.

⇒ Everything is linked! Aim:

The overall aim has been to develop a method for how to soft-link a CGE model with an Energy System model to improve energy and climate policy decision processes.

Philosophy: To develop a method allowing the models to interact in a transparent manner while at the same time maintaining each model's strengths

2

Litterature

Incorporate more technological detail in a CGE model Frei et al. (2003) McFarland et al. (2004) McFarland and Herzog, 2006 ) Böhringer and Rutherford (2008)

To extend an energy bottom-up model with economic interactions

Messner and Schrattenholzer (2000), MESSAGE with MACRO Chen (2005), MARKAL- China with MACRO Remme and Blesl (2006), TIMES with MACRO Strachan and Kannan (2008) , MARKAL-UK with MACRO *MACRO is a one-sectorial general equilibrium module

Combine the strengths of both type of models by soft-linking to existing models

Wene (1996), ETA-MACRO with MESSEGE Jaccard et al. (2003) Schäfer and Jacoby (2006), EPPA (based on GTAP4E) with MARKAL model of transport technology Altamirano et al. (2008), GEMINI-E3 with MARKAL-CHRES

Common for most studies:

Hard-linking where one existing full-scale model is linked with a simplified model capturing the other part (macroeconomic or energy system).

A substantiated description of the soft-linking procedure and its challenges are missing.

3

Approach

I. Identifying the models

II. Identifying what to link (based on Wene, 1996)

III. Deciding how to link

4

C G E M O D E L : E M E C Provides a consistent description of how different

economic sectors interact with each other

E N E R G Y S Y S T E M M O D E L : T I M E S - S W E D E N Provides a technology detailed description of the energy system and capture the most important

interactions within the energy system

I. Identifying the models 5

EMEC: Environmental Medium term EConomic model

A c t i v i t y l e v e l

V a l u e a d d e d

C E S

L a b o u r C a p i t a l

S k i l l e d l a b o u r

C E S

E n e r g y - M a t e r i a l

M a t e r i a l E n e r g y

C E S

L e o n t i e f

1 7 M a t e r i a l i n p u t s

E l e c t r i c i t y W o o d C o a l O i l G a s

U n s k i l l e d l a b o u r

C E S

C E S

T r a n s p o r t s

P a s s A i r H e a v y F r e i g h t

L i g h t t r u c k s

C E S

C E S

T r a i n S e a L a r g e t r u c k s

M e d i u m t r u c k s

D i s t r i c t H e a t i n g

L a b o u r

C E S

6

TIMES-Sweden: The Integrated MARKAL- EFOM System applied on Sweden

En

erg

y S

erv

ice

s

B i o m a s s I

C o a l

O i l

G a s

D i s t r i c t H e a t i n g

B i o m a s s I I

B i o m a s s I I I

E l e c t r i c i t y

U r a n i u m

H y d r o

W i n d

P o w e r P l a n t

C H P

H e a t P l a n t

… … .

… … .

E n e r g y S y s t e m

M o d e l

7

1 . I D E N T I F Y I N G B A S I C D I F F E R E N C E S B E T W E E N T H E M O D E L S

2 . I D E N T I F Y I N G T H E D O M I N A N T M O D E L , W H E N O V E R L A P

3 . I D E N T I F Y I N G A N D D E C I D E U P O N C O M M O N E X O G E N O U S V A R I A B L E S

II. Identifying what to link 8

Identifying basic differences EMEC TIMES-Sweden

Focus EMEC focuses on monetary flows from energy, materials, capital and labour, and in addition calculates emissions in metric tonnes.

TIMES-Sweden focuses on physical flows of energy, materials, emission and certificates.

How prices are treated

Prices are normalized to the base-year value at current prices. Only relative price changes are modeled.

Prices are normalized to a base-year. Energy carriers with exogenous prices have a specified price for each time period. Fuels traded on the global market will vary over time in line with official projections.

How energy conversion technologies are described

Continuous production functions, where substitution elasticities are key parameters (CES-production functions).

Discrete processes / techniques with defined techno (efficiency, availability, etc.) and economic (capital, operating costs, etc.) parameters. Parameters that vary over time to capture technology development.

Time Dimension Static Dynamic

Base-Year 2008 2000 and calibrated to 2005

Sector breakdown Based on national accounts and follows the industry and sector b kd i h i l

Based on energy statistics and follows the industry and sector breakdown in the

i i

Mind-Set

Focus on change

Industry and Sector Breakdown

EMEC treats the economic development in each sub-sector while TIMES-Sweden analyze the effect from the development in end-use

Mapping sectors Which end use sector goes with which?

Not straight forward! What does it mean that a sub-sector is growing?

EMEC: Internal trade within a sector can also generate growth What to do when sub-sectors and end-use don’t match?

Sometimes it doesn’t matter: What is big in the economy doesn’t necessary demand energy.

Sometimes simplifications are needed ⇒ The Mapping depend on the direction! EMEC → TIMES TIMES → EMEC

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19. Rail road transports

20 Road goods transports

21. Road passenger transports

22. Sea transports

23. Air transports

Railway-Freight

Railway- People Long distance

Railway- People Short distance

Road-Freight

Bus - Urban

Bus - Intercity

Navigation/National

Navigation/International

Aviation/National

Aviation/International

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TC-Car- Short distance

TC-Car- Long distance

TC-Motorcycle

Commercial, Service and Public

Residential Sector

24. Other transports

25. Services

26. Real estate

Households

TIMES → EMECSum EMEC transportation fuels in Sector 24-26 & Households = Sum TIMES-Sweden fuel consumption in TC-***

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8. Drug industries

9. Other chemical industries

10. Iron & steel industries

11. Non-iron metal industries

13. Petroleum refineries

14. Electricity supply

15. Hot water supply (DH)

16. Gas distribution

IC-Ammonia

IC-Chlorine

IC-Other

Iron and steel

INF-Aluminium

INF-Copper

INF-Other Non Ferrous Metals

Electricity & Heat

Supply

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1. Agriculture

2. Fishery

3. Forestry

4. Mining

5. Other industries

6. Mineral products

7. Paper (Pulp and paper mills)

7. Paper (Printing & Publishing)

12. Engineering

17. Water and sewage

18. Construction

Agriculture, fishery and forestry

Other industries

INM-Cement

INM-Glass Hollow

INM-Glass Flat

INM-Other

IPP-High quality

IPP-Low quality

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1 . I D E N T I F Y I N G B A S I C D I F F E R E N C E S B E T W E E N T H E M O D E L S

2 . I D E N T I F Y I N G T H E D O M I N A N T M O D E L , W H E N O V E R L A P

3 . I D E N T I F Y I N G A N D D E C I D E U P O N C O M M O N E X O G E N O U S V A R I A B L E S

II. Identifying what to link 11

Identifying overlaps and action

Overlapping sectors: There are many overlaps in sector break-down:

→ The mapping will be different when going from EMEC to TIMES-Sweden compared to when going from TIMES-Sweden to EMEC.

Overlapping endogenous variables, identify the “Dominant Model” (DM), and which model that should adapt: Energy mix:

→ DM: TIMES-Sweden Energy intensity (energy/produced unit):

→ DM: TIMES-Sweden Energy level (EMEC in SEK while TIMES-Sweden in TJ): →The two models should converge

12

1 . I D E N T I F Y I N G B A S I C D I F F E R E N C E S B E T W E E N T H E M O D E L S .

2 . I D E N T I F Y I N G T H E D O M I N A N T M O D E L , W H E N O V E R L A P

3 . I D E N T I F Y I N G A N D D E C I D E U P O N C O M M O N E X O G E N O U S V A R I A B L E S

II. Identifying what to link 13

Identifying similarities

Need similar kind of inputs: Fossil fuel prices Policy instruments (taxes, green certificates, EU-ETS etc)

Estimates: Electricity generation mix Final energy demand Net CO2 emissions

Base-Year calibration Electricity price Energy mix Energy intensity Energy level

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1 .TR A N SFER R ING IN F OR MATION F R OM EM EC T O TIMES

2 .MOVIN G IN F OR MA TION

F R OM TIMES T O EM EC

3 .DECIDING WHER E T O ST A R T

III. Deciding how to link 15

Yearly change in demand:

𝑌𝑌𝑖,1 = ∝𝑖∙ 𝑌𝑌𝑖,1

A c t i v i t y l e v e l

V a l u e a d d e d

C E S

L a b o u r C a p i t a l

S k i l l e d l a b o u r

C E S

E n e r g y - M a t e r i a l

M a t e r i a l E n e r g y

C E S

L e o n t i e f

1 7 M a t e r i a l i n p u t s

E l e c t r i c i t y W o o d C o a l O i l G a s

U n s k i l l e d l a b o u r

C E S

C E S

T r a n s p o r t s

P a s s A i r H e a v y F r e i g h t

L i g h t t r u c k s

C E S

C E S

T r a i n S e a L a r g e t r u c k s

M e d i u m t r u c k s

D i s t r i c t H e a t i n g

L a b o u r

C E S

Energy efficiency parameter: 𝐸𝐸𝑖,2 𝑌𝐸𝑖,2� = 𝐸𝐸𝑖,1

𝑌𝐸𝑖,1�

Energy mix: Over write the existing substitution elasticity (make σ = 0), and define the share of each fuel for each industry/sector.

Energy price: Mark-up on capital in the electricity and heat sector.

σ = ? σ = 0

En

erg

y S

erv

ice

s

B i o m a s s I

C o a l

O i l

G a s

D i s t r i c t H e a t i n g

B i o m a s s I I

B i o m a s s I I I

E l e c t r i c i t y

U r a n i u m

H y d r o

W i n d

P o w e r P l a n t

C H P

H e a t P l a n t

… … .

… … .

E n e r g y S y s t e m

M o d e l

E M E C

TIMES-Sweden

“Translation models”

16

Policy Analysis This is an illustrative example – We have not evaluated

to what extent the results are plausible

Will the iteration between the models change the reference scenario?

R E F E R E N C E S C E N A R I O : • A reference scenario puts the economy and energy at the

"right level“ • The reference scenario is based on the Long-term scenario

developed at the NIER, but without energy efficiency parameters.

C L I M A T E S C E N A R I O : • CO2-taxes in the non ETS sectors increased with 50% • CO2-prices within EU ETS increases to 30 €/ ton CO2 in

2020 and stays on this level over the modeling period (2035)

17

Iteration process → Ref NL

→ Ref SL

→ Climate SL

→ Climate NL-Climate

→ Climate NL-Ref

Ref: Reference Scenario K: Climate Scenario E: EMEC T: TIMES-Sweden xi: iteration nr x NL: No Linking SL: Soft-Linking

Main Conclusions from Iteration

Iteration Process The first iteration result in a significant adaptation of the economy affecting the

energy use. The following iterations only result in smaller changes. →Crucial that the demand assumptions reflect the scenario assumptions The electricity price has been proven an important component

Reference Scenario Iteration Climate Scenario Iteration

Economic development The difference is greatest for the energy-intensive industries.

Relatively small effects on industries' economic development.

Energy level (volume) Decreases Relatively large differences in fuel use in the electricity and district heating sector.

Fuel mix Fuel mix change as when the energy level decreases.

The fuel mix changes differently than in the reference iteration. Especially fuel choice for road transport .

CO2-emissions Decreases Reduction from Reference scenario is similar. However when the absolute levels are lower, the reduction will be easier facilitated.

19

Identified Challenges

Translation parameters (EMEC → TIMES-Sweden): More research is needed on the relation between economic growth and “useful demand”.

Representation of new energy carriers (in EMEC); for example hydrogen Energy prices:

The representation of the cost associated with delivered electricity need to be improved in TIMES-Sweden in order to capture the same features as in EMEC.

The calibration of past years should in addition to the energy balance also include calibration of prices.

Investments: Some studies uses the total system cost from TIMES/MARKAL.

However there are many overlaps in the total system costs. We suggest to instead only use the “investment parts” from the system costs.

Calibration of Base-year:

Similar Base-year is less important. Calibrate both regarding volume, mix and endogenous prices.

Do not underestimate the differences in “mind-set” Communication across borders Both expertise are crucial for the result

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A N N A . K R O O K - R I E K K O L A @ L T U . S E

Thanks for your attention!

S O F T L I N K I N G G I V E S A N E W P I C T U R E O F T H E E C O N O M Y ' S E N E R G Y U S E C O M P A R E D T O

M O D E L R E S U L T S W I T H O U T S O F T L I N K I N G

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References

Altamirano J.-C., L. Drouet, A. Sceia, P. Thalmann and M. Vielle (2008), “Coupling GEMINI-E3 and MARKAL-CHRES to Simulate Swiss Climate Policies”, report from Research lab on the Economics and Management of the Environment, École Polytechnique Fédérale de Lausanne.

Böhringer C., T.F.Rutherford (2008), ”Combining Bottom-Up and Top-Down”, Energy Economics, Vol 30 (2), pp 574-596. Chen W (2005). “The costs of mitigating carbon emissions in China: findings from China MARKAL-MACRO modeling”. Energy

Policy 33: 885–896. Frei C.W., Haldi P-A., Sarlos G. (2003), “Dynamic formulation of a top-down and bottom-up merging energy policy model”.

Energy Policy 31: 1017–1031. Jaccard M., R. Loulou, A. Kanudia, J.Nyboer, A. Bailie, M. Labriet (2003), “Methodological contrasts in costing greenhouse gas

abatement policies: Optimization and simulation modeling of micro-economic effects in Canada”. European Journal of Operational Research, Vol145, pp148–164.

McFarland, J.R., Reilly, J.M., Herzog, H.J. (2004), “Representing energy technologies in top-down models using bottom-up information”. Energy Economics 26, 685-707.

McFarland, J.R., Herzog, H.J. (2006), “Incorporating carbon capture and storage technologies in integrated assessment models ”. Energy Economics 28, 632-652.

Messner S. and L. Schrattenholzer (2000), “MESSAGE-MACRO: linking an energy supply model with a macroeconomic module and solving it iteratively”. Energy Vol. 25 pp 267-282.

Remme U., M. Blesl (2006), Documentation of the TIMES-MACRO model, Energy Technology Systems Analysis Programme. http://www.etsap.org.

Schäfer, A., Jacoby, H.D. (2006), “Experiments with a Hybrid CGE-MARKAL Model”. The Energy Journal, Special Issue, pp. 171-177.

Strachan, N., R. Kannan (2008), “Hybrid modelling of long-term carbon reduction scenarios for the UK”, Energy Economics 30, 2947–2963.

Wene, C-O (1996), “Energy-economy analysis: linking the macroeconomic and systems engineering approaches”, Energy, Vol. 21, pp 809-824.

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