Center for Global Trade AnalysisDepartment of Agricultural Economics, Purdue University403 West State Street, West Lafayette, IN 47907-2056 USA

contactgtap@purdue.eduhttp://www.gtap.agecon.purdue.edu

Global Trade Analysis Project

Electricity Sector Disaggregation

Jeffrey C. PetersCenter for Global Trade Analysis, Purdue University

2015 GTAP Advisory Board MeetingFunded by: EC IPTS, OECD, US EPA, MIT Joint Program

• There is currently one electricity sector (‘ely’)• “production, collection, and distribution of electricity”

• Objectives: • Disaggregate ‘ely’ into transmission & distribution and relevant

generating technologies• Consistent with GTAP• Make the electricity-detailed database and documentation available to

the GTAP community

The objective

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• End of 2014 - Project “begins”

• March 6, 2015 – First draft of v8 database and documentation sent to funding agencies

• May 15 – Review of first draft received from agencies

• May 18 – Automated disaggregation process

• May 22 – Second draft of final GTAP v9 release (2004, 2007, and 2011) and documentation sent to funding agencies

Project timeline (completed)

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• June 30 – Documentation submit to JGEA

• July – Electricity-detailed GTAP v9 databases posted to website• GTAP v9 database (2004, 2007, and 2011)• Funding agencies to determine levels of access

• Board only? Fee? Free access with GTAP?

• GTAP v10 –Automated disaggregation process• New data (costs, taxes, and GWh)• Plan of action on how this exercise could “inform” the GTAP v10 data

Project timeline

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• There is a supply-side, demand-side, and trade aspect to the full disaggregation.

• The supply-side is the most interesting• Reconciling “bottom-up” and “top-down” data

Electricity disaggregation

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Tech 1 Tech … Tech TCapitalO&MCoalGasOil

GTAP ‘ely’CapitalO&MCoalGasOil

• Transmission & distribution• NuclearBL• CoalBL• GasBL• HydroBL• OilBL• WindBL• OtherBL• GasP• OilP• HydroP• SolarP

The disaggregate sectors and technologies

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• Separate T&D from generation• Separate “base” and “peak”

load• Capture basic differences in cost

structures between technologies using same fuels

• Allows for some operational consideration (e.g. nesting)

• Not enough detailed data for specific technologies (i.e. CT, CC, or ST)

• The new sectors must sum to the GTAP ‘ely’ totals• Provides constraints in our optimization problem• Provides values for “own-use” and production taxes

• GTAP ‘cmn’ helps determine the cost structure target for transmission and distribution

• Coverage: all inputs and regions

The “top-down” data: GTAP

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• IEA Energy Balances and EIA International Energy Statistics• IEA has wide coverage• EIA used for small countries and “rest of” GTAP mappings

• Total electricity production by fuel source• Algorithm splits the fuel sources between base and peak for

hydro, oil, and gas• 85% base and 15% peak• Minimized cost allocation• Currently a “bang-bang” solution: only one source is both base and peak

• Coverage: different mappings, but all regions

The “bottom-up” data: GWh

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• Annualized costs of generation (LCOE)

The “bottom-up” data: LCOE

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LCOE Definition GTAP sectorsInvestment (Inv) Overnight costs including pre-construction, construction,

and contingency cost including interest accrued during construction. Includes decommissioning cost

‘Capital’

Fuel Cost of fuel per year based on fixed capacity factor (load factors) and heat rate for each technology.

‘coa’, ‘oil’, ‘p_c’, ‘gas’, ‘gdt’

Own-use Electricity generated for in-plant operations ‘ely’Operating and maintenance (O&M)

Includes labor, inputs, and services used to support the operations of the plant (e.g. lubricants, administration).

All other sectors

Effective tax (tax) Taxes on produced electricity by technology. ‘PTAX’

• IEA/NEA coverage is poor globally:• Investment – 81 out of 1,540 technology-region pairs• O&M - 81 out of 1,540 • Fuel – 51 out of 840• Coverage exists for major economies (US, EU, Russia, and China)

• Tax – totals in GTAP, but no good source by technology• Only US taxes included in current database

• Own-use – totals in GTAP, assumed equal across technologies• Filling in the blanks

• Average capital and O&M• Fuel costs weighted by implicit prices with US as reference

• Example: if gas cost in US is half of Nepal, then LCOE of gas in Nepal is half of US• Residual production taxes distributed equally for each technology

The “bottom-up” data: LCOE

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• O&M doesn’t map as easily to GTAP sectors (58)• We use a “probability” mapping

• Probability an O&M input is T&D versus generation• Probability an O&M input is in a specific generation technology

• Helps construct the target matrix for O&M

The “bottom-up” data: O&M

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GTAP sector NuclearBL CoalBL GasBL WindBL HydroBL OilBL OtherBL GasP HydroP OilP SolarP

omn 0.500 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050 0.050

otp 0.095 0.048 0.095 0.095 0.095 0.095 0.095 0.095 0.095 0.095 0.095

wtp - 1.000 - - - - - - - - -

tech_aspros 0.125 0.063 0.063 0.125 0.063 0.063 0.063 0.125 0.125 0.125 0.063

clerks 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.091

service_shop 0.053 0.105 0.105 0.053 0.105 0.105 0.105 0.105 0.105 0.105 0.053

off_mgr_pros 0.231 0.077 0.077 0.077 0.077 0.077 0.077 0.077 0.077 0.077 0.077

ag_othlowsk 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.091

Others 0 091 0 091 0 091 0 091 0 091 0 091 0 091 0 091 0 091 0 091 0 091

Balanced LCOE

The method

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GTAP

GWh

LCOE

ERP Capital

Targets

Constraints

Fuel

O&M

Assums.

Probs

PTAX

Own-use

RAS

RAS GTA

P-P

ower

(sup

ply-

side

)

Subsidy*

• Row Share

Ad-hoc > ERP > RAS > MSCCE

ERP objective (closeness) preserves economic relationships

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010203040506070

0% 20% 40%Ad-hoc MSCCE RAS ERP

• Cost structure

MSCCE > ERP > RAS > Ad-hoc

0

10

20

30

40

50

0% 20% 40% 60% 80% 100%Ad-hoc MSCCE RAS ERP

Mean absolute percentage deviation across inputs and technologies for each region

How much do the initial and balanced LCOE deviate?

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0%10%20%30%40%50%60%70%80%90%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Shar

e of

tota

l GW

h

Multiplicative bound on deviation from target levelized cost

Which LCOEs are the culprits?

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0

20

40

60

80

100

120

140

160

1/8 1/4 1/2 1 2 4 8

Freq

uenc

y

Multipliciative deviation

InvestmentFuelOwn-useO&M

Which regions are the culprits?

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0

20

40

60

80

100

120

1/8 1/4 1/2 1 2 4 8

Freq

uenc

y

Multiplicative deviation

OECD Regions

Non-OECD Regions

• Exports from a region will have the same share of total value as the supply from that region.

• Firm, government, and household demand for each new electricity sector has the same share as (domestic demands + imports).

• Assumption could be changed to account for additional base/peak or technology-use in particular sectors

• Can be aggregated if one wants an electricity aggregate as demand

Trade and demand-side

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• Differentiation by technology (ideal) rather than by source (data)• Split between base and peak can be improved• Instead of “base” and “peak” split into specific technologies such as combustion turbine,

combined cycle, etc. (given data!)• The assumptions on transmission and distribution tend to cause

large deviations.• Levelized cost data has low coverage outside of OECD

• How can we expand this? To contributors?• Production tax by technology has low/no coverage

• How can we obtain something like this?• Feedback from electricity disaggregation exercise to GTAP ‘ely’

sector• Which is more trustworthy: LCOE or “top-down” accounting?• What are tangible steps we can make to bring “bottom-up” and “top-down” closer

together?

Possible improvements for v10

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• Bert Saveyn – EC JRC/IPTS• Jean Château (and the ENV-Linkages team) – OECD • Richard Garbaccio – US EPA• Sergey Paltsev – MIT Joint Program

• In the end the funding pot of ~$50,000:• created a publicly available, electricity-detailed CGE database for GTAP v9

and beyond• supported a graduate student’s training and part of a dissertation

Thanks for the support

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Center for Global Trade AnalysisDepartment of Agricultural Economics, Purdue University403 West State Street, West Lafayette, IN 47907-2056 USA

contactgtap@purdue.eduhttp://www.gtap.agecon.purdue.edu

Global Trade Analysis Project

Thank you

Jeffrey C. Peterspeters83@purdue.edu

• Fix total input employment (GTAP consistency)• Fix GWh• Target levelized costs:

• “row share”• “cost share/structures” • while meeting GTAP accounting constraints

• Economic relationships are important in CGE modeling (journal article in review)

• Created novel estimation method (journal article in revision)

The ERP method

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• Termed the matrix-balancing problem:• “Given a rectangular matrix Z0, determine a matrix Z that is

close to Z0 and satisfies a given set of linear restrictions on its entries.” (Schneider and Zenios, 1990)

The disaggregation problem

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Tech 1 Tech … Tech T

Capital

O&M

Coal Z0

Gas

Oil

Tech 1 Tech … Tech T

Capital

O&M

Coal Z0

Gas

Oil

‘ely’

Capital

O&M

Coal

Gas

Oil