1

John J. ContiActing Director

Office of Integrated Analysis and Forecasting

Prepared for the Energy Technology System Analysis Program (ETSAP)

Florence, Italy

November 24, 2004

System for the Analysis of Global Energy (SAGE):

Electric Sector Enhancement

2

SAGE Background• A MARKAL-based energy model utilizing the VEDA software

for model creation and results analysis.• Produces integrated energy projections through 2025 for 15

regions of the world.• EIA’s International Energy Outlooks have been based on

SAGE model results since 2003.• Uses a time-stepped approach to address foresight and other

modeling issues (i.e., learning, market sharing, etc).• Each year a number of model enhancements are scheduled

(some are even implemented). • One key improvement this year has been a reformulated electric

sector.

3

Electricity Sector Enhancement• Purpose: to increase model flexibility in choosing

between alternative fuel/technology combinations in response to various changes in inputs to address alternative policies, energy market conditions, or technological characteristics. – Allow model to economically choose to build and operate

appropriate mix of electricity technologies• Maintain selected external constraints to allow for regional

differences and assumed must run/out of merit order generation and capacity selection (e.g., renewable portfolio standards, etc.)

– Allows for the appropriate economic valuation of carbon allowances in electricity sector and flexibility to react to carbon shadow prices or constraints.

4

Elements Modified• Improved the technological

characterization of existing and new capacities.

• Better representation of peaking, intermediate, and baseload demand

5

Concerns with Previous SAGE Electricity Model Formulation

• Model builds and operates large amounts of baseload technologies

• Constraints required to force proportional generation by other fuels

• Model dispatch and capacity choice decision were not based on the technological specifications, capital cost parameters, and fuel costs

6

Concerns with Previous Model Formulation (cont.)

• Annual electricity demand is segmented into 6 periods:– Summer, Winter, and Intermediate– Day and Night

• Electricity capacity expansion and dispatch decisions meet demand varying by the above 6 seasonal/diurnal segmentations.

• The 6 segment load demand curve representation is too flat to adequately capture the comparative economics of peaking and intermediate technologies

7

New SAGE Electricity Model Formulation

• Changed “seasonal/time of day” framework to “load duration curve” concept

• Developed mapping of typical end use load for each end use to aggregate load.

• By region, selected dominant end use load as basis for establishing time slots for load duration curve slices (e.g., industrial world’s peak dominated by cooling load)

• Stayed within default 6 slice limit.

8

New SAGE Electricity Model Formulation (continued)

SAGE load slices

0

100

200

300

400

500

600

700

800

0 2000 4000 6000 8000

time

Gw

Demand met with Peaking capacity

Demand met with Intermediate

Base load

• Demands mapped to load slice based on end use demand’s proportion of load slice • Load slices are organized around load duration curve

1st Slice First 2% of hours

2nd Slice Next 10% of hours

3rd Slice Next 22% of hours

4th Slice Next 22% of hours

5th Slice Next 22% of hours

6th Slice Next 22% of hours

Peak time slice Intermediate time slice

8760

9

Original vs. New SAGE Electricity Load Curves

USA Alternative LDCs

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

- 0.0

5

0.1

0

0.1

5

0.2

0

0.2

5

0.3

0

0.3

5

0.4

0

0.4

5

0.5

0

0.5

5

0.6

0

0.6

5

0.7

0

0.7

5

0.8

0

0.8

5

0.9

0

0.9

5

1.0

0

Fraction of Year

Gig

aw

att

s (

Th

ou

sa

nd

s)

Seasonal Day/Night New LDC

10

Model Results Summary

• Peaking facilities (such as turbines) are built to operate in the 1st (i.e. peak) slice;

• Intermediate facilities (such as combined cycle) are built to operate primarily in 2nd slice.

• Baseload facilities (such as coal or combined cycle) are built to operate in the four baseload slices.

• First, we will look at the capacity expansion decision, followed by the dispatch decision. This is based on the U.S. region for the year 2025.

11

Electric Sector CapacityComparison of Dispatch

Peak + Reserve

0

200

400

600

800

1,000

1,200

Seasonal/Time of Day

Load DurationCurve

GW

Oil

Gas

N GT

N CC

Coal

N Coal

Nuclear

Renew

12

Electric Sector Capacity by SegmentDispatch Using Seasonal/Time of Day Method

0

200

400

600

800

1,000

1,200

Peak +Reserve

Slice 1 Slice 2 Slice 3 Slice 4 Slice 5 Slice 6

GW

Oil

Gas

N GT

N CC

Coal

N Coal

Nuclear

Renew

Dispatch Using Load Duration Curve Method

0

200

400

600

800

1000

1200

Peak +Reserve

Slice 1 Slice 2 Slice 3 Slice 4 Slice 5 Slice 6G

W

13

Comparison of Total GenerationComparison of Total Generation

0

1,000

2,000

3,000

4,000

5,000

6,000

Seasonal/Time of Day

Load DurationCurve

bil

lio

n k

Wh

Oil

Gas

N GT

N CC

Coal

N Coal

Nuclear

Renew

14

Generation by Segment

Generation Using Load Duration Curve Method

0

200

400

600

800

1,000

1,200

1,400

Slice 1 Slice 2 Slice 3 Slice 4 Slice 5 Slice 6b

illio

n k

Wh

Generation Using Seasonal/Time of Day Method

0

200

400

600

800

1,000

1,200

1,400

Slice 1 Slice 2 Slice 3 Slice 4 Slice 5 Slice 6

bil

lio

n k

Wh

Oil

Gas

N GT

N CC

Coal

N Coal

Nuclear

Renew

15

Electricity Reformulation Benefits

• Appropriate model capacity expansion and dispatch is not forced via additional constraints.– Improved model application for policy analysis– Electricity price forecast more reasonable– Electric sector results respond to changes in

endogenous variables such as relative fuel prices.

16

Other SAGE Activities

• In progress:– Improved market share algorithm– Enhanced discount, interest, investment hurdle rate

methodology– Formalized version control, issue tracking, and

software installation.

• Planned:– Kyoto Scenario Analysis