1. 1 John J. Conti Acting 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. 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. 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. 4 Elements Modified Improved the technological characterization of existing and new capacities. Better representation of peaking, intermediate, and baseload demand

5. 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. 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. 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. 8 New SAGE Electricity Model Formulation (continued) SAGE load slices 0 100 200 300 400 500 600 700 800 02000400060008000 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 1 st SliceFirst 2% of hours 2 nd SliceNext 10% of hours 3 rd SliceNext 22% of hours 4 th SliceNext 22% of hours 5 th SliceNext 22% of hours 6 th SliceNext 22% of hours Peak time slice Intermediate time slice 8760

9. 9 Original vs. New SAGE Electricity Load Curves

10. 10 Model Results Summary Peaking facilities (such as turbines) are built to operate in the 1 st (i.e. peak) slice; Intermediate facilities (such as combined cycle) are built to operate primarily in 2 nd 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. 11 Electric Sector Capacity

12. 12 Electric Sector Capacity by Segment

13. 13 Comparison of Total Generation

14. 14 Generation by Segment

15. 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. 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