System for the Analysis of Global Energy (SAGE): Electric Sector Enhancement - PowerPoint PPT Presentation

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System for the Analysis of Global Energy (SAGE): Electric Sector Enhancement

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  1. System for the Analysis of Global Energy (SAGE): Electric Sector Enhancement 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

  2. 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 since2003. 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. SAGE Background

  3. 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. Electricity Sector Enhancement

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

  5. 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 Concerns with Previous SAGE Electricity Model Formulation

  6. 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 Concerns with Previous Model Formulation (cont.)

  7. 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. New SAGE Electricity Model Formulation

  8. SAGE load slices 800 700 600 500 Gw 400 300 200 100 0 0 2000 4000 6000 8000 time New SAGE Electricity Model Formulation (continued) • Demands mapped to load slice based on end use demand’s proportion of load slice • Load slices are organized around load duration curve Peak time slice Intermediate time slice Demand met with Peaking capacity Demand met with Intermediate Base load 8760

  9. Original vs. New SAGE Electricity Load Curves

  10. 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. Model Results Summary

  11. Electric Sector Capacity

  12. Electric Sector Capacity by Segment

  13. Comparison of Total Generation

  14. Generation by Segment

  15. 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. Electricity Reformulation Benefits

  16. 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 Other SAGE Activities