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Input Development for SPSG Scenarios November 13, 2014 Arne Olson, Partner Nick Schlag, Sr. Consultant.

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Presentation on theme: "Input Development for SPSG Scenarios November 13, 2014 Arne Olson, Partner Nick Schlag, Sr. Consultant."— Presentation transcript:

1 Input Development for SPSG Scenarios November 13, 2014 Arne Olson, Partner Nick Schlag, Sr. Consultant

2 2 Topics for Discussion Carbon capture & sequestration technologies Enhanced geothermal Load modifications


4 Cost Reductions – IGCC w/ CCS Reference Case cost: $8,200/kW Consistent with expected cost of Kemper County plant Does not reflect significant technological progress/learning As in prior study cycle, E3 recommends using the Reference assumptions in all scenarios except Scenario 2 Scenario 2 narrative allows for a breakthrough in CCS technology 4 $8,200$4,800 $8,200 IGCC w/ CCS Capital Cost by Scenario ($/kW) No change from Reference Case Technology breakthrough

5 Cost Reduction Recommendations from 2032 In 2012, E3 chose a 40% reduction for IGCC with CCS technology to represent a “breakthrough” based on the lowest available cost estimates for the technology This level of cost reduction would also render IGCC w/ CCS technology competitive with traditional gas CCGT in a high carbon price future ($100/ton) 5 Slide from E3 presentation to MDTF, October 2, 2012 Origin of E3’s Original Recommendation

6 Pre- vs. Post-Combustion CCS Availability of cost estimates for both technologies are limited: Kemper: $5.6 billion for 580 MW unit ($9,600/kW) Boundary Dam: $1.24 billion for 110 MW unit ($11,200/kW) WA Parish: $1 billion for 250 MW unit ($4,000/kW) Other public sources do not suggest substantial differences between current costs for pre- and post-combustion CCS: 6 SourcePC w/ CCSIGCC w/ CCS Pacificorp IRP $5,611$5,434 $6355$6,152 Lazard$8,568$7,650 EIA$6,821$8,612 NETL$5,160$4,819 All costs have been adjusted to reflect AFUDC costs and are expressed in 2014 $


8 8 Enhanced Geothermal Costs Cost estimates for enhanced geothermal systems vary widely and are highly site-specific: “NREL Base Case” costs reflect EGS systems and are obtained from Updated US Geothermal Supply Characterization and Representation for Market Penetration Model Input (Oct 2011)

9 9 Enhanced Geothermal Costs Based on NREL study, a 30% capital cost reduction in EGS technology is plausible Cost reduction could be applied to EGS technologies in Scenarios 2 & 4


11 11 Components of Load Forecast Three independent parameters may drive differences in load between scenarios: 1.How much to increment/decrement Reference Case load forecasts to capture impacts of differences in economic conditions on underlying load growth? 2.How much incremental energy efficiency (beyond that embedded in Reference Case) to include? 3.How much policy-driven electrification load to include? Assumptions used in 2032 scenarios provide a useful starting point for a framework to develop updates GOAL: Review assumptions used in 2032 load forecasts to inform development of 2034 load forecasts

12 12 Changes in Underlying Load Growth (2032 Study) In 2032 study, WECC- wide growth rates were adjusted by ±0.4%/yr between to reflect differences in underlying economic growth: Scenarios 1 & 2: +0.4% Scenarios 3 & 4: -0.4% 1.9% 1.1% 1.5% WECC-Wide CAGR Assumptions, Slide summarizes assumptions from 2032 study

13 13 Changes in Incremental Energy Efficiency (2032 Study) LBNL’s 2032 High DSM load forecast served as the basis for assumptions related to incremental energy efficiency Assumes average efficiency of residential/ commercial end uses in 2032 equals that of today’s best available technology Savings reflected in the High DSM forecast scaled to reflect scenario narratives: Scenarios 1 & 3: no additional EE Scenario 2: very aggressive EE Scenario 4: moderate incremental EE 100% of LBNL 2032 High DSM forecast savings (~21% load reduction) n/a WECC-Wide Incremental Efficency (2032 Study) n/a 50% of LBNL 2032 High DSM forecast savings (~11% load reduction) Slide summarizes assumptions from 2032 study

14 14 Changes in Electrification (2032 Study) Additional load in Scenario 2 driven by electrification of end uses across all sectors, motivated by trend towards deep decarbonization pathways Additional load in Scenario 4 assumed to result from growing penetrations of plug-in electric vehicles +160 TWh (~13% load increase) n/a WECC-Wide Electrification Load (2032 Study) n/a +50 TWh (~5% load increase ) Slide summarizes assumptions from 2032 study

15 Load Forecast – Building Blocks Scenario-specific load adjustments yield a range of load assumptions for studies: Implied growth rates vary from 0.62%/yr (Scenario 4) to 1.75%/yr (Scenario 2) Slide summarizes assumptions from 2032 study

16 Load Forecast - Results Load levels vary widely across scenarios: Slide summarizes assumptions from 2032 study

17 Thank You! Energy and Environmental Economics, Inc. (E3) 101 Montgomery Street, Suite 1600 San Francisco, CA Tel Web

18 18 Scenario 2 Electrification: Review of Long- Term GHG Reduction Studies Assume incremental electrification increases (post-DSM) demand by 20% in 2032 due to electrification across all sectors Studies demonstrate what would be needed to achieve long-term GHG reductions (rather than a forecast of what’s likely given current policies & trends): U.K. Department of Energy and Climate Change, “2050 Pathways Analysis,” July California Council on Science and Technology, “California’s Energy Future: The View to 2050,” May Williams, et al. “The Technology Path to Deep Greenhouse Gas Emissions Cuts by 2050: The Pivotal Role of Electricity,” Science (2012) (written by E3 colleagues and LBNL staff). Comparison of electrification as a share of that year’s total electricity demand 18

19 19 Scenario 4 Electrification : National Academies Press Study Scaled to the WECC 19 Nat’l Academies Study = 11.4 million light-duty vehicles (LDVs) by 2032 in WECC 17% of fleet Equal to ~ 46 TWh of incremental electricity load in WECC in 2032 assuming fully- electric vehicles use ~4,000 kWh/yr National Academies Press report, “Transitions to Alternative Transportation Technologies – Plug-in Hybrid Electric Vehicles,” (PHEVs), (2012).

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