1. National Energy Technology Laboratory Chris Nichols National Energy Technology Laboratory, Office of Strategic Energy Analysis and Planning VCEA 36 th Annual Conference May 19, 2015 Analysis of coal retirement impacts and the prospects for new “anytime electricity” generation capacity

2. The analysis presented and conclusions drawn herein represent solely those views of the author(s), and do not represent the views of the United States Department of Energy. Disclaimer

3. Estimating the impact of announced coal retirements: – Using list of retiring units between now and 2022, we estimated the impacts of these units in terms of jobs, coal usage and monetary value Identifying unit identities from energy model forecasts: – We used our best estimate process to identify likely units and examine state-level impacts Forecasting the prospects for new coal: – No new coal appears in most energy models, but there may be modeling methodologies and assumptions that mask the need for new “anytime electricity” generation capacity Presentation Overview

4. Current baseline coal retirement level of ~40 GW by 2020 was used, based on our data We developed estimates of the following parameters with respect to units projected for retirement: – affected plant workers: 8,691 – coal miners: 6,961 – power plant property tax value: $1.1B – Retail value of electricity generation: $13.4B – Retail value of coal production: $4.2B Evaluating the impact of announced coal retirements

5. Around 16,000 direct jobs are impacted

6. Almost $19B worth of property tax, electricity generation and coal production

7. Retiring units and affected mines

8. Estimating the impact of announced coal retirements: – Using list of retiring units between now and 2022, we estimated the impacts of these units in terms of jobs, coal usage and monetary value Identifying unit identities from energy model forecasts: – We used our best estimate process to identify likely units and examine state-level impacts Forecasting the prospects for new coal: – No new coal appears in most energy models, but there may be modeling methodologies and assumptions that mask the need for new “anytime electricity” generation capacity Presentation Overview

9. Most analyses project 50-100 GW of coal retirements from CPP

10. Energy market models (NEMS, IPM, etc) forecast retirements and new builds of generation capacity, but often do no identify the specific units and may not fully define the grid-level impacts of capacity changes We apply a production cost methodology to model results to develop a list of units most likely to retire and quantify the impacts of their retirements Unit-level assessment allows us to drill down to state- level impacts of retirements to find issues that may be glossed over in national-level results Identifying units from energy forecasts

11. CPP (ESPS) Coal Retirements by 2020 Actual, Announced, and EPA ESPS IPM Model Retirements 2010-2013 -20 GW (210 units) Retirements 2010-2013 -20 GW (210 units) Announced Retirements 2014 - 2020 -36.7 GW (211 units) Announced Retirements 2014 - 2020 -36.7 GW (211 units) Coal Retirements View Layer Off On Actual Retirements (2010-2013) Announced Retirements IPM Retirements IPM Missed Announcements Operating Units as of 2014 /Remaining units in 2020 after applied retirements Summer Capacities *Best Estimate based on unit size, capacity factor, age, and competitiveness Estimated IPM Case Coal Retirements* -97 GW by 2020 Estimated IPM Case Coal Retirements* -97 GW by 2020 Off On X Link to NETL’s “Best Estimate“ methodology

12. Coal and NGCC units in Ohio Announced retirements Projected retirements Continued Operation Pipelines Operating NGCC Under Const NGCC Permitted NGCC Proposed NGCC Transmission

13. Estimating the impact of announced coal retirements: – Using list of retiring units between now and 2022, we estimated the impacts of these units in terms of jobs, coal usage and monetary value Identifying unit identities from energy model forecasts: – We used our best estimate process to identify likely units and examine state-level impacts Forecasting the prospects for new coal: – No new coal appears in most energy models, but there may be modeling methodologies and assumptions that mask the need for new “anytime electricity” generation capacity Presentation Overview

14. AEO Coal Capacity Addition Forecasts A Wide Variation in Outlooks Over a Brief Period of Forecasts Sources: EIA - Annual Energy Outlook 2006 through 2015; AEO’ 06 included 19 GW equivalent of CTL AEO’06 AEO’07 AEO’08 AEO’09 AEO’10 AEO’11 AEO’12 Additions less Retirements AEO’13 AEO’14 AEO’13 AEO’14 Beginning with AEO ‘09, EIA applies financing cost adder to coal plants AEO’15

15. What if – more electricity is needed than projected? – existing plants can’t generate as much as modelers think they will? – Projected fuel costs are lower than what actually happens? – Capital costs are artificially inflated in modeling assumptions? – Unmodeled regulations create a greater shortfall in capacity than currently expected? Do models mask the need for more or different generation capacity?

16. Growth in electricity use slows, but electricity use still increases by 24% from 2013 to 2040 U.S. electricity use and GDP percent growth (rolling average of 3-year periods) Source: EIA, Annual Energy Outlook 2015 Reference case Annual Energy Outlook 2015, April 14, 2015 Structural Change in Economy - Higher prices - Standards - Improved efficiency Projections History 2013 Period Average Growth__ Electricity use GDP 1950s 9.8 4.2 1960s 7.3 4.5 1970s 4.7 3.2 1980s 2.9 3.1 1990s 2.4 3.2 2000-2013 0.7 1.9 2013-2040 0.8 2.4 Gross domestic product Electricity use

17. Sources: BEA – NIPA Table 1.1.6; EIA – Monthly Energy Review; Annual Energy Outlook 2015; *kWh end use (consumption); dashed lines represent 6 th order polynomial fit Historical Trend AEO’15 Forecast Electricity and GDP Growth: Comparing Trends kWh Growth Rate*: AEO’15 vs. historic ratio

18. Growth of U.S. GDP vs. Generation Historic and Forecast Sources: BEA – NIPA Table 1.1.6; EIA – Annual Energy Review; Annual Energy Outlook 2015 ; baseload assumed to operate at 80% capacity factor; 73% of generation is assumed to come from baseload units AEO’15 Forecast “Structural Change in The Economy”, Anticipates Less Energy Required Per Unit of GDP; “Higher Prices” Also Assumed to Suppress Demand Real GDP Billions (2009$) Bubble Divergence Generation GDP Generation (BkWh) What If, in addition, GDP grew at AEO’05 rate? What if historic trend in kWh and GDP growth is applied to forecasted GDP? 650 BkWh* missing in 2040; Equivalent to 474 baseload BkWh ≈ 68 GW Baseload 650 BkWh* missing in 2040; Equivalent to 474 baseload BkWh ≈ 68 GW Baseload 1,161 BkWh* missing in 2040; Equivalent to 848 baseload BkWh ≈ 121 GW baseload 1,161 BkWh* missing in 2040; Equivalent to 848 baseload BkWh ≈ 121 GW baseload 2.5% CAGR 3.0% CAGR 121 GW

19. Generation by fuel As natural gas prices increase in the AEO2013 Reference case, the utilization rate of coal-fired generators returns to previous historical levels and continues to rise, to an average of around 74 percent in 2025 and 78 percent in 2040 “In the Reference case, coal-fired generation increases by an average of 0.2 percent per year from 2011 through 2040. Even though less capacity is available in 2040 than in 2011, the average capacity utilization of coal-fired generators increases over time. In recent years, as natural gas prices have fallen and natural gas-fired generators have displaced coal in the dispatch order, the average capacity factor for coal-fired plants has declined substantially. The coal fleet maintained an average annual capacity factor above 70 percent from 2002 through 2008, but the capacity factor has declined since then, falling to about 57 percent in 2012. As natural gas prices increase in the AEO2013 Reference case, the utilization rate of coal-fired generators returns to previous historical levels and continues to rise, to an average of around 74 percent in 2025 and 78 percent in 2040. Across the alternative cases, coal-fired generation varies slightly in 2025 (Figure 30) and 2040 (Figure 31) as a result of differences in plant retirements and slight differences in utilization rates. The capacity factor for coal-fired power plants in 2040 ranges from 69 percent in the High Oil and Gas Resource case to 81 percent in the Low Oil and Gas Resource case.” AEO’13 Issues in Focus (page 42) The “Ageless Baseload” Assumption

20. Coal & Nuclear Baseload Capacity Renewal Examining Prior EIA Forecasts Reference – Ventyx Velocity Suite (existing units and announced retirements - EIA AEO 2016-2014er (forecasted additions) End of AEO’06-’09 forecast 2030 AEO 2006 AEO 2007 AEO 2008 AEO 2009 AEO 2010 AEO 2011 AEO 2012 AEO 2013 AEO new Coal AEO new Nuclear AEO 2014 Existing aging coal and nuclear fleet EIA Forecasted new coal and nuclear fleet to meet demand and replace aging fleet

21. Examining Historic Coal Unit Capacity Factors Unit Capacity Factors Drop Off as they Age Data source and notes: Data from Ventyx's Energy Velocity. Unit age in each year was calculated then averaged Approximation of actual industry capacity factor experience based on unit age 80% 60% 14% By 2030 average age of existing coal plants imply capacity factors < 50% Avg. age existing coal plants EPA ESPS estimated capacity factor for coal units irrespective of age 78%

22. Gas-fueled units account for most projected capacity additions in the AEO2014 Reference case 2222 U.S. electricity generation capacity additions gigawatts Source: Form EIA-860 & EIA Annual Energy Outlook 2014, Early Release Overview of AEO2014 Accelerated Power Plant Retirement Side Cases May 20, 2014

23. Models are not strong at price prediction Historically, EIA projections have set the floor on gas prices Is it different this time?

24. “GHG Concern” “ The LCOE values shown for each utility - scale generation technology in Table 1 and Table 2 in this discussion are calculated based on a 30 - year cost recovery period, using a real after tax weighted average cost of capital (WACC) of 6.5 %. In reality, the cost recovery period and cost of capital can vary by technology and project type. In the AEO2014 reference case, 3 percentage points are added to the cost of capital when evaluating investments in greenhouse gas (GHG) intensive technologies like coal fired power and coal - to - liquids (CTL) plants without carbon control and sequestration (CCS). In LCOE terms, the impact of the cost of capital adder is similar to that of an emissions fee of $15 per metric ton of carbon dioxide (CO 2 ) when investing in a new coal plant without CCS, which is representative of the costs used by utilities and regulators in their resource planning. 5 The adjustment should not be seen as an increase in the actual cost of financing, but rather as representing the implicit hurdle being added to GHG - intensive projects to account for the possibility that they may eventually have to purchase allowances or invest in other GHG - emission - reducing projects to offset their emissions. As a result, the LCOE values for coal - fired plants without CCS are higher than would otherwise be expected. ” AEO’14 Assumptions Increasing Coal Cost of Capital Nearly 50% Source: EIA, "Levelized Cost and Levelized Avoided Cost of New Generation Resources in the Annual Energy Outlook 2014" http://www.eia.gov/forecasts/aeo/pdf/electricity_generation.pdfhttp://www.eia.gov/forecasts/aeo/pdf/electricity_generation.pdf

25. Alternate NEMS Scenarios* High Gas Prices No cost penalty *Performed by NETL

26. For known retirements: – Lost jobs, coal tonnage and economic impact data can be reasonably quantified and are significant “Best estimate” methodology allows us to identify likely additional units for retirement – Impacts in terms of lost generation, possible pipeline congestion, jobs and revenue can then be calculated Common energy forecasting assumptions and practices may hide the need for new capacity – “anytime electricity” will still be needed If you can look into the seeds of time, and say which grain will grow and which will not, speak then unto me. - William Shakespeare Conclusions

27. Chris Nichols Senior Analyst, Strategic Energy Analysis and Planning National Energy Technology Laboratory 304 285-4172 christopher.nichols@netl.doe.gov Questions and discussion AlbanyPittsburghMorgantown

28. Backup slides

29. – Direct plant employment based on reported FERC Form 1, using a multiplier of 0.22 jobs per MW of capacity – Property tax based on replacement value AEO PC capital cost values State/county property tax average – Miner employment based on MSHA productivity and FERC coal transaction data Methodology and data sources for announced retirement impact analysis

30. NETL’s “Best Estimate” of coal unit retirements ranks coal units in each Electricity Market Module (very close to NERC Subregions) or state by each unit’s adjusted production cost of electricity. Parameters included in determining the adjusted cost are: Baseline production cost: – Fuel cost (consists of heat rate and price of fuel) – Variable O&M – Fixed O&M (includes capacity factor as a component) Emission control costs (if each is required to be added): – Amortized capital cost – O&M costs (includes nameplate capacity and capacity factor) Life extension cost (if unit is greater than 30 years old) – Amortized capital cost – Sliding scale of exposure to full life extension cost based on age (older units pay more of the full cost at once) NETL “Best Estimate” of Coal Unit retirement methodology

31. Once the unit’s adjusted production costs is determined, the unit is ranked with all other coal units in its EMM or state and the cumulative capacity is summed according to ranking. Units with announced retirements are moved to the top of the retirement ranking. The model assigns one of three categories to each unit until the cumulative capacity of retirement is reached in each EMM or state: – Planned retirement – retirement has been announced and documented by EV – Projected retirement – unit is projected to retire based on adjusted production cost and cumulative retired capacity in AEO’14 or IPM cases – Continued operation – unit’s ranking places it above the projected retirement mark for the applicable AEO’14 or IPM case. Methodology (cont)

32. Equation

33. ParameterUnitsDescriptionSource F$/MMBTUFuel cost, avg 2013EV HRMMBTU/kWhHeat rate, avg 2013EV $/MWhVariable O&MEV $/kW-yrFixed O&MEV GENMWhGeneration, 2013EV $/MWhVariable O&M, FGDICF, using EPA data $/kW-yrFixed O&M, FGDICF, using EPA data $/MWhVariable O&M, SCRICF, using EPA data $/kW-yrFixed O&M, SCRICF, using EPA data $/MWhVariable O&M, Hg controlICF, using EPA data $/kW-yrFixed O&M, Hg controlICF, using EPA data $/kWCapital cost, life extensionICF, using EPA data CAPkWGeneration capacity, nameplateEV AGEYearsUnit ageEV Parameters used in equation

34. Comparison of NEMS and IPM Retirements

35. *Summer Capacities Sources - Ventyx – Velocity Suite EIA – AEO 2014 EPA – IPM Option 1 RFC-W Coal Retirements by 2020 ANCR and IPM Actual Retirements (2010-2013) Announced Retirements EIA ANCR Retirements Remaining units by 2020 EPA IPM Retirements Missed announced units by IPM Operating and remaining units Proposed New NGCC Builds Proposed New NGCC Builds (11.5 GW by 2020) NGCC (off) NGCC (on) Off On Off On EIA ANCR Case Coal Retirements ( -13 GW by 2020 EIA ANCR Case Coal Retirements ( -13 GW by 2020 Retirements 2010-2013 -9 GW (62 units) Retirements 2010-2013 -9 GW (62 units) Announced Retirements 2014 - 2020 -11 GW (58 units) Announced Retirements 2014 - 2020 -11 GW (58 units) Estimated IPM Case Coal Retirements* -9 GW by 2020 Estimated IPM Case Coal Retirements* -9 GW by 2020 Construction 1.9GW Permitting 3.6 GW Announced 6 GW X