Greening Iew 2007

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Information about Greening Iew 2007

Published on January 19, 2009

Author: LGDoone

Source: slideshare.net

Description

Analysis of Advanced Nuclear

Spent Nuclear Fuel Disposition and The Market Viability of Nuclear Energy Lorna A. Greening International Energy Workshop Stanford University June 26, 2007

Caveats and Acknowledgements The conclusions and opinions presented are my own. All errors of commission or omission are mine, and the usual caveats apply. I owe a tremendous debt to over 200 individuals who provided data and expertise in specialized areas of energy technology, supply, and consumption over a two year period. Without this “grass roots” community contribution, effort and support, this work would not have been possible.

The conclusions and opinions presented are my own.

All errors of commission or omission are mine, and the usual caveats apply.

I owe a tremendous debt to over 200 individuals who provided data and expertise in specialized areas of energy technology, supply, and consumption over a two year period. Without this “grass roots” community contribution, effort and support, this work would not have been possible.

Today’s Discussion Framing of the issues and the questions. What technologies could replace existing nuclear capacity, and be used to meet growing electricity demand? And at what cost? Will the resource base be sufficient to support the replacement capacity required? Is there a strategy for nuclear capacity development that minimizes spent nuclear fuel (including the ‘legacy’) to levels within the current statutory limit of 63,000 metric tons for Yucca Mountain? Discussion of the means of analysis: Overview of LA-US MARKAL; Depiction of the nuclear fuel cycle. Some results. Factors that could alter this forecast. Some general conclusions from this analysis.

Framing of the issues and the questions.

What technologies could replace existing nuclear capacity, and be used to meet growing electricity demand? And at what cost?

Will the resource base be sufficient to support the replacement capacity required?

Is there a strategy for nuclear capacity development that minimizes spent nuclear fuel (including the ‘legacy’) to levels within the current statutory limit of 63,000 metric tons for Yucca Mountain?

Discussion of the means of analysis:

Overview of LA-US MARKAL;

Depiction of the nuclear fuel cycle.

Some results.

Factors that could alter this forecast.

Some general conclusions from this analysis.

Issues for US Nuclear Electricity Generation In 2001, approximately 20.5% of the electricity generated in the US was provided by nuclear generation. Economics, reliability and safety have improved substantially over the last 20 years for nuclear electricity generation facilities. Much new technology exists and EPAct 2005 provides financial guarantees, but new nuclear generation capacity is not being built. Currently, well over 31,000 metric tons of “legacy” spent nuclear fuel resides in cooling or interim dry storage. By the expiration of the majority of nuclear licenses in 2020, 1.5 Yucca Mountains will be required to store the waste for 10,000 years. Replacement of the existing nuclear technology with other sources will require substantial investments in new generation capacity, and should result in increases in prices of competing fuels. The spent nuclear fuel will still to be be dealt with, and a potentially useful energy resource will be lost.

In 2001, approximately 20.5% of the electricity generated in the US was provided by nuclear generation.

Economics, reliability and safety have improved substantially over the last 20 years for nuclear electricity generation facilities.

Much new technology exists and EPAct 2005 provides financial guarantees, but new nuclear generation capacity is not being built.

Currently, well over 31,000 metric tons of “legacy” spent nuclear fuel resides in cooling or interim dry storage. By the expiration of the majority of nuclear licenses in 2020, 1.5 Yucca Mountains will be required to store the waste for 10,000 years.

Replacement of the existing nuclear technology with other sources will require substantial investments in new generation capacity, and should result in increases in prices of competing fuels.

The spent nuclear fuel will still to be be dealt with, and a potentially useful energy resource will be lost.

Comparison of Nuclear in LA US MARKAL with Other Frameworks US MARKAL contains all of the steps in the nuclear fuel cycle including waste disposal. This is more complete than NEMS (EIA), or any model of this type since Joskow and Baughman, 1976. Depiction of reprocessing, and permanent disposal capture differences in radiotoxicity and heat of materials. This allows the determination of the benefits (e.g., reduced emissions, energy security) of reprocessing, waste partitioning and transmutation, and reduced volume and radiotoxicity disposal strategies for spent nuclear fuel. Longer forecast horizon than other models allows the evaluation of “new generation” nuclear technologies and the development of interim strategies for waste disposal in the face of legal caps on permanent disposal depositories.

US MARKAL contains all of the steps in the nuclear fuel cycle including waste disposal. This is more complete than NEMS (EIA), or any model of this type since Joskow and Baughman, 1976.

Depiction of reprocessing, and permanent disposal capture differences in radiotoxicity and heat of materials. This allows the determination of the benefits (e.g., reduced emissions, energy security) of reprocessing, waste partitioning and transmutation, and reduced volume and radiotoxicity disposal strategies for spent nuclear fuel.

Longer forecast horizon than other models allows the evaluation of “new generation” nuclear technologies and the development of interim strategies for waste disposal in the face of legal caps on permanent disposal depositories.

Attributes of Model of LA-MARKAL All sources of energy represented. Expanded technology choice set of over 4000 technologies. Nine different emissions types (CO 2 , SO 2 , NO x , N 2 O, CO, VOC, CH 4 , particulates, and mercury) tracked through the economy, along with depiction of regulations, and mitigation techniques. Inclusion of demand response to prices and incomes incorporates a response that results in a lower total cost of satisfying energy demand. Electricity and steam: Representation of centrally dispatched, distributed generation, and combined heat and power (including consumption of direct heat and steam). See article in IAEE Newsletter, Fourth Quarter 2003 (pages12-19), www.iaee.org. Table 1 provides a summary comparison with NEMS (EIA).

All sources of energy represented.

Expanded technology choice set of over 4000 technologies.

Nine different emissions types (CO 2 , SO 2 , NO x , N 2 O, CO, VOC, CH 4 , particulates, and mercury) tracked through the economy, along with depiction of regulations, and mitigation techniques.

Inclusion of demand response to prices and incomes incorporates a response that results in a lower total cost of satisfying energy demand.

Electricity and steam: Representation of centrally dispatched, distributed generation, and combined heat and power (including consumption of direct heat and steam).

See article in IAEE Newsletter, Fourth Quarter 2003 (pages12-19), www.iaee.org. Table 1 provides a summary comparison with NEMS (EIA).

Electricity: Central Generation Over 90 centrally dispatched electricity generation technologies are characterized. Fuel/technology types represented include: Fossil (oil, natural gas, coal, MSW) steam. Combined cycle (natural gas, coal, biomass). Conventional and advanced turbines (fossil and methanol). Renewables including solar, wind, biomass, and waste. Nuclear (light water reactors and MOX), and “next generation” including HTGR, HTGR-MOX, HTGR-TRU, Fast-spectrum TRU, CR-1, and MOX burners, and Accelerator-driven TRU and MA burners. Carbon sequestration is depicted where appropriate. Varying annual and daily load profiles are segmented by time of day and load-type with competition among appropriate technology types (e.g., base-load may be satisfied by nuclear or steam and CC). Connection to end-use sector specific grids for CHP/distributed generation resulting in competition between sources of electricity.

Over 90 centrally dispatched electricity generation technologies are characterized.

Fuel/technology types represented include:

Fossil (oil, natural gas, coal, MSW) steam.

Combined cycle (natural gas, coal, biomass).

Conventional and advanced turbines (fossil and methanol).

Renewables including solar, wind, biomass, and waste.

Nuclear (light water reactors and MOX), and “next generation” including HTGR, HTGR-MOX, HTGR-TRU, Fast-spectrum TRU, CR-1, and MOX burners, and Accelerator-driven TRU and MA burners.

Carbon sequestration is depicted where appropriate.

Varying annual and daily load profiles are segmented by time of day and load-type with competition among appropriate technology types (e.g., base-load may be satisfied by nuclear or steam and CC).

Connection to end-use sector specific grids for CHP/distributed generation resulting in competition between sources of electricity.

Nuclear Technologies and Materials Flows High Heat Release (HHR) FP Transuranics (TRU) Minor Actinides (MA) US Surplus Weapons Grade Pu Reactor Grade Pu (3 vectors) Natural U as UF 6 US Surplus HEU LEU from Russian Surplus HEU Recovered Irradiated LEU Depleted U Natural U Mining / Milling (3 cost steps) Imports UF 6 to UO 2 UO 2 to UF 6 Gaseous Diffusion Gas Centrifuge Laser Isotope UOX Fabrication MOX Fabrication Other Fuel Forms: Metal, (An)N, (An)C, .. Present-day LWR (B ~ 38 MWd/kg) ALWR-UOX (B ~ 55 MWd/kg) ALWR-MOX (B ~ 49 MWd/kg) Thermal GCR Fast Reactor Concepts On-site wet On-site dry Off-site interim SF storage PUREX UREX/UREX+ TRUEX or similar Aqueous separation of Cs, Sr, I, Tc Pyrometallurgical separations HEU downblending (UNH process) HLW vitrification SF conditioning / encapsulation Separated actinide and FP storage Materials credit at end of forecast Yucca Mountain Resources Materials Conversion Enrichment Fabrication Irradiation SF Storage Reprocessing Waste Management Planned / Possible Implemented Transport costs assessed but not shown. Gray boxes represent level of resolution of previous MARKAL model.

Disposal Costing Model Based Upon Repository Heat Load Limitations Unit repository disposal costs for spent fuel, less transportation-related charges, are currently estimated by OMB as ca. $440/kgIHM. Disposal costs include vitrification – the glassification of high-level radioactive waste (HLW) in an inert matrix – as well as emplacement of this waste in Yucca Mountain. The capacity of Yucca Mountain is governed not by the mass of material emplaced, but rather by the total decay heat production of that material. Comparing the heat production for high level waste of various compositions to that of spent nuclear fuel, one can estimate an ‘effective’ repository capacity and thus arrive at a cost estimate.

Unit repository disposal costs for spent fuel, less transportation-related charges, are currently estimated by OMB as ca. $440/kgIHM.

Disposal costs include vitrification – the glassification of high-level radioactive waste (HLW) in an inert matrix – as well as emplacement of this waste in Yucca Mountain.

The capacity of Yucca Mountain is governed not by the mass of material emplaced, but rather by the total decay heat production of that material.

Comparing the heat production for high level waste of various compositions to that of spent nuclear fuel, one can estimate an ‘effective’ repository capacity and thus arrive at a cost estimate.

Disposal Cost as a Function of Waste Content The ‘equivalent’ heat load-based repository utilization of HLW is the amount [in kg] of the ca. 63000 tonIHM Yucca Mountain capacity used by HLW of a given composition originating from 1 kgHM. This figure, as well as the derived volume of HLW glass, allows the disposal cost to be formulated based upon: $300,000/m 3 HLW unit vitrification cost (Source: Hanford HLW vitrification program), $332 per ‘equivalent’ kg HLW repository disposal cost, representing $440/kg less the YM cost component relating to waste package fabrication.

The ‘equivalent’ heat load-based repository utilization of HLW is the amount [in kg] of the ca. 63000 tonIHM Yucca Mountain capacity used by HLW of a given composition originating from 1 kgHM.

This figure, as well as the derived volume of HLW glass, allows the disposal cost to be formulated based upon:

$300,000/m 3 HLW unit vitrification cost (Source: Hanford HLW vitrification program),

$332 per ‘equivalent’ kg HLW repository disposal cost, representing $440/kg less the YM cost component relating to waste package fabrication.

Example Disposal Cost Comparison

Example of Reprocessing: Existing U38 Mass (kgIHM) of SNF going to YUCCA Mountain

Resource Impacts of Selected Nuclear Technologies 0 0 [19.7 tonne DU for CR 1 near-breeder] 232 [0 for TRU burner] [20.5 tonne depleted uranium (DU)] 234 to 198 Uranium Resource Consumption [ton U nat / GW-yr (e)] -1140 7.6 to 4.5 [150 to 250 MWd/kg] Accelerator Driven System 0 [CR 1] -450 [CR 0.5] 21.6 to 4.8 [CR 1 to CR 0.5] Fast Spectrum Reactor 167 [U fuelled] -759 [TRU burner] 6.4 to 1.7 [120 to 470 MWd/kg] HTGR (Thermal Spectrum) -389 22.2 [49 MWd/kg] MOX Fuelled LWR 343 to 257 29.8 to 19.8 [38 to 55 MWd/kg] LWR – Uranium Fuel Net Transuranic Production [kg TRU / GWhe] SNF Production [tonne SNF / GW-yr (e)]

Further Gains from ‘Advanced Nuclear Technologies’ a. Less ~10% of net electric power required to drive the accelerator.

Construction Costs are Uncertain Of the major generation technologies in use today, construction costs for new nuclear facilities are the most difficult to quantify. In a survey of nuclear industry executives, the perceived risk associated with construction costs and times was rated as ‘very high’ – far higher than plant O&M, fuel cycle costs, or disaster preparedness: Highest Estimate OECD Lowest Estimate 4700 8 2100 4 1450 3 FR 2300 8 2130 4 1000 3 HTGR 4000 12 1700 4 1000 3 LWR Overnight Costs [$ / kWe]; Construction Time [yr]

Forecast of Electricity Demand (by Generation Fuel) Billion kWh

Forecast of Nuclear Capacity by Type GW Existing U38 HTGRS /Conventional Fuel Advanced ‘ PWRS’ Transmutation/Accelerators

Comparison of Our Capacity Forecast with EIA Advanced Nuclear, AEO 2006 GW EIA Current Fleet Advanced PWRs HTGRs – Driver / Transmuter Fuel HTGRs – UOX Fuel

Commentary For this scenario, repository capacity is constrained and, after the repository opens in 2018, the duration of SF interim storage is limited. Therefore, two paths for nuclear power are available: 1) adopt technologies that close the fuel cycle, or 2) phase out nuclear power. Under these constraints, the model chose HTGRs with two fuel forms: - low enriched uranium oxide fuel (about 75% of HTGR thermal energy production); - so-called “deep burn” driver and transmutation fuel consisting of transuranic oxides (25% of thermal energy production) 1 . See C. Rodriguez et. al., “Deep Burn Transmutation of Nuclear Waste,” in Proceedings of the Conference on High Temperature Reactors , Petten, NL, April 22-24, 2002. Available: http://www.iaea.org/inis/aws/htgr/fulltext/htr2002_207.pdf

See C. Rodriguez et. al., “Deep Burn Transmutation of Nuclear Waste,” in Proceedings of the Conference on High Temperature Reactors , Petten, NL, April 22-24, 2002. Available: http://www.iaea.org/inis/aws/htgr/fulltext/htr2002_207.pdf

Factors That Could Affect Outcome: Political/Regulatory Factors + + + o - Implementation of Carbon Taxes or Emission Permits + + + o - More Efficient NRC Site and Facility Licensing + + - o + More Stringent Repository Performance Criteria - - + + + Opposition to Licensing or Operation of Reprocessing Facilities - + - + + Regulatory Delays in Licensing of Interim Storage or Expanded Cooling Storage - + - o + Delay in Opening of Yucca Mountain Unconstrained Repository, Advanced Fuel Cycle Constrained Repository, Advanced Fuel Cycle Unconstrained Repository Constrained Repository Nuclear Phaseout Risk Factor (+ = Factor increases likelihood of outcome relative to reference case) (- = Factor decreases likelihood) (o = Factor does not strongly affect likelihood)

Conclusions Inclusion of the issue of spent nuclear fuel results in a different technology mix. Limited permanent disposal capacity requires the use of reprocessing and transmutation-oriented nuclear generation technologies. HTGR technologies provide greater flexibility by accepting a greater range of outputs from reprocessing. HTGR generation is conservatively priced at 21% more in over-night costs than LWRs; but HTGRs provide the potential for recycling of transuranics from previously generated SNF. Advanced nuclear generation technologies provide a sustainable power source through reduction of the quantities of spent nuclear fuel.

Inclusion of the issue of spent nuclear fuel results in a different technology mix.

Limited permanent disposal capacity requires the use of reprocessing and transmutation-oriented nuclear generation technologies.

HTGR technologies provide greater flexibility by accepting a greater range of outputs from reprocessing.

HTGR generation is conservatively priced at 21% more in over-night costs than LWRs; but HTGRs provide the potential for recycling of transuranics from previously generated SNF.

Advanced nuclear generation technologies provide a sustainable power source through reduction of the quantities of spent nuclear fuel.

Backup

Embedded Assumptions in Linear Programming A linear program is a linear program . . .is a linear program!! Embedded economic paradigm in a cost minimization framework. The economic paradigm includes: Homogeneous, linear cost functions. Assumption of perfect competition, i.e., large number of economic agents and everybody is a “price taker.” Ease of entry and exit. All markets are in equilibrium, i.e., market clearing assumed, with perfect foresight. Factors that drive energy use or consumption are “energy only.” Bias introduced through choice of decision variables (e.g., technologies) for inclusion in the model.

A linear program is a linear program . . .is a linear program!!

Embedded economic paradigm in a cost minimization framework.

The economic paradigm includes:

Homogeneous, linear cost functions.

Assumption of perfect competition, i.e., large number of economic agents and everybody is a “price taker.”

Ease of entry and exit.

All markets are in equilibrium, i.e., market clearing assumed, with perfect foresight.

Factors that drive energy use or consumption are “energy only.”

Bias introduced through choice of decision variables (e.g., technologies) for inclusion in the model.

Electricity: Distributed Generation/CHP Each end-use sector has a sector-specific electricity and steam grid which is connected to the main grid with the option of selling (i.e., inter-sector trade). Each sector or end-use has over 40 CHP/DG technologies using natural gas or renewables or other fossil fuels. Industrial CHP: “pass-out” turbines (flexible heat/power ratios), wind, and fuel cells. Commercial and residential: microturbines, fuel cells, reciprocating engines, and photovoltaic. Transport: structured for the addition of “mobile” generation sources. DG and CHP are depicted as the “marginal” producer in the base case, i.e., these technologies compete in a market niche with central generation and more efficient end-use technologies.

Each end-use sector has a sector-specific electricity and steam grid which is connected to the main grid with the option of selling (i.e., inter-sector trade).

Each sector or end-use has over 40 CHP/DG technologies using natural gas or renewables or other fossil fuels.

Industrial CHP: “pass-out” turbines (flexible heat/power ratios), wind, and fuel cells.

Commercial and residential: microturbines, fuel cells, reciprocating engines, and photovoltaic.

Transport: structured for the addition of “mobile” generation sources.

DG and CHP are depicted as the “marginal” producer in the base case, i.e., these technologies compete in a market niche with central generation and more efficient end-use technologies.

Distributed Electricity Generation (DG) versus Central Electricity Generation (CG) Dispatched Central Generation Small Distributed Generators Distributed Generation Clearinghouse Local-Use Distributed Generation To Grid To Grid Transmission Losses Transmission Losses Central Generation Consumption Distributed Generation Consumption from Grid Total Consumption from Grid Total Consumption from DG Total Electricity Consumption

Factors That Could Affect Outcome: Market Factors + + o o o Aggressive Growth in Demand for Hydrogen + + + o - Aggregate Electricity Demand Growth Greater than Expected + + - - + Increased Disposal Cost Volatility - - o o o Delay in Availability of Advanced Technologies - o - - + Scarcity of Uranium Resource + + + o - Increased Fossil Fuel Price Volatility Unconstrained Repository, Advanced Fuel Cycle Constrained Repository, Advanced Fuel Cycle Unconstrained Repository Constrained Repository Nuclear Phaseout Risk Factor (+ = Factor increases likelihood of outcome relative to reference case) (- = Factor decreases likelihood) (o = Factor does not strongly affect likelihood)

Factors That Could Affect Outcome: Security Factors + + - - o Repository Becomes a ‘Plutonium Mine’ - - + + + Propagation / Dispersion of Advanced Reprocessing or Enrichment Technologies - - + + + Security of Separated Actinides - - - o + Transportation of SNF + + - o + Nuclear Materials Dispersed at Generation and Interim Storage Facilities Unconstrained Repository, Advanced Fuel Cycle Constrained Repository, Advanced Fuel Cycle Unconstrained Repository Constrained Repository Nuclear Phaseout Risk Factor (+ = Factor increases likelihood of outcome relative to reference case) (- = Factor decreases likelihood) (o = Factor does not strongly affect likelihood)

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