Uncertainties in the Uranium and Enrichment Markets: a Stochastic Approach

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Uncertainties in the Uranium and Enrichment Markets: a Stochastic Approach Erich Schneider, Birdy Phathanapirom The University of Texas at Austin Roderick Eggert, Eric Segal Colorado School of Mines 31st USAEE/IAEE North American Conference, Austin, TX November 5, 2012

Uranium (U) mining and enrichment are steps in the front end of the nuclear fuel cycle (NFC) Competitive markets exist for these services Overview They provide enriched U fuel to nuclear reactors, whose demand for fuel is nearly inelastic in the short run European Nuclear Society

Overview We have devised a market-clearing model that evaluates the evolution of these markets through 2030: primary uranium from mines, secondary uranium from e.g. depleted uranium (DU) upgrading or highly enriched uranium (HEU) down blending conversion to uranium hexafluoride (UF 6 ), enrichment to 4-5% 235 U, as required by most reactors. The model is not used to predict prices, but rather to evaluate policy measures affecting the front end markets, while taking a stochastic approach to account for uncertainties

Methodology Outline Underlying databases Depiction of supply and demand & assumptions Coupling between markets Reference case and one sensitivity study constraints on primary U supply Monte Carlo implementation Other applications

Supply databases Primary uranium (CSM): contains more than 350 uranium properties at various stages of development, representing reserves and resources of over 7 million tonnes U (tu). Secondary uranium (UT-Austin): includes inventories of excess HEU, DU, other government- and utility-held U stocks, and excess weapons grade plutonium (WGPu) Enrichment (UT-Austin) Existing capacity as well as announced and planned expansions through 2018; growth assumed thereafter

Price $/kg U] Market clearing model Constructs annual supply curves from the primary U, secondary U and enrichment plant databases assembled by CSM and UT-Austin Uranium supply and demand cartoon Price [$/kg U] Tails Assay = 0.1% 0.2% Supply Demand 0.3% Tails Assay = 0.4% Intersection determines quantity of uranium produced and marketclearing price Tails = leftover depleted uranium from enrichment Quantity [kg U]

Interplay between markets It would take many years for a reactor (at large cost) to modify its demand for fuel But utilities can substitute uranium for enrichment services so the uranium and enrichment demand curves exhibit considerable short run price elasticity enrichment services are measured in separative work units, SWU The substitution is achieved by adjusting the amount of U-235 left in the depleted uranium tails

Price $/kg U] Market clearing model Simulation marches forward through time Uranium and enrichment market clearing states are solved at each time step in coupled calculations The model responds to shifts in supply and demand, for instance following closure of a major mine: Price [$/kg U] Tails Assay = 0.1% Demand 0.2% if a mine closes, shifting supply... Supply 0.3% Quantity [kg U] Tails Assay = 0.4% utilities consume less U (and more SWU)

Constrained optimization problem solved each time step Demand curves are calculated as the locus of points that minimize cost, C [$], to the consumer: P U, P C, P SWU = market prices of U, conversion, enrichment [$/kg or $/SWU] U d, SWU d, NU d = amount [kg or SWU] of U or SWU Each term is a function of the DU tails U-235 enrichment, x w (and the reactor fuel and natural uranium enrichments x p and x f ). Constraints: Demand for reactor fuel (fixed in the short run) must be satisfied P U treated as free, P SWU = f(swu d ) obtained from clearing enrichment market at each trial x w

Drawing the uranium demand curve Choose an x w,set dc/dx w = 0, solve for P U : where C x W [%] Use constraint to solve for U d (x w ), put one point on U demand curve P U Quantity U d [tu] Solve for P U at which this x w minimizes C Repeat for all feasible x w to derive U demand curve

Supply and demand curves Secondary U (like U sold from gov t inventory) is a supply step with zero cost Shape of U demand curve affected by market clearing enrichment price: Supply steps are color-coded according to deposit type Supply curve changes with each time step as deposits are mined out and other deposits become available NU demand curve can shift over time due to exogenous fuel demand growth rate and change shape as enrichment cost structure evolves

Reference Case Demand growth rate derived from average of OECD Redbook low demand and high demand scenarios Initial demand reflects world values in 2010 Description Value World LEU reactor fuel demand in 2010 6,790 tonnes / yr World U as fuel demand in 2010* 3,390 tonnes / yr Average U 235 content of LEU fuel 4.3 w/o World LEU & NU fuel demand growth rate 2.6 % / year Year enrichment facility capacity growth commences 2018 Enrichment facility capacity growth rate 2.6% / year Cost of yellowcake to fluoride conversion $10 / kg U WGPu fraction in MOX 5 w/o of IHM U 235 content of HEU downblend stock 0.25 w/o * Certain reactors, e.g. CANDU, consume fuel fabricated from unenriched natural uranium.

U supply by source through 2030 2.6% p.a. growth in fuel demand World Nuclear Association (WNA) case, similar demand growth rate, provided for comparison: WNA doesn t clear markets, only add up potential supply sources (figure source: WNA)

Enrichment supply by source through 2030 Each supplier assumed to expand at 2.6% p.a. after 2018 WNA does not assume supply growth except for Russian sources, seeks to identify shortfalls (figure source: WNA)

Results: market-clearing U and SWU prices U price SWU price The reference case predicts Uranium and SWU prices to remain high (in historical terms) through ~2015; Both prices to decline, thereafter in the case of SWU to belowhistorical levels, and remain low through 2020-25; Sympathetic increases in both U and SWU prices beginning in the early 2020s. these increases may be spurious as we do not yet take undiscovered deposits or reserve growth into account.

Constrained primary supply scenario Worst case primary supply scenario where: Olympic Dam mine expansion doesn t take place; Queensland adopts U mining ban; A worldwide U supply slowdown develops (mine capacity factors decreased). Figures. U production by country, base scenario (left) and constrained supply (right)

Effects of constrained primary supply scenario U price rises to $260/kg U by 2030 Substitution of SWU and secondary U for primary U is seen, but these safety valves have only a limited mitigating effect: *Undiscounted. ** Includes oxide-to-fluoride conversion for primary U at $10/kg U.

Monte Carlo implementation Objective: incorporate and propagate uncertainties in supply factors & reactor fuel demand Method: sample inputs from distributions, run independent realizations, aggregate Table. Supply and demand uncertainties for sample case Description Mean Value Distribution & range or standard deviation Reactor fuel demand growth rate 2.6 %/yr Uniform, 1.7% - 3.5% Enrichment capacity growth rate 2.6 %/yr Uniform, 1.7% - 3.5% Uranium Production Cost Multiplier 1.0 Normal, σ = 0.3 SWU Production Cost Multiplier 1.0 Normal, σ = 0.3 Mine Capacity Factor Multiplier 1.0 Normal, σ = 0.3

Results: U price Median shown in black, 90% confidence interval in red

Results: SWU consumption (top), Market clearing SWU price (bottom) Bottleneck in 2015: supply constraints amidst transition from diffusion to centrifuge technology

Conclusions: limitations, applications Limitations: Assumes a single, frictionless world market for uranium and enrichment services at equilibrium Uses production rather than operating costs to dispatch supply Used as policy tool, not as a predictor of uranium prices Policy relevance: Evaluate market impact of inventory sales strategies Assess buying into / disbursing from a uranium bank Support R&D decision making by identifying surplus associated with advanced technologies, e.g. SILEX enrichment