Cost/Risk-Optimised Decisioneering in Nuclear Energy

Transcription

1 Cost/Risk-Optimised Decisioneering in Nuclear Energy

2 Nuclear-21 is an independent expert cabinet providing bankable decision support driving policy, strategies and business development towards optimised nuclear based solutions Optioneering and Designing Strategies Decisioneering Policy and Business Intelligence Optimising Implementation Our services aim to: Identify and analyse the challenges our customers face in developing and using nuclear science & technology based solutions Enrich policy, strategy and business options Support our customers in their policy, strategy and business development activities Recommend decisions based on proven, sector-specific expertise and quantitative, best practice methodologies Broker solutions-focused international partnerships Ensure compliance with international and national requirements and regulations

3 Nuclear Energy in a Financial Risky Energy Market The energy market has become increasingly uncertain despite long-term trends towards increasing electrification and sustainable energy mixes Geopolitical developments with an increasing energy security focus during the next decades Socio-political uncertainties regarding energy policies and sustainability of these Technical-economic with an increasing competitiveness of renewable energy sources Ecological with pending unclear progress globablly towards tangible decarbonisation of the energy vector T here can be a more prominent role for nuclear energy conditional to matching the energy market objectives and particularly by becoming again a bankable option

4 Cost/Risk challenges towards improved bankability A Nuclear energy system (NES) covers at least a century of activities exposed to various cost and timing uncertainties translating into financial risks Generalised Nuclear Energy system Financial Risks Front-End Fuel Cycle: Front-end fuel supply pricing options Fuel Technology development Fuel qualification & licensing Typical Net-Present-Value (NPV) analysis indicates competitiveness of nuclear energy Financial Risks Nuclear Power Plants: NPP Technology Development NPP Market Competitiveness NPP Licensing Process NPP Construction / Project Mgt NPP Socio-Political Acceptance Energy Market Competitiveness Nuclear Waste Management

5 for Nuclear Energy Systems Financial Risks Recycling Fuel Cycle: Economic value for recycling Advanced NPP & Fuel development Socio-political acceptance of reprocessing Uncertain costs and timing of GDF for HLW and recycled UNFs Financial Risks UNF & Waste Management: Investment decisions on UNF-management facilities Uncertain costs and timing of GDF Uncertain safety performance interim stored UNF Security requirements interim stored UNF Damaged UNF management Socio-political acceptance of piling-up UNF Transport of UNF Regulatory changes to UNF-management But challenges for NPP-newbuilds stemming from supply chain and project-management uncertainties

6 We face Multi-Variate Uncertainties in Decisioneering on Nuclear Energy Options Energy Market Competitiveness Societal Acceptance Energy Policy International Financial Market Energy Market Options Today Operational performance Technology Development Regulatory Intra-Nuclear Options Safety & Security performance The Complexity of Decision-Making in (Nuclear) Energy Systems Strategies

7 How to decide in uncertain futures? Classic methodologies as Net-Present-Value (NPV) or Discounted-Cash-Flow (DCF) are not providing answers on important decisional questions under uncertainty, e.g.: Political Stability Framework Geopolitics when to decide which decisional option to execute? what is the value to keep an option open? what is the most robust decisional strategy? what s the affordable value for future decisional flexiblity? what is optimal investment-portfolio in uncertain futures?... Infrastructure Expertise Increasing market and business value for flexibility, i.e. Longer-term policy and business strategies to be segmented in flexible options Matched to the then known market context Our Decisioneering Methodology Decisional Strategy Performance Analysis of robustnes of decisional strategy and defining decisional moments and options Sensitivity analysis on key parameters and identification of decisional treshold markers Decision Tree Analysis Risk analysis of decisional branches and tipping-points analysiss Real Options Value of decisional branches and hedging actions Options Portfolio Analysis Multi-Variate Cost/Risk Segmentation of Options Multi-variate performance analysis of options Identification and characterisation of uncertainties Optioneering Describing and Modeling the foreseeable and feasible options Multi-variate Characterisation of the decisional options Identify and Investigate innovative options Identify and structure decision tree Scenario-analysis projecting decisional impacts

8 Nuclear Energy System Strategies Assessment Toolbox NESSAT provides Up-to-date past, present and future nuclear reactor and fuel cycle information on reactor, utility and/or country level Projection of future deployment scenarios for nuclear reactor park and associated fuel cycle facilities and options Technical-economic analysis of nuclear reactor park and/or fuel cycle options Library of deployment scenarios from Business-As-Usual to transition scenarios towards more advanced nuclear energy system options Analysis of the technology-to-business potential by Market analysis and projected market trends Impact analysis of technology innovation Options value assessment allowing to Value decisional flexibility in nuclear reactor park and/or fuel cycle options deployment Optimize cost and risk exposure by assessing optimal options decision-making Generic Example Two decisional options A and B differ in performance over time. Option B progresses as best option but goes with higher uncertainty over time Option A seemingly becoming the best option When is the best moment to switch from B to A and what s the value for keeping Option A open? Performance Indicator (Min) Option B Option A Relative Risk Time

9 Expected Value Option A is preferentially executed from Year 15 on

10 Spent Nuclear Fuel Management Decisioneering The management of Spent Nuclear Fuel (SNF) is increasingly a financial risk for SNF-owners given: a general wait-and-see delay in the execution of ultimate SNF-management options; eldering Nuclear Power Plants (NPP) with possible stranded SNF at nonoperational NPP-sites; (very) long-term interim storage of SNF may increasingly pose security and safety risks; but also by a changing and uncertain environment: socio-political acceptance of SNF-storage financial market rating and governmental review of provision-fund terms regulatory changed Classical NPV/DCF-analysis do not allow to capture these uncertainties in decisional branching and to assess hedging values of various SNF-management options A typical question: to reprocess or not? SNF may be reprocessed at various moments after discharge. Central question being: Is there a best moment to reprocess given future uncertainties in SNF-management? Cask storage: + Lower cost in short term + Competitive market offers - Lock-in of SNF during minimal period - SNF Degradation under less controllable conditions - Security precautions increasingly important - Defaulting SNF requiring high-cost remediative actions - Increasing cost uncertainties in wait-and-see scenarios Repackaging Reconditioning Pool Storage Cask Storage Pool storage: + Flexibility + Controllability - Slightly higher cost - Stranded SNF? Geological Disposal SNF: - Unclear timing - Infinite Safeguarding Geological Disposal 10 years 60 years 100 years? Recycling Reprocessing Reprocessing & Recycling: - Higher costs initially + Equivalent/Parity Fuels + Possibility to recycle Pu and RepU from various origins + Customised solutions optimiseing fuel Interim Storage HLW: + Reduced Volume + No Safeguarding + Standardisation waste-package + No degradation risks + Flexible in view of uncertain GDF-timing Geological Disposal HLW: - Unclear timing - Infinite Safeguarding + Reduced Volume + No Safeguarding + Standardisation waste-package

11 Comparison of NPV/DCF and Real Options Value (ROV) The OECD/NEA the Economics of the Back-End of the Nuclear Fuel Cycle (2013) applied the classical NPV/DCF-analysis comparing Once-Through Fuel Cycle (OFC) with the mono-pu Recycling Fuel Cycle (RFC) but didn t account for uncertainties in costs and timing of back-end SNF-management operations. Applying uncertainty-values from NEA-study, the expected costs and associated uncertainty-range for costs are essentially governed by GDF cost and timing uncertainties + 10 y + 15 y + 20 y + 25 y +30 y + 5 y t 0 While ROV provide at t 0 same results as NPV/DCF-analysis (i.e. 8 % in favour of LWR-OTC): the increasing uncertainty provides value to LWR- RFC from 10 years after discharge with lower than LWR-OTC costs and significant lower future financial risks More advanced financial risk assessment methodologies, as Real Options Valuation (ROV), provide insights on how utilities and governments may reduce their cost/risk-exposure over time and providing insights on when which option to execute

12 Cost/Risk-Optimised Decisioneering on Spent Nuclear Fuel The multi-variate decisional environment on SNF-management demands more advanced cost/ risk-assessment methodologies allowing to: assess the time-evolving performance of SNF-management options value the flexibility required in uncertain futures optimising the cost/risk-exposure for SNF-owners matching their financial riskexposure As such, our Cost/Risk-Optimised Decisioneering methodology allows to: project optimised decisional strategies on SNF valuing the developments affordable to optimise cost/risk-exposure identify the decisional conditions towards more optimised SNF-management options inform stakeholders and leveraging towards improved understanding of decisional framework by segmenting the SNF-inventory according cost/risk-profile projecting the optimised contractualisation roadmap for SNF-management services what-if? analysis for new SNF-management developments and decisional impacts analyse pricing strategies for SNF-management strategies Generic Example A typical LWR-SNF batch faces multiple decisional options during the decades after discharge with each decision providing: hedging value in view of future uncertainties valuing flexibility keeping future options open

13 Uncertainty Range Option A Option A Option B Uncertainty Range Option B Branching into Option B.b Year Branching into Option B.a Branching into Option A.a Branching into Option A.b A generic example maps the performance evolution of 6 different decisional scenarios in the back-end of the fuel cycle, i.e.: Two main scenarios A and B branch at different moments into A.a / A.b and B.a / B.b respectively; resulting into different performance evolutions over time Main question: Which scenario to execute when by minimising cost/riskexposure? The Value-at-Risk (VaR) analysis concludes that: Option A to be executed till year 16 and then to switch to Option A.a till year 28 where continuation of A.a as well as switching to B, A.b or B.a would be beneficial Real Options Values for development/investments for the options are derived accordingly The Cost/Risk-decisioneering methodology allows to optimise the cost/risk exposure of SNFowners by matching their financial performance rating (example, RFC versus OTF fuel cycle choice)

14 Decisioneering Methodology applicable in various uncertain decisional situations This brochure presented the cost/risk-decisioneering methodology particulary for spent nuclear fuel management decisioneering, though the methodology is widely applicable to, e.g.: market analysis in uncertain market futures value of technology developments in investment analysis pricing analysis in portfolio optimisation risk analysis allowing market segmentation and this in various domains, e.g.: Energy market Market analysis between various technology options Nuclear Power Plant investments Large versus smaller/modular reactors Waste management Decommissioning waste policies & strategies in short, in any decisioneering where uncertain futures need to be valued in today s decisions and costs/risks need to be optimised and matched to investors risk-appetite

15 Contact Us Groenstraat - 35 B-9250 Waasmunster Belgium Cell. +32(0) Champs Elysees F Paris France Euston House 24 Eversholt Street London NW1 1AD United Kingdom Cell info@nuclear-21.net Luc Van Den Durpel (MD) Ross Peel (AP) Hubert Bairiot Frédérique Damerval Gian-Luigi Fiorini Caroline Jorant Jim Kuijper Serge Runge Henri Zaccai

16 The Four Aspects of our Service Offer are Centred around Our Customers Needs policies and frameworks comprehensive plans enabling strategies partnering and project funding due diligence analysis international technology transfer and process industrialisation knowledge management and expert sourcing Optioneering and Designing Strategies model and simulate the policy, strategy and business development futures perform baseline studies verify financial performance document and communicate the decisional options accompany due diligence processes Decisioneering Policy and Business Intelligence technology, policy and business foresighting technology reviews competition analysis market assessments economic and financial risk assessments innovation processes development Optimising Implementation project initiation & guidance project funding & partnering support project operationalisation process and project evaluations performance benchmarking business development & commercial offer support winning new markets