• Cashflow metrics: NPV, IRR, WACC.
• Profitability metrics, ROI, ROA, ROE. Profitability metrics used to assess a business's ability to generate earnings compared to its expenses and other relevant costs incurred during a specific period of time.
• Revenue metrics: Gross Revenue, EBITDA (Earnings before interest, depreciation and amortisation), cash flow available for debt service, net income, margins, etc.
Revenue refers to the income business has earned from the sale of goods and services.
• Coverage ratio is a measure of a company's ability to meet its financial obligations.
In broad terms, the higher the coverage ratio, the better the ability of the enterprise to fulfil its obligations to its lenders. The trend of coverage ratios over time is also studied by analysts and investors to ascertain the change in a company's financial position.
Coverage ratios include debt service coverage ratio, minimum debt service coverage ratio, average debt service coverage ratio, loan life coverage ratio, project life coverage ratio, interest coverage ratio, debt to EBITDA ratio.
Most participants have calculated and discussed the levelized cost of electricity, the net present value of the project as well as its internal rate of return. Many countries have also run sensitivity analysis to understand which parameters or assumptions have the largest impact on financial outcomes. In particular, the LCOE is most sensitive to the cost of capital, financing cost, construction time (construction delays), capacity factor and fluctuations in the exchange rate.
Risk analysis was performed by all the participants, at least by identifying different risks and ranking them (qualitative estimation). Some participants carried on sensitivity analysis (e.g.
China, Croatia, Indonesia, Jordan and Pakistan) to identify the variables that most influence the outcome, and to quantify their impact. Uruguay and Croatia performed also probabilistic analysis using Monte Carlo techniques.
APPENDIX: A SYNTHESIS OF WORK DONE DURING THE CRP Objective for participation Methodology used Key financial metricsKey findings Identify the most common types of nuclear power plant ownership, contractual approaches and to define the most appropriate for the nuclear new build in Bulgaria; Investigate the conventional and alternative approaches for financing nuclear power generation project; Build a model for financial estimation of the nuclear power plant investment; Investigate the nature of the uncertainties arising in the context of nuclear power plants investments; Develop a specific methodological approach to analyse and determine the uncertainties of the project Cost analysis; Financial modelling to evaluate the feasibility and competitiveness of the newbuild project at Kozloduy; Expert survey (for risk assessment). Risks were ranked but not quantified, and a risk matrix has been developed
Cost of equity 10% Cost of debt 5.5% D/E ratio 85/15 WACC 5.7% Starting electricity price US $71/MWh LCOEUS $51.2/MWh ROI 10.19% IRR 8.07% NPV 5692 Min DSCR 0.78 Max DSCR 1.47
Bulgarian electricity sector will need 2400 MW installed and operating nuclear capacity in 2045 year as this nuclear capacity is going to substitute the power from units 5 and 6 of Kozloduy NPP (in case there is a decision not to extent the operation term) or phased out thermal power plants. Main assumption is the implementation of the paid Belene equipment in a new nuclear power plant at the Kozloduy site. The project is carried out based on project financing. Investment in the project will be reimbursed on the basis of future revenues from the sale of electricity without long term contracts for the purchase of electricity at the fully liberalized energy market. Contracts for difference for 35-year period, with a starting price of US $712017/MWh with 2% step-up can to be used to provide electricity price predictability. A split package type of contract is proposed— one for manufacturing and supply of the equipment and other with a constructing company. In the contract pricing a hybrid approach is used. On the premises that a strategic investor is found, the project is financed 85/15 debt to equity, the project is estimated to be profitable. (NPV >0, IRR> WACC, return on investment is more than 10%) The main risks identified are: •Construction (cost overruns and delays in the construction schedule) •Financial and economic (lack of financing, construction and market risk) •Regulatory, political and environmental risks •Absence of a long-term vision for the nuclear fuel cycle Project is exposed to political support, financial risk, market risk and others.One of the major risks for the project is the political risk. To minimize the risk, the government must have a commitment to nuclear power as a part of national energy strategy.
Objective for participation Methodology used Key financial metricsKey findings Understand the basics of capital cost evaluation methodology. Understand world best practices of financing and develop a financial model for financing new NPPs. Understand the world best practices on risks assessment for NPPs construction projects and develop a risk mitigation matrix for new NPPs Cost analysis Financial model Sensitivity to capital cost, financing cost, capacity factor, fuel price Risks assessment (via expert survey)
D/E ~ 80/20 LCOE IRR
The main factors affecting the LCOE of a nuclear project are capital costs, financing costs and capacity factor. The following key risks are identified, and measures for their mitigation are proposed: •Short term loans for long term investment •Interest rate fluctuation •Fluctuation in exchange •Inflation •Project debt risk
Objective for participation Methodology used Key financial metricsKey findings Carry out a feasibility and financial analysis for potential nuclear power plants in Croatia; Define financial approach most compatible with current utility and financial market conditions; Study how the financial risks specific to new large power plants (especially nuclear power) in liberalised markets can be mitigated and allocated to the different stakeholders, and which financial arrangements are consistent with the alternative allocations of the construction and operating risks; Perform feasibility analysis for SMRs.
Combination of financial and energy planning tools: FINPLAN, WASP, MESSAGE and own models. Risk analysis on revenues due to variability in hydroelectric generation.
For SMRs D/E ratio 55/45 LCOE of SMR 93– 106 EUR/MWh
Results for all technologies were compared to hourly electricity market prices in 2014 on power exchanges in Hungary and Slovenia and the result is that NPP (but also all other technologies) cannot be competitive on current electricity markets. In Croatia, SMRs can be better suited than large reactor given the forecasted very small growth of demand and high penetration of subsidised renewable energy sources (RES): they can be built progressively as needs arise and have better features to cope with investment scenario uncertainties, making these projects easier to finance compared to large NPPs. The first preliminary analyses of SMR integration in the Croatian mix show that revenues from electricity markets would be insufficient and situation SMR generators would require some additional forms of remuneration — e. g. capacity payments and load following payments or ancillary services payments.
Objective for participation Methodology used Key financial metricsKey findings
Indonesia
Explore financial viability of new nuclear power plants in Indonesia; Determine technical and economic parameters for a NPP project; Identification of financial sources for nuclear power plants and analysis of financing schemes; Risks identification and risk analysis (construction delay, market risk, etc.) Assess the financial performance of a SMR project taking into account the uncertainties that may occur in the project.
Developing a (deterministic) financing model to assess the financial performance of the project NPV and IRRs). A Monte Carlo technique is used to propagate the uncertainty of multiple variables and to see the impact on IRR and NPV. The variables analysed are (capital cost, O&M cost, fuel cost, capacity factor, construction period, interest rate, inflation and exchange rates)
NPV,IRRand equity IRR. Sensitivityanalysis toselling price of electricity, construction time, exchangerate, overnight cost
Based on the simulation carried out, it is found that most probable value of overnight cost is US $6360/kW for 2 SMR units of 100 MW each. Monte Carlo simulation was performed to determine the effect of the uncertainty variables to the financial performance indicator. The simulation was conducted with discount rate 10%. Electricity sale price becomes critical for a project’s viability and a decision on its approval. The study results indicate that a SMR is feasible at the selling price of US $140 per MWh. At that price a SMR is not competitive with a coal power plant but is still competitive with a renewable power plant. The second parameter affecting the financial viability is the construction period (potential cost overruns will increase the cost); Investment cost has a significant impact on the cost of the project since it’s a significant share of the construction cost. It should be monitored to prevent cost overrun in a project. Domestic currency inflation rate fluctuation is also an important factor. It indicates the big challenge for the Government to stabilize the national economy so that Indonesia is not categorized as a country with high investment risk.
Objective for participation Methodology used Key financial metricsKey findings Identifying contractual structure and ownership structures of nuclear power projects. Developing a financial model and carrying out financial analysis. Analysing the main drivers and parameters affecting the financial feasibility of a nuclear power project looking at a number of contractual and ownership structures. Developing a high-level risk management plan.
Financial model; Scenario analysis; Risk analysis.
D/E ratio: 40/60 Interest on debt: 3.73% (sc. 1) 4.47% (sc. 2) 5.73% (sc. 3) Discount factor: 7% (sc. 1) 8% (sc. 2) 9% (sc. 3)
Compared to conventional power plants, NPPs overnight investment cost is higher and in the range of US $5000–7000/kW. This is coupled with a required time frame of at least 5 years for construction completion. For a newcomer country, the optimum contractual approach is an EPC turkey approach. This approach minimizes risks facing the project especially during the construction phase. The analysis of the three scenarios modelled shows that a Governmental-owned project can attract debt at a lower rate and has a lower required rate of return than projects under a mixed public-private partnership or fully private. Thus, LCOE and the electricity tariff required are significantly lower in case of governmental owned projects: required tariff would be 43% higher for a fully private project, and 20% higher for a joint public-private project. Risk analysis showed the highest risks during the planning phase are unrealistic schedule, changes in standard design due to new technical requirements, limited capabilities to finance the project, additional requirements from lenders, delay in EPC negotiation with unbalanced risks, lack of experience in licensing NPPs, and lack of qualified staff. The top risks for a newcomer country’s nuclear project are concentrated in vendor design, financing, regulatory system and licensing and EPC contract negotiation. The particularity of nuclear power projects makes that a large part of the risks are ultimately managed by the project stakeholders and cannot be transferred to insurance companies as in more conventional projects. However, new tools have emerged to support investors to manage their risks and hedge against them
Objective for participation Methodology used Key financial metricsKey findings Analysis of optimal financing options for Kenya’s NPP Ownership and contractual approaches for NPP in Kenya Risk analysis, categorization and mitigation
Risk analysis, categorization and mitigation. SMR present the most feasible option for Kenya’s NPP due to small size ofgrid Most suitable Contracting approach — turnkey contract. Government-to-Government financing offers a valuable source of foreign funding and experience in the nuclear sector, as the magnitude of funds and nuclear experience is domestically unavailable. Loan Guarantees can provide cheaper interest rates, since a guaranteed loan has lower risk, and therefore lower cost, as well as creating liquidity where it might not otherwise be present. Vendor financing could be explored as the programme advances. Kenya should consider negotiating intergovernmental agreements inclusive of funding arrangements for the pre-construction phase of the power programme (infrastructure support) as well as financing (vendor financing through intergovernmental agreements). Kenya should determine to what extent it will take ownership of the power plant. The parties to the agreements will need to agree on what stake each party will have in the power project and this could in turn impact on financing arrangements for the power project. In order to guarantee sale of the electricity generated, a power purchase agreement will need to be negotiated prior to ground-breaking for the power project. Kenya ought to consider engaging global consultants to assist in the pre-construction phase of the NPP project as well as managing its implementation. Kenya should consider obtaining a proportion of the financing required to implement the country’s nuclear power project from ECAs despite the high costs associated with the loan guarantees that they provide.
Objective for participation Methodology used Key financial metricsKey findings Learn about sources of financing power sector and methods of risk assessment Develop a financial model to calculate: •Investment, Export Credit and Equity required for nuclear programme •Cost of generation •Financial ratios to evaluate the financial viability of plants Perform sensitivity analysis to evaluate financial impact of cost of financing, plant capacity factor and changes in fuel costs. Evaluate impact of increase in indigenisation in construction of plant, and sensitivity to indigenisation Financial model (based on FINPLAN) Sensitivity analysis Impact of localisation content on electricity generation cost
D/E 80/20 ROE 16%
The total investment requirement of the whole nuclear power programme is estimated to be US $26.289 million. It has been estimated that 56% will be available as export credit, 20% will be funded through equity, and the remaining 24% will be raised from local banks. The level of the electricity tariff and some financial indicators (BCR, NPV, payback period and debt services coverage ratio) indicate that the projects are financially viable given the assumptions taken in the present study. This sensitivity analysis shows that nuclear power plants in the programme are extremely financially sensitive to any change in the cost of financing (1% higher cost of financing increases generation cost by 8.5%). These plants are also very sensitive to slight change in the plant’s capacity factor (a 10% lower capacity factor increases cost of generation by 11.4%). Changes in the fuel prices has less impact on the cost of electricity generation. The increasing indigenization of the power plant results in higher construction costs and in increased capital costs (due to a lower proportion of ECA financing). This would result in increased electricity generation cost. It should be noted, however, that this analysis does not cover other supplementary macroeconomic benefits such as employment, social uplift, skill development, industrial advancement etc., or burdens like cost of uplifting industry, infrastructure, etc.
Objective for participation Methodology used Key financial metricsKey findings Calculating the optimal energy mix and the cost of electricity; Calculating cost of NPP; Understanding and mitigating cost variability; Developing methodology to address power plans risk analysis, differentiating aspects to be treated with a deterministic approach and those with a probabilistic approach.
The toolusedfor capacity expansion is WASP IV. Separate toolshave been developed toaccount for some of the financial and risk assessment limitationsof WASP IV A deterministic approach was followed in the first part ofthe study: construction and technologyrisksare consideredwithincapital costs rates through premium risks. A probabilistic approach was followed in the second phase of the study: future prices are handledas stochastic variables toreflect its variability withstatic approach. Future real prices risk ismodelledthrough probability distributionsof annual real growth rates.
Optimal mixof technologies for capacity expansion.
Cost assessment Liquefied natural gas real price and capital real price growth rates variability are identified as the relevant future price uncertainties. In case of LNG price, the values that lead to a structural change of the optimal national power plan are 0.8% and 2.86%, and in the case of capital price annual cumulative average real growth rate, the value is about 1%: •r_(LNG price)≤0.8%: the optimal expansion plan is constituted by a mix of CCGT and wind power; •r_(LNG price)>2.86%: the optimal expansion plan is constituted by a mix of SMRs and wind power; •r_(capital price)≥1.0%: the optimal expansion plan is constituted by a mix of CCGT and wind power. Robustness assessment of Uruguay´s power generation expansion strategy Whatever is the generation mix considered (a mix of CCGT and wind power, a mix of SMR and wind power or a mix of these three technologies), the cost estimates are within an acceptable confidence level for the risk factors described above. A comparative analysis between optimal power plans in a scenario not considering prices’ real growth rates and a scenario considering the expected values of prices’ real growth rates analysed before has been made in order to assess the relevance of these inputs in the Uruguayan case. The outcomes compared are the followings: •Uruguay´s optimal power plan obtained in this study for a scenario not considering growth rates of prices correspond to a mix of CCGT and wind power plants •Considering expected real growth rates of prices, the optimal power plan remains the same until the 2040. However, from 2041 onwards, the optimal plan incorporates SMR instead of CCGT.
Objective for participation Methodology used Key financial metricsKey findings Calculate the total investment cost ofa NPP projectin Vietnam; Develop cost components of the nuclear generation costs; Understand the cost structure of a nuclear project Comparing the cost structure establishedbyVietnam regulatorydocumentstothe calculationsofthe IAEA and other countries. Investigate alternative financial structures for the NPP project. Understand financial arrangements Understanding risk and developing a risk matrix.
Risk were assessed and ranked through expert evaluation (qualitative assessment).
Costs: Total investment are determined by the following: •construction expenses are calculated according to the workload mainly based on the basic design; •Other workloads as estimated based on market data; equipment expenses are calculatedaccording toquantityand categories ofequipment suitable to technological design, market prices of equipment and other elements (if any); •Expenses for compensation, support and resettlement are calculated according to the compensation, support and resettlement workload of the project and relevant state regulations; •Project management and construction investment consultancyand other expenses are determined by making cost estimates or provisional calculation as a percentage of total construction and equipment expenses Potential financial arrangements on NPP construction •Period of Loan: during construction; •Loan interest rate and repayment term: base on government’ agreement; Interest rate: CIRR + Buyer Premium; Repayment period: begins at the Starting Point of Credit and ending on the contractual date of the final repayment of principle; •Guarantee: 100% guarantee by the Vietnamese government Risk assessment Most important finance risks: •Owner’s poor management (budget and scheduling of the project); •Ultimate cost of the plant exceeds original budget and funding expectations; •Delay in the State Budget; •Political decision associated to financial conditions; •Lack of law system necessary for projects. Beside finance risks, NPP project also face many other types of risks, as safety, regulation, quality, etc. The risks can occur at stages of project as: decision-making stage,bidding,design,construction,commissioning, operation; and come from partners of the project: owner, contractor or consultant.
71 REFERENCES
[1] GUPTA, A., “Challenges and Potential Solutions for the Nuclear New Builds. UK New Nuclear: Hinkley Point C Case Study”, IAEA Technical Meeting on Managing the Financial Risks Associated with Nuclear New Build (2017).
[2] OECD, Arrangement on Officially Supported Export Credits, OECD Publishing, Paris, (2019)
[3] OECD NUCLEAR ENERGY AGENCY, Nuclear New Build: Insights into Financing and Project Management, OECD Publishing, Paris, (2015).
[4] INTERNATIONAL ENERGY AGENCY, OECD NUCLEAR ENERGY AGENCY,
Projected Costs of Generating Electricity: 2015 Edition, OECD Publishing, Paris, (2015).
[5] ENERGY INFORMATION ADMINISTRATION, “Levelized Cost of Electricity and Levelized Avoided Cost of Electricity Methodology Supplement”, EIA/DOE, Washington, DC (2013).
[6] INTERNATIONAL ENERGY AGENCY, World Energy model Documentation:
2019 Version, OECD Publishing, Paris, (2019).
[7] INTERNATIONAL ENERGY AGENCY, OECD NUCLEAR ENERGY AGENCY,
Projected Costs of Generating Electricity: 2020 Edition, OECD Publishing, Paris, (In preparation).
[8] DEAN, D., “Types of capital, risk and returns, priority of claims and key metrics”, IAEA Technical Meeting on Managing the Financial Risks Associated with Nuclear New Build (2017).
[9] BENBOW, J., “Benchmarking the Financial Assumptions”, IAEA Technical Meeting on Financial modelling (2016).
[10] INTERNATIONAL ATOMIC ENERGY AGENCY, Managing the Financial Risk Associated with the Financing of New Nuclear Power Plant Projects, Nuclear Energy Series NG-T-4.6, IAEA, Vienna (2017).
[11] INTERNATIONAL ATOMIC ENERGY AGENCY, IAEA tools and methodologies for Energy System Planning and Nuclear Energy System Assessments, IAEA [12] INTERNATIONAL ATOMIC ENERGY AGENCY, Economic Evaluation of Bids
for Nuclear Power Plants, Technological Report Series 396, IAEA, Vienna (2000).
[13] PLN, PT, JAPC and LAPI-ITB, “Feasibility Study for Bangka NPP Project – Non-site aspect”, 2013
73 LIST OF ABBREVIATIONS
BCR benefit cost ratio BOP balance of the plant
CCGT combined cycle gas turbines CFD contracts for difference
CGN China general nuclear power group CIRR commercial interest reference rate COD commercial operation date
CRP coordinated research project DCF discounted cash flow
D/E debt equity ratio
DSCR debt service coverage ratio
EBITDA earnings before interest, tax, depreciation and amortisation ECA export credit agency
EPC² engineering, procurement and construction ESST energy scenarios simulation tool
FINPLAN financial analysis of electric sector expansion plans
FIP feed in premium
FIT feed in tariff
IDC interest during construction IEA international energy agency IRR internal rate of return
LACE levelized avoided cost of electricity LCOE levelized cost of electricity
LIBOR London interbank offered rate LNG liquefied natural gas
LUEC levelized unit electricity cost
MAED model for analysis of energy demands
MESSAGE model of energy supply strategy alternatives and their general environmental impacts
MIRR modified internal rate of return NPP nuclear power plant
NPV net present value
O&M operation and maintenance
OECD organization for economic cooperation and development
PI profitability index
PPA power purchase agreement
PV present value
RAB regulatory asset base RES renewable energy sources
ROA return on assets
ROE return on equity
SMR small modular reactor SPV special purpose vehicle
SNPTC state nuclear power technology company (China) VALCOE value adjusted LCOE
WACC weighted average cost of capital
WASP Wien automatic system planning package
75 CONTRIBUTORS TO DRAFTING AND REVIEW
Al-Bakhit Y., Jordan Atomic Energy Commission, Jordan Al-Majali, J., Jordan Atomic Energy Commission, Jordan Amitayani, E. S. National Nuclear Energy Agency, Indonesia Aulimat, B., Jordan Atomic Energy Commission, Jordan Ayoub, R., Jordan Atomic Energy Commission, Jordan
Bo, Z. Shanghai Nuclear Engineering Research and Design Institute, China
Cometto, M. International Atomic Energy Agency
Imtiaz, M., Pakistan Atomic Energy Commission, Pakistan Ivanova, N. Kozloduy NPP, Bulgaria
Katsva, M. International Atomic Energy Agency
Khan Lodhi, M. H. Pakistan Atomic Energy Commission, Pakistan Kovachev, M International Atomic Energy Agency
Mberia, N. Kenya Nuclear Electricity Board, Kenya Nasrullah, M. National Nuclear Energy Agency, Indonesia Ndubai, W. Kenya Nuclear Electricity Board, Kenya
Nguyen, T. P., Ninh Thuan Nuclear Power Project Management Board, Viet Nam Nuryanti, N., National Nuclear Energy Agency, Indonesia
Osta, A. Ministry of Industry, Energy and Mining, Uruguay Paillère, H. International Atomic Energy Agency
Saleem Ullah, M., Pakistan Atomic Energy Commission, Pakistan Subbotnitskiy, D. International Atomic Energy Agency
Suparman. National Nuclear Energy Agency, Indonesia Tomsic, Z. University of Zagreb, Croatia
van Heek, A. International Atomic Energy Agency Warren, P. International Atomic Energy Agency
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