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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Cost Estimates for NPP Decommissioning Projects and Insights from Cost Analysis - 18118

The technical ability to decommission NPPs shut down after normal operation has been well demonstrated. However, concerns remain about the ability to accurately calculate and demonstrate the validity of decommissioning cost estimates, and to control costs during decommissioning. This paper describes recent international guidance on quality cost estimates for nuclear decommissioning projects and explores the potential added value that could be attained through more systematic analysis and reporting of decommissioning project costs. The OECD Nuclear Energy Agency (NEA) and the International Atomic Energy Agency (IAEA) have long been concerned about the need to promote greater transparency in decommissioning costing and have collaborated in a number of initiatives in pursuit of this objective. Together with the European Commission, they published 'The International Structure for Decommissioning Costing (ISDC)' in 2012. The ISDC provides a useful common reporting format for decommissioning costing. The NEA has also published guidance on the international peer reviews of decommissioning cost studies (2014) and on the practice of decommissioning cost estimation (2015). In September 2017, the NEA and IAEA published detailed guidance on addressing uncertainties in decommissioning cost estimates (the 'Addressing Uncertainties' report). This joint report sets out an approach to treating uncertainties reflecting current good practices in cost estimating. Specifically, it describes how uncertainties in decommissioning cost estimation can be addressed using standardized methods of estimating uncertainty and risk analysis. Its recommendations aim at enabling a consistent and comprehensive treatment of risk and uncertainty in the preparation of decommissioning cost estimates. Together these publications establish a good basis for producing comprehensive and high-quality cost estimates for nuclear decommissioning projects and for enhancing confidence in the estimates through improving transparency concerning the underpinning data and calculations, and more explicit representation of the uncertainties that may impact on project costs. There is increasing attention on understanding variations between cost estimates and apparent escalation of decommissioning costs. This arises both from the need to assure the adequacy of financing arrangements for future decommissioning projects and the ambition to improve the performance and ensure value-for-money in the delivery of decommissioning projects and services. A systematic analysis of actual decommissioning project costs in relation to the cost estimates would be expected to yield valuable insights about key cost drivers in actual decommissioning projects, and the extent to which current cost estimates accurately capture and reflect these. Aligning the reporting of decommissioning project costs with the underpinning cost estimates for the projects would also facilitate the identification of causes of major deviations between projected and actual costs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

EVI-LOCATE: One Stop Solution for Estimating Cost of Installing EV Charging Stations

EVI-LOCATE (Electric Vehicle Infrastructure-Locally Optimized Cost Assessment Tool and Estimator) is a site assessment tool to estimate costs to install EV charging stations. EVI-LOCATE enables users to generate site-specific, user-specific, and location-specific EV charging station installation designs and cost estimates. The tool integrates National Electrical Code, deep-learning pixel classification algorithm, and component-level costs to estimate the costs.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2015

IDC reengineering Phase 2 & 3 US industry standard cost estimate summary

Sandia National Laboratories has prepared a ROM cost estimate for budgetary planning for the IDC Reengineering Phase 2 & 3 effort, using a commercial software cost estimation tool calibrated to US industry performance parameters. This is not a cost estimate for Sandia to perform the project. This report provides the ROM cost estimate and describes the methodology, assumptions, and cost model details used to create the ROM cost estimate. ROM Cost Estimate Disclaimer Contained herein is a Rough Order of Magnitude (ROM) cost estimate that has been provided to enable initial planning for this proposed project. This ROM cost estimate is submitted to facilitate informal discussions in relation to this project and is NOT intended to commit Sandia National Laboratories (Sandia) or its resources. Furthermore, as a Federally Funded Research and Development Center (FFRDC), Sandia must be compliant with the Anti-Deficiency Act and operate on a full-cost recovery basis. Therefore, while Sandia, in conjunction with the Sponsor, will use best judgment to execute work and to address the highest risks and most important issues in order to effectively manage within cost constraints, this ROM estimate and any subsequent approved cost estimates are on a 'full-cost recovery' basis. Thus, work can neither commence nor continue unless adequate funding has been accepted and certified by DOE.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

IDC Reengineering Phase 2 & 3 Rough Order of Magnitude (ROM) Cost Estimate Summary (Leveraged NDC Case).

Sandia National Laboratories has prepared a ROM cost estimate for budgetary planning for the IDC Reengineering Phase 2 & 3 effort, based on leveraging a fully funded, Sandia executed NDC Modernization project. This report provides the ROM cost estimate and describes the methodology, assumptions, and cost model details used to create the ROM cost estimate. ROM Cost Estimate Disclaimer Contained herein is a Rough Order of Magnitude (ROM) cost estimate that has been provided to enable initial planning for this proposed project. This ROM cost estimate is submitted to facilitate informal discussions in relation to this project and is NOT intended to commit Sandia National Laboratories (Sandia) or its resources. Furthermore, as a Federally Funded Research and Development Center (FFRDC), Sandia must be compliant with the Anti-Deficiency Act and operate on a full-cost recovery basis. Therefore, while Sandia, in conjunction with the Sponsor, will use best judgment to execute work and to address the highest risks and most important issues in order to effectively manage within cost constraints, this ROM estimate and any subsequent approved cost estimates are on a 'full-cost recovery' basis. Thus, work can neither commence nor continue unless adequate funding has been accepted and certified by DOE.

Harris, James M.↗
DOE OSTI2022

The development of natural gas and hydrogen pipeline capital cost estimating equations

Natural gas pipeline cost data collected by the Oil and Gas Journal (O&GJ) for interstate pipelines constructed from 1980 through 2017 were used to develop capital cost estimating equations that are a function of pipeline diameter, length, and U.S. region. Equations were developed for material, labor, miscellaneous, and right-of-way costs, the four cost components in the O&GJ data, for six different regions of the United States (U.S.). Each equation is a function of pipeline diameter and length. Adjustment mechanisms were then developed for converting the natural gas pipeline equations into equations for estimating the costs of hydrogen pipelines. These adjustments were based in part on an analysis completed by the National Institute for Standards and Technology (NIST). Here the results of this work were used to update cost models in the Hydrogen Delivery Scenario Analysis Model (HDSAM), developed by Argonne National Laboratory for the U.S. Department of Energy’s Hydrogen Program. Our analysis shows a wide range of pipeline cost across different U.S. regions, especially with respect to labor and right-of-way costs. The developed cost formulas for hydrogen pipelines are both important and timely as hydrogen is being considered as a zero-carbon energy carrier with the potential to decarbonize all energy sectors, and the cost of hydrogen transportation is essential for techno-economic analysis of its potential use in these sectors.

03 NATURAL GAS↗
DOE OSTI2014

IDC Reengineering Phase 2 & 3 Cost Estimate Summary (Version 1.0.1)

Sandia National Laboratories has prepared a cost estimate budgetary planning for the IDC Reengineering Phase 2 & 3 effort. This report provides the cost estimate and describes the methodology, assumptions, and cost model details used to create the cost estimate.

42 ENGINEERING↗
DOE OSTI2019

CatCost™ (Catalyst Cost Estimation Tool) [SWR-18-74]

CatCost™ is a state-of-the-art cost estimation tool designed to reduce the cost uncertainty associated with pre-commercial catalyst materials. The tool combines industry-standard cost estimation methods and resources into an intuitive suite of tools to bring actionable cost insight to every step of catalyst research and development. CatCost™ allows the rapid development of comprehensive catalyst cost estimates. It incorporates detailed insight into manufacturing methods, especially for pre-commercial catalysts, without requiring any process design experience. The tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation. The tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation. Features include: Raw materials pricing: Libraries of common chemicals, cost scaling indices, guidance for obtaining bulk quotes, and methods for extrapolating laboratory-scale prices to bulk. Simplified step method for synthesis by a contract manufacturer: All-in hourly cost for process equipment using methods and data from tollers. (Excel-only in v1.0)

Baddour, Frederick↗
DOE OSTI2025

A Bottom-Up Cost Estimation Tool for Nuclear Microreactors

The rising interest in nuclear microreactors has highlighted the need for comprehensive technoeconomic assessments. However, the scarcity of publicly available designs and cost data has posed significant challenges. To address this issue, the Microreactor Optimization Using Simulation and Economics (MOUSE) tool is developed. MOUSE is a tool that integrates nuclear microreactor design with reactor economics. The design calculations encompass core simulations using the OpenMC Monte Carlo Particle Transport Code [romano2015], along with simplified balance of plant calculations. On the economic side, MOUSE provides detailed bottom-up cost estimates, calculating both the total capital cost and the levelized cost of energy for first-of-a-kind and nth-of-a-kind microreactors. The cost estimation correlations are developed using data from the MARVEL project and additional literature sources. MOUSE has released as an open-source tool on GitHub (MOUSE Tool). By combining design calculations with cost equations, MOUSE enables users to evaluate the impact of various technological consideration, advanced moderators, design changes, material/fuel changes, and geometry modifications—as well as economic parameters like interest rates and construction duration. This comprehensive framework can guide stakeholders towards technological solutions that enhance microreactor competitiveness. Additionally, powered by the WATTS toolkit [romano2022], MOUSE supports optimization studies, parametric analyses, and uncertainty calculations/propagation. Currently, preconceptual designs of three microreactor types are included in MOUSE: a liquid metal thermal microreactor (LTMR), gas cooled TRISO-fueled microreactor (GCMR) and heat-pipe TRISO fueled microreactor (HPMR). To showcase its ability, MOUSE was used to conduct detailed bottom-up cost estimates for the first of a kind (FOAK) and Nth of a kind (NOAK) of the following microreactors • A 20MWt LTMR that is built on the ongoing MARVEL demonstration at Idaho National Laboratory (INL) • A 15 MWt GCMR that was designed to be more representative of the typical commercial microreactor • A 7 MWt HPMR that was built on previous work (Choi 2024) The The reader should note that these three designs and corresponding cost estimates are examples to demonstrate the MOUSE capability. The designs are pre-conceptual, the reactor designs were not optimized, and the cost estimates were developed with incomplete information. Additionally, stakeholders might be interested in a variety of designs that may differ from the examples provided in this report. The MOUSE tool can also be used to study how design choices affect economics. To demonstrate its capability, MOUSE was used conduct parametric studies such as examining the economic impact of the reflector's material and thickness, the moderator's booster material and dimensions, fuel composition and enrichment, core size, and power level. Several insights were gained from these parametric studies.

Hanna, Botros↗
DOE OSTI2020

A nonparametric approach to modeling dependence among production parameters for energy cost estimation

Dependence existing among production parameters can significantly affect energy costs. For material removal processes, processing times and material amounts to be cut have positive dependence, and the dependence can affect energy costs by varying a peak electricity load. Existing methods to model the dependence of production parameters are based on parametric approaches that cannot accurately represent the dependence due to the rigid nature of parametric models. To address this issue, this study proposes a method to quantify dependence among manufacturing parameters through the application of the empirical copula to the dependence between the milling processing time and the amount of volume to be cut. The proposed method is illustrated by a case study of a manufacturing facility consisting of milling machines; a total of 27 scenarios are simulated for energy cost estimations. The case study clearly shows that the proposed method can capture the dependence between the milling parameters more accurately than a conventional dependence measure from parametric correlation models. Furthermore, the findings from this study would be useful to estimate energy costs in that the proposed method provides a better fit to real production data than conventional parametric approaches can.

42 ENGINEERING↗
DOE OSTI2017

IDC Re-Engineering Phase 3 Budgetary Cost Estimate Summary (Leveraged NDC Case)

Sandia National Laboratories has prepared a budgetary cost estimate for planning for the IDC Re-engineering Phase 3 effort, based on leveraging a fully funded, Sandia executed NDC Modernization project. This report provides the budgetary cost estimate and describes the methodology, assumptions, and cost model details used to create the budgetary cost estimate.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Pumped Storage Hydropower Operation & Maintenance Cost Estimation

The National Laboratory of the Rockies (NLR) develops and hosts a pumped storage hydropower (PSH) cost model that is the most detailed bottom-up PSH cost model available to the public. It is available both as a spreadsheet and an interactive web tool, enabling users with a variety of PSH interests to transparently characterize costs of alternative PSH sites and designs. The NLR PSH cost model was designed originally to consider only upfront capital costs only. This slide deck describes methodology to expand the cost model to include operations and maintenance (OM) costs. OM costs are characterized as five distinct components with unique sources and methods for cost estimation. By combining methods for each of these components into a cumulative OM cost estimate, these methods allow a more complete estimation of total OM costs that agrees with existing literature values. The methods are scalable and transparent, allowing them to be readily to applied to any prospective PSH facility for a representative preliminary OM cost estimate in advance of detailed site-specific engineering and other studies.

13 HYDRO ENERGY↗
DOE OSTI2023

First-Principles Cost Estimation of a Sodium Fast Reactor Nuclear Plant

A multi-tiered cost analysis is performed to estimate full costs of a nuclear power plant (NPP) based on sodium-cooled fast reactor (SFR) technology. To address the lack of fully transparent cost estimations from past undertakings for NPPs, we have developed a detailed and first-principles-based cost estimate for a generalized SFR NPP. Our intent is to achieve a high degree of transparency with our cost assumptions and develop a cost model that is flexible and easily extendable to variations in NPP design and other nuclear reactor types. Furthermore, we strive to achieve a clear organization of costs and complete identification of key cost drivers based on first principles. To this end, the cost results of our analysis as given in Table 24 and Table 25 are organized and categorized into a code of accounts (COA) under development at Idaho National Laboratory (INL). Varying degrees of first-principles methods are employed, such as design for manufacture and assembly® (DFMA® ), to elucidate costs in all process levels of the plant equipment, buildings and site structures, personnel, and other miscellaneous but significant cost elements. These approaches have been successfully applied in past cost analysis projects and are designed to enable rapid and flexible cost estimation. Application of these techniques for evaluating NPP costs is similar in concept to the full, detailed estimation of construction and fabrication costs determined in a later stage of NPP development. Note that our approach tries to avoid use of other past analysis results and data such as those from the legacy Energy Economic Data Base (EEDB) Program, as these resources are based on historical NPP costs and thus may not be indicative of new reactor technologies or construction and fabrication/manufacturing techniques. However, we provide a comparison of our SFR NPP cost results in Table 90 against those included in the EEDB for a representative pressurized water reactor (PWR).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Developing Decommissioning Cost Estimating Relationships and the Decommissioning Estimate Analysis Library Estimating System - 20423

DOE-EM's Consolidated Business Center (EM-CBC) Office of Cost Estimating has developed a system of Decommissioning Cost Estimating Relationships (CERs) and Models to improve the reliability and efficiency of its estimates. The development builds on the multi-year process of collecting and organizing historical cost data from DOEEMs decommissioning projects and estimate model development to support project and program-level decommissioning estimates. The latest work has extended these models down to project scope element and component building area levels, allowing the actual costs of work for these estimate components to be assembled into estimates that reflect specific projects. The CERs have been incorporated into two estimator-friendly products - as cost libraries in the MII estimating program and as an MS Excel-based model, and are available for DOE federal staff use. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Cost Estimates of Roll-to-Roll Production of Organic Light Emitting Devices for Lighting

White organic light emitting devices (WOLEDs) offerdistinct advantages as solid state lighting sources, including high energy efficiency, superior color quality,and a flexible, thin profile that can accommodate a vast array of possible fixture designs. Recent advances in device lifetime and high speed deposition suggest that mass production of WOLED panels is approaching an inflection point. To understand the tradeoffs in the volume manufacturing of WOLED lighting panels, in this work, we estimate the cost of white WOLED panel production based on vacuum and vapor phase deposition in a roll-to-roll production line envisioned to yield an annual capacity of at least 6 × 10 6 m 2 . Assuming a WOLED operating luminance at 10 klm/m 2 , we anticipate a $\$12.5$ /klm cost of a WOLED light engine that includes the cost of the current driverand packaging. With incremental reduction in material and driver costs and improved luminance, the costof WOLED lighting can be reduced to $\$6.3$ /klm in thenear term, potentially positioning WOLEDs for use innumerous premium lighting applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Cost Estimation of a Permanent Magnet Synchronous Machine for Use in Adjustable Speed-Pumped Storage Hydropower

Electric machine design has become an easier process with the availability of computers in recent decades. However, the interest in electric machine design among students has declined. University-level design courses must compete with courses perceived as more desirable by the potential job market. Hence, the power system engineers with this expertise are very few and are nearing retirement. Contrarily, renewable energy has been picking up in the past few decades. The indeterminacy and variation of renewable energy sources require a balancing mechanism to maintain the constant voltage and frequency of the grid. Adjustable-Speed Pumped-Storage Hydropower plants are considered the contender for future energy storage, providing large capacity and fast-acting response. Large-scale hydropower applications depend on the natural characteristics of each project site, making less expensive, off-the-shelf generators unfeasible. This work gives a shortcut to estimate the cost of constructing a permanent magnet generator for low-volume manufacturing.

13 HYDRO ENERGY↗
DOE OSTI2016

Decommissioning Cost Estimate Uncertainty: What is It, How Do You Deal with It? - 16527

The issue of decommissioning cost estimate uncertainty has returned to plague the industry. As we gain more hands-on experience, the expectations are that the cost estimates for future projects should be more accurate and the uncertainties reduced. To some extent this is true, but there remains the issue of how to deal with the major elements of uncertainty of allowances, contingency and risk. The OECD/NEA and the IAEA have joined forces through its member states and outside consultants to bring definition and insight into how to deal with uncertainty. The author has been a participant in this joint organization effort since the outset two years ago. This paper will present the current state-of-the-art in the definitions, approaches, and limitations in the topic of uncertainty. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗