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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
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 OSTI2020

Model of Operation-and-Maintenance Costs for Photovoltaic Systems

This article presents a method for calculating costs associated with operation and maintenance (O&M) of photovoltaic (PV) systems. It compiles details regarding the cost and frequency of multiple O&M services to estimate annual O&M costs ($\$$/year) for each year of an analysis period, the net present value ($\$$) of life cycle costs accumulated over the analysis period, and the reserve account amount ($\$$). Here we show that this method is an improvement over the previous averaged or levelized per-unit ($\$$/kW/year) valuations for estimating PV O&M costs, because it allows a detailed selection of services to perform based on system size, market served (e.g., residential, commercial, or utility), type and configuration of system components (e.g., micro-, string or central inverter) and site and environmental conditions (e.g., snow, pollen, bird populations). This model also distinguishes costs that vary from year to year and increase at different rates over time because of heuristic failure distributions (e.g. Weibull or Lognormal distribution) based on actuarial data for many of the services. This cost model was created by the PV O&M Working Group of researchers and industry, sponsored by DOE Solar Energy Technologies Office, and has been published in an on-line version hosted by SunSpec Alliance at apsuite.sunspec.org. A spreadsheet version is included with this paper as supplementary material.

14 SOLAR ENERGY↗
NASA NTRS1980

Operation and maintenance cost data for residential photovoltaic modules/panels

Costs associated with the operation and maintenance of residential photovoltaic modules and arrays are studied. Six basic topics related to operation and maintenance to photovoltaic arrays are investigated: maintenance; cleaning; panel replacement; gasket repair/replacement; wiring repair/replacement; and termination repair/replacement. The effects of the mounting types (rack mount, stand off mount, direct mount and integral mount) and the installation/replacement type (sequential, partial interruption and independent) are identified and described. Methods of reducing maintenance costs are suggested.

Oster, J. R., Jr.↗
DOE OSTI2025

Build-to-Replace Strategy to Reduce Operations and Maintenance Costs for Advanced Reactors

This paper targets the reduction of fixed operations and maintenance (O&M) costs for advanced reactor (AR) designs. This goal will be severely constrained if the underlying assumptions of O&M approaches and practices are not questioned and reexamined, especially today when changes can be implemented effectively and efficiently. Achieving a reduction in AR O&M costs requires a completely new way of thinking -a paradigm shift- not through incremental, technology-focused approaches alone. Here, we address this challenge by evaluating the impact of moving to a shorter design life for major structures, systems, and components and shorter, more predictable refurbishment cycles as modeled by the commercial airline industry: the build-to-replace approach. This paper provides a brief overview of this different mindset to O&M applied to ARs and it provided a set of analytical tools based on multi-objective optimization to identify the benefits of such an approach. In conclusion, we provide a direct example analysis of a build-to-replace scenario by identifying and evaluating scenarios for reduced system and component lifetimes and associated replacement and refurbishment schedules to evaluate impacts on O&M costs and other lifecycle elements, such as structure, system, and component reliability.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Operations, maintenance, and cost considerations for PV+Storage in the United States

Battery storage systems are increasingly being installed at photovoltaic (PV) sites to address supply-demand balancing needs. Although there is some understanding of costs associated with PV operations and maintenance (O&M), costs associated with emerging technologies such as PV plus storage lack details about the specific systems and/or activities that contribute to the cost values. This study aims to address this gap by exploring the specific factors and drivers contributing to utility-scale PV plus storage systems (UPVS) O&M activities costs, including how technology selection, data collection, and related and ongoing challenges. Specifically, we used semi-structured interviews and questionnaires to collect information and insights from utility-scale owners and operators. Data was collected from 14 semi-structured interviews and questionnaires representing 51.1 MW with 64.1 MWh of installed battery storage capacity within the United States (U.S.). Differences in degradation rate, expected life cycle, and capital costs are observed across different storage technologies. Most O&M activities at UPVS related to correcting under-performance. Fires and venting issues are leading safety concerns, and owner operators have installed additional systems to mitigate these issues. There are ongoing O&M challenges due the lack of storage-specific performance metrics as well as poor vendor reliability and parts availability. Insights from this work will improve our understanding of O&M consideration at PV plus storage sites.

14 SOLAR ENERGY↗
NASA NTRS1973

Methanator Fueled Engines for Pollution Control

A methanator fueled Otto-cycle engine is compared with other methods proposed to control pollution due to automobile exhaust emissions. The comparison is made with respect to state of development, emission factors, capital cost, operational and maintenance costs, performance, operational limitations, and impact on the automotive industries. The methanator fueled Otto-cycle engine is projected to meet 1975 emission standards and operate at a lower relative total cost compared to the catalytic muffler system and to have low impact. Additional study is required for system development.

Cagliostro, D. E.↗
NASA NTRS1977

Maintenance and operations cost model for DSN subsystems

A procedure is described which partitions the recurring costs of the Deep Space Network (DSN) over the individual DSN subsystems. The procedure results in a table showing the maintenance, operations, sustaining engineering and supportive costs for each subsystems.

Burt, R. W.↗
DOE OSTI2025

Microreactor Optimization Using Simulation And Economics (mouse)

Microreactor Optimization Using Simulation and Economics (MOUSE) is a tool that integrates both nuclear microreactor design and reactor economics to provide comprehensive evaluations and optimizations. This tool enables stakeholders to explore the interplay between technical and economic variables, guiding them towards effective and competitive microreactor solutions. For the reactor core simulations, MOUSE leverages the OpenMC Monte Carlo Particle Transport Code to perform detailed core simulations for various microreactor designs. The included OpenMC models are 2D core designs of a Liquid Metal Thermal Microreactor (LMTR), a Gas-Cooled TRISO-Fueled Microreactor (GCMR), and a Heat Pipe Microreactor. Beyond core design, MOUSE includes simplified calculations for: - Calculating the masses of heat exchangers within the system. - Mechanical power of pumps. - Estimating the area occupied by various buildings within the nuclear plant. For the economic analysis, MOUSE provides detailed bottom-up cost estimates, encompassing a wide range of costs including preconstruction costs, direct costs, indirect costs, training costs, financial costs, operation & maintenance (O&M) costs, and fuel costs. These cost estimations are developed using data from the MARVEL project and additional literature sources, enabling the calculation of total capital costs and levelized cost of energy for both first-of-a-kind and nth-of-a-kind microreactors. MOUSE also enables analysis of the cost drivers and competitiveness in the electricity market. MOUSE allows users to modify a wide array of technical and economic parameters to evaluate different scenarios and their impacts. Examples of these parameters include: Fuels, coolants, or reflector materials Enrichment levels Control drum materials and geometry Fuel pin geometry and materials Moderator pin geometry and materials Reactor core and reflector dimensions Packing factor for the TRISO particles Nuclear reactor power and reactor burnup Number of sensors Shielding thickness Reactor vessel and guard vessel dimensions Operational staff requirements Number of emergency shutdowns Levelization period Interest rate Construction duration Since MOUSE is powered by the WATTS toolkit, it supports optimization studies, parametric analyses, and uncertainty calculations/propagation. The optimization techniques enable users to identify optimal design and economic configurations. The parametric analysis tools allow users to explore the sensitivity of various parameters, while uncertainty propagation helps quantify the impact of uncertainties on overall performance and cost. User Interface and Workflow: Currently, MOUSE is a command-line-based tool. Users can input various reactor design or economic parameters, modify the designs, run simulations, and visualize results through comprehensive data visualization and reporting capabilities. The typical workflow involves setting up the reactor model, defining economic parameters, running simulations, and analyzing the results to make informed decisions. By combining advanced design calculations with detailed economic modeling, MOUSE provides a robust framework for optimizing nuclear microreactor technologies, enhancing their competitiveness, and guiding stakeholders towards innovative and cost-effective solutions.

Hanna, Botros [Idaho National Laboratory (INL), Id↗
DOE OSTI2021

Big Data For Operation and Maintenance Cost Reduction

The purpose of this research is to develop a first-of-a-kind framework for integrating Big Data capability into the daily activities of our current fleet of nuclear power plants. Big Data is traditionally defined as data sets with high volume, velocity, and heterogeneity, and the existing Big Data analytics capabilities are now widely popular in fields such as finance, weather, e-commerce, healthcare and sports. In the nuclear industry, while the volume and velocity of data may present computational challenges for existing analytics capabilities, data heterogeneity are seen to present the major challenge. This research project mainly focuses on incorporating the wide range of data heterogeneities in nuclear power plants into an integrated Big Data Analytics capability. The primary end-product of this project is a Big Data framework that is capable of dealing with the large volume and heterogeneity of the data found in nuclear power plants to extract timely and valuable information on equipment performance. The framework can generate system insights that are actionable relations between measurable impacts and the corresponding maintenance action plans and enable optimization of plant operation and maintenance based on the extracted information. The developed framework is capable of handling heterogeneous data including both image data and time-series sensor data. Specifically, this developed framework includes the following components. The first component is an overarching maintenance ontology which includes system insights required by maintenance optimization. The maintenance ontology interacts with other components in the developed framework. The second component handles Piping & Instrumentation Diagram (P&ID) data. It can be used to extract system components and their relations automatically from the P&IDs. This extracted information is stored in the first component, i.e., maintenance ontology, and is also used as input to the third component, i.e., a tool for generating the fault tree for the corresponding system. The generated fault tree in turn is stored in the ontology for assessing risk that is used as a criterion in maintenance policy optimization. The fourth component is a tool for inferring the parameters in the Markov degradation model for a nuclear system. It uses basic information from the ontology. The fifth component is a tool for assessing the degradation level using sensor measurement data, for example, pressure, flowrate. This tool can be used for determining corrective maintenance actions. The results obtained from components four and five are returned to the ontology. The sixth component of the framework is a tool for optimizing the maintenance policy for a nuclear system of interest. It takes certain basic information from the ontology, e.g., costs of maintenance actions and system failures, as input, and returns the optimal maintenance policy to the ontology. This tool can be used for determining predictive maintenance actions. A set of experiments have also been conducted to verify the algorithms developed in this project for nuclear system degradation monitoring. The experiments are based on four solenoid valves, similar to the ones used in nuclear power plants. The analyses based on the experimental data using two algorithms, i.e., the Randomized Window Decomposition (RWD) algorithm and the particle filtering algorithm, and the results are introduced in the report. The Big Data framework developed in this project can be used as a support tool in daily activities of plant operation and maintenance and will reduce current costs while maintaining or improving safety levels. Overall, the project will not only benefit existing reactors, however it will open new frontiers to realize the long overdue value of Big Data Analytics in the nuclear sphere.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1977

A maintenance and operations cost model for DSN

A cost model for the DSN is developed which is useful in analyzing the 10-year Life Cycle Cost of the Bent Pipe Project. The philosophy behind the development and the use made of a computer data base are detailed; the applicability of this model to other projects is discussed.

Burt, R. W.↗
NASA NTRS1981

Advanced solar concentrator mass production, operation, and maintenance cost assessment

The object of this assessment was to estimate the costs of the preliminary design at: production rates of 100 to 1,000,000 concentrators per year; concentrators per aperture diameters of 5, 10, 11, and 15 meters; and various receiver/power conversion package weights. The design of the cellular glass substrate Advanced Solar Concentrator is presented. The concentrator is an 11 meter diameter, two axis tracking, parabolic dish solar concentrator. The reflective surface of this design consists of inner and outer groups of mirror glass/cellular glass gores.

Niemeyer, W. A.↗
DOE OSTI2021

WOMBAT (Windfarm Operations and Maintenance cost-Benefit Analysis Tool) WISDEM® [SWR-21-68]

The windfarm operations and maintenance cost-benefit analysis tool (WOMBAT) is software to simulate the operations and maintenance phase of either onshore or offshore windfarms. WOMBAT is a medium-fidelity tool that is designed to model turbine, cable, and substation failures at the subassembly level, but is flexible enough that individual component or asset-level modeling can also be performed. WOMBAT enables users to model technological improvements, the use of a wide range of service equipment from drone repairs and remote resets to heavy lift vessels and crawler cranes, to analyze cost trends with varying trade-offs in conjunction with energy production, availability and a growing range of metrics. This library provides a tool to simulate the operation and maintenance phase (O&M) of distributed, land-based, and offshore windfarms using a discrete event simulation framework. WOMBAT is written around the SimPy discrete event simulation framework. Additionally, this is supported using a flexible and modular object-oriented code base, which enables the modeling of arbitrarily large (or small) windfarms with as many or as few failure and maintenance tasks that can be encoded. Please note that this is still heavily under development, so you may find some functionality to be incomplete at the current moment, but rest assured the functionality is expanding. With that said, it would be greatly appreciated for issues or PRs to be submitted for any improvements at all, from fixing typos (guaranteed to be a few) to features to testing. Also available at: https://pypi.org/project/wombat/

Cooperman, Aubryn↗
DOE OSTI2022

Windfarm Operations and Maintenance cost-Benefit Analysis Tool (WOMBAT)

This report provides technical documentation and background on the newly-developed Wind Operations and Maintenance cost-Benefit Analysis Tool (WOMBAT) software. WOMBAT is an open-source model that can be used to obtain cost estimates for operations and maintenance of land-based or offshore wind power plants. The software was designed to be flexible and modular to allow for implementation of new strategies and technological innovations for wind plant maintenance. WOMBAT uses a process-based simulation approach to model day-to-day operations, repairs, and weather conditions. High-level outputs from WOMBAT, including time-based availability and annual operating costs, are found to agree with published results from other models.

17 WIND ENERGY↗
NASA NTRS1977

Maintenance cost study of rotary wing aircraft

The feasibility was studied of predicting rotary wing operation maintenance costs by using several aircraft design factors for the aircraft dynamic systems. The dynamic systems considered were engines, drives and transmissions, rotors, and flight controls. Multiple regression analysis was used to correlate aircraft design and operational factors with manhours per flight hour, and equations for each dynamic system were developed. Results of labor predictions using the equations compare favorably with actual values.

Source record↗
DOE OSTI2022

Powertrain Performance and Total Cost of Ownership Analysis for Class 8 Yard Tractors and Refuse Trucks

Advanced powertrain technologies, specifically fuel cell electric powertrains, have gained attention as viable alternatives for medium- and heavy-duty (M/HD) vehicles. However, it is unclear how these alternative powertrain vehicles stack up against their diesel counterparts in terms of performance and total cost of ownership (TCO). Furthermore, there are vehicle segments within the M/HD sector that have remained unstudied for fuel cell electric applications. This analysis aims to provide a comparative scoping-level TCO and performance analysis for two heavy-duty vocation vehicles (Class 8 U.S. port-side yard tractor and Class 8 U.S.-based refuse truck) for both conventional diesel and heavy-duty fuel cell electric (HDFC) powertrains. The refuse truck analysis also considered compressed natural gas powertrains (CNG) for comparison. The analysis includes seven timeframes (2020, 2025, 2030, 2035, 2040, 2045, and 2050) for comparison. This simplified TCO analysis includes only direct costs (fuel price, glider purchase price, and operating & maintenance costs) and excludes any associated indirect cost (e.g., dwell time costs and other opportunity based costs). Representative drive cycles for each vehicle were based on on-board GPS logged data and chosen by the analysis team to represent average, non-extreme driving conditions. At the time the analysis was performed, the Inflation Reduction Act was not in effect and therefore any potential subsidies and future cost reductions enacted under the Inflation Reduction Act were not included. Based on the operational setpoints used in this analysis, HDFC powertrains for both yard tractors and refuse trucks have the potential to achieve TCO advantages over conventional diesel powertrains (and CNG for refuse truck applications) in the near- to mid-term future while meeting the necessary duty cycle performance requirements. Yard tractors and refuse trucks spend a significant amount of time operating at low speeds, with long durations of idling, and experience numerous start/stop occurrences. These operational characteristics favor fuel cell performance as fuel cells operate with higher efficiencies at lower percentages of total power output. Conversely, conventional diesel and CNG engines are most efficient at higher percentages of total power output. This helps HDFC powered yard tractors and refuse trucks realize improved fuel economy when compared to their diesel counterparts, which helps reduce total fuel costs and therefore, total TCO. The analysis demonstrates that fuel prices play a significant role in determining TCO for each vehicle and should remain an R&D focus area. Overall, under the analysis' specified conditions, HDFC yard tractors have the potential to achieve cost parity with diesel yard tractors as early as 2025. For refuse trucks, HDFC refuse trucks have the potential to achieve cost parity with diesel and CNG refuse trucks in 2030 and 2040, respectively.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Optimizing an Integrated Renewable-Electrolysis System

Hydrogen is a versatile energy carrier that is used in a wide variety of chemical and industrial processes. Producing hydrogen using electrolysis can enable integration of multiple sectors including electricity, heating, and industrial sectors; however, the cost of producing hydrogen from electrolysis remains a challenge for encouraging greater adoption. With growing amounts of renewable generation on the California grid, there is downward pressure on wholesale electricity prices, particularly during the afternoon from photovoltaics (PV). These lower, or even potentially negative prices, challenge the business cases for new and existing PV plants. In addition, as the grid transitions to less flexible generation, there is greater need for system flexibility. To help improve the economics for both solar PV and hydrogen production using electrolyzers, we explore the benefit of combining PV and electrolysis systems. The optimal breakeven hydrogen production cost for six unique market participation configurations is calculated at six candidate locations where PV is already installed. The six market configurations include islanded, separated, retail, net energy metering (NEM), hybrid retail/wholesale and wholesale. Using the Revenue Operation and Device Optimization Model (RODeO) model, the optimal breakeven hydrogen price over the lifetime of the equipment is calculated. The cost includes production, storage, and compression in preparation for gaseous delivery trucks. Revenue streams include the sale of hydrogen, low carbon fuel standard (LCFS) credits, renewable electricity sold to the grid, and Renewable Energy Credits (REC). The costs included are the electricity costs, capital and fixed operation and maintenance cost (FOM) for the electrolyzer, PV, and storage and compression systems as well as taxes and financing costs. In addition, cost reductions are achieved through retail and wholesale rate optimization, by which electricity is purchased at the lowest price and sold, if possible, at the highest price. For all locations, the breakeven hydrogen production cost results show that, in the order of decreasing cost, the system configurations are islanded (highest), separated, NEM, retail, hybrid retail/wholesale, and wholesale (lowest). The resulting system design balances between the capital and maintenance cost components, the operation costs (i.e., electricity costs) and the additional market revenues. The integration of solar PV and electrolysis is shown to provide a mutually beneficial relationship. For PV, integration with electrolysis offers the potential to hedge against wholesale market price volatility, and integration with electrolysis may offer the potential to defer or avoid transmission investment to deliver power to the point-of-use and instead use it on-site. When compared with SMR without considering any renewable hydrogen premiums, this study finds that PV + Electrolysis systems with current costs are likely not competitive; however, with cost reductions for electrolysis equipment consistent with DOE projections, it was found that systems with wholesale market access would be competitive, largely on account of both low capital costs and low-cost electricity. The electrolysis units can provide greater flexibility than is required based on retail rate optimization, so there is an opportunity for a utility or CAISO to increase system flexibility with PV + Electrolysis systems in return for commensurate compensation. In this way, there are potentially several solutions that fall between the hybrid configuration and the wholesale configuration that could provide sufficient compensation for a PV + Electrolysis unit to compete with SMR while also providing greater flexibility to the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗