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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗
DOE OSTI2023

Modelling the Liquid Waste Operation at the Savannah River Site

Modeling Successes Dounreay – Site Closure Optimization and Risk Reduction Re-structuring and streamlining a complex project plan to achieve site decommissioning in reduced time and at reduced cost, through automated task prioritization. Idaho AMWTP – Multi-stream Optimization Speeding up a complex facility with many process lines, by utilizing all of the process lines more efficiently and reducing overall plant downtime, by coordinating repairs and shutdowns. AWE –Waste Repackaging and Relocation Relocating schedule for waste material from an old storage facility to a new purpose-built one, safely, and in a timely fashion that removed the need to reassure the safety of the old facility. Sellafield – Effluent, Sludge and HAW Treatment Improving a wide range of chemical engineered processes including aqueous effluent treatment, chemically-reactive sludge management and waste vitrification processing. Strategic Petroleum Reserve – Cavern Management Linking chemistry models of petroleum prediction, through engineering cavern management to financial modeling of gasoline sales to benefit US government

Jung, Andrew W.↗
DOE OSTI2021

WISDEM® v3.4.1(Wind Plant Integrated System Design and Engineering Model) [SWR-14-05]

The Wind Plant Integrated System Design and Engineering Model (WISDEM®) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM® is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM® turbine design capability. Please install all of the pre-requisites prior to installing WISDEM® by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM® development, please visit the official NREL systems engineering for wind energy website. https://www.nlr.gov/wind/systems-engineering

Dykes, Katherine↗
DOE OSTI2024

WISDEM® v3.15.2 2024 (Wind-Plant Integrated System Design and Engineering Model) [SWR-14-05]

The Wind-Plant Integrated System Design and Engineering Model (WISDEM®) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM® is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM® turbine design capability. Please install all of the pre-requisites prior to installing WISDEM® by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM® development, please visit the official NREL systems engineering for wind energy website. https://www.nrel.gov/wind/systems-engineering.html

Dykes, Katherine↗
DOE OSTI2025

SAM Linear Fresnel Model, Project B (CRADA Final Report)

Objective performance and economic modeling of solar thermal plants is of keen interest to many EPRI funders. One solar thermal technology that is not currently available to model in any non-vendor, non-proprietary tool is linear Fresnel. This technology has garnered enough interest from EPRI funders to merit investing in a tool to objectively model its performance. Early in 2010, EPRI performed a comparison of modeling solar thermal power plants using the IPSEPRO, CNRS and Solar Advisor (SAM) tools. After completing this effort, EPRI decided to adopt NREL’s Solar Advisor Model as its default modeling tool based in part on user friendliness, flexibility, number of technologies covered, integrated financial model and ease of running sensitivities. Furthermore, it was recognized that NREL continues to invest considerable time and resources into improving capabilities and functionality of the model.

14 SOLAR ENERGY↗
DOE OSTI2023

LH CO 2 MENT Colorado Project (Final Report)

The objective of Electricore’s pre-FEED project “LH CO 2 MENT COLORADO PROJECT” is to accelerate the implementation of a 1.5 million tonnes per year (TPY), and first-of-a-kind (FOAK) at world scale, Svante VeloxoTherm™ carbon capture plant. This project represents a quantum leap to a large-scale facility that will launch Svante’s carbon capture technology into the next era of accomplishments and market acceptance. By completing the Front-End Loading (FEL) Feasibility Study Report (FEL-2) for a fit-for-purpose design at the HOLCIM cement plant, located near Florence Colorado, USA, this technology can be proven as the future of large-scale deployment for carbon capture and storage. This carbon capture plant was designed with the goal of reaching a target of near Net Zero Emissions by capturing 90% of the carbon dioxide (CO 2 ) emissions from the HOLCIM cement plant and from the boiler which produces steam required to regenerate the adsorbent. Additionally, this project will be leveraging a renewable Power Purchase Agreement (PPA) using solar energy to acquire power at the target price of 0.04 $/kWh or less. In its current configuration CO 2 emissions from the HOLCIM cement plant is around 700 – 800 kg/ton of clinker produced. The proposed new carbon capture plant will allow a reduction of CO 2 emissions to about 100 kg/ton of clinker produced. The scope of work consists of the process design and capital & operating cost estimation (Class IV) for a total plant capacity of 4,750 TPD of pipeline grade CO 2 . The Svante VeloxoTherm™ technology is comprised of a Rotary Adsorption Machine (RAM) for intensified Thermal Swing Adsorption (TSA) using Structured Adsorbent Beds (SABs) and related Balance of Plant (BOP), including CO 2 compression. A business case (financial analysis) evaluation has been undertaken for the Owner’s management review. Recommendations on how best to proceed to the next stage of the project have been conveyed and are documented within this report. This analysis has relied on a detailed and comprehensive Project Financial Model, evaluating the Total Project IRR (after tax, unlevered, and including all forecast 45Q PTCs and 100% tax efficiency) – the project financial analysis (as opposed to standard TEA analysis) only considered a 12 year plant economic lifetime as a result of 45Q being the sole driver considered at this stage. The Total Project IRR was evaluated across a large number of potential scenarios. The evaluation demonstrated that if the 45Q PTD is increased to $85/MT for sequestration, there are a large number of feasible scenarios which demonstrate economic returns.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Bifacial PV Module Energy Modeling Validation Study

The cost delta between monofacial and bifacial photovoltaic (PV) modules was decreasing in 2018 when this study was initially proposed, making bifacial modules an attractive offering. However, there were limited field studies available that could be considered utility-scale representative, and PV module manufacturers were stating large ranges for the expected energy yield improvements of bifacial technology. This generated uncertainties regarding bifacial performance gains and the actual LCOE (levelized cost of energy). There was also relatively low confidence in the industry’s energy modeling tools’ ability to accurately predict bifacial energy yield, meaning that early adopters of bifacial modules were not able to fully account for the increased energy yield in their energy and financial models. The intent of this project was to provide the solar industry with greater certainty on the energy yield gains of bifacial modules and provide higher confidence in the ability for different energy modeling software to model bifacial PV site performance. Achieving this would allow for bifacial technology to become bankable (i.e. accepted by Independent Engineers, site financiers and other PV site stakeholders), offering a step change in PV site performance that had not been seen since the widespread adoption of the single-axis tracker. Over the course of this study other economic factors including a significant tariff exemption for bifacial modules resulted in accelerated adoption of bifacial technology throughout the US utility scale solar segment. The number of early adopters increased rapidly, and with many investors accepting this module choice the question of bifacial bankability was seemingly answered faster than expected. However, PVEL’s study has still achieved significant accomplishments in demonstrating the accuracy of bifacial modeling across three different software platforms. The results of this study have shown that the mean biased error (MBE) between the field data and the predicted values from all three software platforms were aligned with a maximum MBE of 1.3% and a minimum MBE of -1.8%.

14 SOLAR ENERGY↗
DOE OSTI2024

Geothermal Power Systems Analysis: Outcome of Industry Stakeholders Workshop: Preprint

Geothermal cost and performance evaluation implemented via technoeconomic assessment (TEA) modeling is critical for the Department of Energy (DOE) and other geothermal industry stakeholders in assessing the current state of geothermal technologies and to identify existing hurdles to commercially viable geothermal development. The Geothermal Electricity Technology Evaluation Model (GETEM) is a major TEA tool used in estimating the economic feasibility and levelized cost of energy (LCOE) of conventional hydrothermal systems and enhanced geothermal systems (EGS). Since 2021, GETEM has been transitioning from an intricate spreadsheet model to a user-friendly tool within the System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL). Apart from enabling an expanded visibility of the geothermal model among other renewable resources, having GETEM in SAM has the advantage of simulation automation, better usability, updates tracking, active user inputs/feedback, and extended financial modeling. GETEM is used in developing supply curves for the Annual Technology Baseline (ATB). The ATB data are inputs to the Renewable Energy Potential (reV) and the Regional Energy Deployment System (ReEDS) models. The geothermal module in NREL’s reV model assesses the geothermal energy potential in the conterminous United States by defining the geospatial intersection of geothermal resources with existing grid infrastructure within the constraint of land use characteristics. The ReEDS model is a capacity expansion model used for simulating the long-term build-out and operation of the US generation and transmission system based on current energy costs and policies. To ensure enhanced representation of current industry trends in our model transitions and development, we organized a two-day virtual workshop to elicit geothermal industry stakeholder input and recommendations on our current approaches and assumptions on technoeconomic, resource assessment, and deployment scenarios modeling of geothermal technologies. Participants included developers, operators, investors, regulatory agencies, system modelers, national laboratory researchers, consultants, and other stakeholders. In this workshop, we gained stakeholder insights on current geothermal plant performance (i.e., capacity factors), updated drilling costs and learning curves, and next generation technologies such as closed loop and superhot rock geothermal. Other outcomes from this workshop and its impact on future geothermal development feasibility, resource availability, and capacity expansion studies are compiled and discussed.

Annual Technology Baseline↗
DOE OSTI2025

Geothermal Power Systems Analysis: Outcome of Industry Stakeholders Workshop

Geothermal cost and performance evaluation implemented via techno-economic assessment (TEA) modeling is critical for the U.S. Department of Energy (DOE) and other geothermal industry stakeholders in assessing the current state of geothermal technologies and to identify existing hurdles to commercially viable geothermal development. The Geothermal Electricity Technology Evaluation Model (GETEM) is a major TEA tool used in estimating the economic feasibility and levelized cost of energy (LCOE) of conventional hydrothermal systems and enhanced geothermal systems (EGS). Since 2021, GETEM has been transitioning from an intricate spreadsheet model to a user-friendly tool within the System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL). Apart from enabling an expanded visibility of the geothermal model among other renewable resources, having GETEM in SAM has the advantage of simulation automation, better usability, updates tracking, active user inputs/feedback, and extended financial modeling. GETEM is used in developing supply curves for NREL's Annual Technology Baseline (ATB), which provides inputs to the Renewable Energy Potential (reV) and the Regional Energy Deployment System (ReEDS) models. The geothermal module in NREL's reV model assesses the geothermal energy potential in the conterminous United States by defining the geospatial intersection of geothermal resources with existing grid infrastructure within the constraint of land use characteristics. The ReEDS model is a capacity expansion model used for simulating the long-term build-out and operation of the U.S. generation and transmission system based on current energy costs and policies. To ensure enhanced representation of current industry trends in our model transitions and development, we organized a two-day virtual workshop to elicit geothermal industry stakeholder input and recommendations on our current approaches and assumptions on techno-economic, resource assessment, and deployment scenarios modeling of geothermal technologies. Participants included developers, operators, investors, regulatory agencies, system modelers, national laboratory researchers, consultants, and other stakeholders. In this workshop, we gained stakeholder insights on current geothermal plant performance (i.e., capacity factors), updated drilling costs and learning curves, and next-generation technologies such as closed-loop and superhot rock geothermal. Other outcomes from this workshop and its impact on future geothermal development feasibility, resource availability, and capacity expansion studies are compiled and discussed.

annual technology baseline↗
DOE OSTI2022

Long-term impact of light- and elevated temperature-induced degradation on photovoltaic arrays

Low levelized cost of electricity (LCOE) has been identified as critical for widespread adoption of photovoltaics (PV) without subsidies. Maintaining decades-long high-energy production is often an under-recognized opportunity in meeting cost goals because component lifetimes are not fully quantified at the time of manufacture. Whereas certain standardized tests minimize risk of early failure, there is little guidance to quantitatively predict degradation (or lack thereof) over decades, based on accelerated tests. In this article, we move toward bridging the understanding between indoor accelerated tests and outdoor performance data, with the goal of predicting energy yield with enough accuracy to inform financial decisions. Light- and elevated temperature-induced degradation (LETID) in p-type Si modules is analyzed in terms of impact on long-term module performance and thus LCOE. A method to predict the progression of LETID, using fixed kinetic constants and a numerical solution to the basic reaction rate equations, is detailed. Predictions are compared against both published data and that new to this study. These data include both indoor accelerated tests and fielded modules. We use the results in financial models to derive LCOE of modules in different climates with varying amounts of LETID, including uncertainty. Cost models based on the predictions indicate that LETID has a significant and climate-dependent impact on LCOE. Finally, we show that - even given the uncertainties identified in the study - these financial calculations can provide useful guidance to quantify risk based on accelerated test results. The analysis serves as an example of developing a predictive approach to PV reliability using physics of failure.

14 SOLAR ENERGY↗
DOE OSTI2023

LA100 Equity Strategies. Chapter 9: Equitable Community Solar Access and Benefits

The LA100 Equity Strategies project integrates community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. This chapter focuses on community solar as a means to provide equitable access to local solar and storage benefits in Los Angeles. Specifically, NREL identified potential community solar sites that could host 30 kilowatts (kW)1 of solar or more and evaluated economic and equity metrics under various program design options. Analysis included a Baseline scenario (business-as-usual) and an Equity scenario, which modeled program enhancements to increase access and benefits to low-income customers. Both scenarios modeled the economics of solar and storage under the LADWP Feed-in Tariff (FiT) program (LADWP 2023b) and the LADWP Feed-in-Tariff Plus Pilot program (LADWP 2023d) compared to a community solar financial model. This research was guided by input from the community engagement process, and associated equity strategies are presented in alignment with that guidance.

14 SOLAR ENERGY↗
NASA NTRS1978

Winter Simulation Conference, Miami Beach, Fla., December 4-6, 1978, Proceedings. Volumes 1 & 2

The papers report on the various aspects of simulation such as random variate generation, simulation optimization, ranking and selection of alternatives, model management, documentation, data bases, and instructional methods. Simulation studies in a wide variety of fields are described, including system design and scheduling, government and social systems, agriculture, computer systems, the military, transportation, corporate planning, ecosystems, health care, manufacturing and industrial systems, computer networks, education, energy, production planning and control, financial models, behavioral models, information systems, and inventory control.

Highland, H. J.↗
DOE OSTI2021

Foundational Open Source Solar System Modeling Through Improvement and Validation of the System Advisor Model and PVWatts (FY19-FY21 Final Technical Report)

Accelerating intelligent deployment of solar energy technologies demands accurate system modeling every step of the way. From project development to policy research, grid integration studies to development of novel technologies, industry and researchers alike need validated, transparent, easy-to-use, extensible, cutting-edge, and accurate models of both the performance and financing of solar systems. The System Advisor Model (SAM) and PVWatts tools provide a platform to fill that need. The overarching goal of this set of software tools is to enable accurate PV system modeling across the industry, and our usage metrics indicate that we continue to succeed in that endeavor, with a user starting SAM every 2 minutes globally, and over 17 million PVWatts hits per month. This project leveraged DOEs past investment in the SAM and PVWatts platforms to continue to provide valuable and extensible PV, battery, and financial modeling resources to the larger solar community. We pursued multiple avenues in parallel: software maintenance and technical support that are foundational to the continued usability of the SAM and PVWatts platforms; platform and PV model improvements and stakeholder engagement activities that are core to the continued relevance of the platforms; and open source activities to foster the continued creation of a vibrant open-source community around the SAM and PVWatts tools, which opens up exciting new opportunities for industry interaction.

14 SOLAR ENERGY↗
DOE OSTI2024

Solar Street Lighting: Highland Park Pathways to Power [Slides]

Through the Communities LEAP (Local Energy Action Program) Pilot, the National Renewable Energy Laboratory (NREL) engaged the Highland Park Stakeholder Coalition to scope four technical assistance work areas to address their energy needs and goals. This slide deck addresses the highlighted tasks under work area "A" related to the city's streetlights. Due to economic collapse, the City of Highland Park negotiated repossession of it's neighborhood streetlights to help pay its debt to its power provider, DTE. Without street lighting on residential streets, public safety was at risk. Local community-based-organization, Soulardarity, began installing off-grid solar street lights to improve visibility for vehicles and pedestrians in Highland Parks neighborhoods. Residents and leaders of the community who served on the Communities LEAP Coalition requested NREL review a financial model Soulardarity proposed to operate a city-wide solar streetlighting program on the City's behalf. The coalition also requested NREL identify examples of similar implemented city-wide solar street lighting programs.

14 SOLAR ENERGY↗
DOE OSTI2020

SAM™ (System Advisor Model™) [SWR-16-02, SWR-10-13]

See the SAM™ website to build a desktop version of the National Laboratory of the Rockies' (NLR's) System Advisor Model™ (SAM). https://sam.nlr.gov/ The System Advisor Model™ (SAM™) is a free techno-economic software model that facilitates decision-making for people in the renewable energy industry: -Project managers and engineers -Policy analysts -Technology developers -Researchers SAM can model many types of renewable energy systems: -Photovoltaic systems, from small residential rooftop to large utility-scale systems -Battery storage with Lithium ion, lead acid, or flow batteries for front-of-meter or behind-the-meter applications -Concentrating Solar Power systems for electric power generation, including parabolic trough, power tower, and linear Fresnel -Industrial process heat from parabolic trough and linear Fresnel systems -Wind power, from individual turbines to large wind farms -Marine energy wave and tidal systems -Solar water heating -Fuel cells -Geothermal power generation -Biomass combustion for power generation -High concentration photovoltaic systems SAM's financial models are for the following types of projects: -Residential and commercial projects where the renewable energy system is on the customer side of the electric utility meter (behind the meter), and power from the system is used to reduce the customer's electricity bill. -Power purchase agreement (PPA) projects where the system is connected to the grid at an interconnection point, and the project earns revenue through power sales. The project may be owned and operated by a single owner or by a partnership involving a flip or leaseback arrangement. -Third party ownership where the system is installed on the customer's (host) property and owned by a separate entity (developer), and the host is compensated for power generated by the system through either a PPA or lease agreement. For a more detailed description of SAM, see Blair et al. (2018), System Advisor Model (SAM) General Description (Version 2017.9.5), NREL/TP-6A20-70414. https://www.nrel.gov/docs/fy18osti/70414.pdf

Ryberg, David↗
DOE OSTI2024

Capital Structure for Techno-Economic Analysis of Hydrogen Projects

This report provides updated generally accepted accounting principles (GAAP) parameter estimates of assumptions that may be used to reflect the cost of financing hydrogen infrastructure deployment. The report also provides parameter estimation for more streamlined financial analysis frameworks such as discounted cash flow and annualized financial models. Parameter values are derived from industry feedback and are reflective of current macro-economic factors such as higher interest rates and higher risk profile of emerging hydrogen technologies, given a myriad of factors such as projects’ construction inexperience, capital costs, and rising inflation, among others.

08 HYDROGEN↗