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DOE OSTI2023

Grand challenges in the design, manufacture, and operation of future wind turbine systems

Abstract. Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push the frontiers in the design of turbine and plant systems. Modern turbine rotors operate through the entire atmospheric boundary layer, outside the bounds of historic design assumptions, which requires reassessing design processes and approaches. Traditional aerodynamics and aeroelastic modeling approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load alleviation potential. Opportunities in co-design can bring controls upstream into design optimization if captured in design-level models of the physical phenomena. It is a research challenge to integrate improved materials into the manufacture of ever-larger components while maintaining quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions needed to continue the progress of wind energy technology toward even lower cost and greater functionality are recommended.

17 WIND ENERGY↗

DOE OSTI2019

North Carolina Implementation Model: Enhancing Performance Contracting for K-12 Schools, Community College, and Local Governments

With funding from the Office of Energy Efficiency and Renewable Energy State Energy Program’s Competitive Financial Assistance program, North Carolina successfully helped 30 local governments implement energy savings performance contracting projects that will result in more than $70 million in lifetime savings.

Energy Savings Performance Contracting, ESPC, Fina↗

DOE OSTI2026

Dataset for Blueprinting Electrified Transit System Implementation

This dataset contains the figures and tabulated results generated from a system-level optimization study of transit fleet electrification planning. The dataset does not include executable modeling code required to reproduce the optimization. The dataset includes results for optimized charging infrastructure deployment by location and power level and service block assignments by fuel type, battery capacity selections, and distributed energy resource sizing. It also contains aggregated financial results, capital expenditures, operating cost summaries, net present cost comparisons across scenarios, and quantified air quality impacts. Results are structured to reflect multiple planning scenarios, including heuristic electrification plans, system-optimized configurations, and sensitivity cases with alternative objective weightings. The modeling was developed using publicly available General Transit Feed Specification data from Omnitrans and standardized modeling assumptions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Dataset for Blueprinting Electrified Transit System Implementation

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Advancing Fusion with Machine Learning Research Needs Workshop Report

Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available at https://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf ). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1999

The Aviation System Analysis Capability Air Carrier Cost-Benefit Model

To meet its objective of assisting the U.S. aviation industry with the technological challenges of the future, NASA must identify research areas that have the greatest potential for improving the operation of the air transportation system. Therefore, NASA is developing the ability to evaluate the potential impact of various advanced technologies. By thoroughly understanding the economic impact of advanced aviation technologies and by evaluating how the new technologies will be used in the integrated aviation system, NASA aims to balance its aeronautical research program and help speed the introduction of high-leverage technologies. To meet these objectives, NASA is building the Aviation System Analysis Capability (ASAC). NASA envisions ASAC primarily as a process for understanding and evaluating the impact of advanced aviation technologies on the U.S. economy. ASAC consists of a diverse collection of models and databases used by analysts and other individuals from the public and private sectors brought together to work on issues of common interest to organizations in the aviation community. ASAC also will be a resource available to the aviation community to analyze; inform; and assist scientists, engineers, analysts, and program managers in their daily work. The ASAC differs from previous NASA modeling efforts in that the economic behavior of buyers and sellers in the air transportation and aviation industries is central to its conception. Commercial air carriers, in particular, are an important stakeholder in this community. Therefore, to fully evaluate the implications of advanced aviation technologies, ASAC requires a flexible financial analysis tool that credibly links the technology of flight with the financial performance of commercial air carriers. By linking technical and financial information, NASA ensures that its technology programs will continue to benefit the user community. In addition, the analysis tool must be capable of being incorporated into the wide-ranging suite of economic and technical models that comprise ASAC. This report describes an Air Carrier Cost-Benefit Model (CBM) that meets these requirements. The ASAC CBM is distinguished from many of the aviation cost-benefit models by its exclusive focus on commercial air carriers. The model considers such benefit categories as time and fuel savings, utilization opportunities, reliability and capacity enhancements, and safety and security improvements. The model distinguishes between benefits that are predictable and those that occur randomly. By making such a distinction, the model captures the ability of air carriers to reoptimize scheduling and crew assignments for predictable benefits. In addition, the model incorporates a life-cycle cost module for new technology, which applies the costs of nonrecurring acquisitions, recurring maintenance and operation, and training to each aircraft equipment type independently.

Gaier, Eric M.↗

DOE OSTI2023

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmarks, With Minimum Sustainable Price Analysis: Q1 2023

The U.S. Department of Energy's (DOE's) Solar Energy Technologies Office (SETO) aims to accelerate the advancement and deployment of solar technology in support of an equitable transition to a decarbonized economy no later than 2050, starting with a decarbonized power sector by 2035. Its approach to achieving this goal includes driving innovations in technology, hardware, and soft cost reductions to make solar affordable and accessible for all. As part of this effort, SETO must track solar cost trends so it can focus its research and development (R&D) on the highest-impact activities. The benchmarks in this report are bottom-up cost estimates of all major inputs to PV and energy storage system installations. Bottom-up costs are based on national averages and do not necessarily represent typical costs in all local markets. Like last year's report, this year's report includes two distinct sets of benchmarks: minimum sustainable price (MSP) benchmarks and modeled market price (MMP) benchmarks. MSP benchmarks can be interpreted as the minimum price a company needs to charge to remain financially solvent in the long term based on the minimum sustainable prices of all inputs including minimum sustainable profit margins. MMP benchmarks can be interpreted as the actual cash sales price a company charges in the given benchmark period. These simplified estimates are useful for tracking technological progress, but they do not reflect all experiences. In fact, no individual estimate under any approach can reflect the diversity of the PV and storage manufacturing and installation industries. Our residential MMP benchmark ($2.90 per watt direct current [Wdc]) is 24% higher than the MSP benchmark ($2.34/Wdc) and 9% lower than our MMP benchmark ($3.18/Wdc) from Q1 2022 in 2022 U.S. dollars (USD). For community solar, our MMP benchmark ($1.75/Wdc) is 18% higher than our MSP benchmark ($1.49/Wdc). Our Q1 2022 benchmark report has no community solar system for comparison. For utility-scale systems with one-axis tracking, our MMP benchmark ($1.17/Wdc) is 22% higher than our MSP benchmark ($0.96/Wdc) and 10% higher than its counterpart ($1.07/Wdc) in Q1 2022 in 2022 USD.

14 SOLAR ENERGY↗

DOE OSTI2024

A Strategic Condition Framework for Energy Innovation

Building upon previous work in innovation, technology, and economic fields, we propose a conceptual framework to address the interplay dynamics of public policy and the value chains of clean energy technology innovation systems, by focusing on market structural and strategic conditions in relation to the rate and direction of knowledge diffusion within activity-based value chains. Our framework extends beyond socio-technical transition models by considering such nuances as: 1) the implications of geography, 2) the locus of knowledge types, 3) the dynamics of financial and knowledge flow, and 4) emphasizing the importance of both market structure and institutional conditions. At the firm level, we consider dynamics of interactions between suppliers and customers, innovation activities, the competitive environment, and the firm’s broader strategic relationship to governance activities and structures; we allow for the fact that each of these aspects of a firm’s identity may have a strategically relevant geographic dimension (e.g., service territories, locational concentration of input resources, etc.). We provide a proof-of-concept application of the U.S. utility-scale solar photovoltaic (PV) and onshore wind sectors, including their interactions with the U.S. power market, which we in present in a web-based information platform (Energy I-SPARK, ei-spark.lbl.gov).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Q1 2023 U.S. Solar Photovoltaic System and Energy Storage Cost Benchmarks With Minimum Sustainable Price Analysis Data File

14 SOLAR ENERGY↗

NASA NTRS1975

Thermal area effectiveness for future aircraft

Problem areas in airport planning, design, and operations identified by a decision matrix developed to display various airport functions interfaced with facilities and an extensive literature survey were investigated. Areas considered include: site selection and growth potential; emissions and noise control/containment for airports; financial and legal aspects of airport planning, contruction, and operation; intra-airport transportation and other passenger flow facilitators; simulation and modeling for airports; guidelines for airport multimodal access planning. Results are summarized and a bibliography is included.

Happ, W. W.↗

NASA NTRS1996

The development, assessment and validation of virtual reality for human anatomy instruction

This research project seeks to meet the objective of science training by developing, assessing, validating and utilizing VR as a human anatomy training medium. Current anatomy instruction is primarily in the form of lectures and usage of textbooks. In ideal situations, anatomic models, computer-based instruction, and cadaver dissection are utilized to augment traditional methods of instruction. At many institutions, lack of financial resources limits anatomy instruction to textbooks and lectures. However, human anatomy is three-dimensional, unlike the one-dimensional depiction found in textbooks and the two-dimensional depiction found on the computer. Virtual reality allows one to step through the computer screen into a 3-D artificial world. The primary objective of this project is to produce a virtual reality application of the abdominopelvic region of a human cadaver that can be taken back to the classroom. The hypothesis is that an immersive learning environment affords quicker anatomic recognition and orientation and a greater level of retention in human anatomy instruction. The goal is to augment not replace traditional modes of instruction.

Marshall, Karen Benn↗

NASA NTRS2019

Cloud Governance at Scale

Operating and maintaining a large multi-tenant ecosystem in the cloud requires scalable solutions to unique technical and process challenges. The Cloud Computing model grants significant permissions to development teams that traditionally were reserved for Data-Center Administrators and Supply-Chain Managers. Earthdata Cloud has worked to re-cast traditional data-center management into a sensible cloud-first model. This talk discusses some of our challenges, solutions, and way ahead.

financial controls↗

DOE OSTI2025

Carbon storage cost modeling for the offshore Gulf of America

At the 2025 Annual University of Houston ROICE Workshop, Dr. Chung Shih delivered an invited talk titled "Carbon Storage Cost Modeling for the Offshore Gulf of America." This presentation highlighted the capabilities of NETL's offshore saline carbon storage cost model (CO2_S_COM_Offshore) in evaluating the economics of both new and reused storage infrastructure. While primarily intended for screening-level analysis, the model comprehensively considers critical components such as onshore facilities, pipelines connecting shore to offshore platforms, main platforms, and satellite platforms. Additionally, its integrated cashflow model encompasses the entire project lifecycle, from initial site screening to post-injection site care, providing users with a thorough understanding of how various operational or financial parameters impact project economics.

cost modeling↗

DOE OSTI2024

Triple Effect Economics: How Do Electric Vehicles, Solar Photovoltaics, and Work-from-Home Transform Household Electricity Cost?

Solutions for deep decarbonization need to be affordable as well as sustainable to garner widespread adoption. The past two decades have seen the introduction of new technologies and paradigms such as electric vehicles (EVs), solar photovoltaics (PVs), and increased work-from-home (WFH), which impact a household's overall energy consumption and cost in different ways. However, much attention has not been paid to explore the joint impact these technologies have on a household's electricity cost burden. Leveraging the 2020 Residential Energy Consumption Survey (RECS), this study presents an integrated model to unravel the extent to which the bundled adoption of EV-PV and stay-at-home decisions impact the total electricity cost of households. National level RECS data revealed that, compared to the baseline (i.e., households that did not own any of these technologies), households that own EVs, PVs, and engage in WFH observed a 13.5% decline in their electricity bills, despite a 25% increase in electricity consumption. The model results indicated that bundled adoption of EVs-PVs reduces electricity costs more significantly for a household, compared to the increased costs imposed by more household members staying at home. This holistic assessment presents an opportunity for decision makers to contextualize the changing energy costs and design effective strategies to foster a sustainable and cost saving mechanism. Policies such as bundled incentivization to motivate co-adoption, education about energy-management strategies, and add-on subsidies to adopt energy-efficient appliances, will not only accelerate decarbonization but increase household financial savings.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

DOE OSTI2022

High-Octane Gasoline from Lignocellulosic Biomass via Syngas and Methanol/Dimethyl Ether Intermediates (2021 State of Technology)

The 2021 state of technology (SOT) assessment for the indirect liquefaction (IDL) of lignocellulosic biomass to high-octane gasoline (HOG) via methanol and dimethyl ether (DME) intermediates details the techno-economic analysis (TEA) results and technical progress of the pathway since the 2020 SOT report. A detailed process description and collection of underlying assumptions is given the 2015 design report. In 2021, research efforts rigorously quantified the selectivity of DME to aromatic compounds. As a result, the overall carbon selectivity to hydrocarbon products was updated based upon new findings. Additionally, research conducted over the past few years resulted in successful lower temperature regeneration of NREL's Cu/BEA catalyst with favorable implications on catalyst longevity. Discussions with an engineering firm resulted in an update to the excess air requirement for process combustors (including the char combustor, tar reformer combustor, and catalyst regenerator) in which excess air was reduced from 20% excess to 10%. The cumulative effect of the above efforts was used to calculate a minimum fuel selling price for the modeled pathway. Sensitivity cases examining federal carbon tax credits from CO 2 capture, product selectivity and yield, catalyst lifetime, and other key financial and process parameters were also considered in this assessment.

09 BIOMASS FUELS↗

NASA NTRS1994

The assessment of virtual reality for human anatomy instruction

This research project seeks to meet the objective of science training by developing, assessing, and validating virtual reality as a human anatomy training medium. In ideal situations, anatomic models, computer-based instruction, and cadaver dissection are utilized to augment the traditional methods of instruction. At many institutions, lack of financial resources limits anatomy instruction to textbooks and lectures. However, human anatomy is three dimensional, unlike the one dimensional depiction found in textbooks and the two dimensional depiction found on the computer. Virtual reality is a breakthrough technology that allows one to step through the computer screen into a three dimensional world. This technology offers many opportunities to enhance science education. Therefore, a virtual testing environment of the abdominopelvic region of a human cadaver was created to study the placement of body parts within the nine anatomical divisions of the abdominopelvic region and the four abdominal quadrants.

Benn, Karen P.↗

DOE OSTI2026

Developing Methane Emissions Inventories by Fusing Airborne, Satellite, and Modeled Assessments: Comprehensive Surveys of the Anadarko and Haynesville Basin

The objective of this program is to create basin-specific methane emissions inventories of the Haynesville and Anadarko (Woodford shale) basins, based on truly basin-scale data collection and analysis. Emissions of natural gas, predominantly composed of methane, present a significant financial loss to the oil and gas sector and reduce the competitiveness of American energy sources. While large emissions, above 10 kg/h, occur at only a small percentage of oil and gas sites, they account for a disproportionately large volume of emissions. To address this, we executed a concurrent campaign combining cutting-edge bottom-up modeling with top-down aerial and satellite surveys to capture the heavy-tailed distribution of these large emissions to accurately characterize total emissions throughout both regions.

03 NATURAL GAS↗

DOE OSTI2024

Artificial ground reflector size and position effects on energy yield and economics of single‐axis‐tracked bifacial photovoltaics

Abstract Artificial ground reflectors improve bifacial energy yield by increasing both front and rear‐incident irradiance. Studies have demonstrated an increase in energy yield due to the addition of artificial reflectors; however, they have not addressed the effect of varying reflector dimensions and placement on system performance and the impact of these parameters on the reflectors' financial viability. We studied the effect of high albedo (70% reflective) artificial reflectors on single‐axis‐tracked bifacial photovoltaic systems through ray‐trace modeling and field measurements. In the field, we tested a range of reflector configurations by varying reflector size and placement and demonstrated that reflectors increased daily energy yield up to 6.2% relative to natural albedo for PERC modules. To confirm the accuracy of our model, we compared modeled and measured power and found a root mean square error (RMSE) of 5.4% on an hourly basis. We modeled a typical meteorological year in Golden, Colorado, to demonstrate the effects of artificial reflectors under a wide range of operating conditions. Seventy percent reflective material can increase total incident irradiance by 1.9%–8.6% and total energy yield by 0.9%–4.5% annually after clipping is considered with a DC–AC ratio of 1.2. Clipping has a significant effect on reflector impact and must be included when assessing reflector viability because it reduces reflector energy gain. We calculated a maximum viable cost for these improvements of up to $2.50–4.60/m 2 , including both material and installation, in Golden. We expanded our analysis to cover a latitude range of 32–48°N and demonstrated that higher‐latitude installations with lower energy yield and higher diffuse irradiance content can support higher reflector costs. In both modeling and field tests, and for all locations, the ideal placement of the reflectors was found to be directly underneath the module due to the optimized rear irradiance increase.

14 SOLAR ENERGY↗