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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Analysis of Benefits Associated With Projects and Technologies Supported by the Clean Transportation Program

The California Energy Commission's Clean Transportation Program (CTP) supports a wide range of alternative, low-carbon fuel and vehicle projects. This report improves upon the 2014 Alternative and Renewable Fuel and Vehicle Technology Program (ARFVTP) Benefits Report(the former name of the Clean Transportation Program), which focused on two components of benefit calculation: expected benefits and market transformation benefits. The "expected benefits" are defined as benefits that accrue because of the direct displacement of petroleum-based fuels or vehicle technologies. The "market transformation benefits" accrue because of CTP funding shifting the underlying market dynamics and accelerating the adoption of alternative fuel vehicles. This report documents the updated methods used in the benefits analysis in 2014 and applies them for this 2021 Clean Transportation Program Benefits Report. The project team used data collected from CTP projects funded from 2009 to the third quarter of 2021 to estimate the benefits between 2021 and 2030. CTP projects valued at $\$898.3 million$ were assessed (out of $\$1.04 billion$ funded) to estimate expected benefits of 249 million gallons per year petroleum reduction and 2.79 million metric tons per year of carbon dioxide equivalent greenhouse gas (GHG) reduction in 2030. Market transformation benefits are additive to the expected benefits and were estimated with high and low ranges for the 315 relevant projects evaluated. The market transformation benefits' GHG reductions are estimated as 2.2 million to 6.2 million metric tons of carbon dioxide equivalent per year and the petroleum reductions as 145.3 million to 671.5 million gasoline gallon equivalents per year in 2030. Combining both benefit types, the CTP projects can make significant progress toward meeting California's long-term GHG and petroleum fuel use reduction goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Hydrogen Considerations Tree: Executive Deck [Slides]

The Hydrogen Considerations Tree is designed to enhance the understanding and capabilities of U.S. Agency for International Development Missions and country partners, empowering them to make informed decisions regarding potential support for hydrogen and its derivatives, such as e-fuels, hydrogen carriers, or ammonia, within their respective nations. Moreover, the Considerations Tree is designed to provide fundamental and applied information for the identification of deployment, regulation, policy priorities for hydrogen technologies in the context of each country or region. Key topics are organized into a "considerations tree," enabling stakeholders to systematically and holistically address technical, regulatory, economic, environmental, social, and analytical questions.

08 HYDROGEN↗
DOE OSTI2024

Saving Energy, Saving Money [Slides]

Make sure you have CO detectors installed; Test batteries regularly; Have your furnace serviced annually; Don’t use grills or generators indoors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Bioenergy and Climate Change in Ukraine: How climate can impact the sustainability of bioenergy production

The Russian invasion has exacerbated Ukraine’s energy security issues, prompting a shift toward diversifying energy supply sources. Additionally, strategic documents aim to align Ukraine’s energy system with EU climate requirements, focusing on reducing reliance on fossil fuels and advancing decarbonization efforts. This report focuses on the expansion of bioenergy as an alternative source of energy in Ukraine. Current assessments suggest that Ukraine has substantial bioenergy potential, primarily from agricultural residues and energy crops. However, the challenges posed by climate change and the ongoing war might impact the outcome of these projections. This report highlights the importance of integrating climate factors into energy modeling using tools like the integrated assessment models to provide a comprehensive understanding of Ukraine’s bioenergy potential under various climate scenarios. It also emphasizes the need for climate-smart agriculture and forestry practices to mitigate risks, enhance energy efficiency, and support resilient crop supplies. Recommendations for stakeholders include diversification of the energy supply sources, developing adaptation strategies, diversifying bioenergy feedstocks, and ensuring robust decision-making to navigate the impacts of climate change on Ukraine’s energy system.

09 BIOMASS FUELS↗
DOE OSTI2018

Breaking Through Historical Biases in Performance Assessments - 18056

Performance assessments (referred to as safety assessments internationally), which include mathematical modeling of natural and engineered systems for many hundreds and thousands of years, play an important role in decision-making for disposal of radioactive waste and cleanup of sites and facilities contaminated with radioactive material. These decisions can involve options costing hundreds of millions or even billions of dollars. Thus, it is critical to understand the underlying assumptions behind regulatory and technical aspects of these assessments to better understand and communicate the basis for decisions. Policy and technical biases deliberately built into early assessment approaches allowed safety margin to account for uncertainties known to be present, but not quantitatively assessed. Many of these biases (e.g., regulatory standards, human habits, effectiveness of waste forms, inadvertent intrusion assumptions, etc.) continue to exist in spite of advances in technical approaches and knowledge. These built-in biases, often not effectively communicated, can lead to misleading interpretation of results and potentially influence public confidence and costly regulatory decisions regarding the safety of a disposal facility or a closure action. (authors)

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

Requesting an Exemption from Standard Compliance: EPAct State and Alternative Fuel Provider Fleet Program Guidance Document

The U.S. Department of Energy established the Alternative Fuel Transportation Program (Program) and associated regulatory requirements pursuant to the Energy Policy Act of 1992. The Program, otherwise known as the State and Alternative Fuel Provider Fleet Program, requires covered state government and alternative fuel provider fleets operating under Standard Compliance to acquire alternative fuel vehicles (AFVs) as a specific percentage of their annual non-excluded light-duty vehicle acquisitions. The opportunity for covered fleets operating under Standard Compliance to request exemptions from their AFV-acquisition requirements serves as administrative relief in the unlikely event a fleet is unable to satisfy its requirements through the normally available compliance alternatives. These alternatives include the acquisition of light-duty AFVs, the acquisition of other, creditable vehicles (e.g., gasoline-fueled hybrid electric vehicles), making certain investments, the purchase of biodiesel for use in medium- or heavy-duty vehicles to the maximum extent allowed, and purchasing or trading for banked AFV credits. This document addresses requests for exemptions from the AFV-acquisition requirements to help covered fleets better understand: How to file a request for an exemption, information and documentation DOE needs to process an exemption request, and important policies relevant for filing exemption requests.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2024

At Risk Population Estimates for Belarus, Poland and Slovakia with Machine Learning

High-resolution gridded population modeling is crucial for various applications, including disaster response planning, infectious disease spread modeling, climate change impact estimation, policy development, and more. Multiple gridded population datasets have been developed, each tailored to meet specific objectives. Among them, LandScan Global dataset is designed to represent ambient and unwarned population distributions. However, this dataset relies on a statistical approach that requires manual adjustments, making it time consuming and labour intensive. Existing machine learning (ML) methods often train and test at different spatial resolutions, potentially leading to inflated results, and they rely on Census population totals for disaggregation. To address these limitations, in this study we developed population estimates using ML models trained and tested at a consistent 30 arc-second resolution (≈1 square kilometer), specifically using Random Forest (RF) and XGBoost. These models were trained on 2020 datum to predict for 2021 for three countries: Belarus, Poland, and Slovakia. Our findings show that both RF (MAE varies from 5.75 to 13.25) and XGBoost (MAE varies from 8.15 to 23.44) model performance is close to LandScan Global estimates. Furthermore, neither of the models performed the best across all grid cells: the RF model was more effective in areas with lower populations, while XGBoost excelled in more densely populated regions. The proposed approach can be used for countries where the Census data is not available.

Lebakula, Viswadeep [ORNL] (ORCID:0000000152935914↗
DOE OSTI2023

Effectiveness and predictability of in-network storage cache for Scientific Workflows

Large scientific collaborations often have multiple scientists accessing the same set of files while doing different analyses, which create repeated accesses to the large amounts of shared data located far away. These data accesses have long latency due to distance and occupy the limited bandwidth available over the wide-area network. To reduce the wide-area network traffic and the data access latency, regional data storage caches have been installed as a new networking service. To study the effectiveness of such a cache system in scientific applications, we examine the Southern California Petabyte Scale Cache for a high-energy physics experiment. By examining about 3TB of operational logs, we show that this cache removed 67.6% of file requests from the wide-area network and reduced the traffic volume on wide-area network by 12. 3TB (or 35.4%) an average day. The reduction in the traffic volume (35.4%) is less than the reduction in file counts (67.6%) because the larger files are less likely to be reused. Due to this difference in data access patterns, the cache system has implemented a policy to avoid evicting smaller files when processing larger files. We also build a machine learning model to study the predictability of the cache behavior. Tests show that this model is able to accurately predict the cache accesses, cache misses, and network throughput, making the model useful for future studies on resource provisioning and planning.

Sim, Caitlin↗
DOE OSTI2023

Optimizing Performance on Trinity Utilizing Machine Learning, Proxy Applications and Scheduling Priorities

The sheer number of nodes continues to increase in today’s supercomputers, the first half of Trinity alone contains more than 9400 compute nodes. Since the speed of today’s clusters are limited by the slowest nodes, it more important than ever to identify slow nodes, improve their performance if it can be done, and assure minimal usage of slower nodes during performance critical runs. This is an ongoing maintenance task that occurs on a regular basis and, therefore, it is important to minimize the impact upon its users by assessing and addressing slow performing nodes and mitigating their consequences while minimizing down time. These issues can be solved, in large part, through a systematic application of fast running hardware assessment tests, the application of Machine Learning, and making use of performance data to increase efficiency of large clusters. Proxy applications utilizing both MPI and OpenMP were developed to produce data as a substitute for long runtime applications to evaluate node performance. Machine learning is applied to identify underperforming nodes, and policies are being discussed to both minimize the impact of underperforming nodes and increase the efficiency of the system. In this paper, I will describe the process used to produce quickly performing proxy tests, consider various methods to isolate the outliers, and produce ordered lists for use in scheduling to accomplish this task.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Energy and remote sensing applications

The nature of the U.S. energy problem is examined. Based upon the best available estimates, it appears that demand for OPEC oil will exceed OPEC productive capacity in the early to mid-eighties. The upward pressure on world oil prices resulting from this supply/demand gap could have serious international consequences, both financial and in terms of foreign policy implementation. National Energy Plan objectives in response to this situation are discussed. Major strategies for achieving these objectives include a conversion of industry and utilities from oil and gas to coal and other abundant fuels. Remote sensing from aircraft and spacecraft could make significant contributions to the solution of energy problems in a number of ways, related to exploration of energy-related resources, the efficiency and safety of exploitation procedures, power plant siting, environmental monitoring and assessment, and the transportation infrastructure.

Summers, R. A.↗
DOE OSTI2022

Clean energy technology pathways from research to commercialization: Policy and practice case studies

Clean energy research and development (R and D) leading to commercial technologies is vital to economic development, technology competitiveness, and reduced environmental impact. Over the past 30 years, such efforts have advanced technology performance and reduced cost by leveraging network effects and economies of scale. After demonstrating promise in applied R and D, successful clean energy and energy efficiency technologies are incorporated into an initial product sold by the private sector. Despite its importance, processes by which first commercialization occurs are difficult to generalize while capturing specific insights from practitioners in markets and technologies. This paper presents a policy-focused qualitative assessment of the first commercialization of four diverse energy technologies: thin film photovoltaics, wind turbine blades, dual-stage refrigeration evaporators, and fuel cells for material handling equipment. Each technology presents distinct value propositions, markets, and regulatory drivers. The case studies indicate three common characteristics of successful first commercialization for new energy technologies: 1) good fit between the technology, R&D infrastructure, and public-private partnership models; 2) high degree of alignment of government regulations and R&D priorities with market forces; and 3) compatibility between time scales required for R&D, product development, and opportunities. These findings may inform energy investment decision-making, maximize benefits from R&D, and advance the transition to a low-emission future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2012

Policy for Robust Space-based Earth Science, Technology and Applications

Over the past six decades, satellite remote sensing technology has contributed to the transformation of using earth science not only to advance science, but to improve quality of life. With satellite missions launched almost every year, new types of earth science data are being incorporated into science, models and decision-making systems in a broad array of organizations. A challenge for space agencies has been ensuring that satellite missions serve both the scientific community and the applied community of decision makers without the missions becoming unfocused and overly expensive. By understanding and considering the needs of the environmental data and applied research user community early on in the mission-design process, agencies can ensure that satellites meet the needs of multiple constituencies. This paper describes the mission development process in the European Space Agency and the National Aeronautics and Space Administration and compares and contrasts the successes of and challenges faced by these agencies in balancing science and applications within their missions.

Brown, Molly E.↗
DOE OSTI2018

Estimating the Value of Improved Distributed Photovoltaic Adoption Forecasts for Utility Resource Planning

Misforecasting the adoption of customer-owned distributed photovoltaics (DPV) can have operational and financial implications for utilities; forecasting capabilities can be improved, but generally at a cost. This paper informs this decision-space by using a suite of models to explore the capacity expansion and operation of the Western Interconnection over a 15-year period across a wide range of DPV growth rates and misforecast severities. The system costs under a misforecast are compared against the costs under a perfect forecast, to quantify the costs of misforecasting. Using a simplified probabilistic method applied to these modeling results, an analyst can make a first-order estimate of the financial benefit of improving a utility’s forecasting capabilities, and thus be better informed about whether to make such an investment. For example, under our base assumptions, a utility with 10 TWh per year of retail electric sales who initially estimates that DPV growth could range from 2% to 7.5% of total generation over the next 15 years could expect total present-value savings of approximately $4 million if they could reduce the severity of misforecasting to within ±25%. Utility resource planners can compare those savings against the costs needed to achieve that level of precision, to guide their decision on whether to make an investment in tools or resources.

14 SOLAR ENERGY↗
DOE OSTI2021

NETL 45Q Addendum to the CO2U LCA Guidance Toolkit

This document provides additional guidance and changes to the Carbon Dioxide Utilization Life Cycle Analysis Guidance for the U.S. DOE Office of Fossil Energy and Carbon Management, Version 2.0 to make it more applicable to taxpayers preparing life cycle analyses for the 45Q tax credit.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Accelerating Low-Income Financing and Transactions (LIFT) for Solar Access Everywhere (Final Technical Report)

The Accelerating Low-Income Financing and Transactions (LIFT) for Solar Access Everywhere project’s goal was to expand Low-to-Moderate Income (LMI) solar access for homeowners and renters. The LIFT project researched and gathered data on 453 LMI community solar project across the country. Following three years of research, the project delivered three groundbreaking research papers in June 2022, focused on 1) customer experience, 2) the growth of community solar programs, and 3) project-level financial best practices for serving LMI communities. These were followed by a user-friendly web-based Toolkit allowing users to interact with project data and key findings in November 2022. The customer experience research examined community solar subscribers’ primary motivations to join and remain satisfied with projects. Our research identified 453 projects across the country that dedicated some portion of the system capacity to LMI households. Seventeen of these projects participated in the LIFT customer experience research, allowing the project team to survey their customers and gain insight into how LMI subscribers feel about community solar and the programs that serve them. Subscribers in our sample indicated that the most critical issue that motivated them to participate in their program, however, was not savings but helping the environment. This was true for both LMI and non-LMI subscribers. Helping the environment was also the most important issue for LMI subscribers to measure how well their program was working for them. LIFT also explored how rapidly community solar has grown since its inception in 2006, publishing results in the Growth of U.S. Community Solar Serving LMI Households report. The results showed that community solar projects serving LMI households are one of the fastest growing segments of the solar industry. The report identifies and recommends ways developers should overcome real or perceived risks to LMI customer acquisition and subscriber management. Through the analysis of community solar project finance research, LIFT showed that most community solar projects serving LMI households are financed in the same ways mainstream community solar projects are financed. The value stacks and financial returns are no different, although LMI inclusion and participation rate varied across programs in our sample, ranging from between 10% and 100%. Based on the findings from the LIFT research, the team built a web-based user-friendly Toolkit, consisting of case studies, project finance best practices, and several tools built around the national dataset of 453 community solar projects that serve LMI households. These allow users to engage with the dataset in multiple ways; to explore the landscape of LMI community solar in the U.S., and to design community solar projects to optimize LMI inclusion, equity, and savings levels. The Toolkit also includes a library of LIFT-generated and LIFT-curated resources for users to learn more about how to best serve LMI communities through community solar. LIFT officially published the Toolkit on October 31, 2022, followed by a launch event (public webinar) on November 17, 2022. The core LIFT partners continue to engage in outreach and dissemination efforts to promote the LIFT Toolkit and research publications. Our driving motivation is to continue enabling solar developers to leverage the findings of this three-year research effort. By implication, the LIFT Toolkit is designed for use by utilities, energy service providers, and financiers or investors as a learning and decision-making tool to rapidly scale project models that optimize LMI inclusion and maximize real household savings.

14 SOLAR ENERGY↗
DOE OSTI2024

2023 IEDO Peer Review Report

On behalf of the U.S. Department of Energy (DOE) Industrial Efficiency and Decarbonization Office (IEDO), we are pleased to share the report from our 2023 peer review. Peer review provides us with invaluable insight into our office strategy and program direction from a diverse group of external thought leaders. The findings and actionable recommendations from peer review inform our decision making and help us maintain a constant state of evolution and growth.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Identifying institutional barriers and policy implications for sustainable energy technology adoption among large organizations in California

Large organizations wield considerable market power, their procurement activities can be leveraged to achieve social, economic and environmental goals by ‘pulling’ more desirable products into the market. However, while there is substantial research in individual consumer buying behavior and market barriers to sustainable technology adoption, less is known about large organizational buying behavior and the impact of institutional barriers in this area. To address these research gaps, in this work we conducted an exploratory study aimed at better understanding the process through which large organizations purchase sustainable energy technologies and what internal barriers they experience during that process. Additionally, we surveyed and interviewed 120 individuals involved in procurement from Californian organizations representing both public and private sectors. Survey results indicate the need to resolve the conflict between prioritizing lowest first cost and lowest life cycle cost, better engage multiple stakeholders involved in internal decision-making around purchasing, and improve existing procurement tools or offer new ones. We provide recommendations for how policymakers can apply our findings to increase the adoption of sustainable energy technologies in their own organizations and communities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Summary Analysis of Different Offshore Wind Capacity Density Drivers in Proposed U.S. Projects and Impacts on Progress Towards State and Federal Deployment Targets

Understanding the density of offshore wind development - or the "capacity density" - is important for state and federal offshore wind planning efforts and to track progress towards policy goals. NREL has traditionally assumed a capacity density of 3 megawatts per square kilometer (MW/km2) when estimating the U.S. project pipeline (Musial et al. 2022), but capacity densities for existing European offshore wind farms ranged from 2-19 MW/km2 (Borrmann et al. 2018). We track the expected capacity densities of the proposed U.S. projects in the East Coast and make an analysis by state and by developer to identify what are the capacity density norms in the industry and whether the state in which the development efforts are taking place has some impact on capacity density. We also analyze the effects of the area occupied by station keeping systems on capacity density for lease areas dedicated to floating projects and provide a list of main capacity density drivers. This summary analysis sets a baseline to study how different capacity density drivers could impact the progress towards state and federal deployment targets. Given the currently delineated Renewable Energy Areas in the Outer Continental Shelf (OCS) and the basis from the summary analysis, we estimate the expected offshore wind deployment over time federally and by state and compare it to the state and federal deployment targets. The proposed analysis helps identify gaps and needs to meet state and federal targets, which provides sufficient information to propose strategic supply chain and policy planning with the objective of meeting deployment goals.

capacity density↗